ISIMIP2a atmospheric climate input data

Cite as

Stefan Lange, Matthias Büchner (2020): ISIMIP2a atmospheric climate input data (v1.0). ISIMIP Repository. https://doi.org/10.48364/ISIMIP.886955

Metadata

DOI:
https://doi.org/10.48364/ISIMIP.886955
Title:
ISIMIP2a atmospheric climate input data
Version:
1.0
Creators:
Abstract:

The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for advanced estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate impacts across sectors.

ISIMIP2a is the first simulation round of the second phase of ISIMIP, focusing on historical simulations of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This will serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming.

These datasets contain the historical (atmospheric) climate data to be used in ISIMIP2a simulations. All datasets provide the variables near-surface air temperature (tas), precipitation (pr), near-surface relative humidity (rhs), surface downwelling longwave radiation (rlds), surface downwelling shortwave radiation (rsds), surface pressure (ps), and near-surface wind speed (wind). In addition, some datasets also provide daily minimum and maximum near-surface air temperature (tasmin and tasmax, respectively).

Included are 6 datasets: GSWP3, PGMFD, WATCH, WATCH-WFDEI, GSWP3-EWEMBI, and GSWP3-W5E5. They all have global coverage at daily temporal and 0.5° spatial resolution. Temporal coverage differs between datasets.

Methods:

All 6 datasets are observational in nature, i.e., based on reanalyses and other observational data sources. GSWP3 v0.5b covers 1901-2010, was generated in phase 3 of the Global Soil Wetness Project (GSWP3; Dirmeyer et al., 2006) and is a dynamically downscaled and bias-adjusted version of the 20th Century Reanalysis v2 (Compo et al., 2011; Kim, 2017).

The Princeton Global Meteorological Forcing Dataset (PGMFD) v2.1 covers 1901-2012 and is an interpolated and bias-adjusted version of the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP-NCAR) reanalysis (Kalnay et al. 1996; Kistler et al. 2001), with data for years prior to 1948 generated based on resampled NCEP-NCAR data (Sheffield et al., 2006).

The WATCH Forcing Dataset (also known als WFD) covers 1901-2001 and was generated in the WATer and Global Change (WATCH) project. It is an interpolated and bias-adjusted version of ERA-40, the 40-year reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF; Uppala et al., 2005), with data for years prior to 1958 generated based on resampled ERA-40 data (Weedon et al., 2011).

WATCH-WFDEI covers 1901-2016 and is a combination of WATCH for 1901-1978 with WFDEI for 1979-2016, where WFDEI is an interpolated and bias-adjusted version of the ERA-Interim reanalysis (Dee et al., 2011; Weedon et al., 2014). Since the two input datasets were not homogenized prior to their combination, the WATCH-WFDEI data are potentially discontinuous at the 1978/1979 transition, and results must be interpreted with caution (Müller Schmied et al., 2016).

GSWP3-EWEMBI covers 1901-2016 and is a combination of GSWP3 v0.5b for 1901-1978 with EWEMBI v1.1 for 1979-2016, where EWEMBI is another interpolated and bias-adjusted version of the ERA-Interim reanalysis (Lange, 2018; Lange, 2019a). In order to reduce discontinuities at the 1978/1979 transition, prior to their combination, GSWP3 data were homogenized with EWEMBI data using the bias-adjustment method ISIMIP3BASD v2.4.1 (Lange, 2019b; Lange, 2020).

GSWP3-W5E5 covers 1901-2016 and is a combination of GSWP3 v0.5b for 1901-1978 with W5E5 v1.0 for 1979-2016, where W5E5 is an interpolated and bias-adjusted version of the ERA5 reanalysis (Hersbach et al., 2020; Lange, 2019c; Cucchi et al., 2020). Also in this case, prior to their combination, GSWP3 data were homogenized with W5E5 data using ISIMIP3BASD v2.4.1.

Publication date:
Nov. 16, 2020
Publisher:
ISIMIP Repository
Contributors:

Here we list the persons and organizations, who are responsible for the collection, the management, and the publication of this dataset.

Rights

CC0 1.0 Universal Public Domain Dedication
CC0 1.0 Universal Public Domain Dedication (CC0 1.0)
When using ISIMIP data for your research, please appropriately credit the data providers, e.g. either by citing the DOI for the dataset, or by appropriate acknowledgment. We strongly encourage to offer co-authorship to at least a representative of the data providers. Further information can be found in our terms of use.

