Arnold Gruber

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...

The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset

The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global, monthly precipitation dataset covering the period July 1987 through December 1995. The primary product in the dataset is a merged analysis incorporating precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit-satellite infrared data, and rain gauge observations. The dataset also contains the individual input fields, a combination of the microwave and infrared satellite estimates, and error estimates for each field. The data are provided on 2.5° × 2.5° latitude-longitude global grids. Preliminary analyses show general agreement with prior studies of global precipitation and extends prior studies of El Nino-Southern Oscillation precipitation patterns. At the regional scale there are systematic differences with standard climatologies.

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.

The Status of the NOAA Outgoing Longwave Radiation Data Set

Abstract National Oceanic and Atmospheric Administration (NOAA) satellites have provided over eight years of observations from which estimates of the earths total longwave emittance can be derived. Changes in satellite instrumentation, orbit, and algorithms used in obtaining these estimates are briefly summarized. The algorithms used by NOAA in obtaining a longwave radiation data set are provided.

Comparison of the GPCP and CMAP Merged Gauge-Satellite Monthly Precipitation Products for the Period 1979-2001

Abstract The two monthly precipitation products of the Global Precipitation Climatology Project (GPCP) and the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) are compared on a 23-yr period, January 1979–December 2001. For the long-term mean, major precipitation patterns are clearly demonstrated by both products, but there are differences in the pattern magnitudes. In the tropical ocean the CMAP is higher than the GPCP, but this is reversed in the high-latitude ocean. The GPCP–CMAP spatial correlation is generally higher over land than over the ocean. The correlation between the global mean oceanic GPCP and CMAP is significantly low. It is very likely because the input data of the two products have much less in common over the ocean; in particular, the use of atoll data by the CMAP is disputable. The decreasing trend in the CMAP oceanic precipitation is found to be an artifact of input data change and atoll sampling error. In general, overocean precipitation represented by the GPCP...

GOES Multispectral Rainfall Algorithm (GMSRA)

Abstract A multispectral approach is used to optimize the identification of raining clouds located at a given altitude estimated from the cloud-top temperature. The approach combines information from five channels on the National Oceanic and Atmospheric Administration Geostationary Operational Environmental Satellite (GOES): visible (0.65 μm), near infrared (3.9 μm), water vapor (6.7 μm), and window channels (11 and 12 μm). The screening of nonraining clouds includes the use of spatial gradient of cloud-top temperature for cirrus clouds (this screening is applied at all times) and the effective radius of cloud-top particles derived from the measurements at 3.9 μm during daytime. During nighttime, only clouds colder than 230 K are considered for the screening; during daytime, all clouds having a visible reflectance greater than 0.40 are considered for the screening, and a threshold of 15 μm in droplet effective radius is used as a low boundary of raining clouds. A GOES rain rate for each indicated raining ...

A Comparison of the NCEP–NCAR Reanalysis Precipitation and the GPCP Rain Gauge–Satellite Combined Dataset with Observational Error Considerations

Abstract The Global Precipitation Climatology Project (GPCP) has released monthly mean estimates of precipitation that comprise gauge observations and satellite-derived precipitation estimates. Estimates of standard random error for each month at each grid location are also provided in this data release. One of the primary intended uses of this dataset is the validation of climatic-scale precipitation fields that are produced by numerical models. Nearly coincident with this dataset development, the National Centers for Environmental Prediction and the National Center for Atmospheric Research have joined in a cooperative effort to reanalyze meteorological fields from the present back to the 1940s using a fixed state-of-the-art data assimilation system and large input database. In this paper, monthly accumulations of reanalysis precipitation are compared with the GPCP combined rain gauge–satellite dataset over the period 1988–95. A unique feature of this comparison is the use of standard error estimates tha...

Discrepancy between Gauges and Satellite Estimates of Rainfall in Equatorial Africa

Abstract The Global Precipitation Climatology Project (GPCP) satellite estimates have approximately twice the magnitude of estimates produced from the rain gauges used by the GPCP in central equatorial Africa. Different possible explanations are identified and investigated. The first is that there may not be enough GPCP rain gauges in the area to provide accurate estimates of rainfall for comparisons with satellite estimates. A comparison of the time-averaged GPCP rain gauge estimate with a long-term (over 40 yr) climatology indicates that the GPCP gauge estimates are similar to long-term rainfall averages, suggesting that the GPCP rain gauge analysis is not underestimating rainfall. Two other possible explanations related to the physical properties of the air masses in this region are studied. Evidence from the literature and from estimates of the effective radii of cloud droplets suggests that there may be an abundance of aerosols in central Africa, resulting in an abundance of cloud condensation nuclei...

Results from the GPCP Algorithm Intercomparison Programme

Abstract Three algorithm intercomparison experiments have recently been conducted as part of the Global Precipitation Climatology Project with the goal of (a) assessing the skill of current satellite rainfall algorithms, (b) understanding the differences between them, and (c) moving toward improved algorithms. The results of these experiments are summarized and intercompared in this paper. It was found that the skill of satellite rainfall algorithms depends on the regime being analyzed, with algorithms producing very good results in the tropical western Pacific and over Japan and its surrounding waters during summer, but relatively poor rainfall estimates over western Europe during late winter. Monthly rainfall was estimated most accurately by algorithms using geostationary infrared data, but algorithms using polar data [Advanced Very High Resolution Radiometer and Special Sensor Microwave/Imager (SSM/1)l were also able to produce good monthly rainfall estimates when data from two satellites wore availabl...

The Comparison of Two Merged Rain Gauge–Satellite Precipitation Datasets

Abstract Two large–scale precipitation datasets, one produced by the Global Precipitation Climatology Project (GPCP) and the other by the Climate Prediction Center of the National Weather Service, and called Climate Prediction Center Merged Analysis of Precipitation (CMAP), were compared. Both datasets blend satellite and gauge estimates of precipitation. And while the latter has its heritage in the GPCP, different analysis procedures and some additional types of input data used by CMAP yielded different values. This study used the error characteristics of the data to assess the significance of the observed differences. Despite good spatial and temporal correlations between the two fields some of the observed differences were significant at the 95% level. These were traced to the use of some different input data such as the use by CMAP of atoll gauges in the tropical Pacific and gauges uncorrected for wetting evaporation and aerodynamic effects. The former impacts the tropical ocean rain amounts and the l...