12 Meteorological data handling
12.1 Introduction ..................................................................................................................................... 2
12.2 Meteo Object: the data container .................................................................................................. 2
12.3 Meteo Object tab by tab .............................................................................................................. 3
12.3.1 Guide including online data description ..................................................................................... 3
12.3.2 Purpose ......................................................................................................................................... 7
12.3.3 Data .............................................................................................................................................. 8
12.3.3.1 Import setup .......................................................................................................................... 8
12.3.3.2 Calibration ........................................................................................................................... 11
12.3.3.3 Configuration ....................................................................................................................... 13
12.3.3.4 Data setup ........................................................................................................................... 18
12.3.3.4.1 The Add… button: adding & generating wind data at new heights ................................. 23
12.3.3.4.2 Remove tower shading: Add merged height ................................................................... 24
12.3.3.5 Time series ......................................................................................................................... 34
12.3.3.6 Frequency table .................................................................................................................. 36
12.3.3.7 Weibull ................................................................................................................................ 36
12.3.3.8 Turbulence .......................................................................................................................... 37
12.3.4 Graphics ...................................................................................................................................... 39
12.3.4.1 Time series ......................................................................................................................... 39
12.3.4.2 Weibull/Table ...................................................................................................................... 41
12.3.4.3 Turbulence .......................................................................................................................... 42
12.3.4.4 Rose view ........................................................................................................................... 42
12.3.4.5 Wind speed difference ........................................................................................................ 43
12.3.4.6 General XY graph ............................................................................................................... 43
12.3.4.7 Profile .................................................................................................................................. 44
12.3.5 Statistics ...................................................................................................................................... 46
12.3.6 Shear .......................................................................................................................................... 49
12.3.7 Mesoscale terrain ....................................................................................................................... 50
12.3.8 Report ......................................................................................................................................... 51
12.4 Meteo analyser .............................................................................................................................. 52
12.5 Meteo analyser: tab by tab ........................................................................................................... 53
12.5.1 Data: overview and selection of data .......................................................................................... 53
12.5.2 Graphics: Compare time series .................................................................................................. 54
12.5.3 Substitute: Perform data substitutions ........................................................................................ 55
12.5.4 Cross predict: WAsP vertical and horizontal extrapolation ......................................................... 56
12.5.5 Time variation: complete 1 year of data ..................................................................................... 59
12.5.6 Scaling create a new scaled time series using the Scaler ...................................................... 61
12.5.7 RSD verification .......................................................................................................................... 67
12.6 Flagging and data screening ....................................................................................................... 68
12.6.1 What is a flag? ............................................................................................................................ 68
12.6.2 Building conditions ...................................................................................................................... 69
12.6.3 Multiple conditions ...................................................................................................................... 72
12.6.4 Actions for flags .......................................................................................................................... 72
12.6.5 Flags in Meteo Analyser ............................................................................................................. 74
12.6.6 Import/Export flags ...................................................................................................................... 74
12.6.7 Showing flags in time series graph ............................................................................................. 75
12.6.8 Showing flags in time series table .............................................................................................. 76
12.6.9 Showing flags in XY graph and Wind Speed Relations graph ................................................... 76
12.6.10 Cleaning data with flags .......................................................................................................... 77
Introduction 2
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
12.1 Introduction
Meteorological data is commonly supplied as time series, meaning large data amounts. There is a large range
of data sources, from local measurements to refined mesoscale model data. While local measurements often
have gaps or erroneous values and cover typically shorter periods, model data are usually available for long
periods back in time, whilst at the same time not being so accurate.
Different data sources complement each other, and efficient tools for comparisons and manipulations are
essential for preparing the data representing the long-term meteorological reality at the specific location. In
windPRO the tools for importing, screening, comparing, repairing and validating meteorological data can handle
most situations thanks to decades of development.
This chapter describes two main components:
The Meteo Object : For importing, screening, analyzing, synthesizing, merging, wake-cleaning (along with
PARK calculation), etc. data from a single source (mast, remote sensor, model output, etc.) with one or more
heights.
The Meteo Analyser : For comparison of multiple Meteo Objects data series (same station or different
stations), featuring cross-predictions, substitutions, gap filling and RSD (Remote Sensing Device) verification.
In both components, the SCALER function can be used. See details in Chapter 3 Energy on this comprehensive
model-based tool to transfer/extrapolate time series from one to another point for comparison and thereby
evaluation/calibration of the model.
Finally, it’s worth mentioning the online data service, whence data from all over the world can be downloaded
into a Meteo Object (subject to license conditions). It is probably the easiest-to-use and most comprehensive
service to be found in the business.
12.2 Meteo Object: the data container
The Meteo Object is the input object for wind data and other measurements or model data.
Input can be from the very simplest form:
input manually one wind speed (annual mean) in one sector together with Weibull k=2, and you can
calculate AEP based on just a simple mean wind speed and a Rayleigh distribution (Weibull with k=2)
to the very advanced form:
import measurements from a SODAR or LIDAR file with 25 different heights for a long measurement
period with high time resolution. The data files might even have changed format or units during the
measurement period. The Meteo Object importer can also read from compressed files, such as .ZIP
directly. Finally, it can read the NRG logger files (.RWD) directly (although this is processed through the
NRG data retriever software that must be installed).
Data from other loggers must first be converted to ASCII files (such as .txt or .csv) with the logger
proprietary software. Additionally, windPRO has an automatic filter for Zephir LIDAR data files so that
all definitions for all channels are filled out automatically.
A newer option is to load data directly from databases through an API.
The measurements can be used directly (i.e. without use of models) for AEP calculations in the calculation
module METEO. The most common method of use, however, is with MCP for long-term correction (see Chapter
3) and using these data and terrain information to generate a long-term representative wind statistic or time
series. These can then be used to calculate AEP with ATLAS, WAsP interface or (most commonly) the PARK
module.
Meteo Object tab by tab 3
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
12.3 Meteo Object tab by tab
12.3.1 Guide including online data description
The different options for starting are explained here.
Figure 1 Guide in Meteo Object
1.
Typically, time series will be the most common format in which data is made available if users have any
doubts about reading them, start with the Wizard.
Meteo Object tab by tab 4
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
2.
APIs make it possible to download measurement data from external data servers.
Two options are currently available: the Ammonit server and the generic EMD Meteo API:
The EMD Meteo API is an open API interface which allows you to connect to your own data servers by
implementing the EMD Meteo API. For more information on how to connect, please visit:
https://help.emd.dk/knowledgebase/content/EMD_technote_Meteo_API.pdf or contact support@emd.dk
Once connected and logged in, you can download your company’s own data directly from windPRO:
Figure 2 Example implementation of the EMD Meteo API
The other API option is the Ammonitor API:
To access the Ammonit server, select this option, and enter your project credentials and a name in the
AppId (e.g. windPRO):
Meteo Object tab by tab 5
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Open a browser and log into AmmonitOR and visit the Project settings:
Click the Edit button under “API: 3
rd
party applications”:
Click the Allow access button for the application name you chose for AppID (e.g. “windPRO”):
Go back to windPRO and click Login to select which data to download. You can filter by logger and by
start/end date:
Hitting Ok starts the data download and everything is loaded into the Meteo Object.
Meteo Object tab by tab 6
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
3.
This option gives access to data on the EMD online server, where we add (mostly) free data for fast and
easy download. Data for purchase is also available, and in this case the EMD server links to commercial
data servers. Click the GO Online button to see your current options. These are expanded regularly. If a
Meteo Object with online data is reopened, the Online button changes into “Refresh online data, to allow
you to update previously downloaded data.
The online data download interface looks like this:
Figure 3 Online data download in Meteo Object with spatial coverage check
The first screen shows the list of available datasets. Here, check relevant datasets to test if there is
coverage near the site. The date of the most recent record is shown.
The list of the datasets available is nowadays very long. The focus is on wind, but several data sets have
several other climate parameters, including Heliosat solar irradiation and the Danish Wind Index.
The datasets are regularly updated, and the latest information about the data can be found here:
help.emd.dk/mediawiki/
After coverage check, dots on the map and radio buttons in the list show the locations of the data.
Click on one of the dots to see which database it refers to. With Ok the selected dataset will be downloaded.
The data will automatically be imported in the Meteo Object, ready for analyses.
Note that it is possible to download more datasets at a time from the Meteo Analyser! Users have the choice
of filtering the download period according to the available data and their own requirements.
Meteo Object tab by tab 7
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 4 Selection of data set for download.
12.3.2 Purpose
Figure 5 “Purpose” settings help to structure the data and their use.
If there are several datasets loaded in a windPRO project, giving them a purpose may provide a better overview.
Only the relevant data based on the purpose chose in this tab will be available in specific places within windPRO.
Meteo Object tab by tab 8
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
12.3.3 Data
Figure 6 The Data tab - Import setup
The Data tab controls and hosts a number of functions and applications, listed as further tabs to the left side of
the window; before importing data:
Import setup (identifying file structure(s))
Calibration (applying correction to the data)
Configuration (input of configuration of the measuring equipment and check against standards)
Data setup (setting up the signals required for each height)
and after importing data more tabs will appear:
Time series (raw data table, can be sorted by any signal)
Frequency table (summary table binned by sector and wind speed)
Weibull data (Weibull fit parameters per sector)
Turbulence data (summary table binned by sector and wind speed)
Below, each function in this tab is explained.
12.3.3.1 Import setup
This is the heart of the importing system. It teaches windPRO how the files are formatted and should be read.
File types supported: Only ASCII files can be imported. This means raw logger files, Excel files or database
files must be converted to text files before data can be imported. Compressed text files are supported (.zip, .rar
etc.).
