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Emergence of seasonal delay of tropical rainfall during 1979–2019

Nature Climate Change volume 11, pages 605–612 (2021)Cite this article

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Abstract

Tropical rainfall exhibits a prominent annual cycle, with characteristic amplitude and phase representing the range between wet and dry seasons and their onset timing, respectively. Previous studies note enhanced amplitude over ocean and delayed phase over land in model projections of global warming, underpinned by first-order physical principles. However, it is unclear whether these changes have emerged in observations. Here we use gridded precipitation datasets to report a seasonal delay of 4.1 ± 1.1 and 4.2 ± 0.9 days (P < 0.05) during 1979–2019 over the northern tropical land and Sahel, respectively. Most of the delay is driven by external forcings, dominated by greenhouse gases (GHG) and anthropogenic aerosols (AER). Increasing GHG and decreasing AER in the recent decades delay rainfall by producing a moister atmosphere, thus increasing its lag in response to seasonal solar forcing. As GHG increase and AER decrease, these seasonal delays are projected to further amplify in the future.

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Fig. 1: Observed and simulated phase changes of precipitation annual cycle.
Fig. 2: Linear trends of precipitation inter-seasonal difference (SON – MAM) during 1979–2019.
Fig. 3: Energetic constraint on precipitation annual cycle phase changes under GHG and AER.
Fig. 4: Changes in annual-mean temperature and relative humidity under GHG and AER during 1850–2020.
Fig. 5: Future projection of precipitation annual cycle phase evolutions and energetic constraints in twenty-first century.

Data availability

The Climate Prediction Center (CPC) merged analysis of precipitation dataset is available at https://psl.noaa.gov/data/gridded/data.cmap.html. The Global Precipitation Climatology Project dataset is available at https://www.ncei.noaa.gov/data/global-precipitation-climatology-project-gpcp-monthly/access/. The PRECipitation REConstruction over Land dataset is available at https://psl.noaa.gov/data/gridded/data.precl.html. The Global Precipitation Climatology Centre dataset is available at https://psl.noaa.gov/data/gridded/data.gpcc.html. U-Delaware is available at https://psl.noaa.gov/data/gridded/data.UDel_AirT_Precip.html. The Climatic Research Unit dataset is available at https://catalogue.ceda.ac.uk/uuid/89e1e34ec3554dc98594a5732622bce9. The CPC dataset is available at https://psl.noaa.gov/data/gridded/data.cpc.globalprecip.html.

CMIP5 model outputs are available at http://www.ipcc-data.org/sim/gcm_monthly/AR5/Reference-Archive.html. CMIP6 model outputs are available at https://esgf-node.llnl.gov/search/cmip6/. CESM1 LENS are available at http://www.cesm.ucar.edu/projects/community-projects/LENS/. MPI-GE are available at https://esgf-data.dkrz.de/projects/mpi-ge/. CanESM2 LENS are available at https://open.canada.ca/data/en/dataset/aa7b6823-fd1e-49ff-a6fb-68076a4a477c.

Code availability

The code used to generate the figures and table are based on NCAR Command Language (NCL v.6.4.0; https://doi.org/10.5065/D6WD3XH5). The codes used to calculate the observed and simulated seasonal phase of precipitation, conduct the atmospheric energetic analysis and produce the main figures are available at https://zenodo.org/record/4695287#.YHi4HS1h3vE.

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Acknowledgements

This research is supported by the US Department of Energy Office of Science Biological and Environmental Research as part of the Regional and Global Model Analysis program area. PNNL is operated for the Department of Energy by Battelle Memorial Institute under contract DE-AC05-76RL01830. The authors acknowledge the World Climate Research Program’s Working Group on Coupled Modeling, which is responsible for CMIP5 and CMIP6, and thank the climate modelling groups for producing and making available their model output. The authors also thank the NCAR CESM group for making the large-ensemble (LENS) experiments available, the MPI-ESM group for making the MPI-GE experiments available and the CanESM2 group for making the CanESM2 LENS experiments available. For CMIP5 and CMIP6, the US DOE’s Program for Climate Model Diagnostics and Intercomparison provides coordinating support and led the development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

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Authors and Affiliations

  1. Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA

    Fengfei Song, L. Ruby Leung, Jian Lu, Lu Dong, Wenyu Zhou, Bryce Harrop & Yun Qian

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  1. Fengfei Song
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Contributions

F.S. and L.R.L. designed the research. F.S. performed the analysis, drew all the figures and wrote the first draft of the paper. All authors provided comments on different versions of the paper.

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Correspondence to Fengfei Song or L. Ruby Leung.

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Extended data

Extended Data Fig. 1 The observed and simulated phase changes of precipitation annual cycle over the NTL and Sahel in each dataset.

