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CGIAR Climate Action CGIAR Climate Data Hub — Wikis

References and further reading

The full bibliography for this wiki section. Citations are grouped by topic; each individual wiki page links directly to the source rather than to a footnote here.

Foundational climate-science references

  • Eyring, V., et al. (2016). “Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organisation.” Geosci. Model Dev. 9, 1937–1958. DOI
  • Hawkins, E. & Sutton, R. (2009). “The potential to narrow uncertainty in regional climate predictions.” Bull. Am. Meteorol. Soc. 90, 1095–1108. DOI
  • Hourdin, F., et al. (2017). “The art and science of climate model tuning.” Bull. Am. Meteorol. Soc. 98, 589–602. DOI
  • Knutti, R. & Sedláček, J. (2013). “Robustness and uncertainties in the new CMIP5 climate model projections.” Nat. Clim. Change 3, 369–373. DOI
  • Knutti, R., et al. (2013). “Climate model genealogy: Generation CMIP5 and how we got there.” Geophys. Res. Lett. 40, 1194–1199. DOI
  • Sanderson, B. M., et al. (2015). “A representative democracy to reduce interdependency in a multimodel ensemble.” J. Climate 28, 5171–5194. DOI
  • Tebaldi, C. & Knutti, R. (2007). “The use of the multi-model ensemble in probabilistic climate projections.” Phil. Trans. R. Soc. A 365, 2053–2075. DOI

Climate sensitivity and the hot model problem

  • Brunner, L., et al. (2020). “Reduced global warming from CMIP6 projections when weighting models by performance and independence.” Earth Syst. Dynam. 11, 995–1012. DOI
  • Forster, P., et al. (2021). “The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity.” In AR6 WGI Chapter 7. IPCC
  • Hausfather, Z., Marvel, K., Schmidt, G. A., Nielsen-Gammon, J. W., Zelinka, M. (2022). “Climate simulations: recognize the ‘hot model’ problem.” Nature 605, 26–29. DOI
  • Sherwood, S. C., et al. (2020). “An assessment of Earth’s climate sensitivity using multiple lines of evidence.” Rev. Geophys. 58, e2019RG000678. DOI
  • Bloch-Johnson, J., Rugenstein, M., Gregory, J., Cael, B. B. & Andrews, T. (2022). “Climate impact assessments should not discount ‘hot’ models.” Nature 608, 667. DOI
  • Tokarska, K. B., et al. (2020). “Past warming trend constrains future warming in CMIP6 models.” Sci. Adv. 6, eaaz9549. DOI

Downscaling and bias correction

  • Cannon, A. J., Sobie, S. R., Murdock, T. Q. (2015). “Bias correction of GCM precipitation by quantile mapping: How well do methods preserve changes in quantiles and extremes?” J. Climate 28, 6938–6959. DOI
  • Ehret, U., et al. (2012). “Should we apply bias correction to global and regional climate model data?” Hydrol. Earth Syst. Sci. 16, 3391–3404. DOI
  • Giorgi, F. & Gutowski, W. J. Jr. (2015). “Regional dynamical downscaling and the CORDEX initiative.” Annu. Rev. Environ. Resour. 40, 467–490. DOI
  • Gutiérrez, J. M., et al. (2019). “An intercomparison of a large ensemble of statistical downscaling methods over Europe.” Int. J. Climatol. 39, 3750–3785. DOI
  • Lange, S. (2019). “Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0).” Geosci. Model Dev. 12, 3055–3070. DOI
  • Maraun, D. (2016). “Bias correcting climate change simulations — a critical review.” Curr. Clim. Change Rep. 2, 211–220. DOI
  • Maraun, D. & Widmann, M. (2018). Statistical Downscaling and Bias Correction for Climate Research. Cambridge University Press. DOI
  • Thrasher, B., et al. (2022). “NASA Global Daily Downscaled Projections, CMIP6.” Sci. Data 9, 262. DOI
  • Wood, A. W., et al. (2004). “Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs.” Clim. Change 62, 189–216. DOI

African regional evaluations

  • Faye, A. & Akinsanola, A. A. (2022). “Evaluation of extreme precipitation indices over West Africa in CMIP6 models.” Climate Dynamics 58, 925–939. DOI
  • Ayugi, B., et al. (2021). “Future Changes in Precipitation Extremes over East Africa Based on CMIP6 Models.” Water 13, 2358. DOI
  • Endris, H. S., Lennard, C., Hewitson, B., Dosio, A., Nikulin, G., Artan, G. A. (2019). “Future changes in rainfall associated with ENSO, IOD and changes in the mean state over eastern Africa.” Climate Dynamics 52, 2029–2053. DOI
  • Lim Kam Sian, K. T. C., Wang, J., Ayugi, B. O., Nooni, I. K., Ongoma, V. (2021). “Multi-Decadal Variability and Future Changes in Precipitation over Southern Africa.” Atmosphere 12(6), 742. DOI
  • Iturbide, M., et al. (2020). “An update of IPCC climate reference regions for subcontinental analysis of climate model data.” Earth Syst. Sci. Data 12, 2959–2970. DOI
  • Makinde, A. A., et al. (2026). “How Well Do CMIP6 Models Simulate the Influence of the West African Westerly Jet on Sahel Precipitation?” International Journal of Climatology. DOI
  • Park, S., Sniderman, J. M. K., Frierson, D. M. W., McKinnon, K. A. (2023). “Understanding CMIP6 biases in the representation of the Greater Horn of Africa long and short rains.” Climate Dynamics. DOI
  • Pinto, I., Jack, C., Hewitson, B. (2018). “Process-based model evaluation and projections over Southern Africa from CORDEX and CMIP5 models.” International Journal of Climatology 38(11), 4251–4264. DOI
  • Samuel, S., Mengistu Tsidu, G., Dosio, A., Mphale, K. (2025). “Assessment of Historical and Future Mean and Extreme Precipitation Over Sub-Saharan Africa Using NEX-GDDP-CMIP6: Part I — Evaluation of Historical Simulation.” Int. J. Climatol. DOI

