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List of datasets covered by this document
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General definitions
In the scope of the Copernicus Climate Change Service (C3S), a Climate Data Record (CDR) always has a fixed end point in time, whereas an Interim Climate Data Record (ICDR) is extended continuously, often serving as an extension of a respective completed CDR.
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The GPCP provides an interim product for the monthly solutions, too. It is based on the same satellite data and respective algorithms, but relies on the input of only a preliminary version of the rain-gauge dataset by the Global Precipitation Climatology Centre (‘First Guess’ in contrast to the ‘Monitoring Product’ or the ‘Full Data Monthly’ product). Consequently, it is available much earlier than the fully processed data. When the rain-gauge dataset becomes available and the processing can be completed, the files containing the interim dataset are replaced by the fully processed ones. In the scope of brokering the GPCP data to C3S, we choose not to broker the interim monthly data in order to avoid confusion and frequent updates. Users interested in these more up-to-date files are referred to the original data repositories (see below).
Scope of the document
This document provides information on how to use the satellite- and rain gauge-based estimates of precipitation by the Global Precipitation Climatology Project (GPCP) at the University of Maryland (UMD). These datasets are brokered to the Climate Data Store (CDS) by the Copernicus Climate Change Service (C3S). The respective data products (daily and monthly means) are first described in terms of their input data and a brief overview of the algorithms; their target requirements in the scope of C3S and achieved performances are given; relevant information for usage is provided. The latter comprises geographical grid specifications, the data format, naming conventions, and the acknowledgement policy. This document is not part of the official GPCP documentation, but produced only in the scope of brokering the data to the CDS.
Executive summary
Estimates of precipitation by the Global Precipitation Climatology Project (GPCP) from the University of Maryland (UMD) are brokered to the Climate Data Store (CDS) by the Copernicus Climate Change Service (C3S). The GPCP is part of the international World Climate Research Programme (WCRP) and its Global Energy and Water Exchanges (GEWEX) project. All intellectual property rights remain with the GPCP.
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Compared to different satellite-based precipitation products TMPA 3B42 and 3B43 in lower latitudes (±50°), the spatial means of the monthly product achieve absolute deviations of less than 0.3 mm/d. The respective comparison for the daily product shows that almost 92.5% of all spatial means are within 0.3 mm/d. The specified decadal stability criterion of 0.034 mm/d/dec in this comparison is achieved by both the monthly (0.027 mm/d/dec) and the daily (0.032 mm/d/dec) products. Data covering times after Dec 2019 will be evaluated routinely with respect to ERA5, as TMPA products have been decommissioned. The mismatch between GPCP and ERA5 is generally larger than between GPCP and TMPA.
1. GPCP global monthly precipitation v2.3
The GPCP global monthly precipitation v2.3 product is brokered to the CDS by the C3S from the University of Maryland (UMD). The intellectual property rights remain with the GPCP team. The landing page for the product at UMD is http://gpcp.umd.edu/. The product provides estimates of monthly mean global precipitation and respective errors over land and ocean based on satellite and gauge measurements on a 2.5 degree grid since January 1979 until present.
1.1 Product description
The GPCP global monthly precipitation product merges rainfall estimates from several satellite-borne sensors and the gridded rain gauge-based product by the Global Precipitation Climatology Centre (GPCC). A respective list of input data is given in Table 1, based on Tables 1 and 2 in the C-ATBD [D1]. The methods used for generating the dataset are described in the C-ATBD [D1] and Adler et al. (2003). Recent changes related to the upgrade to latest version (v2.3) are discussed by Adler et al. (2018).