Meteo Object tab by tab 9
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Add file(s): links to the data files to be imported. Note, these MUST all have the same structure if not, add
more “Import filters and add the different files “below” each import filter.
Add folder(s): links to folder(s) with the data files to be imported. Note, these MUST have the same structure
if not, add more import filters. If there are data from more masts or different files in the folder, it is possible to set
a mask, e.g. “*.txt”, so only relevant files will be used.
Figure 7 Adding folders in Meteo Object, and specifying the optional “file mask”.
Remove: removes the selected files in the list from the import filter.
Edit: edits the import setting, like the file mask in “Add folder(s)”.
View file: shows the selected file with the current import settings applied. This is very useful to identify the
structure of the file and see if the import settings will work as desired.
Online data (requires an active license for the METEO or MCP module): starts a communication with EMD
server (see help.emd.dk/mediawiki/index.php?title=Category%3AWind_Data).
Time zone: if data are in UTC/GMT (the meteorological standard), or in any time other than the project time
zone, they will automatically be transformed to the time zone set in the Project Properties. For the individual
measurement heights, you’ll later have the option to shift in time the data series individually. This is needed, for
example, when importing NCAR data where 10 m data are actually forecasts 6 hour ahead, whereas the other
data refer to the indicated time.
Import filter (structure of the files): each file structure defined in this window is called a “Filter”, and given a
name (I1, I2, …), and can be saved for later use. This helps saving time if similarly formatted files are used in
different projects. If you do not have a Filter saved, use the “Auto detect” feature.
Auto detect: a powerful tool to recognize the “base structure” of many types of data files.
Use text-to-numbers: converts, for example, wind directions described as N, NNE, ENE, etc., to numbers.
When "Auto detect" is used, the lower part of the window is filled automatically. Several standard logger output
files can be automatically detected, and new types are continuously added. Some file formats, however, must
be manually set up, if they are, for example, user-defined Excel exports etc. Let’s see how to do this.
There must be an entry for each data signal which will be used in the object. The signals not used will just be
ignored if the option “ignore” is chosen. Signals can always be set up and used at a later stage.
1. Choose “type” in the dropdown list, such as “Time stamp” or “wind speed” (note that the standard
deviation (StDev) of a wind speed signal is also classified as a wind speed).
2. Choose “sub type”, such as “year” or “mean” etc.
3. Choose “unit” – note that non-metric units (e.g. mph, knots, Fahrenheit) will be automatically converted
to metric units in the object.
4. Choose “height” this must be in meters. Files set to feet” will automatically be converted to meters.
Always check that height is correct.
In case a signal is undefined, the missing cell will be highlighted in pink.
Meteo Object tab by tab 10
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 8 Setting up import filter in Meteo Object
Figure 9 The signal types available currently.
The signal type list is expanded when new demands occur. Above the status of predefined types are shown.
Some types have sub types and more units to choose from. And some types will have a special status. E.g. the
Solar irradiation is dedicated to irradiation on horizontal plane, the only type that can be used in Solar-PV
calculations at present, where direct and diffuse just can be used for evaluations.
When all signals are set up, go to the “Calibration” tab or skip directly to the Data Setup” tab.
Meteo Object tab by tab 11
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
12.3.3.2 Calibration
The Calibration tab is used to:
1. View the scale and offset parameters input in the logger, when available in a file format recognized by
windPRO.
2. Input correction or recalibration parameters (scale and offset) to be applied to the data when necessary.
This can be relevant when the values from the data logger differ from the values from calibration
certificates. Knowing the official values from calibration certificates, windPRO can automatically
calculate the needed correction to be applied on the “wrongly” logged data.
3. Check the average magnetic declination value valid at the position of the Meteo Object for the middle
of the data period. Wind direction data can be then corrected for magnetic declination if necessary
4. Provide documentation of data treatment, through the Report (see 12.3.8)
The tab consists in two main parts: the Calibration table and the Timeline. The Calibration table and timeline are
automatically created from the Import setup tab. If files are added at a later stage, these will be detected, and
the table will be amended accordingly. If the Manual mode checkbox is selected, no changes will be made upon
import of additional logger files. If un-checked the table values will automatically update.
Figure 10 Calibration tab
Calibration table
Each line of the calibration table relates to a calibration period of a given sensor.
A calibration period is defined as an interval of time for which a specific set of scale, offset and magnetic
declination relating a specific dataset from a given sensor. A given sensor can have more than one calibration
period, for example when it has been recalibrated as recommend by Measnet after 2 years.
The calibration periods are firstly automatically created by windPRO after screening all data files defined in
Import setup.
A calibration period is created for each time interval with constant Channel (if available), serial number (if
available) AND constant 2 scale/offset values (if available), for any Type of data (speed, direction, temperature
…) with sub type defined as “Mean” in the import filter.
Please note that windPRO detects only one calibration period per file. It is therefore not recommended to gather
all data into one data file if several calibration periods are covered.
Meteo Object tab by tab 12
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
The calibration periods can also be created manually using the + at the bottom of the table or a right click on the
line and select Duplicate line. An existing line can be split in 2 lines to allow the user to identify distinctive periods
for different calibration factors in case this has not been detected automatically. Alternatively, right click on a line
of the table.
The columns From data file under the header Logger relate to the Scale and Offset values read from the file
(if available).
The columns User input under the header Correction allows the user to decide which scale and offset to apply
to a dataset. The same correction is applied to all signals under the same channel, like mean wind speed, min
and max wind speed. The standard deviation is however only using the scale factor, not the offset.
The Result column shows the result of the correction of first data of the first file loaded under the given Import
filter. It can be useful to make a sanity check of the result to expect. In the rare case when several calibration
periods are created from files under a same import filter (occurring if the scale and offset information from the
files changes in raw data files), then it is only the result of the first file which is shown and not the result for each
file.
The Comment column is available for user text input.
Recalibration table
The Calibration table can be extended to a more advanced table by checking the checkbox Recalibration in
the upper left corner. The recalibration table is used to:
Provide documentation of the calibration values applied to the data
Calculate the corrections to apply to data in case of mismatch between the logger and official values
Figure 11 Recalibration table
The columns User input under the Logger header allows to manually enter the scale and offset as setup in the
logger, when these are not available or properly detected.
The columns under the header Official (from certificates) give the option to input the scale/offset values as
presented in the calibration certificates documents.
Under the Correction header, the Calculated columns are automatically filled when data is available in the
Logger columns and the Official (from certificates) columns.
The calculated correction for scale is calculated as: Scale(official)/Scale(logger).
The calculated correction for offset is calculated as: Offset(official)-(scale(official)/scale(logger))xOffset(logger)
When both logger values are available in the From data file or User input columns, only User input is used for
the Calculated correction columns. If a cell of User input is left blank, the value 1 is assumed for scale data and
0 for offset data.
The Final columns under the Correction header consists firstly in the selected of the correction to apply, that is
either the calculated one as presented in the Calculated columns, or the User Input ones or none. Then to the
right of the Apply column a final visual check of the correction selected and used later on in windPRO can be
made.
Calibration values from Kintech, Ammonit and Symphonie datafiles are automatically loaded. Also note that
some EMD on-line data have calibration factors for heatflux automatically input in the table while downloading.
Timeline
The Timelines gives an overview of the different calibration period(s) for each sensor as defined in the Calibration
table. This feature is especially useful when a sensor is concerned by several calibration periods. If a sensor
Meteo Object tab by tab 13
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
has been (re)calibrated over time, a new calibration period is created on the same line in a lighter color. Clicking
on a line will mark the corresponding line in the table and vice versa.
Note that the function of the timeline is to provide a view of different calibration periods, not of the data
availability. If there are holes in the time series, they will not be reflected here but for example under Graphics
tab, Recovery.
Magnetic declination
By checking View magnetic declination, it is possible to see the magnetic declination as provided by the
International Geomagnetic Reference Field, 13
th
Generation, released in December 2019
(http://geomag.bgs.ac.uk/data_service/models_compass/igrf_calc.html). The value is calculated at the position
of the Meteo Object and for the central date of the whole measurement period.
Figure 12 Magnetic declination
If needed, the direction data can be corrected for the magnetic declination by checking Allow correction of
vane offset for magnetic declination. The correction for magnetic declination is only relevant if it has not been
considered during the installation of the wind vane(s) nor in the input of calibrating factors in the logger. The
value of magnetic declination is added to the direction data in order to get the direction relative to true North
(assuming that the vane has been installed relative to the magnetic North). The final correction applied to the
data can be seen in the Calibration table, where it can also be deselected or changed manually.
12.3.3.3 Configuration
The Configuration tab is used to:
Document the configuration of the sensor installation on a typical mast
Evaluate the compliance of this configuration to standards for wind data measurements (at the moment
IEC 61400-50-1 ed. 1).
Meteo Object tab by tab 14
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 13 Configuration tab
Met station
It is possible to define the type of Met station between Lattice mast, (triangular or square section), tubular mast,
SODAR or LIDAR. The difference between lattice (whatever section type) and tubular has an influence on the
IEC check for the distortion from the mast (involving Ct value or not, see below). For SODAR or LIDAR, no
configuration table nor compliancy check is available at present.
It shall be specified if the top mounted anemometer(s) is single or side-by-side, since this is relevant for the IEC
checks.
The height of the mast structure AGL is the total height of the lattice or tubular mast from bottom to top.
Logger
If available in the raw data file, information on the logger, such as the manufacturer, Model, serial number … is
presented automatically. It is also possible to input the information manually and to add a line if the logger has
been changed with a new one during the measurement campaign.
