Eric Nelkin

The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales

Abstract The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) provides a calibration-based sequential scheme for combining precipitation estimates from multiple satellites, as well as gauge analyses where feasible, at fine scales (0.25° × 0.25° and 3 hourly). TMPA is available both after and in real time, based on calibration by the TRMM Combined Instrument and TRMM Microwave Imager precipitation products, respectively. Only the after-real-time product incorporates gauge data at the present. The dataset covers the latitude band 50°N–S for the period from 1998 to the delayed present. Early validation results are as follows: the TMPA provides reasonable performance at monthly scales, although it is shown to have precipitation rate–dependent low bias due to lack of sensitivity to low precipitation rates over ocean in one of the input products [based on Advanced Microwave Sounding Unit-B (AMSU-B)]. At finer scales the TMPA is successful at approximately reproducing the s...

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 TRMM Multi-Satellite Precipitation Analysis (TMPA)

The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) is intended to provide a “best” estimate of quasi-global precipitation from the wide variety of modern satellite-borne precipitation-related sensors. Estimates are provided at relatively fine scales (0.25° × 0.25°, 3-h) in both real and post-real time to accommodate a wide range of researchers. However, the errors inherent in the finest scale estimates are large. The most successful use of the TMPA data is when the analysis takes advantage of the fine-scale data to create time/space averages appropriate to the user’s application. We review the conceptual basis for the TMPA, summarize the processing sequence, and focus on two new activities. First, a recent upgrade for the real-time version incorporates several additional satellite data sources and employs monthly climatological adjustments to approximate the bias characteristics of the research quality post-real-time product. Second, an upgrade for the research quality post-real-time TMPA from Versions 6 to 7 (in beta test at press time) is designed to provide a variety of improvements that increase the list of input data sets and correct several issues. Future enhancements for the TMPA will include improved error estimation, extension to higher latitudes, and a shift to a Lagrangian time interpolation scheme.

Tropical Rainfall Distributions Determined Using TRMM Combined with Other Satellite and Rain Gauge Information

Abstract A technique is described to use Tropical Rainfall Measuring Mission (TRMM) combined radar–radiometer information to adjust geosynchronous infrared satellite data [the TRMM Adjusted Geostationary Operational Environmental Satellite Precipitation Index (AGPI)]. The AGPI is then merged with rain gauge information (mostly over land) to provide finescale (1° latitude × 1° longitude) pentad and monthly analyses, respectively. The TRMM merged estimates are 10% higher than those from the Global Precipitation Climatology Project (GPCP) when integrated over the tropical oceans (37°N–37°S) for 1998, with 20% differences noted in the most heavily raining areas. In the dry subtropics the TRMM values are smaller than the GPCP estimates. The TRMM merged product tropical-mean estimates for 1998 are 3.3 mm day−1 over ocean and 3.1 mm day−1 over land and ocean combined. Regional differences are noted between the western and eastern Pacific Ocean maxima when TRMM and GPCP are compared. In the eastern Pacific rain m...

Regional Rainfall Climatologies Derived from Special Sensor Microwave Imager (SSM/I) Data

Abstract Climatologies of convective precipitation were derived from passive microwave observations from the Special Sensor Microwave Imager using a scattering-based algorithm of Adler et al. Data were aggregated over periods of 3–5 months using data from 4 to 5 years. Data were also stratified by satellite overpass times(primarily 0600 and l800 local time). Four regions [Mexico, Amazonia, western Africa, and the western equatorial Pacific Ocean (TOGA COARE area)] were chosen for their meteorological interest and relative paucity of conventional observations. The strong diurnal variation over Mexico and the southern United States was the most striking aspect of the climatologies. Pronounced morning maxima occurred offshore, often in concavities in the coastline, the result of the increased convergence caused by the coastline shape. The major feature of the evening rain field was a linear-shaped maximum along the western slope of the Sierra Madre Occidental. Topography exerted a strong control on the rainf...

