Figure 1
A schematic diagram showing three components of the WMO High-Quality Global Data Management Framework for Climate (HQ-GDMFC).
Table 1
Details of the datasets which have been assessed by the SMM-CD up to September 2020. Updated list available at WMO Climate Data Catalogue of assessed datasets https://climatedata-catalogue.wmo.int/assessed-datasets.
| DOMAIN | DATASET | INSTITUTION | TYPE | DATE OF ASSESSMENT | WEBPAGE |
|---|---|---|---|---|---|
| Surface temperature | NOAAGlobalTemp v4.0.1 | NOAA | merged land–ocean surface temperature analysis | 2018-10-15, updated 2019-03-12 | https://www.ncdc.noaa.gov/data-access/marineocean-data/noaa-global-surface-temperature-noaaglobaltemp, http://dx.doi.org/10.1175/2007JCLI2100.1 |
| HadCRUT.4.6.0.0 | Met Office Hadley Centre | gridded dataset | 2019-03-08, updated 2019-03-21 | http://www.metoffice.gov.uk/hadobs/hadcrut4 (v4.5.0.0 also at https://catalogue.ceda.ac.uk/uuid/22a878b3ada24590970974588642f585) | |
| GISTEMP v3 | NASA | surface temperature analysis | 2019-03-09, updated 2020-01-21 | https://data.giss.nasa.gov/gistemp/ | |
| Precipitation | GPCC Full Data Monthly | DWD | globally gridded monthly totals | 2019-02-27, updated 2020-06-18 | www.doi.org/10.5676/DWD_GPCC/FD_M_V2018_100 |
| Crowdsourcing (Rain, hail & Snow fall) | CoCoRaHS | Colorado State Edu | observations | 2018-10-07, updated 2019-03-29 | https://www.cocorahs.org/ |
| Sea level | GLOSS | IOC | observations | 2018-10-17, updated 2019-04-17 | http://www.gloss-sealevel.org/ |
| CCl-SeaLevel | ESA | satellite | 2018-10-26, updated 2019-04-30 | https://climate.esa.int/en/projects/sea-level/ | |
| C3S-SeaLevel | Copernicus Climate Change Service | satellite | 2018-10-26, updated 2019-04-30 and 2020-08-31 | https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-sea-level-global?tab=overview | |
| Sea Ice | SeaIce Index | NSIDC | satellite | 2018-10-24, updated 2019-04-29 | https://nsidc.org/data/g02135, https://doi.org/10.7265/N5K072F8 |
| Ice Sheets | GLAS-DEM-500m | NASA-JPL | satellite | 2018-10-24, updated 2019-03-11 | https://nsidc.org/data/nsidc-0304, https://doi.org/10.5067/K2IMI0L24BRJ |
| GLAS-DEM-1km | NASA-JPL | satellite | 2018-10-24, updated 2019-03-18 | https://nsidc.org/data/nsidc-0422, https://doi.org/10.5067/H0FQ1KL9NEKM | |
| Antarctica-GRACE | NASA-JPL | satellite | 2018-10-24, updated 2019-03-10 | https://podaac.jpl.nasa.gov/dataset/ANTARCTICA_MASS_TELLUS_GRACE_MASCON_CRI_TIME_SERIES_RL05_V1, https://doi.org/10.5067/TEMSC-ANTS1 | |
| Greenland-GRACE | NASA-JPL | satellite | 2018-10-24, updated 2019-04-29 | https://podaac.jpl.nasa.gov/dataset/GREENLAND_MASS_TELLUS_GRACE_MASCON_CRI_TIME_SERIES_RL05_V1, https://doi.org/10.5067/TEMSC-GRTS1 | |
| Glaciers | GLIMS | GLIMS | satellite | 2018-10-24, updated 2019-02-24 | http://www.glims.org/ |
| Climate Extremes Indices | HadEX2 | Met Office Hadley Centre | observations and model data | 2018-05-07, updated 2019-06-16 | www.climdex.org, https://doi.org/10.1002/jgrd.50150 |
| Hydrology | GRDC | Bundesanstalt fuer Gewaesserkunde | observations | 2018-10-05, updated 2019-03-19 | https://www.bafg.de/GRDC/EN/01_GRDC/grdc_node.html |
| Marine | WOD13 | NOAA and IODE | observations | 2018-09-12, updated 2019-03-29 | https://www.nodc.noaa.gov/OC5/WOD/pr_wod.html, https://www.ncei.noaa.gov/products/world-ocean-database |
| ICOADS | NOAA | simple gridded monthly summary products | 2018-11-02, updated 2019-03-27 | https://icoads.noaa.gov/, http://dx.doi.org/10.1002/joc.4775 |
Figure 2
Diagram of SMM-CD Categories and Aspects. Based on Fig. 2 in Peng et al. (2019).
Figure 3
The maturity scale structure for the WMO SMM-CD. Based on Fig. 1 in Peng et al. (2019).
Figure 4
The maturity scale structure for the WMO SMM-CD_NRP.
Figure 5
Diagram of SMM-CD_NRP Categories and Aspects.
