The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Robust Future Changes in Meteorological Drought in CMIP6 Projections Despite Uncertainty in Precipitation
Open accessAbstract
Quantifying how climate change drives drought is a priority to inform policy and adaptation planning. We show that the latest Coupled Model Intercomparison Project (CMIP6) simulations project coherent regional patterns in meteorological drought for two emissions scenarios to 2100. We find robust projected changes in seasonal drought duration and frequency (robust over >45% of the global land area), despite a lack of agreement across models in projected changes in mean precipitation (24% of the land area). Future drought changes are larger and more consistent in CMIP6 compared to CMIP5. We find regionalized increases and decreases in drought duration and frequency that are driven by changes in both precipitation mean and variability. Conversely, drought intensity increases over most regions but is not simulated well historically by the climate models. The more robust projections of meteorological drought compared to mean precipitation in CMIP6 provides significant new opportunities for water resource planning.
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Cites
An Overview of CMIP5 and the Experiment Design
Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-11-00094.1 · Cited by 14,052
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., & Taylor, K. E. (2016) · Geoscientific Model Development · doi:10.5194/gmd-9-1937-2016 · Cited by 11,981
Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010) · Journal of Climate · doi:10.1175/2009jcli2909.1 · Cited by 9,493
The representative concentration pathways: an overview
van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., et al. (2011) · Climatic Change · doi:10.1007/s10584-011-0148-z · Cited by 7,741
(1993) · Cited by 7,699
Updated high‐resolution grids of monthly climatic observations – the CRU TS3 .10 Dataset
Harris, I., Jones, P. D., Osborn, T. J., & Lister, D. H. (2014) · International Journal of Climatology · doi:10.1002/joc.3711 · Cited by 6,094
The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., et al. (2016) · Geoscientific Model Development · doi:10.5194/gmd-9-3461-2016 · Cited by 5,241 · cited 1×
“5 is a high emissions “fossil‐fueled development” scenario (O'Neill et al., 2016).”
BackgroundRobust Responses of the Hydrological Cycle to Global Warming
Held, I. M., & Soden, B. J. (2006) · Journal of Climate · doi:10.1175/jcli3990.1 · Cited by 4,959
Increasing drought under global warming in observations and models
Dai, A. (2013) · Nature Climate Change · doi:10.1038/nclimate1633 · Cited by 4,762
Cited by
Hydrological cycle and water resources in a changing world: A review
Yang, D., Yang, Y., & Xia, J. (2021) · Geography and Sustainability · doi:10.1016/j.geosus.2021.05.003 · Cited by 518
Song, Y. H., Shahid, S., & Chung, E. (2022) · International Journal of Climatology · doi:10.1002/joc.7386 · Cited by 45
Cano, I. M., Shevliakova, E., Malyshev, S., John, J. G., Yu, Y., Smith, B., & Pacala, S. W. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2203200119 · Cited by 34
Metadata
- Authors
- Ukkola, A. M., De Kauwe, M. G., Roderick, M. L., Abramowitz, G., & Pitman, A. J.
- Venue
- Geophysical Research Letters
- Publisher
- American Geophysical Union (AGU)
- Published
- 2020-06-09
- Volume
- 47
- Issue
- 11
- ISSN
- 0094-8276 (ISSN-L)
- 1944-8007
- OpenAlex
- W3023267714
- Cited by
- 528
- References
- 44
- FWCI
- 27.64
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Ukkola, A. M., De Kauwe, M. G., Roderick, M. L., Abramowitz, G., & Pitman, A. J. (2020). Robust Future Changes in Meteorological Drought in CMIP6 Projections Despite Uncertainty in Precipitation. Geophysical Research Letters. https://doi.org/10.1029/2020gl087820
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