Table 1: Input data for GPCP monthly, see Tables 1 and 2 and algorithm description in [D1]. Anchor table1 table1
Name | Data type | GPCP time period | Data source | Notes |
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RSS SSMI Tb CDR | Brightness temperature | Aug 1987 to Dec 2008 | NCEI | Data from satellites F08: Jul 1987 to Dec 1991 (excl. Dec 1987) F11: Jan 1992 to May 1995 F13: June 1995 to Dec 2008 The passive microwave (brightness temperature) observations are used to retrieve precipitation rates over the oceans |
RSS SSMIS Tb CDR | Brightness temperature | Jan 2009 to present | NCEI | Replaces SSM/I Tb; data only from satellite F17 |
Ferraro | Precipitation | Aug 1987 to present | NESDIS/STAR | Precipitation rates over land based on SSMI/SSMIS observations, according to Ferraro (1997) |
TOVS | Precipitation | Aug 1987 to Dec 2002 | GPCP/GSFC | TOVS-based precipitation estimates (Susskind et al., 1997) merged with SSMI-based estimates and replace those estimates moving poleward from 40 degree latitude. |
AIRS V6 | Precipitation | Jan 2003 to present | GSFC DISC | Replaces TOVS |
OPI | Precipitation | Jan 1979 to Dec 1985 | GPCP/GSFC | Satellites used: TIROS-N, NOAA-6, NOAA-7, NOAA-9 AVHRR-based Outgoing Longwave Radiation Precipitation Index (OPI) |
IR Monthly | Brightness temperature | Jan 1986 to Dec 1996 | GPCP/GSFC | Infrared observations by geostationary satellites |
IR 3 hourly files | Brightness temperature | Jan 1997 to present | CPC | Files include IR histograms and OPI precipitation |
GPCC version 7 Full Data Reanalysis | Precipitation | Jan 1979 to Dec 2013 | DWD (GPCC) | Climate quality 2.5° gridded gauge data over land; reprocessed regularly Over land, the bias of the satellite-based is adjusted to match the bias of GPCC; then a weighted average of GPCC and satellite-based estimates is computed as final output of the algorithm |
GPCC Monitoring Product version 5 | Precipitation | Jan 2014 to present | DWD (GPCC) | Interim version of full analysis intended to continue record |
1.2 Target requirements
Table 2 provides an overview of achieved and targeted coverage and error-related properties of the TCDR-part of the dataset (until 12/2017). The target requirements (errors, stability) have been formulated in the context of monitoring the quality of precipitation products within C3S via Key Performance Indicators (KPI). They refer to the comparison of the dataset to a specific reference dataset. Here, the achieved specifications are computed in comparison with TMPA 3B43 (TRMM, 2011) which is available between 50°S and 50°N.
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Dataset property | Achieved | Target requirement | ||||||||||
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Geographic coverage | Global | Global | ||||||||||
Temporal coverage | 01/1979 - 12/2017 | Multi-decadal and up-to-date | ||||||||||
Random error | Absolute:
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Relative: | ||||||||||||
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Systematic error | 100% achieved* | 0.3 mm/d | ||||||||||
Stability | 0.027 mm/d/dec*,** | 0.034 mm/d/dec |
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The absolute random error percentiles are computed based on the uncertainties that are provided with the dataset at all grid cells and at all available time slices. The respective percentiles of the relative error are relative to the retrieved grid cell-wise precipitation estimates. The systematic error is computed per month as absolute bias (i.e. difference between GPCP monthly and TMPA 3B43 mean values in the TMPA window). The stability is the absolute of the slope of the bias time series of GPCP with respect to TMPA.
Table 3 provides an overview for the continuously updated ICDR-part of the dataset (from 01/2018; see the General Definitions section for details). Stability is not evaluated over such short periods. The targets for the systematic error are based on the respective performance of the TCDR – here the 2.5- and 97.5-percentiles; see the PQAR [D3] for details. Due to the decommissioning of TMPA products in 12/2019, the KPI accuracy is evaluated with respect to precipitation in ERA5 (C3S, 2017) for the data from 01/2020.
Table 3: Characteristics of the GPCP monthly mean precipitation rate v2.3 (ICDR – Jan 2018 onwards) Anchor table3 table3
Dataset property | Achieved | Target requirement |
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Geographic |
coverage | Global |
Global | |
Temporal |
coverage | 01/2018 - present |
Continuous updates | |
Random |
error | Same distribution as in Table 2 applies. |
n/a | ||
Systematic error | 100% achieved | 2018 & 2019: 2020 onwards: |
Stability | n/a | n/a |
1.3 Data usage information
The data format is NetCDF, compatible with conventions CF 1.6 and ACDD 1.3. The filenames are gpcp_v02r03_monthly_dYYYYMM.nc
where YYYY
specifies the year and MM
specifies the month to which the monthly mean provided in the file refers.
