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PERSIANN 0.25° Product Access Tools

1. Archive of Adjusted PERSIANN 3 Hourly data

Full monthly archives of PERSIANN's final 0.25° are available at 3 hourly temporal resolution. To obtain data for each month, just click on the x in the table below.

Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2010
x
x
x
x
2009
x
x
x
x
2008
x
x
x
x
x
x
x
x
2007
x
x
x
x
x
x
x
x
2006
x
x
x
x
x
x
x
x
x
x
x
x
2005
x
x
x
x
x
x
x
x
x
x
x
x
2004
x
x
x
x
x
x
x
x
x
x
x
x
2003
x
x
x
x
x
x
x
x
x
x
x
x
2002
x
x
x
x
x
x
x
x
x
x
x
x
2001
x
x
x
x
x
x
x
x
x
x
x
x
2000
NA
NA
x
x
x
x
x
x
x
x
x
x
                     
NOTE: adjusted PERSIANN data after September 2009 will be available later in 2011.

README Information

Format:

4-byte binary float (little-endian byte order).
Units: mm/3hr

Spatial coverage is:
60° to -60° lat
0° to 360° long

Spatial Resolution:
.25° x .25° resolution

Geometry:
480 rows x 1440 cols

The data is stored in C style row centric format. with the
first value centered at 59.875,.125,
the second value at 59.875,.375,
and the last 2 values are centered at: -59.875,359.625 & -59.875,359.875

sample matlab code:


function om = loadbfn(fn,dim,sz)
% loadbfn -- loads a binary file fn of dim 
%       ([nrows ncols]) of sz 'float','int', etc.
%
%       by DKB on 2/5/96
%
if(nargin < 3)
  sz = 'float32';
end
f = fopen(fn,'r','l');
if(nargout > 0)
   om = fread(f,flipud(dim(:))',sz)';
end
fclose(f); 

This bias corrected PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) precipitation maintains total monthly precipitation estimates, consistent with GPCP (Global Precipitation Climatology Project) product. The newly released data set retains the spatial and temporal features of precipitation estimates provided by the original PERSIANN algorithm at 0.25-degree spatial and 3-hourly temporal resolution.

PERSIANN precipitation estimation relies on cloud texture information from longwave infrared images (~10.2-11.2 µm) obtained from geostationary satellites and updated using the higher quality rainfall estimates from low-orbit passive microwave sensors (Hsu et al., 2007; Soroosh et al., 2000). To reduce bias while preserving spatial and temporal patterns in high resolution, PERSIANN precipitation is adjusted based on GPCP rainfall (Version 2.1) at 2.5o monthly resolution (Adler et al., 2003; Huffman et al., 2009). Before applying bias adjustment, missing data in PERSAINN estimation is filled with passive microwave rainfall estimation at each 30 minutes time step. In the subsequent step, the data is aggregated to 2.5o monthly scale and a correction factor is computed based on the ratio of GPCP rainfall and PERSIANN rainfall at a grid of 2.5o monthly scale. This ratio is then used to calculate the PERSIANN rainfall fine spatial (0.25o) and temporal scale (hourly) within the 2.5o coverage. The final product is provided to users at 3-hour and 0.25o resolution.

Adler, R.F., G.J. Huffman, A. Chang, R. Ferraro, P. Xie, J. Janowiak, B. Rudolf, U. Schneider, S. Curtis, D. Bolvin, A. Gruber, J. Susskind, and P. Arkin, 2003: The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present). J. Hydrometeor., 4,1147-1167.

George J. Huffman, Robert F. Adler, David T. Bolvin, Guojun Gu. (2009) Improving the global precipitation record: GPCP Version 2.1. Geophysical Research Letters 36:17,

Hsu, K., X. Gao, S. Sorooshian, and H.V. Gupta, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks, Journal of Applied Meteorology, 36(9), 1176-1190, 1997.

Sorooshian, S., K. Hsu, X. Gao, H.V. Gupta, B. Imam, and Dan Braithwaite, Evaluation of PERSIANN System Satellite-Based Estimates of Tropical Rainfall, Bulletin of the American Meteorological Society, 81(9), 2035-2046, 2000.