EMD-WRF India

Illustration of the Data Coverage of the EMD-WRF India Dataset

Introduction and Model Domain

EMD-WRF India is a high resolution mesoscale dataset modelled and provided by EMD International A/S. The dataset covers major part of India, all of Sri Lanka and parts of Pakistan. The model domain for EMD-WRF India is shown in the figure to the right.

Please Note:

This dataset is no longer updated.
It is feely available to windPRO users with an active service subscription (see below).
If you need updated mesoscale data from within this region, please consider the EMD-WRF On-Demand Service

Dataset Description

The mesoscale model is run at a spatial resolution of 0.029°x0.029°, approximately 3x3 km, and with hourly temporal resolution. ERA Interim data from ECMWF (http://www.ecmwf.int) is the global boundary data. The timespan of the data is back to 1994 and up until the latest available boundary data (see below for the Release Schedule). Data access is via WindPRO’s user friendly interface to on-line data.

Release Schedule

Data is updated monthly with approximately 3 months delay defined by ERA Interim's availability. Before contacting support because of delays in the release schedule, please check ERA interim's availability on the ERA availability page. EMD-WRF India data cannot be computed before ERA interim data is available.

When downloading the most recent data, please note that the last day of the last month will be missing until the next month is added. This is because, in order to compute a full day of data, the 24:00h (or 0:00 of following day) time stamp is required, but the last time stamp of a month in ERA interim data is 18:00 h.

Usage Note: The EMD-WRF India (ERA-Interim) dataset is discontinued from ultimo 2019

2020-02-20: The last month with ERA-Interim data was august 2019 as ECMWF has discontinued this dataset and has replaced it with the ERA5 Data. EMD has ceased to update the EMD-WRF India (ERA-Interim) dataset as the source data is no longer available.

Validation

The model-setup has been validated through various internal investigations on masts spatially distributed in the modelling area.
The findings (the correlations) are summarized in the product datasheet available (here).
In addition, the EMD-WRF modelling setup has been evaluated in a number of external benchmarks.
We have a separate EMD-WRF Benchmark Wiki-Page that holds links to those investigations.

Required modules/licenses

To access the EMD-ConWx meso-scale data the following licenses/modules are required in your WindPRO setup:

Basis
METEO

If you are holding an active windPRO service subscription and the modules above, then, when the license fee is paid, you then have access to the full dataset without further cost. The price is available from the price-list on the EMD-homepage. Downloading of data is unrestricted for licenced users, however, a "fair use" policy applies. Unlicenced users may download three months of data from any point, however, multiple downloads are not allowed from the same point.

Visit EMD online ordering to purchase the needed licences.

Dataset Parameters

A large quantity of useful parameters are available directly in WindPRO to aid in your analysis.
The different parameters in the EMD-WRF India dataset that are available from within WindPRO are shown in the table below.

Table: Overview of EMD-WRF India Dataset Parameters (3 km grid).
Parameter	Unit	Description	Type
time		UTC time stamp
psfc	Pa	Pressure at site	Instantaneous
msl	Pa	Pressure at mean sea level	Instantaneous
wSpeed.x	m/s	Wind speeds at different physical levels (x). Heights (x): 10m, 25m, 50m, 75m, 100m, 150m, 200m	Instantaneous
wDir.x	deg	Wind speeds at different physical levels (x). Heights (x): 10m, 25m, 50m, 75m, 100m, 150m, 200m	Instantaneous
wSpeed.0-30mb	m/s	Wind speeds at pressure level 0-30mb.	Instantaneous
wDir.0-30mb	deg	Wind speeds at pressure levels 0-30mb.	Instantaneous
wSpeed.850hpa	m/s	Wind speeds at pressure level 850hPa.	Instantaneous
wDir.850hpa	deg	Wind speeds at pressure levels 850hPa.	Instantaneous
temperature.x	celcius	Temperatures at different heights (x) Heights (x): 2m and 100m	Instantaneous
waterTemp	celcius	Water temperature	Instantaneous
soilTemp.0-10cm	celcius	The temperature in the upper 10 cm of the soil	Instantaneous
relHumidity.2	%	Relative humidity in height 2m above ground level	Instantaneous
snowDepth	m	Snow depth (if present)	Instantaneous
vis.s	m	Visibility at surface	Instantaneous
sensHeatFlux.s	w/m2	Sensible Heat Flux at surface	Instantaneous
totPrecip.s	kg/m^2	Total Precipitation at surface	1h Accumulated
downShortWaveFlux.s	w/m2	Downward shortwave irradiance at surface	1h Average
totalCloudCover.a	%	Total cloud cover in atmosphere	1h Average
convCloudCover.a	%	Convective cloud cover in atmosphere	1h Average
Data below this line are not shown in a default import of EMD-WRF India data, but can be made available by clicking on the "+" button in the lower left corner of the import table.
4LFTX	K	N/A
rmol	1/m	Inverse Monin-Obukhov-Length ^[1]
znt	m	Rougnhess length
sqrtTKE.x	m/s	Wind speed given as standard deviation in m/s. Derived from the turbulent kinetic energy (TKE). Results available in different physical levels. Heights (x): 10m, 25m, 50m, 75m, 100m, 150m, 200m	Instantaneous
cloudWater.100	kg/kg	Parameter intended for estimating probability of icing.^[2]	Instantaneous
cloudIce.100	kg/m^2	Parameter intended for estimating probability of icing. ^[2]	Instantaneous

Attribution

If data from this dataset is used within any private or public disseminations, then EMD and its data providers must be acknowledged.

Source: 
EMD-WRF India - Copyright (C) - EMD International A/S, 2019. Distribution through EMD and windPRO.
This dataset uses ERA-Iterim which is being developed through the European Centre for Medium-Range Weather Forecasts (ECMWF).

Footnotes

↑ It is still being investigated whether this inverse Monin-Obukhov-Length can be used for stability clasification.
↑ ^2.0 ^2.1 CloudWater and cloudIcing values are extracted directly from the WRF meso-scale model and are normal output parameters of the same run as the other parameters (wind, temperature etc.). They are controlled by the WRF microphysics scheme for which Ferrier was used. For further information, please access the numerous internet resources about WRF use. EMD has not done any validation on the parameters, so they are provided as is.

[rmol-1] It is still being investigated whether this inverse Monin-Obukhov-Length can be used for stability clasification.

[ice-2] 2.0 ^2.1 CloudWater and cloudIcing values are extracted directly from the WRF meso-scale model and are normal output parameters of the same run as the other parameters (wind, temperature etc.). They are controlled by the WRF microphysics scheme for which Ferrier was used. For further information, please access the numerous internet resources about WRF use. EMD has not done any validation on the parameters, so they are provided as is.

[1]

[2]