Export

Download

API

References

  • Weedon, G.P., S.S. Gomes, P.P. Viterbo, W.J. Shuttleworth, E.E. Blyth, H.H. Österle, J.C. Adam, N.N. Bellouin, O.O. Boucher, and M.M. Best, 2011: Creation of the WATCH Forcing Data and Its Use to Assess Global and Regional Reference Crop Evaporation over Land during the Twentieth Century. J. Hydrometeor., 12, 823–848 https://doi.org/10.1175/2011JHM1369.1
  • Weedon, G. P., G. Balsamo, N. Bellouin, S. Gomes, M. J. Best, and P. Viterbo (2014), The WFDEI meteorological forcing data set: WATCH Forcing Data methodology applied to ERA-Interim reanalysis data, Water Resour. Res., 50, 7505–7514 https://doi.org/10.1002/2014WR015638
  • Dirmeyer, P. A., Gao, X., Zhao, M., Guo, Z., Oki, T. and Hanasaki, N. (2006). GSWP-2: Multimodel Analysis and Implications for Our Perception of the Land Surface. Bulletin of the American Meteorological Society, 87(10), 1381–98 https://doi.org/10.1175/BAMS-87-10-1381
  • Cucchi, M., Weedon, G. P., Amici, A., Bellouin, N., Lange, S., Müller Schmied, H., Hersbach, H., and Buontempo, C.: WFDE5: bias-adjusted ERA5 reanalysis data for impact studies, Earth Syst. Sci. Data, 12, 2097–2120, 2020. https://doi.org/10.5194/essd-12-2097-2020
  • Lange, S. (2019b): Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0), Geosci. Model Dev., 12, 3055–3070 https://doi.org/10.5194/gmd-12-3055-2019
  • Sheffield, J., G. Goteti, and E. F. Wood, 2006: Development of a 50-yr high-resolution global dataset of meteorological forcings for land surface modeling, J. Climate, 19 (13), 3088-3111 https://doi.org/10.1175/JCLI3790.1
  • Lange, Stefan. (2020). ISIMIP3BASD (2.4.1). Zenodo. https://doi.org/10.5281/zenodo.3898426
  • Compo, G.P., Whitaker, J.S., Sardeshmukh, P.D., Matsui, N., Allan, R.J., Yin, X., Gleason, B.E., Vose, R.S., Rutledge, G., Bessemoulin, P., Brönnimann, S., Brunet, M., Crouthamel, R.I., Grant, A.N., Groisman, P.Y., Jones, P.D., Kruk, M.C., Kruger, A.C., Marshall, G.J., Maugeri, M., Mok, H.Y., Nordli, Ø., Ross, T.F., Trigo, R.M., Wang, X.L., Woodruff, S.D. and Worley, S.J. (2011), The Twentieth Century Reanalysis Project. Q.J.R. Meteorol. Soc., 137: 1-28. https://doi.org/10.1002/qj.776
  • Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R., Jenne, R., & Joseph, D. (1996). The NCEP/NCAR 40-Year Reanalysis Project, Bulletin of the American Meteorological Society, 77(3), 437-472. https://doi.org/10.1175/1520-0477(1996)077%3C0437:TNYRP%3E2.0.CO;2
  • Kistler, R., Kalnay, E., Collins, W., Saha, S., White, G., Woollen, J., Chelliah, M., Ebisuzaki, W., Kanamitsu, M., Kousky, V., van den Dool, H., Jenne, R., & Fiorino, M. (2001). The NCEP–NCAR 50-Year Reanalysis: Monthly Means CD-ROM and Documentation, Bulletin of the American Meteorological Society, 82(2), 247-268. https://doi.org/10.1175/1520-0477(2001)082%3C0247:TNNYRM%3E2.3.CO;2
  • Uppala, S.M., KÅllberg, P.W., Simmons, A.J., Andrae, U., Bechtold, V.D.C., Fiorino, M., Gibson, J.K., Haseler, J., Hernandez, A., Kelly, G.A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R.P., Andersson, E., Arpe, K., Balmaseda, M.A., Beljaars, A.C.M., Berg, L.V.D., Bidlot, J., Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher, M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B.J., Isaksen, L., Janssen, P.A.E.M., Jenne, R., Mcnally, A.P., Mahfouf, J.-F., Morcrette, J.-J., Rayner, N.A., Saunders, R.W., Simon, P., Sterl, A., Trenberth, K.E., Untch, A., Vasiljevic, D., Viterbo, P. and Woollen, J. (2005), The ERA-40 re-analysis. Q.J.R. Meteorol. Soc., 131: 2961-3012. https://doi.org/10.1256/qj.04.176
  • Dee, D.P., Uppala, S.M., Simmons, A.J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M.A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A.C.M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A.J., Haimberger, L., Healy, S.B., Hersbach, H., Hólm, E.V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A.P., Monge-Sanz, B.M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N. and Vitart, F. (2011), The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol. Soc., 137: 553-597. https://doi.org/10.1002/qj.828
  • Müller Schmied, H., Adam, L., Eisner, S., Fink, G., Flörke, M., Kim, H., Oki, T., Portmann, F. T., Reinecke, R., Riedel, C., Song, Q., Zhang, J., and Döll, P.: Variations of global and continental water balance components as impacted by climate forcing uncertainty and human water use, Hydrol. Earth Syst. Sci., 20, 2877–2898, 2016. https://doi.org/10.5194/hess-20-2877-2016
  • Lange, S.: Bias correction of surface downwelling longwave and shortwave radiation for the EWEMBI dataset, Earth Syst. Dynam., 9, 627–645, 2018. https://doi.org/10.5194/esd-9-627-2018
  • Hersbach, H, Bell, B, Berrisford, P, et al. The ERA5 global reanalysis. Q J R Meteorol Soc. 2020; 146: 1999– 2049. https://doi.org/10.1002/qj.3803

Source datasets

Additional documentation

GCMD Keywords

  • EARTH SCIENCE > ATMOSPHERE
  • Global Change Master Directory (GCMD) Keywords are a hierarchical set of controlled vocabularies maintained by NASA (more information).

Datasets for this DOI

There are 62 datasets for this DOI. You can use the search interface to further restrict your query: https://data.isimip.org/search/query/10.48364/ISIMIP.886955/
pFad - Phonifier reborn

Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy