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Merge ERA5 Ag version 2.0 and variable update
Merge ERA5 Ag version 2.0 and variable update
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‎awesome-gee-catalog-examples/weather-climate/AGERA5-DATASETS‎

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// Read in Image Collection and get first image
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var agera5_ic = ee.ImageCollection('projects/climate-engine-pro/assets/ce-ag-era5/daily')
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var agera5_ic = ee.ImageCollection('projects/climate-engine-pro/assets/ce-ag-era5-v2/daily')
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var agera5_i = agera5_ic.first()
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// Print first image to see bands
@@ -12,6 +12,6 @@ Map.addLayer(agera5_i.select('Precipitation_Flux'), {min: 0, max: 1, palette: pr
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Map.addLayer(agera5_i.select('Temperature_Air_2m_Max_24h').selfMask().subtract(273.15), {min: -10, max: 50, palette: temp_palette}, 'Temperature_Air_2m_Max_24h')
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Map.addLayer(agera5_i.select('Temperature_Air_2m_Min_24h').selfMask().subtract(273.15), {min: -10, max: 50, palette: temp_palette}, 'Temperature_Air_2m_Min_24h')
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Map.addLayer(agera5_i.select('Temperature_Air_2m_Mean_24h').selfMask().subtract(273.15), {min: -10, max: 50, palette: temp_palette}, 'Temperature_Air_2m_Mean_24h')
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Map.addLayer(agera5_i.select('Dew_Point_Temperature_2m_Mean').selfMask().subtract(273.15), {min: -10, max: 50, palette: temp_palette}, 'Dew_Point_Temperature_2m_Mean')
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Map.addLayer(agera5_i.select('Snow_Thickness_Mean'), {min: 0, max: 100, palette: prec_palette}, 'Snow_Thickness_Mean')
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Map.addLayer(agera5_i.select('Snow_Thickness_LWE_Mean'), {min: 0, max: 20, palette: prec_palette}, 'Snow_Thickness_LWE_Mean')
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Map.addLayer(agera5_i.select('Dew_Point_Temperature_2m_Mean_24h').selfMask().subtract(273.15), {min: -10, max: 50, palette: temp_palette}, 'Dew_Point_Temperature_2m_Mean')
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Map.addLayer(agera5_i.select('Snow_Thickness_Mean_24h'), {min: 0, max: 100, palette: prec_palette}, 'Snow_Thickness_Mean')
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Map.addLayer(agera5_i.select('Snow_Thickness_LWE_Mean_24h'), {min: 0, max: 20, palette: prec_palette}, 'Snow_Thickness_LWE_Mean')