Comparison of GPCP Monthly and Daily Precipitation Estimates with High-Latitude Gauge Observations

Abstract Monthly and daily products of the Global Precipitation Climatology Project (GPCP) are evaluated through a comparison with Finnish Meteorological Institute (FMI) gauge observations for the period January 1995–December 2007 to assess the quality of the GPCP estimates at high latitudes. At the monthly scale both the final GPCP combination satellite–gauge (SG) product is evaluated, along with the satellite-only multisatellite (MS) product. The GPCP daily product is scaled to sum to the monthly product, so it implicitly contains monthly-scale gauge influence, although it contains no daily gauge information. As expected, the monthly SG product agrees well with the FMI observations because of the inclusion of limited gauge information. Over the entire analysis period the SG estimates are biased low by 6% when the same wind-loss adjustment is applied to the FMI gauges as is used in the SG analysis. The interannual anomaly correlation is about 0.9. The satellite-only MS product has a lesser, but still rea...

Evolution of tropical and extratropical precipitation anomalies during the 1997–1999 ENSO cycle

The 1997–1999 El Nino–Southern Oscillation (ENSO) period was very powerful, but also well observed. Multiple satellite rainfall estimates combined with gauge observations allow for a quantitative analysis of precipitation anomalies in the tropics and elsewhere accompanying the 1997–1999 ENSO cycle. An examination of the evolution of the El Nino and accompanying precipitation anomalies revealed that a dry Maritime Continent (MC) preceded the formation of positive sea-surface temperature (SST) anomalies in the eastern Pacific Ocean. Thirty- to sixty-day oscillations in the winter of 1996–1997 may have contributed to this lag relationship. Furthermore, westerly wind burst events may have maintained the drought over the MC. The warming of the equatorial Pacific was then followed by an increase in convection. A rapid transition from El Nino to La Nina occurred in May 1998, but as early as October–November 1997, precipitation indices captured substantial changes in Pacific rainfall anomalies. The global precipitation patterns for this event were in good agreement with the strong consistent ENSO-related precipitation signals identified in earlier studies. Differences included a shift in precipitation anomalies over Africa during the 1997–1998 El Nino and unusually wet conditions over northeast Australia during the later stages of the El Nino. Also, the typically wet region in the north tropical Pacific was mostly dry during the 1998–1999 La Nina. Reanalysis precipitation was compared with observations during this time period and substantial differences were noted. In particular, the model had a bias towards positive precipitation anomalies and the magnitudes of the anomalies in the equatorial Pacific were small compared with the observations. Also, the evolution of the precipitation field, including the drying of the MC and eastward progression of rainfall in the equatorial Pacific, was less pronounced for the model compared with the observations. Copyright

Evaluation of Passive Microwave Precipitation Algorithms in Wintertime Midlatitude Situations

Abstract The second intercomparison project of the Global Precipitation Climatology Project examined the estimation of midlatitude, cool-season precipitation. As part of that effort, the authors report here on the results of two microwave techniques the Goddard scattering algorithm and the physical retrieval algorithm of Kummerow. Results from the estimation of instantaneous rain rate for five overpasses of the Special Sensor Microwave/Imager (SSM/I) are presented in a case study mode to illustrate both the strong and weak points of each technique. These five cases represent a sampling of the various types of precipitating systems observed. Results for the complete set of 20 swaths chosen by the United Kingdom Meteorological Office are then categorized by scatterplots and statistics of instantaneous radar versus microwave-estimated rain rate, rain/no-rain contingency tables, and scatterplots of arch coverage of rainfall. Neither algorithm produced a good statistical correlation with the radar data, yet in...