Notes
This field is available for user-defined text for documentation purposes. It could be relevant to enter references
to various installation and maintenance reports related to the installation and operation of the measurement
mast.
Sensor/Equipment installation
The sensor/Equipment installation table lists the various sensors involved in the measurement campaign of the
data defined in Import filter and allows to input the dimensions relevant for the compliancy check to standards.
The relevant input concerns:
the horizontal booms (direction, length from mast center and diameter)
the vertical booms, that is both the smaller tube directly attached to the sensor and the supporting tube.
The supporting tube is the additional tube used to stabilize the smaller tube attached to the body of
single or side-by-side top anemometers
The body diameter of the sensor
The calibration number from the certificates (for documentation purposes)
The mast width and thrust (Ct), the latter only in case of lattice tower
The distance to anemometer and the alignment with the anemometer of the lightning finial.
The dimensions of certain sensor/equipment types are not relevant for compliancy check and therefore not
available for input in the table (grey cell).
The cells of the table can be filled in from the Clipboard (preferably from a Copy from Excel) using Paste relative
to currently selected cell will.
Meteo Object tab by tab 15
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
The dimensions are presented in the diagram below, using the same colour as the headers of the table.
Figure 14 Diagram of the dimensions to input in the Sensor/Equipment installation table
This diagram is also available under the Guide button.
The table is based on the Calibration table but changing the data type (wind speed, wind direction, …) to
corresponding sensors (anemometer, wind vane, …). Wind speed signal is by default assumed to come from a
cup anemometer. It is possible to change the Type of sensor to sonic anemometer in the drop-down menu of
the Type column. The data such as temperature, pressure or humidity are reported as belonging to a sensor
type called Weather station.
Loads Channels: (Re-)Loads the Sensor/equipment installation table based on the Calibration tab.
If two calibration periods have been defined for a data type in the calibration tab, two sensor lines will be created
in the configuration table matching each period and assuming that the configuration between the two periods
could be different. If this is not the case, lines can be manually deleted (with the at the bottom of the table) or
modified; the Start and End date can also be manually changed.
At the bottom of the list, a line is added for a lightning finial.
Mounting
The mounting is relevant for the IEC compliancy checks. The mounting is filled in automatically as a first best
guess. It is recommended to check that it corresponds to the mast configuration at stake. The mounting of the
top anemometer(s) and of the lightning finial require user input. The different types of mounting are:
Single-top: The top anemometer is placed on the top of the mast and centered on the cross section
Side-mounted: The sensor is placed on a horizontal boom
Shared boom: The sensor is placed on a horizontal boom together with another sensor (at the same
height and direction)
Top (Lightning finial): The lightning finial is placed on the top of the mast and centered on the cross
section
Boom (lightning finial): The lightning finial is placed on horizontal boom
Used in windPRO heights
This column is automatically filled once the data have been setup and loaded under the data setup tab. It refers
to the heights that are defined and used in the Meteo Object from the Data setup tab. It can be used for
traceability of the data.
Lightning finial, distance, and alignment
The horizontal distance between the finial and a given top anemometer is calculated automatically in windPRO
for most of the common combination of anemometer and finial mounting, as presented in the following table.
Meteo Object tab by tab 16
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Table 1. Automatic input of distance and alignment direction between finial and anemometer in
Sensor/Equipment installation table used for the IEC checks about distortion from finial.
Combinations of anemometer and finial
Automatic input in Configuration table
Anemometer mounting
Finial mounting
Distance to anemometer
Finial-anemometer alignment direction
Single, top (centred)
On a boom
Length of finial boom
direction of finial
Single, side mounted
Top (centred)
Length of anemometer boom
180 + direction of anemometer boom
Single, side mounted
On a boom
-
-
Side-by-side, top
Top (centred)
Length of anemometer boom
180 + direction of anemometer boom
Side-by-side, top
On a boom
-
-
The calculated distance or alignment can be modified manually in the table (“Distance to anemo.” Column).
Main wind direction
The input of main wind direction is used for the check of the mast distortion and of the lightning finial giving wake
in compliance with IEC 61400-50-1 Ed 1.
Advanced settings
Checking the advanced settings gives access to tolerance values used in some Compliance checks. The
IEC/Tolerance for boom orientation vs main wind direction gives a margin (+/-) around the ideal orientation of
the boom that will return OK to compliancy.
The tolerance IEC/Wake sector for distortion from finial is the wind direction sector in which the finial is supposed
to give wake, assuming that it is centered on the finial.
The default values are arbitrary and can be changed.
Compliancy check
The input made in the Sensor/equipment installation table is used to check the configuration of the mast to the
most important requirements defined in the IEC standard 61400-50-1 Ed.1.0 Wind energy generation systems-
Part 50-1: Wind measurements Application of meteorological mast, nacelle and spinner mounted instruments.
Once the table is filled, provided there is an input in all the green cells (Height of mast structure, Main wind
direction and Mounting of lightning finial), the Compliancy check can be launched clicking on the button Show
compliancy check.
Meteo Object tab by tab 17
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
For more detail about the checks conducted, please refer to the online documentation: https://www.emd-
international.com/files/windpro/240903_Notes_compliancy_check_in_WP.pdf, also available from the
Compliancy Check window through the link in the bottom right corner in the window.
A color code is used to give a quick overview of the result of the compliancy check. Green color is used for
compliancy, red for non-compliancy and orange for a non-critical non compliancy. When a check involving two
condition is not passed, the result is NO. It is possible to see which condition is not fulfilled by mouseover the
cell, as shown in the example below.
Figure 15 Example of explanatory text in case one condition is not met
In case of missing data, the checks cannot be performed. The required input from the configuration table is listed
for each check in the online documentation
Note that it is possible to select whether all or only some compliancy checks shall be presented in the final report
(See 12.3.8).
Meteo Object tab by tab 18
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
12.3.3.4 Data setup
This is the tab where we can finally load the data from the files whose structure has been defined previously.
Note: in the Meteo Object, “Heights” always refer to the height of wind speed measurements!
This is how to proceed. Ignore the Add… button for now, as it will be treated later.
1 2 3
Figure 16 The data panel in the Data setup tab. (1) Click Auto-create, to create signals at the available heights.
(2) Click Clear and load all to load data into the signals. (3) Click Add… to add more wind data at other heights.
The Auto Create” button is, by default, green, as this will be the typical starting point. This will automatically
create all the wind speed measurement heights in the import setup, providing the file can be read by windPRO.
The signals created by default are:
Wind speed
Wind direction
Turbulence intensity
Wind direction is taken from the wind vane vertically closest to each anemometer/wind speed signal.
The “Remove” button removes any heights selected in the list. Holding down SHIFT or CTRL it is possible to
select multiple heights and remove them in one go. This can be useful when working with remote sensing
devices that have many heights and you wish to limit the number of heights.
Meteo Object tab by tab 19
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Clear and load all will clear data, in case of already loaded data. If new data have been added to the import
filter, the Load new will make sure the data already loaded data are maintained with flagging, disabling etc.
And this is how the window will look like, after importing data.
Figure 17 The Data setup tab, after data loading
You can now switch between different measurement heights by clicking in the Heights panel to the right.
Never change the value indicated in the Height [m] field on the left! This would effectively modify the height
of that particular instrument/signal!
Figure 18 Data type and displacement height
It is possible to set a displacement height, if the mast is, for example, in a forest (positive disp. height) or on a
very narrow rock (island) (negative disp. height), which is NOT included in the elevation data. The data type,
mast, Lidar, etc. can be specified. This information can be used by modules like PARK and SITE COMPLIANCE,
and is used in the wind profile graphic, discussed later. The data type Mast, Lidar etc. can be selected and is
used for relevant purposes. For example, for downscaling Meso data in Scaler the data type must be Meso.
Creating a wake-cleaned wind speed signal will be handled differently if the datatype is Nacelle or Mast. If
Nacelle, the turbine nearest the Meteo Object is not included in calculations. However, it is checked that there
is indeed a Turbine Object within 5 m distance.
Meteo Object tab by tab 20
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Add (Figure 16) adds a new height. We will treat it later.
Update online refreshes data previously loaded from On-line data (updates with most recent months and,
optionally, extends data back in time, if data are available).
Setup allows setting of rules for concurrency, disabling of turbulence and rules for use of data for the turbulence
table. Also, a special feature is available for very-high time resolution data.
Export exports all or selected data into a flat text file format. The flag definitions are included in the export (see
their explanation in the text file itself). Below is an example where 80m and 60m data are exported:
Figure 19 Export selections
Meteo Object tab by tab 21
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 20 Export format from Meteo Object
Status values are coded, so the sum in the status columns can be decoded for precise identification of, for
example, “disabled”, “out of range” (this means that multiple flags can be applied to the same data point). There
is also a status column for all signals as well as one for each signal. The headers are exported unicoded (UID),
meaning that the same text will appear no matter from which Windows language it is exported. Thus, it is easy
to maintain a large database with exports from many different users around the world, as only one windPRO
meteo importer will be needed.
Import imports data from the export file (Note: a whole Object export can be performed from the Object List).
Back to the central part of the Data setup tab:
Figure 21 Data panel below the signals in Data setup tab
Add signal is used for adding other signals not automatically considered by windPRO; for example, temperature
or max. wind speed. The range of signals that can be included is constantly expanded:
WindPRO Meteo Data Export version 7
Longitude:
9.707051 Latitude: 51.24978
Easting: 549346.4
Northing:
5677839 EPSG: 32632
Description: Mast
User label:
Date time format: dd/mm/yyyy hh:nn
Decimal separator: .
