EMD-WRF Europe+ (ERA5): Difference between revisions
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== Dataset Decription == | == Dataset Decription == | ||
The meso-scale model is run at a high spatial resolution of approximately 3x3 km with data extraced in a hourly temporal resolution. [[ERA5_Data|ERA-5 reanalysis data | The meso-scale model is run at a high spatial resolution of approximately 3x3 km with data extraced in a hourly temporal resolution. [[ERA5_Data|ERA-5]] reanalysis data from ECMWF (http://www.ecmwf.int) is the global boundary data. At release time, the timespan of the data is at least 10 years back from today - the data is currently extended continiously - and will cover a minimum of 20 years during 2019. Data access is via WindPRO’s user friendly interface to on-line data and requires payment of an annual subscription fee. | ||
== Dataset Parameters == | == Dataset Parameters == |
Revision as of 11:31, 25 June 2019
Introduction
The EMD-WRF Europe+ dataset is our most accurate, high-resolution mesoscale dataset covering Europe - based on ERA-5 reanalysis data. It is the successor of the EMD-ConWx Meso Data Europe.
Note: This dataset requires an additional license (see below).
Dataset Decription
The meso-scale model is run at a high spatial resolution of approximately 3x3 km with data extraced in a hourly temporal resolution. ERA-5 reanalysis data from ECMWF (http://www.ecmwf.int) is the global boundary data. At release time, the timespan of the data is at least 10 years back from today - the data is currently extended continiously - and will cover a minimum of 20 years during 2019. Data access is via WindPRO’s user friendly interface to on-line data and requires payment of an annual subscription fee.
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 Europe+ dataset that are available from within windPRO are shown in the table below.
Parameter | Unit | Description | Type |
---|---|---|---|
time | UTC time stamp | ||
wSpeed.x | m/s | Wind speeds at different heights above ground (x). Heights (x): 10,25,50,75,100,150,200,300,400,500,750,1000,4000m |
Instantaneous |
wDir.x | deg | Wind directions at different heights above ground (x). Heights (x): 10,25,50,75,100,150,200,300,400,500,750,1000,4000m |
Instantaneous |
sqrtTKE.x | m/s | Wind speed given as standard deviation in m/s. Derived from the turbulent kinetic energy (TKE) at different heights above ground (x). Heights (x): 10,25,50,75,100,150,200,300,400,500,750,1000,4000m |
Instantaneous |
press.x | Pa | Pressure at different heights above ground (x). Heights (x): 10,25,50,75,100,150,200,300,400,500,750,1000,4000m |
Instantaneous |
temp.x | celcius | Temperature at different heights above ground (x). Heights (x): 10,25,50,75,100,150,200,300,400,500,750,1000,4000m |
Instantaneous |
rh.x | % | Relative humidity at different heights above ground (x). Heights (x): 10,25,50,75,100,150,200,300,400,500,750,1000,4000m |
Instantaneous |
cloudWater.x | kg/kg | Cloud water content at different heights above ground (x). Heights (x): 10,25,50,75,100,150,200,300,400,500,750,1000,4000m |
Instantaneous |
cloudIce.x | kg/m^2 | Cloud icing content at different heights above ground (x). Heights (x): 10,25,50,75,100,150,200,300,400,500,750,1000,4000m |
Instantaneous |
psfc | Pa | Pressure at site | Instantaneous |
msl | Pa | Pressure at mean sea level | Instantaneous |
wSpeed.850hpa | m/s | Wind speeds at pressure level 850hPa. | Instantaneous |
wDir.850hpa | deg | Wind speeds at pressure levels 850hPa. | Instantaneous |
temperature.2 | celcius | Temperatures at 2m | 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 | Show 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/s | Total Precipitation at surface | 1h Average |
downShortWaveFlux.s | w/m2 | Downward shortwave irradiance at surface | 1h Average |
swdDir.s | w/m2 | Direct shortwave irradiance at surface | 1h Average |
swdDif.s | w/m2 | Diffuse shortwave irradiance at surface | 1h Average |
cloudBottom | m | Height of cloud bottom | Instantaneous |
cloudTop | m | Height of cloud top | Instantaneous |
totalCloudCover.a | % | Total cloud cover in atmosphere | 1h Average |
convCloudCover.a | % | Convective cloud cover in atmosphere | 1h Average |
rmol | 1/m | Inverse Monin-Obukhov-Length [1] | |
znt | m | Rougnhess length | Instantaneous |
u* | m/s | U-start (friction velocity) | Instantaneous |
pblh | m | Height of the PBL boundary layer | Instantaneous |
Required Modules/Licenses
To access the EMD-WRF Europe+ mesoscale data the following licenses/modules are required in your windPRO setup:
- Basis
- METEO
- EMD-WRF Europe+
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.
Validation
The model-setup has been rigorously validated through various internal investigations on more than 300 high-quality meteorological masts spatially distributed in the modelling area. The performance statistics are summarized on the second-page of the datasheet (see this pdf-file) - here.
In addition to the EMD-validations, 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.
Acknowledgement
- Model development and integration of this dataset into EMD services - was co-supported through the WindPROSPER project. The windPROSPER project is co-funded by the Danish Innovation Fund and the EuroStars framework programme.
External Links
- WindPROSPER at Eurostars
- Innovation Fund Denmark - https://innovationsfonden.dk
Footnotes
- ↑ It is still being investigated whether this inverse Monin-Obukhov-Length can be used for stability clasification.