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A list of known issues is included in the respective C-ATBD [D1], section 6 “Assumptions and Limitations”.
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Please also include the following dataset and literature citations:
Dataset citation
Adler, Robert; Wang, Jian-Jian; Sapiano, Matthew; Huffman, George; Chiu, Long; Xie, Ping Ping; Ferraro, Ralph; Schneider, Udo; Becker, Andreas; Bolvin, David; Nelkin, Eric; Gu, Guojun; and NOAA CDR Program (2016). Global Precipitation Climatology Project (GPCP) Climate Data Record (CDR), Version 2.3 (Monthly). National Centers for Environmental Information. doi:10.7289/V56971M6 [access date]
Literature citation
Adler, R. F., M. Sapiano, G. J. Huffman, J.-J. Wang, G. Gu, D. Bolvin, L. Chiu, U. Schneider, A. Becker, E. Nelkin, P. Xie, R. Ferraro, and D.-B. Shin, 2018: The Global Precipitation Climatology Project (GPCP) Monthly Analysis (New Version 2.3) and a Review of 2017 Global Precipitation. Atmosphere, 9(4), 138, doi:10.3390/atmos9040138.
2. GPCP global daily precipitation v1.3
The GPCP global daily precipitation product v1.3 is brokered to the CDS by the C3S from the University of Maryland (UMD). The intellectual property rights remain with the GPCP team. The landing page for the product at UMD is http://gpcp.umd.edu/. The product provides estimates of daily mean global precipitation over land and ocean based on satellite measurements and on calibration of the fractional rainfall by the monthly GPCP product (see above) on a 1.0 degree grid since October 1996 until present. There is no error estimate provided with the dataset.
2.1 Product description
The GPCP global daily precipitation product merges rainfall estimates from several satellite-borne sensors. A respective list of input data is given in Table 4, based on the Table 1 in the C-ATBD [D2]. The methods used for generating the dataset are described in the C-ATBD [D2] and Huffman et al. (2001).
Table 4: Input data for GPCP daily, see Table 1 and algorithm description in [D2]. Anchor table4 table4
Name | Data type | GPCP time period | Data source | Notes |
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RSS SSMI Tb CDR | Brightness temperature | 1996 to 2008 | NCEI | Satellite F13 The passive microwave (brightness temperature) observations are used to retrieve precipitation rates over the oceans |
RSS SSMIS Tb CDR | Brightness temperature | 2009 to present | NCEI | Replaces SSM/I Tb; data only from F17 |
GPCP Monthly Analysis V2.3 | Precipitation | 1996 to present | NCEI | Fractional rainfall observations are calibrated by GPCP monthly |
TOVS | Precipitation | 1996 to 2002 | GPCP/GSFC | TOVS-based precipitation estimates (Susskind et al., 1997) merged with SSMI-based estimates and replace those estimates moving poleward from 40 degree latitude. |
AIRS V6 | Precipitation | 2003 to present | GSFC DISC | Replaces TOVS |
IR 3 hourly files | Brightness temperature | 1996 to present | CPC | Infrared observations by geostationary satellites Files include IR histograms and OPI precipitation |
2.2 Target requirements
Table 5 provides an overview of achieved and targeted coverage- and error-related properties of the TCDR dataset. The target requirements (errors, stability) have been formulated in the context of monitoring the quality of precipitation products within C3S via Key Performance Indicators. They refer to the comparison of the dataset to a specific reference dataset. Here, the achieved specifications are computed in comparison with TMPA 3B42 (Goddard Earth Sciences Data and Information Services Center, 2016) which is available between 50°S and 50°N.
