We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Hi,
When making an egep call using with get_inv.pl and get_grib.pl the AWS GEFS returns different data to NOMADS.
For example:
:(TMP:850 mb|HGT:500 mb|PRMSL|CSNOW.(surface)|APCP|TMAX.(2 m above ground)|TMIN.(2 m above ground)):
Will download the following variables:
APCPsfc 0,1,0 0,1,8,1 ** surface Total Precipitation [kg/m^2] CAPE180_0mb 0,108,18000,0 0,7,6 ** 180-0 mb above ground Convective Available Potential Energy [J/kg] CFRZRsfc 0,1,0 0,1,193,0 ** surface Categorical Freezing Rain [-] CICEPsfc 0,1,0 0,1,194,0 ** surface Categorical Ice Pellets [-] CIN180_0mb 0,108,18000,0 0,7,7 ** 180-0 mb above ground Convective Inhibition [J/kg] CRAINsfc 0,1,0 0,1,192,0 ** surface Categorical Rain [-] CSNOWsfc 0,1,0 0,1,195,0 ** surface Categorical Snow [-] DLWRFsfc 0,1,0 0,5,192,0 ** surface Downward Long-Wave Rad. Flux [W/m^2] DSWRFsfc 0,1,0 0,4,192,0 ** surface Downward Short-Wave Radiation Flux [W/m^2] HGTprs 12,100 0,3,5 ** (1000 925 850 700 500.. 250 200 100 50 10) Geopotential Height [gpm] ICETKsfc 0,1,0 10,2,1 ** surface Ice Thickness [m] LHTFLsfc 0,1,0 0,0,10,0 ** surface Latent Heat Net Flux [W/m^2] PRESsfc 0,1,0 0,3,0 ** surface Pressure [Pa] PRMSLmsl 0,101,0 0,3,1 ** mean sea level Pressure Reduced to MSL [Pa] PWATclm 0,200,0 0,1,3 ** entire atmosphere (considered as a single layer) Precipitable Water [kg/m^2] RHprs 12,100 0,1,1 ** (1000 925 850 700 500.. 250 200 100 50 10) Relative Humidity [%] RH2m 0,103,2 0,1,1 ** 2 m above ground Relative Humidity [%] SHTFLsfc 0,1,0 0,0,11,0 ** surface Sensible Heat Net Flux [W/m^2] SNODsfc 0,1,0 0,1,11 ** surface Snow Depth [m] SOILW0_10cm 0,106,0,0.1 2,0,192 ** 0-0.1 m below ground Volumetric Soil Moisture Content [Fraction] TCDCclm 0,10,0 0,6,1,0 ** entire atmosphere Total Cloud Cover [%] TMAX2m 0,103,2 0,0,4,2 ** 2 m above ground Maximum Temperature [K] TMIN2m 0,103,2 0,0,5,3 ** 2 m above ground Minimum Temperature [K] TMPprs 12,100 0,0,0 ** (1000 925 850 700 500.. 250 200 100 50 10) Temperature [K] TMP2m 0,103,2 0,0,0 ** 2 m above ground Temperature [K] TSOIL0_10cm 0,106,0,0.1 2,0,2 ** 0-0.1 m below ground Soil Temperature [K] UGRDprs 12,100 0,2,2 ** (1000 925 850 700 500.. 250 200 100 50 10) U-Component of Wind [m/s] UGRD10m 0,103,10 0,2,2 ** 10 m above ground U-Component of Wind [m/s] ULWRFsfc 0,1,0 0,5,193,0 ** surface Upward Long-Wave Rad. Flux [W/m^2] ULWRFtoa 0,8,0 0,5,193,0 ** top of atmosphere Upward Long-Wave Rad. Flux [W/m^2] USWRFsfc 0,1,0 0,4,193,0 ** surface Upward Short-Wave Radiation Flux [W/m^2] VGRDprs 12,100 0,2,3 ** (1000 925 850 700 500.. 250 200 100 50 10) V-Component of Wind [m/s] VGRD10m 0,103,10 0,2,3 ** 10 m above ground V-Component of Wind [m/s] VVEL850mb 0,100,85000 0,2,8 ** 850 mb Vertical Velocity (Pressure) [Pa/s] WEASDsfc 0,1,0 0,1,13 ** surface Water Equivalent of Accumulated Snow Depth [kg/m^2]
On the NOMADS server the same request will return a much smaller and (I think correct) subset of variables:
APCPsfc 0,1,0 0,1,8,1 ** surface Total Precipitation [kg/m^2] CSNOWsfc 0,1,0 0,1,195,0 ** surface Categorical Snow [-] HGT500mb 0,100,50000 0,3,5 ** 500 mb Geopotential Height [gpm] PRMSLmsl 0,101,0 0,3,1 ** mean sea level Pressure Reduced to MSL [Pa] TMAX2m 0,103,2 0,0,4,2 ** 2 m above ground Maximum Temperature [K] TMIN2m 0,103,2 0,0,5,3 ** 2 m above ground Minimum Temperature [K] TMP850mb 0,100,85000 0,0,0 ** 850 mb Temperature [K]
It seems that egrep regex is not working correctly on the AWS servers.
The text was updated successfully, but these errors were encountered:
cstner
No branches or pull requests
Hi,
When making an egep call using with get_inv.pl and get_grib.pl the AWS GEFS returns different data to NOMADS.
