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Emergent constraints on future precipitation changes

Nature volume 602, pages 612–616 (2022)Cite this article

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Abstract

Future projections of global mean precipitation change (ΔP) based on Earth-system models have larger uncertainties than projections of global mean temperature changes (ΔT)1. Although many observational constraints on ΔT have been proposed, constraints on ΔP have not been well studied2,3,4,5 and are often complicated by the large influence of aerosols on precipitation4. Here we show that the upper bound (95th percentile) of ΔP (2051–2100 minus 1851–1900, percentage of the 1980–2014 mean) is lowered from 6.2 per cent to 5.2–5.7 per cent (minimum–maximum range of sensitivity analyses) under a medium greenhouse gas concentration scenario. Our results come from the Coupled Model Intercomparison Project phase 5 and phase 6 ensembles6,7,8, in which ΔP for 2051–2100 is well correlated with the global mean temperature trends during recent decades after 1980 when global anthropogenic aerosol emissions were nearly constant. ΔP is also significantly correlated with the recent past trends in precipitation when we exclude the tropical land areas with few rain-gauge observations. On the basis of these significant correlations and observed trends, the variance of ΔP is reduced by 8–30 per cent. The observationally constrained ranges of ΔP should provide further reliable information for impact assessments.

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Fig. 1: Observational constraints on the future ΔP.
Fig. 2: Discrepancies between observed precipitation datasets.
Fig. 3: Spatial patterns of differences in future temperature and precipitation changes.

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Data availability

All data that support the findings of this study are available from the following: CMIP5, https://esgf-node.llnl.gov/search/cmip5/ (last access, 9 February 2021); CMIP6, https://esgf-node.llnl.gov/search/cmip6/ (last access, 9 February 2021); HadCRUT4, https://www.metoffice.gov.uk/hadobs/hadcrut4/ (last access, 7 October 2020); GISTEMP4, https://data.giss.nasa.gov/gistemp/ (last access, 9 March 2020); MSWEP2 (v2.2), http://www.gloh2o.org/ (last access, 30 September 2020); GSWP3, http://search.diasjp.net/en/dataset/GSWP3_EXP1_Forcing (last access, 13 October 2020); GPCC, https://www.dwd.de/EN/ourservices/gpcc/gpcc.html (last access, 26 February 2021).

Code availability

The codes are available from https://doi.org/10.6084/m9.figshare.16816714.

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Acknowledgements

This work was supported by the Integrated Research Program for Advancing Climate Models (JPMXD0717935457), Grants-in-Aid for Scientific Research (JP21H01161) of the Ministry of Education, Culture, Sports, Science and Technology of Japan, the Environment Research and Technology Development Fund (JPMEERF20202002) and the National Research Foundation of Korea grant (MSIT) (2021H1D3A2A03097768).

Author information

Authors and Affiliations

  1. Earth System Division, National Institute for Environmental Studies, Tsukuba, Japan

    Hideo Shiogama & Nagio Hirota

  2. Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Japan

    Masahiro Watanabe

  3. Moon Soul Graduate School of Future Strategy, Korea Advanced Institute of Science and Technology, Daejeon, Korea

    Hyungjun Kim

  4. Dept. of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea

    Hyungjun Kim

  5. Institute of Industrial Science, University of Tokyo, Tokyo, Japan

    Hyungjun Kim

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  1. Hideo Shiogama
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Contributions

H.S. mainly performed the analyses and wrote the paper. M.W. provided insights about the physics of precipitation changes and emergent constraints. H.K. provided the GSWP3 data and the information about the uncertainty sources of the observed precipitation datasets. N.H. contributed to the data collection, the selection of the observed datasets and the interpretation of the results. All authors discussed the results and commented on the manuscript.

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Correspondence to Hideo Shiogama.

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Nature thanks Chad Thackeray, Sabine Undorf and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Relationships between future ΔT and ΔP.

Horizontal and vertical axes indicate the future (2051–2100 minus 1851–1900) ΔT (°C) and ΔP (% of the 1980–2014 mean), respectively. Crosses and diamonds are CMIP5 and CMIP6 ESMs (ensemble mean for each ESM), respectively. Pearson’s correlations of the CMIP5 and CMIP6 ESMs are denoted in the panel. Those correlations are significant at the 5% level.

Extended Data Fig. 2 Definition of P*.

White shaded areas in the top panels indicate tropical (30° S–30° N) land regions where 1980–2014 mean numbers of rain gauge observations37 (Methods) are less than (a) 1, (b) 2 and (c) 3. Panels (d), (e) and (f) show P* anomalies relative to the 1980–2014 mean (%). Here P* represents the precipitation averaged over the pink shading areas of panels (a), (b) and (c), respectively. Solid lines are GPCP34 (red), MSWEP235 (green) and GSWP336 (blue). Dashed lines show their linear trends. Panel (e) is the same as Fig. 2b. We mainly focus on the case of panels (b) and (e) in this paper. (g) Relationships between the 1980–2014 trends of P and P* (P* in the case of (e)). Vertical and horizontal axes indicate the 1980–2014 trends of P and P* (% per 35 yr), respectively. Crosses and diamonds are CMIP56 and CMIP67,8 ESMs (ensemble mean for each ESM), respectively. Dashed line indicates the linear regression. Pearson’s correlation of the CMIP5 and CMIP6 ESMs is denoted in the panel. This correlation is significant at the 5% level. Grads was used to draw the maps.

Extended Data Fig. 3 Observational constraints on the future ΔP using only CMIP5 or CMIP6.