The Global Precipitation Climatology Project (GPCP) Monthly Analysis (New Version 2.3) and a Review of 2017 Global Precipitation

The new Version 2.3 of the GPCP Monthly analysis is described in terms of changes made to improve the homogeneity of the product, especially after 2002. These changes include corrections to cross calibration of satellite data inputs and updates to the gauge analysis. Over ocean, changes starting in 2003 result in an overall precipitation increase of 1.8% after 2009. Updating the gauge analysis to its final, high quality version increases the global land total by 1.8% for the post-2002 period. These changes correct a small, incorrect dip in the estimated global precipitation over the last decade in the earlier Version 2.2. The GPCP analysis is also used to describe global precipitation for 2017. The general La Nina pattern for 2017 is noted and the evolution from the early 2016 El Nino pattern is described. The 2017 global value is one of the highest for the 19792017 period, exceeded only by 2016 and 1998 (both El Nino years) and reinforces the small positive trend. Results for 2017 also reinforce significant trends in precipitation intensity (on a monthly scale) in the tropics. These results for 2017 indicate the value of the GPCP analysis for climate monitoring in addition to research.

GPCP Version 2.2 Combined Precipitation Data Set

NOTE: This dataset has been superseded by GPCP Version 2.3, which is available in RDA dataset ds728.4 [https://rda.ucar.edu/datasets/ds728.4/]. Users are advised to transition to this updated dataset.\n\n This dataset contains Version 2.2 of the Global Precipitation Climatology Project (GPCP) combined satellite-gauge precipitation estimate and combined satellite-gauge error estimate. The data are monthly analyses defined on a global 2.5 degree by 2.5 degree longitude/latitude grid and cover the period January 1979 to (delayed) present. A monthly climatology (1979-2011) is also available.\n\n Please note that the original binary data were written using the big endian representation of unformatted binary words. Users reading this data on little endian platforms, therefore, will need to byte swap the data.\n\n The GPCP was established by the World Climate Research Program (WCRP) and subsequently attached to the Global Energy and Water Exchange program (GEWEX) to address the problem of quantifying the distribution of precipitation around the globe over many years. The general approach is to combine the precipitation information available from each of several sources into a final merged product, taking advantage of the strengths of each data type. The passive microwave estimates are based on Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager/Sounder (SSMIS) data from the series of Defense Meteorological Satellite Program (DMSP, United States) satellites that fly in sun-synchronous low-earth orbits at 6am / 6pm. The infrared precipitation estimates are computed primarily from geostationary satellites (United States, Europe, Japan), and secondarily from NOAA series polar-orbiting satellites (United States). Additional low-Earth orbit estimates include Atmospheric Infrared Sounder (AIRS) data from the NASA Aqua, and Television Infrared Observation Satellite Program (TIROS) Operational Vertical Sounder (TOVS) and Outgoing Longwave Radiation Precipitation Index (OPI) data from the NOAA series satellites. The precipitation gauge data are assembled and analyzed by the Global Precipitation Climatology Centre (GPCC) of the Deutscher Wetterdienst.\n\n The Version 2.2 Data Set contains data from the following contributing centers: \n * GPCP Polar Satellite Precipitation Data Centre - Emission (SSM/I and SSMIS emission estimates)\n * GPCP Polar Satellite Precipitation Data Centre - Scattering (SSM/I and SSMIS scattering estimates)\n * GPCP Geostationary Satellite Precipitation Data Centre (GPI and OPI estimates)\n * NASA/GSFC Sounder Research Team (TOVS and AIRS estimates)\n * GPCP Global Precipitation Climatology Centre (precipitation gauge analyses)\n\nRequest to users from the data authors: The GPCP datasets are developed and maintained with international cooperation and are used by the worldwide scientific community. To better understand the evolving requirements across the GPCP user community and to increase the utility of the GPCP product suite, the dataset authors request that a citation be provided for each publication that uses the GPCP products. Please email the citation to george.j.huffman@nasa.gov or david.t.bolvin@nasa.gov. Your help and cooperation will provide valuable information for making future enhancements to the GPCP product suite.