Digit group separator: ,
Displacement height [m]: 0
All time stamps: (UTC+01:00) Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna
UTC offset [minutes]: -60
StatusValues:
Ok 0
Disabled 1
Below limit 2
Above limit 4
Duplicate 8
Null value 16
Missing 32
Other error 128
Note that SampleStatus takes precedence over DataStatus which means that DataStatus is only relevant if SampleStatus is OK.
TimeStamp
MeanWindSpeedUID_100.7m|Mean wind speed|L-1.00|U75.00
DirectionUID_100.7m|Wind direction|L0.00|U360.00
TurbIntUID_100.7m|Turbulence intensity|L0.00
Comment_100.7m
TimeStampStatus_100.7m
SampleStatus_100.7m
DataStatus_MeanWindSpeedUID_100.7m
DataStatus_DirectionUID_100.7m
DataStatus_TurbIntUID_100.7m
MeanWindSpeedUID_100.5m|Mean wind speed|L-1.00|U75.00
DirectionUID_100.5m|Wind direction|L0.00|U360.00
TurbIntUID_100.5m|Turbulence intensity|L0.00
Comment_100.5m
[m/s] [Degrees] [m/s] [Degrees]
28/09/2013 00:00 7.2 119 0.0556 0 0 0 0 0 7.2 119 0.0556
28/09/2013 00:10 7.2 119 0.0556 0 0 0 0 0 7.1 119 0.0563
28/09/2013 00:20 7.1 120 0.0563 0 0 0 0 0 7 120 0.0571
28/09/2013 00:30 7.2 118 0.0694 0 0 0 0 0 7.2 118 0.0694
28/09/2013 00:40 7.71 118 0.039 0 0 0 0 0 7.7 118 0.039
Meteo Object tab by tab 22
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 22 Current predefined signals.
Full flexibility is given for creating a specific signal at a certain height from other signals/measurements. The
signals available match the import filter types + sub types and some extra signals, calculated from more signals,
e.g. Turbulence Intensity, which requires wind speed and Std.dev wind speed.
Let’s see a few examples.
If the data come from files with different formats (multiple import filters used), always check the dropdown buttons
in the column “Based on” to see if the signals from the different import filters (I1, I2, …) are correctly included:
Figure 23 In this example, wind speed data come from Filter I1, which refers to certain data files only, whereas
the direction is going to be read from Filter I2, referring to other files, with a different data structure. The Filters
were defined in the Import Setup tab
Note also the column Low/high limit (next to Signal name): this is used to define the valid range of the values
the data can assume. By default the low limit for wind speed is -1 m/s. It is important not to set this to “0”. If “0”
wind speeds are not included in the data set, the Weibull distribution will be wrong and the calculations will be
wrong.
Shear can be added as a signal, giving options for comprehensive analyses of shear within the Graphics tab.
Since shear requires more heights, these can be selected in drop-down buttons as illustrated in next figure.
When adding shear, the user has full flexibility about which heights will be used to calculate the shear time series
(minimum of 2 heights is needed).
Meteo Object tab by tab 23
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 24 Setup of shear calculation
Delete signal removes unwanted signals from a height.
(Re)load all files for selected height loads the data from the files for the selected height only. The right side
button (Load new files for selected height) only loads new files added after the last load operation. The Reload
button preserves the results of any data cleaning (“disabling”) operation that might have been done previously.
This doesn’t happen with the “Clear and load all” button presented earlier.
Figure 25 Features at the top of the tab
The various Activate options activate the different types of data presentations, such as the Weibull or
Turbulence tabs. If you have no intention of using the Weibull distribution, or you have table data but no time
series data, this feature is useful.
Lock existing time series is used when new data are added, but previously loaded data do not exist as files
on the PC or they have been added with different import settings in WindPRO 2.5 or previous versions. Basically,
adding new data requires intact import filters and files for all data except when older data series are locked.
12.3.3.4.1 The Add… button: adding & generating wind data at new heights
We have so far left behind a very important feature: the Add… button. It essentially creates a new measurement
height, where wind data can be read from files or generated by different methods.
Meteo Object tab by tab 24
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Its submenu gives hints of the different features and purposes:
Add height simply creates a new height, where the presence of wind data is automatically assumed,
and the user will have to select their source, as in Figure 23.
Add merged height allows to merge two or more wind speed time series based on wind direction; it is
typically used to remove the mast shading effects when two anemometers are mounted at the same
height
Add sheared height gives access to a shear calculator that extrapolates measured data to another
height on the basis of the measured wind shear.
Add scaled height creates a new data series, which can be, for example, a downscaled mesoscale
time series (if EMD mesoscale data are loaded) or the output of a flow model used to extrapolate wind
data from one or more measurement heights to a new height. There are many possible scenarios here
due to the high flexibility of the Scaler tool.
Add stability creates an artificial atmospheric stability classification based on user-defined classes for
day, night and season.
Add wake cleaned height is based on a PARK model (which must be pre-run), which cleans the
measured data series from wakes generated by neighbouring turbines.
Let’s discuss the details of each feature.
12.3.3.4.2 Remove tower shading: Add merged height
Figure 26 Compare wind speeds by direction
When two wind speed measurements are at the same height, both measurements can be used to remove the
influence of tower shading and thereby get a “clean” signal. Note that the original data are never modified: we
will create a new time series, merging the two existing ones.
This procedure should be used only after the quality control procedures have filtered out (“disabled”) bad data.
A typical setup is shown above. Here, wind speed data from “Height 1” is used as “base” and wind speed data
from “Height 2” is merged into the “base” data within the given sector defined by From [deg] - To [deg]. Only
wind speed data from “Height 2 that have survived quality control are used for the merging. The merging is not
Meteo Object tab by tab 25
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
performed if the direction data of Height 1 are disabled. Looking at the data above, it is obvious that wind speed
data from “Height 1 are underestimated due to mast shadow between 320° and 350° (the difference, ”Height
1” minus ”Height 2”, is negative). We then enter this angular window in the relevant fields; clicking on Ok, the
following screen appears:
Figure 27 Merging data from more sensors
The rules established for the merged series are shown. Before loading the merged data (green button), the rules
can be edited by clicking the small dots to the right of each rule; any rule based on any signal can be created.
12.3.3.4.2.1 Shear-extrapolate to new height: Add sheared height
Data can be scaled to a new height based on a shear extrapolation using one of four options:
Time series shear
Internal shear matrix
External shear matrix
Shear table
Figure 28 Selection of shear extrapolation options
The first option, Time series based shear, the shear exponent is calculated at every time step and so is the
synthetic wind speed.
Two or more heights can be used as source data for the calculation and it is recommended to pick the tallest
heights when extrapolating. The reference height determines the wind direction. The target height is the
desired height of the new synthetic wind speed.
Meteo Object tab by tab 26
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 29 Selection of reference, target and source heights
Since a time series based shear exponent has a fluctuating nature, it is advisable to use a rolling window for
smoothing the signal. The rolling (or moving) window takes the median of the values of the window and is
always centered around the current time step. A rolling window of e.g. seven time steps, uses three time
steps before the current time step, the current time step, and then three time steps after. An internal study has
shown that applying a rolling window is particularly necessary when using only two source heights. The size of
the rolling window is specified by a given number of time steps. When the reference height has been selected,
the actual window size will appear in the brackets.
Figure 30 Application of a 7-step rolling window for a 10-minute resolution dataset. The smoothing window
includes 3x10 min before the time step, the time step itself, and 3x10 min after the time step.
It is possible to apply an omnidirectional or sector-wise displacement height to the shear extrapolation. This is
beneficial if the measurement device is located in forested terrain. The wind direction is taken from the
selected Reference height.
Figure 31 Selection of displacement height for shear extrapolation
Limits to the shear component can also be enforced by specifying a minimum limit and a maximum limit of the
calculated shear (not each shear value inside the rolling window). This option is disabled by default. If
enabled, and the calculated shear exponent exceeds the threshold, you can opt for discarding the value or to
override (cap) the calculated shear value to the threshold.
Figure 32 Selection of shear limits
Click on the green Calculate button and then Ok to generate a new shear extrapolated (or interpolated) time
series including wind speed, wind direction, turbulence intensity and shear. Remember to reload the selected
height.
Meteo Object tab by tab 27
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Referring to Figure 33, the two next shear extrapolation options, Internal shear and External shear, rely on a
shear matrix, calculated within the current Meteo Object in the first case or exported from another Meteo Object
in the second case. The fourth option uses a shear table from the shear tab of the current Meteo Object (see
12.3.6 about the shear tab).
Figure 33 Create sheared data
The Reference height is the height from which wind speed will be extrapolated from to the target height
specified in Height. Both heights need to be specified to start the shear matrix calculation.
To calculate the shear values, at least two heights must be selected and one of them will also define the direction.
The shear matrix contains shear values in several bins: monthly bins (yearly variation), hour bins (daily
variations) and directions. It is up to the user to define these resolutions.
The shear matrix is calculated from Weibull-fitted mean wind speeds in each bin (season, time of day and
direction) and will therefore partly represent atmospheric stability conditions. The extrapolation to a new height
will then be based on the individual bin values for shear. Note: In complex terrain, on a smooth hill, or in a forest,
very inaccurate extrapolations can occur. Using a model, such as WAsP (or better, WAsP-CFD, when terrain is
really complex) for the extrapolation will be the best choice.
The shear matrix can be more or less detailed, depending on how good and long-term period of data is available.