Table 5: Characteristics of the GPCP daily mean precipitation rate v1.3 (CDR) Anchor table5 table5
Dataset property | Achieved | Target requirement |
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Geographic coverage | Global | Global |
Temporal coverage | 10/1996 - 12/2017 | Multi-decadal and up-to-date |
Random error | n/a | n/a |
Systematic error | 92.47% achieved* | 0.3 mm/d |
Stability | 0.032 mm/d/dec*,** | 0.034 mm/d/dec |
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The systematic error is computed per day as the absolute bias (i.e. difference between GPCP daily and TMPA 3B42 mean values in the TMPA window). The stability is the absolute of the slope of the bias time series of GPCP with respect to TMPA.
Table 6 provides a respective overview for the continuously updated ICDR-part of the dataset (from 01/2018; see the General Definitions section for details). Stability is not evaluated over such short periods. The targets for the systematic error are based on the respective performance of the TCDR – here the 2.5- and 97.5-percentiles; see the PQAR [D3] for details. Due to the decommissioning of TMPA products in 12/2019, the KPI accuracy is evaluated with respect to precipitation in ERA5 (C3S, 2017) for the data from 01/2020.
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Dataset property | Achieved | Target requirement |
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Geographic coverage | Global | Global |
Temporal coverage | 01/2018 - present | Continuous updates |
Random error | n/a | n/a |
Systematic error | 100% achieved | 2018 & 2019: 2020 onwards: |
Stability | n/a | n/a |
2.3 Data usage information
The data format is NetCDF, compatible with conventions CF 1.6 and ACDD 1.3. The filenames are gpcp_v01r03_daily_dYYYYMMDD.nc
where YYYY
specifies the year, MM
specifies the month, and DD
specifies the day of the month to which the daily mean provided in the file refers.
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Please also include the following dataset and literature citations:
Dataset citation
Adler, Robert; Wang, Jian-Jian; Sapiano, Mathew; Huffman, George; Bolvin, David; Nelkin, Eric; and NOAA CDR Program (2017). Global Precipitation Climatology Project (GPCP) Climate Data Record (CDR), Version 1.3 (Daily) [Indicate subset used.]. NOAA National Centers for Environmental Information. doi:10.7289/V5RX998Z [access date]
Literature citation
Huffman, G. J., R. F. Adler, M. Morrissey, D. T. Bolvin, S. Curtis, R. Joyce, B. McGavock, J. Susskind, 2001: Global Precipitation at One-Degree Daily Resolution from Multi-Satellite Observations. J. Hydrometeor., 2(1), 36-50, doi:10.1175/1525-7541(2001)002<0036:GPAODD>2.0.CO;2
3. Data access information
3.1 Data access through the UMD
The original repository for the data at the UMD can be found at http://gpcp.umd.edu/. Respective documentation at a separate NOAA repository (see URLs below) includes the C-ATBDs [D1, D2], acknowledgment guidelines, maturity matrices, and source codes.
- https://www.ncdcncei.noaa.gov/cdr/atmosphericproducts/climate-data-records/precipitation-gpcp-monthlydaily
- https://www.ncdcncei.noaa.gov/cdr/atmosphericproducts/climate-data-records/precipitation-gpcp-dailymonthly
3.2 Data access through the CDS
Within C3S, the distribution will be through the CDS (https://cds.climate.copernicus.eu/) where the C-ATBDs [D1, D2] will be uploaded, too. Additional documentation created for the inclusion of the dataset in the CDS, such as this PUGS document, will also be provided.
References
Adler, R.F., G.J. Huffman, A. Chang, R. Ferraro, P. Xie, J. Janowiak, B. Rudolf, U. Schneider, S. Curtis, D. Bolvin, A. Gruber, J. Susskind, P. Arkin, E. Nelkin, 2003: The Version 2 Global Precipitation Climatology Project (GPCP) Daily Precipitation Analysis (1979-Present). J. Hydrometeor., 4,1147-1167.
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Tropical Rainfall Measuring Mission (TRMM) (2011), TRMM (TMPA/3B43) Rainfall Estimate L3 1 month 0.25 degree x 0.25 degree V7, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC), doi: 10.5067/TRMM/TMPA/MONTH/7
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This document has been produced in the context of the Copernicus Climate Change Service (C3S). The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation agreement signed on 11/11/2014). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose. The users thereof use the information at their sole risk and liability. For the avoidance of all doubt , the European Commission and the European Centre for Medium - Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view. |
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