Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems

IEEE Transactions on Geoscience and Remote Sensing
By: , and 

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Abstract

Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems
Series title IEEE Transactions on Geoscience and Remote Sensing
DOI 10.1109/TGRS.2015.2502956
Volume 54
Issue 5
Year Published 2016
Language English
Publisher IEEE
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Description 11 p.
First page 2552
Last page 2562
Online Only (Y/N) N
Additional Online Files (Y/N) N