Error Modeling of the Modified-INSAT Multi Spectral Rainfall Algorithm
Abstract
Quantifying the uncertainty associated with Satellite Rainfall Estimates (SREs) is as important as rainfall estimation. These error estimates are essential for applications such as hydrological modeling, land data assimilation systems, real time flood modeling, water management policy making and similar applications. Recently, a few studies were attempted to develop error models for different SREs. However, these models are developed and evaluated only over small homogeneous regions. Hence, there is a pressing need to evaluate the applicability of these models over large highly varied regions (both in terms of topographically and climatologically) and also for different SREs. Accordingly, in the present study a non-parametric error model has been implemented to the recently developed Modified-INSAT Multispectral Rainfall Algorithm (M-IMSRA) which is specifically meant for Indian region. The non-parametric error model developed for M-IMSRA estimates show promising results over most of the climate regions of India except over Himalayan regions where the distribution of gauge is found to be poor. The main advantage of the developed error model is that it gives error estimates for all hit, miss and false precipitations with the associated probability of occurrence.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.H13J1537P
- Keywords:
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- 3354 Precipitation;
- ATMOSPHERIC PROCESSESDE: 1840 Hydrometeorology;
- HYDROLOGYDE: 1848 Monitoring networks;
- HYDROLOGYDE: 1854 Precipitation;
- HYDROLOGY