A new CPC high-resolution gauge-satellite merged analysis for improved observation of global daily precipitation

Multiple sets of global and regional precipitation data sets have been developed in the past two decades using gauge observations, satellite estimates and their combinations. While these data sets played important roles in documenting spatial distribution and temporal variations of precipitation, discrepancies exist among the various precipitation products due primarily to the differences in the input information and the retrieval / analysis techniques applied. At NOAA/CPC, a project is underway to create a unified suite of precipitation products by collecting and analyzing gauge observation and satellite estimates from a combined database through advanced objective analysis techniques. In this work, we have developed a set of gauge-satellite merged analyses of global daily precipitation.

The gauge-based analysis is defined by interpolating quality controlled gauge reports from over 30K stations through the OI-based algorithm of Xie et al. (2007) and created on a fine-resolution of 0.5olat/lon over the global land areas for a period from 1979 to the present. Several years ago, a new algorithm, called CPC Morphing technique (CMORPH, Joyce et al. 2004), is developed and applied successfully to generate precipitation estimates at very high resolution (8km/30-min) over the globe from 60oS to 60oN by combining information from all available satellite microwave observations as well as infrared images from geostationary platforms. Due to the complicated nature of the relationship between precipitation and the radiances measured by satellite observations, precipitation estimates derived from satellite observations alone will present regionally dependent and seasonally changing biases. An effective way to remove the biases is to combine the satellite estimates with in situ measurements.

The gauge-satellite merged analysis is defined by combining the CMORPH satellite estimates with the gauge analysis over land, and by adjusting the CMORPH against the GPCP pentad analysis over ocean. Over the land areas, a two step algorithm is developed to remove the bias in the CMORPH through matching the PDF of CMORPH with that of the gauge analysis and to combine the gauge analysis with the bias-removed CMORPH through an OI-based technique where the bias-corrected CMORPH is used as the first guess and the gauge analysis is utilized as the observations to improve the quantitative accuracy of the analysis where gauge data are available. Over ocean, the CMORPH estimates are calibrated against the pentad GPCP analysis so that calibrated CMORPH presents close quantitative agreements with the long-term but low-resolution data set while retains information of high-resolution precipitation variations. The gauge-satellite merged analysis is constructed on a 0.25olat/lon grid over the globe for a time period from 1998 to the present when the CMORPH satellite estimates are available.

As the second part of this work, we performed a series of experiments to examine to what extent as in the satellite estimates of oceanic precipitation can be reduced using the current network of in situ measurements (atolls and tropical buoys) and how the configuration of the in situ network has to be to provide appropriate reference of ‘ground truth' of precipitation over various parts of the global oceans. Detailed results will be reported at the conference.