Interpolate for the remaining longitudes!

**How to interpolate values for the missing longitudes** (See the png file attached)

ncid1 = netcdf.open('uwnd.mon.mean.nc','NC_NOWRITE');
uwind = netcdf.getVar(ncid1,3,[0 0 0],[144 73 1],'double');

ncid2 = netcdf.open('vwnd.mon.mean.nc','NC_NOWRITE');
vwind = netcdf.getVar(ncid2,3,[0 0 0],[144 73 1],'double');

lon1 = netcdf.getVar(ncid1,1,0,144); %longitude values are 0 to 357.5
lat1 = netcdf.getVar(ncid1,0,0,73); %latitude values are -90 to 90

for p = 1:144
    for q = 1:73
        map1(q,p)  = uwind(p,q);
    end
end

for p1 = 1:144
    for q1 = 1:73
        map2(q1,p1)  = vwind(p1,q1);
    end
end

wnd_spd = sqrt((uwind.*uwind)+(vwind.*vwind))
for p3 = 1:144
    for q3 = 1:73
        map3(q3,p3)  = wnd_spd(p3,q3);
    end
end

Answer 1

[ANKUR KUMAR]

Suppose, you have stored all the missing longitudes in the variable lon and the corresponding latitudes in the variable lat. So you can use interp2 to get the wind speed over these lat long.

For example, lon_missing and lat_missing are the set of lon-lats on which you want to find the wind speed. Suppose, LON and LAT are the lon-lats of the main data file. Wind_speed is the wind speed from your main data file.

lon_missing=[69:0.2:71];  
lat_missing=[20:0.2:22];
Wind_speed=randi(25,120,250);  % wind speed from your main data file. This is just an example.
LAT=linspace(3,35,250);
LON=linspace(65,95,120);
[x y]=meshgrid(lon_missing,lat_missing);
for ii=1:size(x,2)
   interpolated_wind_speed(:,ii)=interp2(LON,LAT,Wind_speed',x(:,ii),y(:,ii));
end