Journal article
On the relationship between the GOES precipitation index and ISCCP data set variables
Journal of Geophysical Research Atmospheres, Vol.104(D24), pp.31467-31476
1999
DOI: 10.1029/1999JD900229
Abstract
The GOES Precipitation Index (GPI) is used for global, monthly rainfall estimation in the Global Precipitation Climatology Project (GPCP). Previous work has identified the existence of locally and seasonally varying bias in the GPI estimates. Most sources of bias involve cloud properties, as the GPI method uses the fraction of pixels with infrared cloud temperature below 235°K to estimate monthly rainfall totals averaged over 2.5° × 2.5° latitude/longitude grid boxes. In this work, the bias in the GPI is compared to cloud variables derived by the International Satellite Cloud Climatology Project (ISCCP). ISCCP data are used as predictor variables in regression models with the GPI estimation error as the dependent variable. The GPI estimation error is calculated using the global rain gage analysis produced by the GPCP for those locations where the rain gage network density is high. Fourteen ISCCP cloud variables were selected as the predictors in linear and nonlinear regression models. The nonlinear model explains over 60% of the variance of the GPI bias, while the linear model explains about 45% of the variance. Comparison with another method of GPI bias estimation is discussed.
Details
- Title: Subtitle
- On the relationship between the GOES precipitation index and ISCCP data set variables
- Creators
- Jeffrey R McCollumWitold F Krajewski
- Resource Type
- Journal article
- Publication Details
- Journal of Geophysical Research Atmospheres, Vol.104(D24), pp.31467-31476
- DOI
- 10.1029/1999JD900229
- ISSN
- 0148-0227
- eISSN
- 2156-2202
- Language
- English
- Date published
- 1999
- Academic Unit
- Civil and Environmental Engineering
- Record Identifier
- 9983992058702771
Metrics
15 Record Views