GlennDoodle
New member
Hello,
I am trying to run a simulation from back in 1983 on finer resolution grids (3km and 1km). The issue that I am having is that the finest resolution SST data that I have found is 0.25deg x 0.25deg. Using the default METGRID.TBL, I get a very blocky (not surprisingly) pattern in the center of the Great Lakes from the supplied SST and then the METGRID does an extrapolation of the rest of the lake temperatures toward the shoreline of the Great Lakes. I modified the METGRID.TBL so that the SST was spread out to the lake coastlines by changing
name=SST
interp_option=sixteen_pt+four_pt
fill_missing=0.
missing_value=-1.E30
flag_in_output=FLAG_SST
to
name=SST
interp_option=sixteen_pt+four_pt+wt_average_4pt+wt_average_16pt+search
fill_missing=0.
missing_value=-1.E30
flag_in_output=FLAG_SST
This worked for the Great Lakes, but the unresolved lakes (e.g. Finger Lakes in New York) became much warmer as did many lakes in Canada due to the extrapolation. So, I tried the TAVG method, grabbing a weeks worth of data to make a TAVG file to reduce my "hot lake" issue for the unresolved lakes. While I prefer the values supplied to the small unresolved lakes, this method overwrote the SST values over the Great Lakes and thus I lost some information over the Great Lakes (the TAVG reduced my Great Lake temperatures by up to 4K). So, my question is, can I use the TAVG method but mask out the Great Lakes so that I they do use the SST values which were resolved in the ERA5 data set? Is this an option in METGRID? Would I need to redefine the landuse values over the Great Lakes to be the same as ocean points instead of the special lake category that is used by METGRID.
For completeness sake the METGRID.TBL entry is
name=SKINTEMP
mpas_name=skintemp
interp_option=sixteen_pt+four_pt+wt_average_4pt+wt_average_16pt+search
masked=both
interp_land_mask = LANDSEA(1)
interp_water_mask = LANDSEA(0)
fill_missing=0.
Thanks for your time!
I am trying to run a simulation from back in 1983 on finer resolution grids (3km and 1km). The issue that I am having is that the finest resolution SST data that I have found is 0.25deg x 0.25deg. Using the default METGRID.TBL, I get a very blocky (not surprisingly) pattern in the center of the Great Lakes from the supplied SST and then the METGRID does an extrapolation of the rest of the lake temperatures toward the shoreline of the Great Lakes. I modified the METGRID.TBL so that the SST was spread out to the lake coastlines by changing
name=SST
interp_option=sixteen_pt+four_pt
fill_missing=0.
missing_value=-1.E30
flag_in_output=FLAG_SST
to
name=SST
interp_option=sixteen_pt+four_pt+wt_average_4pt+wt_average_16pt+search
fill_missing=0.
missing_value=-1.E30
flag_in_output=FLAG_SST
This worked for the Great Lakes, but the unresolved lakes (e.g. Finger Lakes in New York) became much warmer as did many lakes in Canada due to the extrapolation. So, I tried the TAVG method, grabbing a weeks worth of data to make a TAVG file to reduce my "hot lake" issue for the unresolved lakes. While I prefer the values supplied to the small unresolved lakes, this method overwrote the SST values over the Great Lakes and thus I lost some information over the Great Lakes (the TAVG reduced my Great Lake temperatures by up to 4K). So, my question is, can I use the TAVG method but mask out the Great Lakes so that I they do use the SST values which were resolved in the ERA5 data set? Is this an option in METGRID? Would I need to redefine the landuse values over the Great Lakes to be the same as ocean points instead of the special lake category that is used by METGRID.
For completeness sake the METGRID.TBL entry is
name=SKINTEMP
mpas_name=skintemp
interp_option=sixteen_pt+four_pt+wt_average_4pt+wt_average_16pt+search
masked=both
interp_land_mask = LANDSEA(1)
interp_water_mask = LANDSEA(0)
fill_missing=0.
Thanks for your time!