For example:
:(TMP:850 mb|HGT:500 mb|PRMSL|CSNOW.(surface)|APCP|TMAX.(2 m above ground)|TMIN.(2 m above ground)):
Will download the following variables:
APCPsfc 0,1,0 0,1,8,1 ** surface Total Precipitation [kg/m^2]
CAPE180_0mb 0,108,18000,0 0,7,6 ** 180-0 mb above ground Convective Available Potential Energy [J/kg]
CFRZRsfc 0,1,0 0,1,193,0 ** surface Categorical Freezing Rain [-]
CICEPsfc 0,1,0 0,1,194,0 ** surface Categorical Ice Pellets [-]
CIN180_0mb 0,108,18000,0 0,7,7 ** 180-0 mb above ground Convective Inhibition [J/kg]
CRAINsfc 0,1,0 0,1,192,0 ** surface Categorical Rain [-]
CSNOWsfc 0,1,0 0,1,195,0 ** surface Categorical Snow [-]
DLWRFsfc 0,1,0 0,5,192,0 ** surface Downward Long-Wave Rad. Flux [W/m^2]
DSWRFsfc 0,1,0 0,4,192,0 ** surface Downward Short-Wave Radiation Flux [W/m^2]
HGTprs 12,100 0,3,5 ** (1000 925 850 700 500.. 250 200 100 50 10) Geopotential Height [gpm]
ICETKsfc 0,1,0 10,2,1 ** surface Ice Thickness [m]
LHTFLsfc 0,1,0 0,0,10,0 ** surface Latent Heat Net Flux [W/m^2]
PRESsfc 0,1,0 0,3,0 ** surface Pressure [Pa]
PRMSLmsl 0,101,0 0,3,1 ** mean sea level Pressure Reduced to MSL [Pa]
PWATclm 0,200,0 0,1,3 ** entire atmosphere (considered as a single layer) Precipitable Water [kg/m^2]
RHprs 12,100 0,1,1 ** (1000 925 850 700 500.. 250 200 100 50 10) Relative Humidity [%]
RH2m 0,103,2 0,1,1 ** 2 m above ground Relative Humidity [%]
SHTFLsfc 0,1,0 0,0,11,0 ** surface Sensible Heat Net Flux [W/m^2]
SNODsfc 0,1,0 0,1,11 ** surface Snow Depth [m]
SOILW0_10cm 0,106,0,0.1 2,0,192 ** 0-0.1 m below ground Volumetric Soil Moisture Content [Fraction]
TCDCclm 0,10,0 0,6,1,0 ** entire atmosphere Total Cloud Cover [%]
TMAX2m 0,103,2 0,0,4,2 ** 2 m above ground Maximum Temperature [K]
TMIN2m 0,103,2 0,0,5,3 ** 2 m above ground Minimum Temperature [K]
TMPprs 12,100 0,0,0 ** (1000 925 850 700 500.. 250 200 100 50 10) Temperature [K]
TMP2m 0,103,2 0,0,0 ** 2 m above ground Temperature [K]
TSOIL0_10cm 0,106,0,0.1 2,0,2 ** 0-0.1 m below ground Soil Temperature [K]
UGRDprs 12,100 0,2,2 ** (1000 925 850 700 500.. 250 200 100 50 10) U-Component of Wind [m/s]
UGRD10m 0,103,10 0,2,2 ** 10 m above ground U-Component of Wind [m/s]
ULWRFsfc 0,1,0 0,5,193,0 ** surface Upward Long-Wave Rad. Flux [W/m^2]
ULWRFtoa 0,8,0 0,5,193,0 ** top of atmosphere Upward Long-Wave Rad. Flux [W/m^2]
USWRFsfc 0,1,0 0,4,193,0 ** surface Upward Short-Wave Radiation Flux [W/m^2]
VGRDprs 12,100 0,2,3 ** (1000 925 850 700 500.. 250 200 100 50 10) V-Component of Wind [m/s]
VGRD10m 0,103,10 0,2,3 ** 10 m above ground V-Component of Wind [m/s]
VVEL850mb 0,100,85000 0,2,8 ** 850 mb Vertical Velocity (Pressure) [Pa/s]
WEASDsfc 0,1,0 0,1,13 ** surface Water Equivalent of Accumulated Snow Depth [kg/m^2]
On the NOMADS server the same request will return a much smaller and (I think correct) subset of variables:
APCPsfc 0,1,0 0,1,8,1 ** surface Total Precipitation [kg/m^2]
CSNOWsfc 0,1,0 0,1,195,0 ** surface Categorical Snow [-]
HGT500mb 0,100,50000 0,3,5 ** 500 mb Geopotential Height [gpm]
PRMSLmsl 0,101,0 0,3,1 ** mean sea level Pressure Reduced to MSL [Pa]
TMAX2m 0,103,2 0,0,4,2 ** 2 m above ground Maximum Temperature [K]
TMIN2m 0,103,2 0,0,5,3 ** 2 m above ground Minimum Temperature [K]
TMP850mb 0,100,85000 0,0,0 ** 850 mb Temperature [K]
It seems that egrep regex is not working correctly on the AWS servers.
The text was updated successfully, but these errors were encountered: