How can I calculate the percentage of clouds within each grid box i.e. 1 degree x 1 degree?

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Hello everyone,
My data (clouds: 11376*270) has a spatial resolution of 5 km. It contains values: 1 (clear), 2 (probably clear), 3 (cloudy) and 4 (probably cloudy). How can I calculate the percentage/fraction of clouds within each grid box i.e. 1 degree x 1 degree (for just condition 3 (cloudy))? I want to make a figure of spatial distribution of percentage frequencies of cloudy (case 3).
My code and the figure it produces:
figure
h1=axesm('mercator', 'MapLatLimit',[15 55],'MapLonLimit',[80 150]);
gridm;
framem on;
mlabel on;
plabel on;
xlabel ('Spatial distribution of occurence frequencies (%) of clouds')
tightmap;
geoshow(h1,lat,lon,clouds,'DisplayType','texturemap')
colormap(jet(4))
labels={'Clear','P_Clear','Cloudy','P_Cloudy'};
lcolorbar(labels,'fontweight','bold');
hold on
coast=load('coast');
geoshow(coast.lat, coast.long,'DisplayType','line','Color','red')
Any suggestions what I'm missing or what changes should I need to do in my code?
Kindly help.
  2 Comments
IMC
IMC on 27 Mar 2021
Didn't get your question.
I have data from 2 days (around 18 files/granules per day for my defined area) . And for each granule, latitude and longitude values are different. Below image shows lat values for just one granule (406 rows and 270 columns). Similarly lon and data (clouds) for one granule will also have 406*270.

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Answers (2)

darova
darova on 28 Mar 2021
Here is an example using griddata
% x y v are your data
% create new mesh 0.1 degree in each direciton
x1 = min(x(:)):0.1:max(x(:));
y1 = min(y(:)):0.1:max(y(:));
v1 = griddata(x,y,z,x1,y1); % interpolate data
v11 = v1*0; % preallocate
for i = 1:10:size(x1,1)
for j = 1:10:size(x1,2)
C = v1(i:i+9,j:j+9);
v11(i:i+9,j:j+9) = sum(C(:)==3)/100; % find '3' and sum
end
end
pcolor(v11)
  4 Comments
IMC
IMC on 28 Mar 2021
It's actually data from geostationary satellite and had lat (y) and lon (x) as a column vector. So, I used meshgrid to create a matrix. Below is figure of latitude values (4802*2401).

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Bruno Luong
Bruno Luong on 29 Mar 2021
Take a look at function histcount2 and histogram2

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