East African Paradox

  • Schwarzwald, K., Brönnimann, S., Vellinga, M., Schmid, M. (2024). “Revisiting the ‘East African Paradox’: CMIP6 Models Also Struggle to Reproduce Strong Observed Long Rain Drying Trends.” Journal of Climate 37(24). DOI
  • Wainwright, C. M., Marsham, J. H., Black, E., Allan, R. P. (2019). “‘Eastern African Paradox’ rainfall decline due to shorter not less intense Long Rains.” npj Clim. Atmos. Sci. 2, 34. DOI

IPCC AR6 chapters most-cited here

  • AR6 WGI Summary for Policymakers (Masson-Delmotte et al. 2021). Link
  • AR6 WGI Chapter 1 — Framing, Context, Methods. Chapter
  • AR6 WGI Chapter 3 — Human Influence on the Climate System. Chapter
  • AR6 WGI Chapter 4 — Future Global Climate: Scenario-Based Projections. Chapter
  • AR6 WGI Chapter 7 — Earth’s Energy Budget, Climate Feedbacks, and Sensitivity. Chapter
  • AR6 WGI Chapter 10 — Linking Global to Regional Climate Change. Chapter
  • AR6 WGI Chapter 11 — Weather and Climate Extreme Events. Chapter
  • AR6 WGI Atlas Chapter (Gutiérrez et al. 2021). Chapter
  • AR6 WGII Chapter 9 — Africa (Trisos et al. 2022). Chapter
  • AR6 Interactive Atlas (Iturbide, Gutiérrez et al.). Interactive Atlas

Grey literature and institutional sources

  • CORDEX project — CORDEX · 2025 domain activities at CORDEX 2025. Note: a specific Coppola et al. 2021 paper on CORDEX-CORE was cited in an earlier draft of this wiki; the DOI didn’t resolve to a real paper. CORDEX-CORE is now cited via the project page only until a definitive peer-reviewed reference is identified.
  • Nikulin, G., Jones, C. G., Giorgi, F., et al. (2012). “Precipitation Climatology in an Ensemble of CORDEX-Africa Regional Climate Simulations.” Journal of Climate 25(18), 6057–6078. DOI
  • van Vuuren, D. P., O’Neill, B. C., Tebaldi, C., Sanderson, B. M., et al. (2026). “The Scenario Model Intercomparison Project for CMIP7 (ScenarioMIP-CMIP7).” Geoscientific Model Development 19, 2627–2656. DOI
  • ICPAC publications — ICPAC publications · CMIP6 Climate Change Information Portal ICPAC RCC climate change
  • NASA NEX-GDDP-CMIP6 product page — NASA NCCS
  • CHELSA-CMIP6 product page — chelsa-climate.org/cmip6
  • ISIMIP framework documentation — isimip.org · ISIMIP3b bias-adjustment fact sheet PDF
  • WCRP CMIP7 Fast Track — WCRP-CMIP CMIP7
  • WMO State of the Climate in Africa 2024 — WMO publications
  • WMO State of the Climate in Africa 2023 — PDF on UNECA-ACPC
  • AR6 Interactive Atlas methodology paper — Gutiérrez et al. (2025) on PLOS Climate DOI
  • Carbon Brief explainers — How climate models work · Hot models
  • World Bank Climate Knowledge Portal — CCKP
  • Copernicus Climate Data Store — Copernicus CDS
  • GCF document library — GCF
  • AICCRA project deliverables — aiccra.cgiar.org

Observational and reanalysis datasets

  • Hersbach, H., et al. (2020). “The ERA5 global reanalysis.” Q. J. R. Meteorol. Soc. 146, 1999–2049. DOI
  • Funk, C., et al. (2015). “The climate hazards infrared precipitation with stations — a new environmental record for monitoring extremes.” Sci. Data 2, 150066. DOI
  • Funk, C., et al. (2019). “A high-resolution 1983–2016 Tmax climate data record based on infrared temperatures and stations by the Climate Hazards Center.” J. Climate 32, 5639–5658. DOI
  • Gelaro, R., et al. (2017). “The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2).” J. Climate 30, 5419–5454. DOI
  • Sheffield, J., Goteti, G., Wood, E. F. (2006). “Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling.” J. Climate 19, 3088–3111. DOI
  • Cucchi, M., et al. (2020). “WFDE5: bias-adjusted ERA5 reanalysis data for impact studies.” Earth Syst. Sci. Data 12, 2097–2120. DOI

How this list is maintained

This bibliography is updated as the wiki pages are written; each citation that appears inline on a wiki page also appears here for at-a-glance review. When a new edition of an annual publication (e.g. WMO State of Climate Africa) drops, the entry above is refreshed.

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