Pingping Xie

Global precipitation : A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs

Gridded fields (analyses) of global monthly precipitation have been constructed on a 2.5° latitude–longitude grid for the 17-yr period from 1979 to 1995 by merging several kinds of information sources with different characteristics, including gauge observations, estimates inferred from a variety of satellite observations, and the NCEP–NCAR reanalysis. This new dataset, which the authors have named the CPC Merged Analysis of Precipitation (CMAP), contains precipitation distributions with full global coverage and improved quality compared to the individual data sources. Examinations showed no discontinuity during the 17-yr period, despite the different data sources used for the different subperiods. Comparisons of the CMAP with the merged analysis of Huffman et al. revealed remarkable agreements over the global land areas and over tropical and subtropical oceanic areas, with differences observed over extratropical oceanic areas. The 17-yr CMAP dataset is used to investigate the annual and interannual variab...

The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–Present)

Abstract The Global Precipitation Climatology Project (GPCP) Version-2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5° latitude × 2.5° longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit satellite microwave data, geosynchronous-orbit satellite infrared data, and surface rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The dataset is extended back into the premicrowave era (before mid-1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the rain gauge analysis. The dataset archive also contains the individual input fields, a combined satellite estimate, and error estimates for each field. This m...

CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution

Abstract A new technique is presented in which half-hourly global precipitation estimates derived from passive microwave satellite scans are propagated by motion vectors derived from geostationary satellite infrared data. The Climate Prediction Center morphing method (CMORPH) uses motion vectors derived from half-hourly interval geostationary satellite IR imagery to propagate the relatively high quality precipitation estimates derived from passive microwave data. In addition, the shape and intensity of the precipitation features are modified (morphed) during the time between microwave sensor scans by performing a time-weighted linear interpolation. This process yields spatially and temporally complete microwave-derived precipitation analyses, independent of the infrared temperature field. CMORPH showed substantial improvements over both simple averaging of the microwave estimates and over techniques that blend microwave and infrared information but that derive estimates of precipitation from infrared data...

Analyses of Global Monthly Precipitation Using Gauge Observations, Satellite Estimates, and Numerical Model Predictions

Abstract An algorithm is developed to construct global gridded fields of monthly precipitation by merging estimates from five sources of information with different characteristics, including gauge-based monthly analyses from the Global Precipitation Climatology Centre, three types of satellite estimates [the infrared-based GOES Precipitation Index, the microwave (MW) scattering-based Grody, and the MW emission-based Chang estimates], and predictions produced by the operational forecast model of the European Centre for Medium-Range Weather Forecasts. A two-step strategy is used to: 1) reduce the random error found in the individual sources and 2) reduce the bias of the combined analysis. First, the three satellite-based estimates and the model predictions are combined linearly based on a maximum likelihood estimate, in which the weighting coefficients are inversely proportional to the squares of the individual random errors determined by comparison with gauge observations and subjective assumptions. This c...

Global Land Precipitation: A 50-yr Monthly Analysis Based on Gauge Observations

Abstract This paper describes the initial work toward the production of monthly global (land and ocean) analyses of precipitation for an extended period from 1948 to the present. Called the precipitation reconstruction (PREC), the global analyses are defined by interpolation of gauge observations over land (PREC/L) and by EOF reconstruction of historical observations over ocean (PREC/O). This paper documents the creation of the land component of the analyses (PREC/L) on a 2.5° latitude/longitude grid for 1948–2000. These analyses are derived from gauge observations from over 17 000 stations collected in the Global Historical Climatology Network (GHCN), version 2, and the Climate Anomaly Monitoring System (CAMS) datasets. To determine the most suitable objective analysis procedure for gridding, the analyses generated by four published objective analysis techniques [those of Cressman, Barnes, and Shepard, and the optimal interpolation (OI) method of Gandin] were compared. The evaluation demonstrated two cru...

