dani_caputi
New member
Hello NCAR team,
I have been running forecasts out to 48h using the GFS model for my boundary conditions, allowing 24h of spin-up. Looking at a particular set of my runs over the Milwaukee, WI region from 10/24 - 11/3 (I was using the wxchallenge as a test for my project), I have an average 11 K cold bias for daily high temperature and 7 K cold bias for daily low temperature. This bias was similar in magnitude in all regions I tested it, and there was no snow cover that time of year. I don't think it is an urban physics issue either, because the bias is similar across the entire area of the model that includes both urban and rural regions.
I've attached my namelist.input. Also, as a sanity check - my way of calculating temperature from the wrfout_* netcdf files is to take the base temperature and add the perturbation temperature. In python this would be:
from netCDF4 import Dataset
wrf = Dataset('wrfout_xxx'), 'r')
T0 = wrf.variables['T00'][0] #stores base temperature as T0
T = wrf.variables['T'] #stores perturbation temperatures as T
Surface_Temp = T[0,0,x,y]+T0 #calculates surface temperature at grid cell x,y
I have been running forecasts out to 48h using the GFS model for my boundary conditions, allowing 24h of spin-up. Looking at a particular set of my runs over the Milwaukee, WI region from 10/24 - 11/3 (I was using the wxchallenge as a test for my project), I have an average 11 K cold bias for daily high temperature and 7 K cold bias for daily low temperature. This bias was similar in magnitude in all regions I tested it, and there was no snow cover that time of year. I don't think it is an urban physics issue either, because the bias is similar across the entire area of the model that includes both urban and rural regions.
I've attached my namelist.input. Also, as a sanity check - my way of calculating temperature from the wrfout_* netcdf files is to take the base temperature and add the perturbation temperature. In python this would be:
from netCDF4 import Dataset
wrf = Dataset('wrfout_xxx'), 'r')
T0 = wrf.variables['T00'][0] #stores base temperature as T0
T = wrf.variables['T'] #stores perturbation temperatures as T
Surface_Temp = T[0,0,x,y]+T0 #calculates surface temperature at grid cell x,y