If there is too little data for a bin (direction sector, diurnal period and seasonal period), the bin will be given data
based on the following priority:
1. Annual value for the direction and diurnal period.
2. Mean value for the nearest two directions
Meteo Object tab by tab 28
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
3. Overall mean
For instance, if a direction has almost no data, not even a year’s worth of values might be present for a certain
diurnal bin, then the two nearest directions are used. If those (or just one of them) also have too little data, the
algorithm moves to step 3. Note that these substitutions are not very critical, since they will basically represent
bins where wind is rarely experienced.
It is possible to use an omnidirectional displacement height or a sector-wise displacement height. If using an
omnidirectional displacement height, it should be consistent with the displacement height provided in the meteo
object. In case this value differs from a previously defined fixed displacement height, you will be asked to
overwrite the old value with the new value.
Finally, click on Calculate shear matrix. Once it has been calculated, it can be viewed (and/or exported) and
finally used to synthesize the data (clicking OK). The tab Displacement height shows the calculated
displacement heights and can be copied to clipboard.
Figure 34 Shear matrix (shown here for all directions)
Meteo Object tab by tab 29
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 35 Load sheared data with the green button
The new sheared height is created and must be loaded. With the Edit” button you can go back to the shear
calculation setup and adjust.
When data are loaded, the tabs with the different data presentations will be added.
In the case of an exported shear matrix, a .shearmat file is created. This file contains all the information needed
to replicate the matrix in another Meteo Object (or the same). This option can be useful especially for co-located
remote sensors (LIDAR, SODAR). Care must be taken that an imported shear matrix is representative (for
example concurrent in time or same terrain or stability conditions) of the data that it is going to be applied to.
12.3.3.4.2.2 Add Scaled height
Here, the Scaler is used e.g. to downscale mesoscale data to the microscale and create a time series within the
Meteo Object. Then, it will be easy to compare the scaled data to the original data within the Object.
Meteo Object tab by tab 30
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 36 Selecting the scaler and heigths
It is important to note that the data are scaled to the same position of the current Object. Therefore, it is possible
to move a Meteo Object containing mesoscale data to a position where a “virtual mast” is needed. The
mesoscale-based Meteo Object knows its original position and uses the mesoscale terrain from this position,
but then the microscale terrain is used for the new current position.
12.3.3.4.2.3 Create atmospheric stability statistics: Add stability
This tool creates a statistic of the climate of atmospheric stability on site, relying entirely on user input. In other
words, the user must know, and enter, the expected stability conditions at different times of the day and year.
This is useful if this knowledge is available, but no hard data are at hand, on the matter.
One can decide in how many classes atmospheric stability should be classified (with a minimum of three, Stable,
neutral and unstable), and also how day and night are defined. Then, for each season and period of the day,
the expected mean stability condition must be entered:
Figure 37 Setting up stability class definitions
Meteo Object tab by tab 31
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
The resulting user-made statistic can be shown in various histograms under the Graphics tab, where a new
tab called Stability view will be created.
It is worth mentioning that a more appropriate way of investigating the behaviour of atmospheric stability on site
is to estimate its state from hard data (Monin-Obukhov length, heat flux, Temperature differences, …): many of
these parameters are available from mesoscale models, such as the EMD-WRF.
Figure 38 Stability can be imported in Meteo Object
Above, the EMD-WRF Europe+ mesoscale data. The “rmol_mean” signal is the inverse Monin-Obukov length
available in this data set. Stability can be viewed in Graphics tab under Stability View:
Figure 39 graphic view of stability classes.
Different settings are available. The graphic view is the first step; in future versions of windPRO, the Stability
information will be included in calculations.
Meteo Object tab by tab 32
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 40 Setup of stability legend.
In the legend above, the grouping of the stability classes can be user defined. Note in EMD-ConWx mesoscale
data, it is the reverse Monin Obukov length (1/L) that will be imported, in the definition above it is the Monin
Obukov length, L that is shown, with option for showing 1/L.
12.3.3.4.2.4 Clean measurements from wake effects: Add wake-cleaned height
Figure 41 Setup of the calculation for wake cleaning
Lastly, it is possible to remove the effects of turbine wakes on measurements. This requires to run first a PARK
calculation.
Meteo Object tab by tab 33
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
The setup window simply requires you to load the PARK result, the height of the instrument affected and to
define the kind of instrument you have at that height. This can be a real device on ground (mast, RSD, …), or a
nacelle anemometer.
In the first case, the measurement device coordinates are already known from the selected PARK calculation.
In the case of a nacelle instrument, the software checks if there is a WTG Object in the PARK calculation within
few meters from the Meteo Object used: if not, the calculation cannot be performed. If there is, this WTG Object
is automatically removed from the PARK calculation.
The wake cleaning is based on the calculation of a wake reduction matrix with resolutions of 1° and 1 m/s. Note
that a simplified PARK model is actually run, where time-based turbulence is not used (a fixed wake decay
constant for invalid turbulence values would be used instead). Similarly, curtailment settings will not be included.
Figure 42 Advanced wake settings of the PARK calculation are not included in wake cleaning. The WDC for
invalid TI is used, instead of time-dependent values
When the wake-reduced wind speed matrix is calculated, the method is: for each time step, a lookup in the
matrix from the wake-reduced wind speed identifies the free wind speed, and replaces the recorded value with
this in the wake-cleaned time series.
It is, of course, of high importance that the wake model settings are correct, and that the wake model does a
reasonable job.
The advantage of this method compared to e.g. a simple scaling, is that the wind speed reduction dependency
on wind speed is handled correctly.
Meteo Object tab by tab 34
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
12.3.3.5 Time series
Figure 43 Time series data
With a coloured background, data characteristics such as “Out of range” are clearly shown. Click in the coloured
field and the cursor jumps to the first event. Data can be sorted by clicking on the header.
Select: allows to select data with different characteristics a selection can also be performed “manually” by
dragging the mouse in the list.
Meteo Object tab by tab 35
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Selected: once data have been selected, you can apply on the selected data any of the actions listed (Copy,
Delete, …). For example, data can be copied to clipboard and pasted to other programs, e.g., Excel.
Enable/disable: can be performed manually in the list by checking the checkbox next to the time stamp, as
shown above, or via the “Advanced disable/deletetool, which allows to disable or delete the data according to
specified conditions:
Figure 44 Advanced disable/enable/delete
Once the conditions have been entered (above in time and on a specific signal, the wind speeds at 100.7 m),
pressing the "Action" button opens the Advanced disable/enable/delete feature for ALL heights and signals (with
same time stamp or within ± 5) that fulfill the conditions in the filter settings. Then the user decides which signal
should be disabled in those circumstances:
Figure 45 Advanced disable/enable/delete tool
Meteo Object tab by tab 36
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Selecting the All wind signals options will automatically select and deselect all wind speed and turbulence
signals for that height in one go.
12.3.3.6 Frequency table
Only Enabled data not out of range or duplicated are used in the aggregated presentation described here. The
aggregated data are automatically updated if changes in the original time series data are performed.
Figure 46 Data frequency table
12.3.3.7 Weibull
Only Enabled data not out of range or duplicated are used in the aggregated presentation described here. The
aggregated data are automatically updated if changes in the original time series data are performed.
The method for Weibull fit is energy weighted with the same method used by WAsP, as described in the
“European Wind Atlas”. The Weibull distribution can be used as input if the Meteo Object data are used for
further calculations, e.g., with the WAsP model.
Meteo Object tab by tab 37
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 47 The Weibull fitted data.
12.3.3.8 Turbulence
Only Enabled data not out of range or duplicated are used in the aggregated presentation described here. The
aggregated data are automatically updated if changes in the original time series data are performed.
Turbulence data can be shown as mean values and as standard deviations. By copying these two tables to
Excel, any combination of mean and standard deviation can be made for turbulence evaluations (e.g.,
Characteristic values as defined in IEC 61400-1 ed.2: mean + 1 x StDev and ed. 3: mean + 1.28 x StDev).
Meteo Object tab by tab 38
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 48 Turbulence data
Meteo Object tab by tab 39
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
12.3.4 Graphics
The Graphics tab holds advanced features for the evaluation of the measurements. Also included are features
for disabling erroneous data found by the graphic screening of the data.
On each graph there is a “Copy to Excel” button. The graph data as seen” can be copied to clipboard, and,
from there, pasted to Excel or similar.
The Graphics tab has the following main tabs, each with different viewing options:
Time series
Weibull/table
Rose view
Turbulence
Wind speed relations
General XY graph
Profile
Only a selection of the graphs within each tab will be shown below, as the others should be self-explanatory.
12.3.4.1 Time series
Figure 49 The time series view
The time series view is efficient for finding erroneous data visual comparison then simply right-click in the
graph at the start and end of erroneous data to disable that particular period. You can also add comments (right-
click) and these will be listed in a separate report. Zooming by mouse drag is possible as well.
Meteo Object tab by tab 40
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
With the check boxes for each height and signal, viewing can be controlled.
Figure 50 Disable by right-clicking and dragging the mouse along the time series graph.
Furthermore, data can be highlighted with flags based on logical expressions. See section 12.6.
The graphs showing the individual data points, like the “Gun shot and XY graph, data points can be disabled
by right-click on the data point. Thereby obvious outliers can be eliminated.
Figure 51 In scatter plots, disabling is available by right click.
Meteo Object tab by tab 41
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
12.3.4.2 Weibull/Table
Figure 52 The Weibull/Table graph for two different heights
The measurement histogram and the relevant Weibull fit are shown here. Note that the axis can be scaled
manually by the “Edit graph” feature, activated with the button or by double-clicking on the graph. This
feature is of course available almost anywhere in windPRO.
Figure 53 Advanced editing of the graph setup
Meteo Object tab by tab 42
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
12.3.4.3 Turbulence
Figure 54 Turbulence graphs
In the Turbulence graphs, different options for including comparisons with the IEC Standard are available. Note
that the axes can be scaled manually by the “Edit graph” feature mentioned above.
12.3.4.4 Rose view
The Rose graphs are shown below for one height, in a monthly view. The layout can be changed to contain a
user-defined number of graphs at a time.
Figure 55 The monthly Rose graphs
Meteo Object tab by tab 43
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
12.3.4.5 Wind speed difference
Based on two different wind speed sensors, usually at the same height, a difference/ratio plot can be created.
This is a useful way to evaluate boom directions and influence. Data points in the graph can be binned by
direction, and flags can be defined and shown on the graph.
Figure 56 Plot of the directional distribution of the ratios of wind speed from two same-height anemometers
12.3.4.6 General XY graph
With the General XY graph, you can plot any signal versus any other. When the cursor is placed on top of a
data point, the hint box shows the values, the date and time. This is an efficient tool to evaluate “outliers”:
Double-click on the point, and you’re taken to the relevant time in the time series.
Right-click on the point to disable its data.
Use the “Select points tools” to select and possibly disable a whole batch of outliers.
Finally, one can colour-code the data points with a third time series, thus adding a third dimension to the graph.
Meteo Object tab by tab 44
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 57 General XY graph
12.3.4.7 Profile
Figure 58 The profile graph
The profile view shows the terrain together with the wind speed profile. This is an efficient tool to analyse data
and compare them to model results.
Meteo Object tab by tab 45
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
The profile viewer illustrates how the measured wind profile looks by showing the best fits of both power law
profile and logarithmic profile. Also, a WAsP-calculated profile can be shown.
There are 3 view options:
Aggregated (average values of concurrent data for all heights used; default)
Runtime (record by record)
Manual (aggregated, but manually controlled values for power and logarithmic profiles)
The “height for fixed data” will be used as input in a WAsP calculation, if the WAsP profile is chosen. (WAsP can
only calculate from one measurement height, and creates the profile shape based on a fixed profile, modified
by surface and terrain effects).
Note that only in flat terrain the power or logarithmic profiles can be extrapolated to higher levels with reasonable
accuracy. If there are flow compressions due to hills, simple power or logarithmic profile extrapolations should
NOT be trusted. A WAsP profile will be a better estimate since it will include corrections by a flow model to
account for the compression effects.
The profile view window holds many options. To mention the more important ones:
Select heights by type a quick way to select and show data: e.g. only the original data, so the calculated
shear values are not influenced by other artificial” data (remember that only concurrent data are shown!); or
only wake-cleaned data, to get the free wind flow expected shear.
Meteo Object tab by tab 46
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Show MODEL profile Here, you select the model for generating the mean wind speed profile.
The Scaler-calculated profile has the advantage of being based on the whole time series, thereby resulting in
time-dependent profiles, to be compared with the relevant measured profiles.
Include disp. height Includes in the graph a fixed or sector-wise displacement height, the latter calculated on
the basis of tree height data to be provided by the user.
Copy profile data Used for extracting the data which make up the graph. Includes information such as Meteo
Object name and displacement height.
12.3.5 Statistics
There are three different tabs for statistics:
Main statistics
Monthly means
Recovery (data availability)
Monthly Weibull parameters
Meteo Object tab by tab 47
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 59 First view of Main statistics.
Figure 60 Monthly means
Meteo Object tab by tab 48
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Monthly means can be shown signal by signal by right-clicking, the tables can be copied to the clipboard and
easily integrated into documentation.
Figure 61 Data recovery view
Data recovery can be shown height by height and for a signal alone or a combination of wind speed AND
direction. In this case, the data are considered available only if BOTH signals are available. The table shows the
percentage of available data in the first column and then the number of samples enabled per day and hour.
Color coding gives a fast overview of the availability. Green shows that no samples are missing nor disabled.
The cells in red show that all samples are missing or disabled, and yellow is in between.
The Effective data period equals the total period x recovery rate.
The results presented under Enabledare relative to the enabled period. In this case, if data are disabled at the
start or the end of the measurements, the recovery is calculated only between the first and last enabled data.
Change status of selected samples allows to graphically select data in the table and change their status to
enabled/disabled.
Meteo Object tab by tab 49
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
12.3.6 Shear
Figure 62 Shear for simple METEO calculations and evaluations
In the graph above, two different shear calculation options are tested against each other.
When doing a METEO AEP calculation based on a Meteo Object, the shear tables available here can be
selected as input for the calculation.
Shear can be either entered manually or calculated on the basis of different models:
The most robust method is based on the shear matrix, and this also adds value analyzing the data (see
12.3.3.4.2.1).
The Shear tab can hold an unlimited number of shear calculations. The text in the yellow dialog box explains its
use.
The shear calculations based on Weibull method use the Weibull mean wind speed. Direction from only one
height is used, so the mean Weibull wind speed used is based on concurrent time records.
Meteo Object tab by tab 50
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
12.3.7 Mesoscale terrain
This tab only appears in Meteo Objects holding EMD-WRF mesoscale data. It contains the EMD-WRF
mesoscale terrain used in the model.
Figure 63 Mesoscale terrain in Meteo Object
Note: there are two different roughness files - a min. (winter) and a max. (summer). The mesoscale model uses
seasonal surface roughness.
If an EMD-WRF Icing calculation has been run on our server, additional parameters such as icing intensity, ice
load, instrumental icing and meteorological icing will appear here. If at least 10 seasons are included in the
calculation, additional reports will apper. These can be accessed in the lower part of the window:
The mesoscale terrain map and icing maps can be added as a result layer by clicking “Add as result layer”.
Meteo Object tab by tab 51
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 64 Mesoscale minimum roughness as a Result layer shown on map
12.3.8 Report
Figure 65 Reports from Meteo Object
The Report tab lets you create a report, where a number of optional tables and graphics can be included. A
template with a preferred setup can be saved for later use.
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12.4 Meteo analyser
The Meteo Analyser is a tool started from the Climate tab:
The Meteo Analyser works directly on the data from one or several Meteo Objects. It can therefore perform
operations that are not possible within the individual Meteo Objects, such as:
Graphic comparison of data from multiple Meteo Objects.
Disable/Enable concurrent data from multiple Meteo Objects.
Substitute/Fill data from one signal to another, with the option of applying scaling factors.
Cross predict to set up and perform a cross prediction based on the WAsP model from height to height, and
from mast to mast (test the accuracy of the model vertical and horizontal extrapolations). In addition, RIX
correction parameters can be found.
Time variation data files (.WTI) can be generated from one or more time series affected by gaps, by
merging/interpolating/patching. The .WTI files generated hold a complete one-year dataset with user-defined
time resolution for use in time-varying PARK calculations or for detailed loss calculations.
Scaling creates a new time series based on the Scaler, for immediate comparison with measurements (e.g.
downscale mesoscale data to a measurement mast and compare the two signals. This can then be used for
post-calibration of the initial result to get a perfect match with measurements).
RSD verification based on the IEA Wind Expert Group recommended practices.
Meteo analyser: tab by tab 53
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12.5 Meteo analyser: tab by tab
12.5.1 Data: overview and selection of data
Figure 66 Selection of data in Meteo Analyser
Figure 67 "Show time lines" gives a nice temporal overview of selected data
Meteo analyser: tab by tab 54
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 68 The view allows to filter the visible datasets by the Purpose given in the relevant Meteo Object
12.5.2 Graphics: Compare time series
Figure 69 Graphic comparison of more Meteo Object data.
In the Graphics tab you will see the same graphs as in a Meteo Object, but coming from multiple Meteo Objects.
Meteo analyser: tab by tab 55
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
12.5.3 Substitute: Perform data substitutions
We never overwrite the original data. Thus, first of all, a new data series will be created or selected, if one or
more substituted series have been created. The name of this new dataset will get the extension “Subst.” as the
last part of the name.
Figure 70 Substitution of data
Then, choose the time series that needs substitutions/repair in the field Base new substitution data series on.
Then click Create.
Now, there are two ways to perform the substitution:
Manual: based on a time series graphic view, where intervals for substitution are marked manually:
select "start" and "end" of interval by right clicking.
Auto: where the entire time series is checked for gaps to be filled.
In both cases, the final window you’ll get is the following. Here, you can decide which signal(s) are to be
substituted and the source and transfer function (scale and offset).
Typically, only disabled and missing data records will be substituted (while disabling of “bad data” is performed
first), and only enabled data are used for the substitution.
Meteo analyser: tab by tab 56
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 71 After choosing between Manual and Auto, this screen will let you decide what data from the Source
instruments should be used to patch missing or disabled data in the Target.
12.5.4 Cross predict: WAsP vertical and horizontal extrapolation
Cross prediction from one mast or height to another by a model based on concurrent data is the best way to find
how well the model performs on a site. The model’s ability to horizontally and vertically extrapolate is tested in
one process on concurrent data.
Four different models can be currently tested. The selection is done by choosing in the field Use the type of link
between windPRO and WAsP:
a Site Data Object, for a WAsP calculation
a WAsP-CFD result file
the Scaler, to run the calculation in the time domain (again, choose with WAsP or WAsP-CFD)
Next, choose the link itself in the sixth column of the table, which will change name according to your choice
above. For example, in the case of a classic WAsP-based calculation, we select the Site Data Object used for
STATGEN:
Meteo analyser: tab by tab 57
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Then, select between which signals/heights the calculation should be done. Typically, between different heights
at one mast, and between same heights at different masts.
Finally, click Calculate.
The results will be shown by default as the relative error made by the model, but you can switch to the absolute
error, or simply the calculated wind speed, which can be compared with the measurements, already shown:
Figure 72 Results of cross predictions
If cross predictions are poor, there can be several reasons:
1. Measurement equipment is poorly calibrated
2. Masts are wrongly positioned in the terrain
3. Terrain is not described well enough (roughness, height contours, summit detail, local obstacles)
4. The wind climate is not the same at the different masts (and thereby the model is not able to cross-
predict accurately)
5. The steepness in the terrain is high and a well-know modelling problem, related to flow separation,
results in poor model handling of the wind flow transformation.
For the last one a “fix” is available: the RIX correction. If steepness seems to be the problem, the tab RIX
correction/evaluation can be used to find the best RIX correction parameters (and to evaluate if the RIX method
seems to fix the cross prediction issue). It can only be used if at least two masts are available on site!
The RIX correction/evaluation tool shows the logarithmic wind speed deviation versus the Delta RIX. From the
site-specific trend line obtained from the cross prediction errors, the slope (Alfa) is extracted, and can then be
used in the RIX correction, either in PARK or in LOSS & UNCERTAINTY. In the figure below, the value for Alpha
of 0.5 would be the choice in the RIX correction tool.
Meteo analyser: tab by tab 58
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 73 The RIX correction/evaluation tool
Only the cross predictions calculated on the previous tab can be used in the Rix evaluation. See further
documentation on RIX calculation in 3.4.11 RIX calculation or in the PARK or LOSS & UNCERTAINTY manual
sections.
In complex terrain, however, the real solution is to abandon a linear model such as WAsP, and upgrade to a
CFD calculation!
Finally, the prediction versus measurement can be inspected with the Profile viewer. But note that only one
measurement point is shown - the one from the selection “Predicted at”. However, more profiles can be shown
based on the different predictors (if more exist). For analyses of how well the vertical profile is predicted, use
the Meteo Object.
Meteo analyser: tab by tab 59
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 74 Prediction versus measurement inspected in the Profile viewer
NOTE: The profiles are ONLY shown if you have checked the “Calculate profiles for graphic display” BEFORE
running the cross prediction calculation:
Figure 75 Check for profile calculation
12.5.5 Time variation: complete 1 year of data
WTI (WindTImevariation) is the extension given to the file generated with this tool. Therefore, the tool is simply
named the WTI Generator.
The basic idea is that, for some purposes like calculation of the expected AEP variation in time (as, for example,
12-24 tables for PPA negotiation), often some data are missing, e.g. 15 days. Therefore, no production will be
calculated for that half month. Leaving out half a month is, of course, not realistic, but it might not need to be a
very accurate calculation for that half month. In this case, the WTI generator is convenient since it can fill in the
gaps in reasonably smart ways and make sure that every 10’ or 1 h record has a reasonable value for wind
speed and direction (and other parameters like temperature, if selected).
Meteo analyser: tab by tab 60
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 76 Generation of complete time series with no gaps. The setup for generation of a complete wind data
series. It can then be used for calculating a “complete” time varying AEP and/or detailed loss calculation.
Another use is in loss calculation. If, for example, the loss due to shut down below -20
o
C shall be calculated, a
time series with both wind and temperature can be used, where the loss module finds how much energy is
calculated to be produced in the time steps where temperature is below 20
o
C. If the temperature sensor was
not working all the time (1 year), or simply not present, data can be substituted from a nearby met station or
mesoscale data into the basic measurement so that all relevant variables are available after the processing by
the WTI generator.
Basically, three methods are available for filling gaps:
Take from other measurement (other height, other mast or a dataset like NCAR)
Fill the gap by linear interpolation (if the gap is smaller than X hours)
Fill by patching (copying nearest period of same length into the gap)
The three methods can be used in combination. Data will be “resampled” to any user-defined time resolution,
but, typically, a 10’ or 60 resolution should be used. NOTE: taking data from another mast does not include any
scaling options! Eventually, scaling is needed to bring the two masts to the same level. This must be done
upfront with the Substitute function in the Meteo Analyser.
The .WTI file is, by default, saved in the project folder and can be selected from PARK Time Varying calculation
or from the LOSS & UNCERTAINTY module. The wind speed data is automatically scaled to the calculated
mean wind speed for the actual site in order to have as correct of a distribution of the calculated AEP on time
stamps as possible. It is possible to re-use the WTI file in another project
Meteo analyser: tab by tab 61
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12.5.6 Scaling create a new scaled time series using the Scaler
The scaling can be used on measurements as well as model data. The most obvious use is to scale mesoscale
data to a mast position for comparison. This approach is described here.
The procedure is to compare mesoscale data downscaled to a measurement station (cleaned using mesoscale
terrain and applied with local microscale terrain) to the actual measurements. If the match is not perfect, the
downscaled data can then be forced to match an iterative procedure using scaling factors on directional, diurnal
and monthly wind speeds. The following is a demonstration of the procedure.
Figure 77 List of data sets (Meteo Objects) in Meteo Analyser
The Meteo Objects in the project are shown above. You only need to check the datasets used for the operation
the Meteo Object representing the measuring station where the mesoscale data shall be “scaled to” - in this
case, the East Mast. Then proceed to the Scaling tab:
Figure 78 Scaling setup in meteo analyser
Meteo analyser: tab by tab 62
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
The only Meteo Object that appears in the “Scale to Meteo Object” field is indeed the one selected above.
“Scale from” is where the Scaler is chosen and set up, and the source Meteo Object(s) is selected. In this
scenario, the EMD Default Meso Scaler is chosen, together with the EMD-WRF mesoscale data near the mast.
Click Create scaled data series and the transfer function created by the Scaler generates a time series based
on the mesoscale data, at the mast position.
Now, let’s Switch to the Graphics tab to start the comparisons:
Figure 79 Compare scaled to measured time series (10’ vs 1h values, of course!)
If the match looks reasonable at a time series level, the real evaluation will be on the aggregated presentations
of concurrent data.
Figure 80 Monthly comparison scaled and measured
Meteo analyser: tab by tab 63
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Looking at the monthly wind speeds, it is seen the monthly variations match reasonably well, although there is
clearly a seasonal bias (overestimation in winter months and viceversa in summer the site is in the Southern
emisphere!).
Another interesting comparison is by direction:
Figure 81 Directional comparison, scaled (green) and measured (red)
If we want a perfect match, the post-calibration can be used. The number of sectors can be increased for a more
detailed work.
Click the Excel button on the graph, and copy the data that constitute it.
Meteo analyser: tab by tab 64
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 82 Extracting data from the graph
Figure 83 Calculating the ratios in Excel. Note the huge correction required in Sectors 8 and 9.
The data are copied to Excel, and the ratio measured/scaled (sic!) is calculated.
Now, return to the Scaler tab and open its Setup. Here, the ratios are inserted by pasting them in the Post
calibration tab, sector-wise approach.
Meteo analyser: tab by tab 65
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 84 Enter the post calibration factors in the Scaler. Note how the very large corrections required in Sectors
8 and 9 have been trimmed by windPRO to the default limit of ±25%, a value that can be changed above, if
really needed.
Click Ok to return to the main window, where you re-run the model; and the result is:
Meteo analyser: tab by tab 66
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
Figure 85 Compare calibrated scaled data to measured. The two sectors where the calibration was not sufficient
are the only ones not perfectly matching the measurements.
Now, other aggregated results can be evaluated, and further corrected with the same procedure.
Figure 86 Monthly and diurnal comparison of measured and scaled data
Meteo analyser: tab by tab 67
© EMD International A/S www.emd.dk windPRO 4.1 September 2024
What is important to notice is that the scaling can sometimes be a compensation for how well the calculation
model handles the terrain. If the hill speed-up is over/under estimated, this can be compensated with the scaling.
This compensation would not then work for all the site, only at the parts of the site that have similar speed-up
errors. Therefore, the scaling must be handled very carefully, especially in complex terrain. Having more masts
to test the Scaler settings will, of course, be the best method since it gives a more detailed feedback.
When the Meteo Analyser session is finalized, the Apply button writes the modifications to the Meteo Objects.
For example, the series to the mast Object will be written there, and the data can be used in calculations as a
long-term (!) virtual mast.
12.5.7 RSD verification
Remote Sensing Devices (RSD) will often be installed next to a traditional measurement mast to evaluate the
quality of the device. An expert group has established recommendations:
These recommendations have been transferred onto the RSD Verification tool in windPRO, which will reproduce
exactly the same tables and graphs required in the IEA text. A link to the document is available in windPRO:
please refer to it for knowledge.
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Figure 87 Example graph from RSD verification tool
12.6 Flagging and data screening
windPRO lets you visually highlight data which meet a set of logical expressions, with the purpose to assist in
screening and cleaning data without having to scroll through multiple signals simultaneously to spot problematic
data.
For information about how to use flags, see: Quick guide Cleaning Data with flagging in meteo. The following
section goes into details about the flagging system.
12.6.1 What is a flag?
A flag is a set of logical expressions which can be used to define certain phenomena such as icing, spiking and
faulty sensors (or any other trigger). A simple example could be the one below:
If (Wind speed is less than 0.2 m/s AND Temperature is less than 0°)
OR (Wind direction changes less than 2° AND Temperature is less than 0°)
THEN Show a blue flag at the time where the above conditions are met.
Such a set a of conditions will result in a flag being displayed in the background of the time series graph, XY
graph or wind speed relations graph:
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Flags do not directly influence or change the data in any way but are stored as metadata. Flagging can however
be used to disable some or all the highlighted data. Any changes to the original data only occur when you actively
decide to disable data.
A flag consists of a name and color. A flag can contain multiple cases, which group conditions together. The
properties of a flag can be seen below:
Notice the “Action” property. This allows you to create a flag which looks at the temperature but applies the flag
to the wind speed signal. The signals used in a condition may thus not be the same as the signals being flagged.
12.6.2 Building conditions
To add a new flag, open your Meteo Object (also from the Meteo Analyser). Select the “Graphics” tab and click
on the “Edit flags” button. This will open the Setup window. windPRO comes with four pre-defined categories of
flag: Icing, Bad signal, Mast shadow and Other. Since they are all site-specific, they are still empty. You can edit
these flag categories or create your own.
When you Add a new case under a certain category, and the Add a condition, the following window appears,
consisting of five parts:
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Type of data to evaluate
Signals to evaluate
Operator and threshold to
evaluate data against
Duration for which the
condition should stay true
Special considerations
In the following section the properties of the different parts are explained
Type of data to evaluate
The first property to define is the type of data to evaluate. The choice of data type influences the options available
further on. The formulas of the types of data to evaluate can be found below:
Type of Data
Example
Mathematical expression
Value
A is equal to 0.5
If
Difference
Difference between A and B is equal to 0.5
If
Absolute difference
Absolute difference between A and B is equal to 0.5
If
Ratio
Ratio between A and B is equal to 0.5
If
You can decide if data should be
flagged when B=0 using the
“Condition met if second signal is
zero”
Shear
Shear between A and B is equal to 0.5
if
You can decide if data should be
flagged when B=0 using the
“Condition met if second signal is
zero”
Change in time
Change in time of A is equal to 0.5
If
Signals to evaluate
Next step in the condition building process is to select which signal(s) to evaluate. You can decide to evaluate
a specific signal with a name (e.g. the wind speed at 60 m), or all signals of a certain type (e.g. the mean wind
speed from any sensor):
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In the above example, the conditions will be tested against all the signals categorized in the Data setup as “Mean
wind speed”. If just one of the mean wind speed signals meets the conditions, then the condition will be true.
Bear in mind, that you can flag another signal than the one used in the condition. For instance, you can use the
Turbulence Intensity signal in a condition, and then display a flag only on a wind speed signal.
When you chose a type of data involving the evaluation of two signals, you can use the “signal type” to evaluate
against any other signal of the same type, but at lower, same or higher height. This can for instance be used for
identifying wind speed inversions.
Operator and threshold to evaluate data against
A number of operators are available to compare the signal to a threshold. For example, consider a wind speed
signal with the following values: 0,5,10,15,20 m/s. The conditions will then be true for the data below:
If value of wind speed @80m is
Equal to
10
Then the condition is true for
10
If value of wind speed @80m is
Not equal to
10
Then the condition is true for
0;5;15;20
If value of wind speed @80m is
Less than or equal to
10
Then the condition is true for
0;5;10
If value of wind speed @80m is
Greater than
10
Then the condition is true for
15;20
If value of wind speed @80m is
Greater than or equal to
10
Then the condition is true for
10;15;20
If value of wind speed @80m is
Within interval
5 and 15
Then the condition is true for
5;10;15
If value of wind speed @80m is
Outside interval
5 and 15
Then the condition is true for
0;20
If value of wind speed @80m is
Missing
-
Then the condition is true for
-
Condition over multiple consecutive time steps
When building a condition, it is possible to specify for how long this condition must stay true before the flag is
applied to the data.
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The conditions are evaluated differently over time depending on the type of data being evaluated:
Example Type of Data
Flag data
Value of A is equal to 0.5 over 2 consecutive time steps
If AND
Difference between A and B is equal to 0.5 over 2
consecutive time steps
If AND
Absolute difference between A and B is equal to 0.5
over 2 consecutive time steps
If AND
Ratio between A and B is equal to 0.5 over 2
consecutive time steps
If AND
Shear for A and B is equal to 0.5 over 2 consecutive
time steps
if AND
Change in time of A is equal to 0.5 over 3 consecutive
time steps
If
AND No missing samples between and
Special considerations
They appear only in some cases. If a condition involves dividing numbers (ratios), there is a chance that the
denominator will be zero. How to handle division by zero can be controlled using the “Condition met if second
signal is zero”. Checking it means the condition is considered true, even if there is no value due to division-by-
zero.
12.6.3 Multiple conditions
A case can contain multiple conditions. All conditions must be met before a flag can be applied to the time step.
12.6.4 Actions for flags
Once the conditions have been defined, it is time to decide which signals to flag. Per default, the flag will be
applied to all signals used in the condition builder, but this can be changed. There are two ways of specifying
which signals should be flagged:
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“Affected signal”: Flag (some of) the signals which are used in the conditions.
“Specific signal”: Flag whatever signal you want, no matter which signals are used in the condition.
Example: Create a case with two conditions: One involving temperature, and another involving wind speed.
You can specify what should happen when these two conditions are met:
o All affected signals: The flag will be applied to the temperature signal and wind speed signal used in the
condition at the time steps where both conditions are met.
o All affected Mean wind speed signals: The flag will only be applied to the wind speed signal used in the
condition at the time steps where both conditions are met. The flag will thus not be applied to the
Temperature signal.
If you select both All affected Mean wind speed signal and All affected Temperature signals, this will be equal
to selecting All affected signals.
If you select Specific signal, you can specify that the flag should be applied to a signal, regardless of the signals
used in the conditions.
You can decide if the flag should be applied to more data than just the data which meets the conditions:
For example, the data surrounding an icing event are often suspicious. Then it’s possible to extend the flag, so
it is applied to more data than meets the conditions:
Time steps where conditions are met:
Time steps to flag:
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These extensions can also be negative numbers, so fewer time steps are flagged.
The actual number of flagged samples can be seen in the left-side window:
Each case applies a flag to a number of samples. Since multiple conditions can be met at the same time, the
total number of applied flags is not necessarily the sum of samples meeting the conditions of the cases. In the
image above, the two cases flag data in many of the same time steps.
12.6.5 Flags in Meteo Analyser
The flagging feature is used in the same way in the Meteo Analyser as in the Meteo Object.
When creating conditions in Meteo Analyser, the list of available signals depends on the selection of Meteo
Objects in the Data tab.
No flags created in the Meteo Analyser are added to the individual Meteo Objects. Likewise, flags created in the
individual Meteo Objects are not added in Meteo Analyser. It is therefore possible to define one set of flags in
the individual Meteo Object, and another set of flags in the Meteo Analyser. As always, any disabling made in
Meteo Analyser is applied to the individual Meteo Object.
Flagging data with different resolutions
Often in Meteo Analyser, you will have data at different temporal resolutions, e.g. one dataset in 1-hour time-
steps, and another in 10-minute time-steps. If you create a condition which applies the flag to both datasets,
then it is not possible to see which dataset the flag is applied to, as the flags for each dataset will be merged on
the graph. When using the disable or enable features in the flagging window, the two time-series will be treated
individually, however this cannot be distinguished when viewing the graph.
12.6.6 Import/Export flags
Flags can be exported from the “Edit flags” window by clicking the Export button:
The entire flag setup (flag names, colors, cases, conditions and actions) is saved in a XML file in a user-defined
location. The exported flag definition can be used in different Meteo Objects, projects, and in Meteo Analyser.
To Import a flag setup, click the Import from the Edit flags window. Any existing flag definition will be
overwritten.
If you import flag definitions from a Meteo Object which does not contain the same signals as the Meteo Object
you are exporting to, you will be asked to re-assign the signals in the conditions:
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Considerations for creating templates
Using the Import/Export functionality, you can create templates for use in other projects. When creating such a
template it is recommended to always define the conditions using the “signal type” conditions, and then apply
the flag to an “Affected signal”:
This way, the template can be used in any Meteo Object without having to reassign any missing signals. This
strategy can also be useful when re-using flag definitions for multiple Meteo Objects in the same project.
12.6.7 Showing flags in time series graph
Flags can be shown in three graphs: the time series graph, XY graph and Wind speed relations graph. They can
also be shown in the Time series table (Data tab).
To see the flags in the Time series graph, make sure the “Show flags” checkbox is ticked.
If you only want to display some of the flags or cases, you can open the flag window and untick the relevant
checkboxes in the flag list:
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12.6.8 Showing flags in time series table
Flags are shown in the time series table found in the Data tab. The flags are shown as a small square next to
the values flagged:
Hover the mouse over a flag to display the flag name.The flags shown in the time series table reflect the choice
of visible flags in the “Edit Flags”.
You can select all data with a certain flag using the Select button in the right-hand side:
12.6.9 Showing flags in XY graph and Wind Speed Relations graph
When showing flags in the XY graph, the data points will be colored with the same color as the flag:
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If you use the “Color code with third series” option, the flagged samples will be shaped as triangles:
12.6.10 Cleaning data with flags
There are two ways to disable data with flags.
One way is to use the graph controls in the bottom of the “Edit flag” window. The graph setup can be used
without having to close the “Edit flags” window. You can jump between flagged data segments using the Next
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or Previous buttons in the Edit flags” window, when showing the time series graph. You can control which flags
to jump between by highlighting a flag in the list of flags.
To disable the flagged data which has been highlighted in the graph, simply click the Disable button. If you want
to speed up your disabling process, you can click the small Disable menu, and select Automatically move to
next flag, after disabling. Then the next flag will be highlighted.
Alternatively, you can disable the traditional way using the select “Advanced Disable/enable” functionality, see
section 12.3.4.1.
Currently, flags are completely independent from disabling, so any changes to the flag will not influence the
disabling and vice versa. It is not yet possible to print a report of the amount of data disabled due to a flag.