‎docs/projects/agera5_datasets.md‎

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# AgERA5 (ECMWF) dataset
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# AgERA5 (ECMWF) dataset, version 2.0
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Daily surface meteorological data for the period from 1979 to present as input for agriculture and agro-ecological studies. This dataset is based on
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the hourly ECMWF ERA5 data at surface level and is referred to as AgERA5. Acquisition and pre-processing of the original ERA5 data is a complex and
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the hourly ECMWF ERA5 data at surface level and is referred to as AgERA5, version 2.0. Acquisition and pre-processing of the original ERA5 data is a complex and
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specialized job. By providing the AgERA5 dataset, users are freed from this work and can directly start with meaningful input for their analyses and
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modeling. To this end, the variables provided in this dataset match the input needs of most agriculture and agro-ecological models. Data were
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aggregated to daily time steps at the local time zone and corrected towards a finer topography at a 0.1° spatial resolution. The correction to the 0.
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| Variable | Details |
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|---------------------------|--------------------------------------|
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| Wind speed ('Wind_Speed_10m_Mean') | - Units: Meters/second |
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| Wind speed ('Wind_Speed_10m_Mean_24h') | - Units: Meters/second |
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| | - Scale factor: 1.0 |
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| Minimum temperature, 2m ('Temperature_Air_2m_Min_24h') | - Units: Degrees Kelvin |
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| | - Scale factor: 1.0 |
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| | - Scale factor: 1.0 |
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| Mean temperature, 2m, nighttime ('Temperature_Air_2m_Mean_Night_Time') | - Units: Degrees Kelvin |
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| | - Scale factor: 1.0 |
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| Dewpoint temperature, 2m ('Dew_Point_Temperature_2m_Mean') | - Units: Degrees Kelvin |
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| Dewpoint temperature, 2m ('Dew_Point_Temperature_2m_Mean_24h') | - Units: Degrees Kelvin |
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| | - Scale factor: 1.0 |
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| Precipitation ('Precipitation_Flux') | - Units: Millimeters |
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| | - Scale factor: 1.0 |
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| Precipitation rain duration fraction ('Precipitation_Rain_Duration_Fraction') | - Units: Count |
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| | - Scale factor: 1.0 |
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| Precipitation solid duration fraction ('Precipitation_Solid_Duration_Fraction') | - Units: Count |
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| | - Scale factor: 1.0 |
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| Snow depth ('Snow_Thickness_Mean') | - Units: Centimeters |
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| FAO56 Reference ET ('ReferenceET_PenmanMonteith_FAO56') | - Units: Millimeters |
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| | - Scale factor: 1.0 |
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| Snow water equivalent ('Snow_Thickness_LWE_Mean') | - Units: Centimeters |
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| Snow depth ('Snow_Thickness_Mean_24h') | - Units: Centimeters |
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| | - Scale factor: 1.0 |
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| Vapour pressure ('Vapour_Pressure_Mean') | - Units: hPa |
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| Snow water equivalent ('Snow_Thickness_LWE_Mean_24h') | - Units: Centimeters |
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| | - Scale factor: 1.0 |
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| Vapour pressure ('Vapour_Pressure_Mean_24h') | - Units: hPa |
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| | - Scale factor: 1.0 |
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| Vapour pressure deficit ('VVapour_Pressure_Deficit_at_Maximum_Temperature') | - Units: hPa |
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| | - Scale factor: 1.0 |
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| Downward solar radiation ('Solar_Radiation_Flux') | - Units: J m-2d-1 |
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| | - Scale factor: 1.0 |
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| Cloud cover ('Cloud_Cover_Mean') | - Units: Fraction |
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| Cloud cover ('Cloud_Cover_Mean_24h') | - Units: Fraction |
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| | - Scale factor: 1.0 |
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| Relative humidity, 2m 06h ('Relative_Humidity_2m_06h') | - Units: Percent |
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| | - Scale factor: 1.0 |
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```js
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// Read in Image Collection and get first image
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var agera5_ic = ee.ImageCollection('projects/climate-engine-pro/assets/ce-ag-era5/daily')
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var agera5_ic = ee.ImageCollection('projects/climate-engine-pro/assets/ce-ag-era5-v2/daily')
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var agera5_i = agera5_ic.first()
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// Print first image to see bands
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Map.addLayer(agera5_i.select('Temperature_Air_2m_Max_24h').selfMask().subtract(273.15), {min: -10, max: 50, palette: temp_palette}, 'Temperature_Air_2m_Max_24h')
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Map.addLayer(agera5_i.select('Temperature_Air_2m_Min_24h').selfMask().subtract(273.15), {min: -10, max: 50, palette: temp_palette}, 'Temperature_Air_2m_Min_24h')
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Map.addLayer(agera5_i.select('Temperature_Air_2m_Mean_24h').selfMask().subtract(273.15), {min: -10, max: 50, palette: temp_palette}, 'Temperature_Air_2m_Mean_24h')
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Map.addLayer(agera5_i.select('Dew_Point_Temperature_2m_Mean').selfMask().subtract(273.15), {min: -10, max: 50, palette: temp_palette}, 'Dew_Point_Temperature_2m_Mean')
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Map.addLayer(agera5_i.select('Snow_Thickness_Mean'), {min: 0, max: 100, palette: prec_palette}, 'Snow_Thickness_Mean')
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Map.addLayer(agera5_i.select('Snow_Thickness_LWE_Mean'), {min: 0, max: 20, palette: prec_palette}, 'Snow_Thickness_LWE_Mean')
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Map.addLayer(agera5_i.select('Dew_Point_Temperature_2m_Mean_24h').selfMask().subtract(273.15), {min: -10, max: 50, palette: temp_palette}, 'Dew_Point_Temperature_2m_Mean')
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Map.addLayer(agera5_i.select('Snow_Thickness_Mean_24h'), {min: 0, max: 100, palette: prec_palette}, 'Snow_Thickness_Mean')
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Map.addLayer(agera5_i.select('Snow_Thickness_LWE_Mean_24h'), {min: 0, max: 20, palette: prec_palette}, 'Snow_Thickness_LWE_Mean')
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```
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Sample code: https://code.earthengine.google.com/?scriptPath=users/sat-io/awesome-gee-catalog-examples:/weather-climate/AGERA5-DATASETS

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