GPCP Pentad Precipitation Analyses: An Experimental Dataset Based on Gauge Observations and Satellite Estimates

As part of the Global Precipitation Climatology Project (GPCP), analyses of pentad precipitation have been constructed on a 2.58 latitude‐longitude grid over the globe for a 23-yr period from 1979 to 2001 by adjusting the pentad Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) against the monthly GPCP-merged analyses. This adjustment is essential because the precipitation magnitude in the pentad CMAP is not consistent with that in the monthly CMAP or monthly GPCP datasets primarily due to the differences in the input data sources and merging algorithms, causing problems in applications where joint use of the pentad and monthly datasets is necessary. First, pentad CMAP-merged analyses are created by merging several kinds of individual data sources including gauge-based analyses of pentad precipitation, and estimates inferred from satellite observations. The pentad CMAP dataset is then adjusted by the monthly GPCP-merged analyses so that the adjusted pentad analyses match the monthly GPCP in magnitude while the high-frequency components in the pentad CMAP are retained. The adjusted analyses, called the GPCP-merged analyses of pentad precipitation, are compared to several gauge-based datasets. The results show that the pentad GPCP analyses reproduced spatial distribution patterns of total precipitation and temporal variations of submonthly scales with relatively high quality especially over land. Simple applications of the 23-yr dataset demonstrate that it is useful in monitoring and diagnosing intraseasonal variability. The Pentad GPCP has been accepted by the GPCP as one of its official products and is being updated on a quasi-real-time basis.

Global Monthly Precipitation Estimates from Satellite-Observed Outgoing Longwave Radiation

Abstract The relationship between the flux of outgoing longwave radiation (OLR) estimated from satellite observations and precipitation is investigated using monthly OLR data from the NOAA polar-orbiting satellites and the merged analysis of precipitation of Xie and Arkin for the 8-yr period from July 1987 to June 1995. The mean annual cycle of OLR in the Tropics is dominated by changes in cloudiness and exhibits a strong negative correlation with precipitation, while in the extratropics the strongest influence on the annual cycle of OLR is surface temperature and a positive correlation with precipitation is found. However, the anomaly of OLR exhibits a negative correlation with precipitation over most of the globe. The regression coefficient relating the anomaly of precipitation to that of OLR is spatially inhomogeneous and seasonally dependent but can be expressed with high accuracy as a globally uniform linear function of the local mean precipitation. Based on these results, a new technique is develope...

An Intercomparison of Gauge Observations and Satellite Estimates of Monthly Precipitation

Abstract In order to further our quantitative understanding of the advantages and the shortcomings of the various sources of data used to represent climatic-scale precipitation, monthly gauge observations and satellite estimates are intercompared for global grid areas of 2.5° latitude/longitude for a period from July 1987 to June 1990. The results show that 1) at least five gauges are necessary to construct an areal-averaged monthly mean for the grids with accuracy of 10%, and 10% of the global land grids satisfy the requirement; 2) both microwave- and IR-based satellite estimates give similar spatial distributions of precipitation with good agreement with gauge observations for the warm seasons and over the tropical Pacific Ocean; and 3) the satellite estimates, especially those from the IR-based algorithm, exhibit poorer correspondence with gauge observations over land areas for the cold seasons. These results show that, for many applications, no single type of data can be used as the source for a month...

CAMS–OPI: A Global Satellite–Rain Gauge Merged Product for Real-Time Precipitation Monitoring Applications

A method has been developed to produce real-time rain gauge‐satellite merged analyses of global monthly precipitation. A dataset of these analyses spans the period from January 1979 to the present, which is sufficiently long to allow the computation of reasonably stable base period means from which departures from ‘‘normal’’ can be computed. The dataset is used routinely for global precipitation monitoring purposes at the National Oceanic and Atmospheric Administration/National Weather Service/National Centers for Environmental Prediction/Climate Prediction Center, is updated monthly, and is available via the Internet.

Gauge‐based monthly analysis of global land precipitation from 1971 to 1994

Monthly gridded fields of global land precipitation have been constructed on 2.5° latitude/longitude grids for a 24-year period from 1971 to 1994 by interpolating gauge observations at over 6000 stations contained in the Global Historical Climatology Network of the Carbon Dioxide Information Center of U.S. Department of Energy and the Climate Anomaly Monitoring System of the Climate Prediction Center of National Oceanic and Atmospheric Administration. Sensitivity tests indicated that this gauge-based analysis has relatively high quality in general and that its quantitative accuracy increases with the gauge network density. Significant value-dependent bias and random error, however, exist in the analysis over grid areas with few gauges. The mean distribution and annual cycle of the 24-year gauge-based analysis showed close agreement with those of several published long-term means, and the inter-annual variations in precipitation associated with the El Nino-Southern Oscillation phenomenon were evident. Despite the ability of this gauge-based analysis to describe large-scale precipitation over global land areas, further efforts are needed to improve the interpolation algorithm, to increase gauge network density, and to combine the gauge analysis with other information sources based on satellite observations, especially over grid areas with poor gauge coverage.