Horizontal axes show the recent past (1980–2014) trends of (top) T (°C per 35 yr) and (bottom) P* (% per 35 yr) for (left) CMIP5 and (right) CMIP6. Vertical axes indicate the future ΔP (2051–2100 minus 1851–1900 of hist+4.5, % of the 1980–2014 mean values). P* indicates precipitation averaged over the world except for some tropical land regions with few rain gauge observations (Extended Data Fig. 2b). Crosses and diamonds are CMIP5 and CMIP6 ESMs (ensemble mean for each ESM), respectively. Purple crosses/diamonds denote the ESMs whose recent past T trends are higher than the upper bound of HadCRUT4. Pearson’s correlations of the ESMs are denoted in the panels. Those correlations are significant at the 5% level. Dashed lines show the linear regressions. Horizontal bars indicate the 5–95% ranges of HadCRUT4 (light blue), GISTEMP4 (light green), GPCP (red), MSWEP2 (green) and GSWP3 (blue) (Methods). Box plots show the average (white line), 17–83% range (box), and 5–95% range (vertical bar) for the raw ESMs (black) and the constrained ranges using the observations (colours; navy and yellow for Had+GIS and GP+MS+GS, respectively).

Extended Data Fig. 4 Past trends of P due to individual and all forcing factors.

(a) Long-term (left, 1851–2014, % per 164 yr) and recent (right, 1980–2014, % per 35 yr) past trends of P in the ensembles of hist-GHG (red), hist-aer (blue) and hist-nat (green). (b) Horizontal and vertical axes are the long-term past trends of P (% per 164 yr) in hist+4.5 and hist-GHG, respectively. (c) Horizontal and vertical axes are the recent past trends of P (% per 35 yr) in hist+4.5 and hist-GHG, respectively.

Extended Data Fig. 5 Observational constraints on the future ΔP using historical P trend.

Vertical axis indicates the future ΔP (2051–2100 minus 1851–1900 of hist+4.5, % of the 1980–2014 mean values). Horizontal axis shows the recent past (1980–2014) trends of P (% per 35 yr). Crosses and diamonds are CMIP5 and CMIP6 ESMs (ensemble mean for each ESM), respectively. Purple crosses/diamonds denote the ESMs whose recent past T trends are higher than the upper bound of HadCRUT4. Dashed line shows the linear regression. Horizontal bars indicate the 5–95% ranges of GPCP (red), MSWEP2 (green) and GSWP3 (blue) (see Methods). Box plots show the average (white line), 17–83% range (box), and 5–95% range (vertical bar) for the raw CMIP5 and CMIP6 ESMs (black) and the constrained ranges using the observations (colours; yellow for GP+MS+GS). Triangle and asterisk symbols denote the 5–95% ranges using only the CMIP5 or CMIP6 ESMs, respectively. Pearson’s correlations of the CMIP5 and CMIP 6 ESMs are denoted in the panel. Those correlations are significant at the 5% level.

Extended Data Fig. 6 Discrepancies between observed precipitation datasets over the ocean and land.

Solid lines indicate the time series of precipitation anomalies relative to the 1980–2014 mean (%) averaged over (a) the ocean area plus Antarctica and (b) the land area except for Antarctica. Dashed lines show the linear trends. Red, green, blue and black (only for (b)) lines are GPCP, MSWEP2, GSWP3 and GPCC, respectively.

Extended Data Fig. 7 Effects of difference in the P* definition on the constraints.

Vertical axes indicate the future ΔP (2051–2100 minus 1851–1900 of hist+4.5, % of the 1980–2014 mean values) of the CMIP5 and CMIP6 ESMs. Box plots show the average (white line), 17–83% range (box), and 5–95% range (vertical bar) for the raw CMIP5/6 ESMs (black) and the constrained ranges using the P* trends of GP+MS+GS (yellow). The horizontal axis indicates the thresholds of rain gauge numbers used for the calculation of P*.

Extended Data Fig. 8 Relationships between past and future dP/dT (% per °C).

Vertical axes indicate the future dP/dT (calculated by dividing ΔP by ΔT of ‘2051–2100 minus 1851–1900’). Horizontal axes show the recent past (a) dP/dT and (b) dP*/dT (calculated by dividing the 1980–2014 trends of P and P* by the 1980–2014 T trends). Pearson’s correlations of the CMIP5 and CMIP6 ESMs are denoted in the panels. Those correlations are significant at the 5% level except for the CMIP5 of (b). Horizontal bars indicate the 5–95% ranges of GPCP (red), MSWEP2 (green) and GSWP3 (blue). Box plots show the average (white line), 17–83% range (box), and 5–95% range (vertical bar) for the raw CMIP5 and CMIP6 ESMs (black) and the constrained ranges using observations (colours). Because all the CMIP5 and CMIP6 ESMs are out of the range of MSWEP2/GISTEMP4 in (a), the corresponding constrained range is not available. Triangle and asterisk symbols denote the 5–95% ranges using only the CMIP5 or CMIP6 ESMs, respectively.

Extended Data Table 1 The analysed CMIP6 (left) and CMIP5 (right) ESMs and their ensemble sizes
Full size table
Extended Data Table 2 The mean values and the constrained 5–95% ranges of the future ΔP (2051–2100 minus 1851–1900, % of 1980–2014)
Full size table

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Shiogama, H., Watanabe, M., Kim, H. et al. Emergent constraints on future precipitation changes. Nature 602, 612–616 (2022). https://doi.org/10.1038/s41586-021-04310-8

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