![CHOMPS precipitation estimates for January 1, 2000. [Climate Data Guide; D. Shea]](https://climatedataguide.ucar.edu/sites/default/files/styles/node_teaser_image/public/teaser_images/CHOMPS.dy_.2000_2.png?itok=ADU5HnBC)
CHOMPS utilizes all available passive microwave satellite estimates to develop improved global daily rainfall time series. No IR values are used. Satellite sources include SSM/I, AMSU, AMSR-E and TRMM. The most recent/accurate and consistent retrieval schemes have been used in the creation of the individual precipitation estimates. The original data are binned and optimal interpolation is used to merge the data and reduce errors. There are two data sets versions. One includes all passive satellite sources (CHOMPS) and one that does not include data from the AMSU sensor (CHOMPS-NoA). This was done to account for possible discontinuities when the AMSU instrument was added.
Key Strengths:
- Uses all available passive microwave satellite estimates and most recent/accurate and consistent retrieval schemes
- Data from multiple satellites binned to reduce diurnal sampling biases and optimal interpolation used to reduce random errors. Error estimates provided.
- High temporal and spatial resolution
Years of Record
Formats
Timestep
Data Time Period Extended?
Domain
Spatial Resolution
Ocean or Land
Missing Data Flag
Vertical Levels
Input Data
Data Access: Please Cite data sources, following the data providers' instructions.
- Joseph, Renu, Thomas M. Smith, Mathew R. P. Sapiano, Ralph R. Ferraro, 2009: A New High-Resolution Satellite-Derived Precipitation Dataset for Climate Studies. J. Hydrometeor, 10, 935–952
- M. Tugrul Yilmaz, P. Houser, R. Shrestha, V. G. Anantharaj. (2010) Optimally Merging Precipitation to Minimize Land Surface Modeling Errors. Journal of Applied Meteorology and Climatology 49:3, 415-423