Table 2
The scores and evidence for each aspect from the Copernicus Climate Change Service (C3S) Sea level dataset assessed by the SMM-CD. These have been taken from the assessment document available through the WMO Data Catalogue.
| CATEGORY | ASPECT | SCORE ACHIEVED | SCORE EVIDENCE |
|---|---|---|---|
| Data Access | Discoverability | 5 | Dataset is discoverable in the C3S online searchable Climate Data Store (CDS, https://cds.climate.copernicus.eu/) including overview and metadata description. Operational production is maintained, and temporal extensions are routinely provided. Procedures for data integration in the catalogue are defined and applied. |
| Accessibility | 4.5 | Data is available through the institutional C3S CDS web interface with the possibility to select the period of interest. However, no spatial sub-setting is possible. All variables available must be downloaded together and data are made available on an ftp-based pull-mode access. Visualization is possible through the CDS toolbox (https://cds.climate.copernicus.eu/cdsapp#!/toolbox) | |
| Usability & Usage | Data Portability | 4.5 | Data format is NetCDF-4 and follow Climate-Forecast (CF) conventions. The CDS toolbox is available and allows further processing and customization of the data by the users |
| Documentation | 5 | Documentation based on a standard C3S template is available online with a unique ID and version number. The production system is fully described in the documentation. Altimetry tutorials are available online (http://www.altimetry.info/) and use cases produced with the C3S toolbox are in the process of being published. | |
| Usage and Impact | 5 | Sea level rise is a direct consequence of climate change and thus, the altimeter sea level time series is cited in numerous peer-reviewed publications (CMEMS OSR#4: https://marine.copernicus.eu/wp-content/uploads/2020/06/OSR4_Summary_WEB_SinglePages.pdf), in institutional reports (C3S European State of the Climate Report: https://climate.copernicus.eu/ESOTC), international climate assessment reports (ESA SL_CCI http://www.esa-sealevel-cci.org/webfm_send/584, IPCC SROCC 2019: www.ipcc.ch/srocc/) and is also used in policy-making process (WMO State of the Global Climate report: https://library.wmo.int/doc_num.php?explnum_id=10211). | |
| Quality Management | Quality Assurance and Control Procedure | 5 | QA/QC procedures are fully documented and applied to the full historical record and to the regular temporal extensions. Estimated accuracy numbers are available, derived from published studies of error characterization. The C3S EQC component aims at informing the users about the fitness for purpose of the datasets with an independent approach. Target requirements and gap analysis are available, and a dedicated user service desk considers user feedback. (https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-sea-level-global?tab=doc). |
| Quality Assessment | 5 | Product quality assurance procedure and assessment report are available in the data documentation. The dataset is produced and distributed within the European C3S. Detailed error budget has been produced, leading to uncertainty characterization and results have been published in peer-reviewed journal (Ablain et al., 2015; Taburet et al., 2019; Ablain et al., 2019; Prandi et al., 2021). | |
| Data Integrity | 5 | The copy of data files from the production server to the diffusion platform is made using the “rsync” Unix command which includes a ‘checksum’ verification step. Data integrity is thus systematically verified with a standard approach to ensure that data received, archived and disseminated are conform to the initial data files. | |
| Data Management | Preservation | 4 | The C3S sea level data are distributed on an institutionally maintained platform. The architecture of the equipment required for the production, diffusion and backup systems is defined and described in the public technical documentation. The diffusion server consists in a main server and a redundant one (hosted in a backup separated data centre). The data are systematically stored, saved and archived using secured internal repository, following defined and implemented procedure which is conform to community standards. |
| Metadata | 5 | The metadata available in each data file are compliant with international standards and support dataset provenance. Metadata is updated following each evolution of the input data. The input data are described in the Product User Guide and Specification (http://datastore.copernicus-climate.eu/documents/satellite-sea-level/D3.SL.1-v1.2_PUGS_of_v1DT2018_SeaLevel_products_v2.4.pdf) so that data product can be linked to the version of the data from which it was derived. | |
| Governance | 5 | The responsibility of the data production is clearly defined within the E.U. C3S. Point of contact is clearly defined. The entity in charge of the management of the data production and delivery service is audited annually. |
Table 3
Details of the datasets which have been assessed by the SMM-CD_NRP up to September 2020.
| DOMAIN | DATASET | INSTITUTION | TYPE | DATE OF ASSESSMENT | WEBPAGE | NOTES |
|---|---|---|---|---|---|---|
| Brazil | Temperature, Precipitation and Humidity | INMET | Automatic and Manual Weather Stations | 24.09.2020 | https://bdmep.inmet.gov.br | The annual number of stations varies according to the year of implementation of automatic stations and removal of conventional stations |
| Canada | Daily maximum and minimum temperatures, monthly mean temperature | Environment and Climate Change Canada | Homogenized data time series using observations from manual and automatic stations | 11.08.2020 | Daily data at http://crd-data-donnees-rdc.ec.gc.ca/CDAS/products/EC_data/AHCCD_daily/ and monthly data at ftp://ccrp.tor.ec.gc.ca/pub/AHCCD/ | |
| Germany | QuWind100 | DWD | model data | 20.08.2020 | https://www.dwd.de/DE/leistungen/quwind100/qu-wind_100.html | Download at https://opendata.dwd.de/climate_environment/CDC/grids_germany/multi_annual/wind_parameters/Project_QuWind100/ |
| Germany | Radar-based Precipitation Climatology for Germany | DWD | remote sensing data | 20.08.2020 | https://opendata.dwd.de/climate_environment/GPCC/radarklimatologie/ | Download at https://www.doi.org/10.5676/DWD/RADKLIM_RW_V2017.002 |
| France | DRIAS 2020 Climate simulations corrected over Metropolitan France | Méteo-France | Climate simulation | 04.09.2020 | http://www.drias-climat.fr/ |