The time evolution of precipitation annual cycle phase in (a, c) eight observational datasets (OBS) and (b, d) five historical simulations ensembles (EXT) during 1979-2019 over (a-b) the NTL (0°-25°N) and (c-d) the Sahel. The numbers in the brackets show the total phase changes (days) during their respective periods (1979-2019 for GPCP, CMAP, PRECL, CPC, CRU and all EXT simulations; 1979-2017 for U-Delaware; 1979-2016 for GPCC; 1979-2014 for GHCN) and the confidence levels; the reference period is 1980-1999.

Extended Data Fig. 2 The observed and simulated phase changes of precipitation annual cycle over the southern tropical land in each dataset.

Same as Extended Data Fig. 1a,b but for the southern tropical land (0°-25°S).

Extended Data Fig. 3 The observed and simulated amplitude changes of precipitation annual cycle over the northern and southern tropical ocean in each dataset.

Same as Extended Data Fig. 1a,b but for the precipitation annual cycle amplitude over (a, c) the northern tropical ocean (0°-25°N) and (b, d) the southern tropical ocean (0°-25°S).

Extended Data Fig. 4 The linear trends of precipitation for the inter-seasonal difference (SON - MAM) during 1979-2019 in each simulation dataset.

The linear trends of precipitation (units: mm (day)-1 (41-year)-1) for the inter-seasonal difference of September-November (SON) minus March-May (MAM) in (a) CMIP5 MME, (b) CMIP6 MME, (c) CESM1 LENS, (d) MPI-GE and (e) CanESM2 LENS during 1979-2019. The black dots indicate the trend is significant at the 90% confidence level.

Extended Data Fig. 5 The observed and simulated phase changes of precipitation annual cycle over the Sahel during 1950-2014.

The time evolution of precipitation annual cycle phase (units: days) over the Sahel during 1950-2014 in (a) five observational datasets (CPC, CRU, GHCN, GPCC and U-Delaware) and (b) five external forcing simulations (CanESM2 LENS, CESM1 LENS, CMIP5, CMIP6, and MPI-GE). The reference period is 1980-1999. The black lines show the ensemble average and the fitting lines during 1950-1982 and 1979-2014 (the trend and confidence level are shown).

Extended Data Fig. 6 The linear trends of precipitation and each energy term for the inter-seasonal difference (SON - MAM) during 1979-2019.

The linear trends of the inter-seasonal difference of September-November (SON) minus March-May (MAM) in (a-b) precipitation (units: mm (day)-1 (171-year)-1), (c-d) atmospheric heat transport divergence (∇·AHT; units: W m-2 (171-year)-1), (e-f) vertically-integrated moist static energy tendency (\(- \frac{{\partial < h > }}{{\partial t}}\); units: W m-2 (171-year)-1), (g-h) net energy input to the atmosphere (Fnet; units: W m-2 (171-year)-1) and (i-j) latent heat flux (units: W m-2 (171-year)-1) during 1850-2020 in the (left panel) GHG and (right panel) AER simulations. The black dots indicate the trend is significant at the 90% confidence level.

Extended Data Fig. 7 The time evolution of the inter-seasonal difference (SON - MAM) of Fnet and its each term over the NTR (0°-25°N) under GHG and AER.

(left panels) GHG and (right panels) AER simulations. Units: W m-2. The red and blue lines show the linear trend during 1850-2020 and 1979-2019, respectively; the numbers in the brackets show the total changes during the corresponding period and the confidence levels. The reference period is 1980-1999.

Extended Data Fig. 8 The time evolution of the inter-seasonal difference (SON - MAM) of Fnet and its each term over the Sahel under GHG and AER.

The same as Extended Data Fig. 7 but over the Sahel.

Extended Data Fig. 9 The future projection of precipitation annual cycle phase evolutions and the energetic constraints in the 21st century in the southern tropical land.

The time evolution of (a) precipitation annual cycle phase (units: days). The overlaid purple line is the inter-seasonal difference (MAM - SON) of precipitation (units: mm day-1). (b) the inter-seasonal difference (MAM - SON) in the atmospheric heat transport divergence (∇·AHT; black line; units: W m-2), net energy input to the atmosphere (Fnet; red line; units: W m-2) and vertically-integrated moist static energy tendency (\(- \frac{{\partial < h > }}{{\partial t}}\); blue line; units: W m-2) over the southern tropical land (0°-25°S) in the CMIP5 MME during 1962-2099. The numbers in the brackets show the total changes during 1962-2099 and the confidence levels; the reference period is 1980-1999.

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Song, F., Leung, L.R., Lu, J. et al. Emergence of seasonal delay of tropical rainfall during 1979–2019. Nat. Clim. Chang. 11, 605–612 (2021). https://doi.org/10.1038/s41558-021-01066-x

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