ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF. Copyright © 2011 Royal Meteorological Society

The ERA-Interim reanalysis: configuration and performance of the data assimilation system

The ERA5 global reanalysis

ERA-40 is a re-analysis of meteorological observations from September 1957 to August 2002 produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) in collaboration with many institutions. The observing system changed considerably over this re-analysis period, with assimilable data provided by a succession of satellite-borne instruments from the 1970s onwards, supplemented by increasing numbers of observations from aircraft, ocean-buoys and other surface platforms, but with a declining number of radiosonde ascents since the late 1980s. The observations used in ERA-40 were accumulated from many sources. The first part of this paper describes the data acquisition and the principal changes in data type and coverage over the period. It also describes the data assimilation system used for ERA-40. This benefited from many of the changes introduced into operational forecasting since the mid-1990s, when the systems used for the 15-year ECMWF re-analysis (ERA-15) and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis were implemented. Several of the improvements are discussed. General aspects of the production of the analyses are also summarized.

A number of results indicative of the overall performance of the data assimilation system, and implicitly of the observing system, are presented and discussed. The comparison of background (short-range) forecasts and analyses with observations, the consistency of the global mass budget, the magnitude of differences between analysis and background fields and the accuracy of medium-range forecasts run from the ERA-40 analyses are illustrated. Several results demonstrate the marked improvement that was made to the observing system for the southern hemisphere in the 1970s, particularly towards the end of the decade. In contrast, the synoptic quality of the analysis for the northern hemisphere is sufficient to provide forecasts that remain skilful well into the medium range for all years. Two particular problems are also examined: excessive precipitation over tropical oceans and a too strong Brewer-Dobson circulation, both of which are pronounced in later years. Several other aspects of the quality of the re-analyses revealed by monitoring and validation studies are summarized. Expectations that the ‘second-generation’ ERA-40 re-analysis would provide products that are better than those from the firstgeneration ERA-15 and NCEP/NCAR re-analyses are found to have been met in most cases. © Royal Meteorological Society, 2005. The contributions of N. A. Rayner and R. W. Saunders are Crown copyright.

The ERA‐40 re‐analysis

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...

/pdf/the-trmm-multisatellite-precipitation-analysis-tmpa-quasi-3wulgfnahi.pdf

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

The Global Precipitation Climatology Project (GPCP) Version 2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5 degrees x 2.5 degrees latitude-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 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 data set is extended back into the premicrowave era (before 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 raingauge analysis. This monthly analysis is the foundation for the GPCP suite of products including those at finer temporal resolution, satellite estimate, and error estimates for each field. The 23-year GPCP climatology is characterized, along with time and space variations of precipitation.

/pdf/the-version-2-global-precipitation-climatology-project-gpcp-3uwujryhcr.pdf

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

To improve our understanding of global energy and water cycle variability, and to improve model simulations of climate variations, it is vital to have accurate latent heat fluxes (LHF) over global oceans. Monthly LHF, 10-m wind speed (U10m), 10-m specific humidity (Q10h), and sea-air humidity difference (Qs-Q10m) of GSSTF2 (version 2 Goddard Satellite-based Surface Turbulent Fluxes) over global Oceans during 1992-93 are compared with those of HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data), NCEP (NCEP/NCAR reanalysis). The mean differences, standard deviations of differences, and temporal correlation of these monthly variables over global Oceans during 1992-93 between GSSTF2 and each of the three datasets are analyzed. The large-scale patterns of the 2yr-mean fields for these variables are similar among these four datasets, but significant quantitative differences are found. The temporal correlation is higher in the northern extratropics than in the south for all variables, with the contrast being especially large for da Silva as a result of more missing ship data in the south. The da Silva has extremely low temporal correlation and large differences with GSSTF2 for all variables in the southern extratropics, indicating that da Silva hardly produces a realistic variability in these variables. The NCEP has extremely low temporal correlation (0.27) and large spatial variations of differences with GSSTF2 for Qs-Q10m in the tropics, which causes the low correlation for LHF. Over the tropics, the HOAPS LHF is significantly smaller than GSSTF2 by approx. 31% (37 W/sq m), whereas the other two datasets are comparable to GSSTF2. This is because the HOAPS has systematically smaller LHF than GSSTF2 in space, while the other two datasets have very large spatial variations of large positive and negative LHF differences with GSSTF2 to cancel and to produce smaller regional-mean differences. Our analyses suggest that the GSSTF2 latent heat flux, surface air humidity, and winds are likely to be more realistic than the other three flux datasets examined, although those of GSSTF2 are still subject to regional biases.

A Comparison of Latent Heat Fluxes over Global Oceans for Four Flux Products

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.

GPCP Version 2.2 Combined Precipitation Data Set

The 1997-1999 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 1997-99 ENSO cycle. An examination of the evolution of the El Nino and accompanying precipitation anomalies revealed that a dry Maritime Continent preceded the formation of positive SST anomalies in the eastern Pacific Ocean. 30-60 day oscillations in the winter of 1996/97 may have contributed to this lag relationship. Furthermore, westerly wind burst events may have maintained the drought over the Maritime Continent. 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 1997-98 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 1998-99 La Nina. Reanalysis precipitation was compared to 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 to the observations. Also, the evolution of the precipitation field, including the drying of the Maritime Continent and eastward progression of rainfall in the equatorial Pacific was less pronounced for the model compared to the observations.

https://ntrs.nasa.gov/api/citations/20000086133/downloads/20000086133.pdf

Evolution of Tropical and Extratropical Precipitation Anomalies During the 1997 to 1999 Enso Cycle

The TRMM Multi-satellite Precipitation Analysis (TMPA) provides a calibration-based sequential scheme for combining multiple precipitation estimates from satellites, as well as gauge analyses where feasible, at fine scales (0.25 degrees x 0.25 degrees and 3-hourly). It 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 data set covers the latitude band 50 degrees N-S for the period 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 in one of the input products (based on AMSU-B). At finer scales the TMPA is successful at approximately reproducing the surface-observation-based histogram of precipitation, as well as reasonably detecting large daily events. The TMPA, however, has lower skill in correctly specifying moderate and light event amounts on short time intervals, in common with other fine-scale estimators. Examples are provided of a flood event and diurnal cycle determination.

The TRMM Multi-satellite Precipitation Analysis (TMPA): Quasi-Global Precipitation Estimates at Fine Scales

Precipitation retrieval is a challenging topic, especially in high latitudes (HL), and current precipitation products face ample challenges over these regions. This study investigates the potential of the Advanced Very High-Resolution Radiometer (AVHRR) for snowfall retrieval in HL using CloudSat radar information and machine learning (ML). With all the known limitations, AVHRR observations should be considered for HL snowfall retrieval because (1) AVHRR data have been continuously collected for about four decades on multiple platforms with global coverage, and similar observations will likely continue in the future; (2) current passive microwave satellite precipitation products have several issues over snow and ice surfaces; and (3) good coincident observations between AVHRR and CloudSat are available for training ML algorithms. Using ML, snowfall rate was retrieved from AVHRR’s brightness temperature and cloud probability, as well as auxiliary information provided by numerical reanalysis. The results indicate that the ML-based retrieval algorithm is capable of detection and estimation of snowfall with comparable or better statistical scores than those obtained from the Atmospheric Infrared Sounder (AIRS) and two passive microwave sensors contributing to the Global Precipitation Measurement (GPM) mission constellation. The outcomes also suggest that AVHRR-based snowfall retrievals are spatially and temporally reasonable and can be considered as a quantitatively useful input to the merged precipitation products that require frequent sampling or long-term records.

/pdf/assessment-of-the-advanced-very-high-resolution-radiometer-3kasjebj7i.pdf

Eric Nelkin

Papers

A Comparison of Latent Heat Fluxes over Global Oceans for Four Flux Products

GPCP Version 2.2 Combined Precipitation Data Set

Evolution of Tropical and Extratropical Precipitation Anomalies During the 1997 to 1999 Enso Cycle

The TRMM Multi-satellite Precipitation Analysis (TMPA): Quasi-Global Precipitation Estimates at Fine Scales

Assessment of the Advanced Very High-Resolution Radiometer (AVHRR) for Snowfall Retrieval in High Latitudes Using CloudSat and Machine Learning