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JCSDA / CRTMv3

CRTMv3 repository for coordinated development and releases. Code history is not carried in this repository prior to v3, to reduce the cloning overhead. For v2.x history leading up to v3, see JCSDA/crtm repository.
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CRTM surface emissivity #183

Open chengdang opened 1 week ago

chengdang commented 1 week ago

Current status:

Vis/IR default

    Default_IRlandCoeff_File    = 'NPOESS.IRland.EmisCoeff.bin'
    Default_IRsnowCoeff_File    = 'NPOESS.IRsnow.EmisCoeff.bin'
    Default_IRiceCoeff_File     = 'NPOESS.IRice.EmisCoeff.bin'
    Default_VISlandCoeff_File   = 'NPOESS.VISland.EmisCoeff.bin'
    Default_VISsnowCoeff_File   = 'NPOESS.VISsnow.EmisCoeff.bin'
    Default_VISiceCoeff_File    = 'NPOESS.VISice.EmisCoeff.bin'

CRTM_NPOESS_Emissivity

chengdang commented 1 week ago

In comparison: U Mich surface emissivity: https://huang.engin.umich.edu/182-2/

File: surface_emissivity_for_11types_53deg_2.nc (from 10-200 cm^-1, every 10 cm^-1)

Umich_Emissivity_Type

chengdang commented 1 week ago

Comparison: snow emissivity, CRTM default versus U Mich: CRTM_Umich_IR

chengdang commented 1 week ago

IR Snow/Water Optional tables:

https://ieeexplore.ieee.org/document/10050863 https://www.mdpi.com/2072-4292/15/23/5509

BenjaminTJohnson commented 2 days ago

https://e4ftl01.cr.usgs.gov/MEASURES/

Here are brief descriptions of the MEaSUREs products available in the directories:

CAM5K30CF: Cloud fraction data for climate modeling. CAM5K30EM: Emission data for atmospheric studies. GEOLST4KHR: Land surface temperature at high resolution. GFCC30: Global Forest Cover Change in various formats (FCC, SR, TC, WC). GFSAD: Global Food Security analysis data, focusing on cropland extent and distribution. GLanCE30: Global Land Change datasets. NASADEM: Digital elevation models derived from Shuttle Radar Topography. SRTM: Topography from Shuttle Radar Topography Mission. VCF5KYR: Vegetation Continuous Fields over a 5-year period. VIP: Vegetation indices and phenology products.

Plan to align the CAM5K30EM dataset with land surface types:

Obtain a Land Surface Type Dataset: Use a global land cover product like MODIS Land Cover (MCD12Q1) or the ESA CCI Land Cover datasets.

Reproject and Resample: Ensure both datasets are in the same projection and spatial resolution. You can use tools like GDAL or Python libraries like rasterio and pyproj for this.

Spatial Alignment: Use xarray or rasterio in Python to align the grids, overlay the datasets, and extract corresponding land types for CAM5K30EM grid cells.

Need to consider land surface types in UFS. I've emailed Mike Barlage.

https://github.com/ufs-community/ccpp-physics/blob/5a363134a77535f35594e56b58ba1e6141a23d2b/physics/Radiation/radiation_surface.f#L798

appears applicable only to LW radiance (e.g., for RRTMG, but not 100% sure).