Exploring the Factors Controlling the Annual Range of Amazon Precipitation

Pei-Syuan Liao aDepartment of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan

Search for other papers by Pei-Syuan Liao in
Current site
Google Scholar
PubMed
Close
,
Chia-Wei Lan aDepartment of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan

Search for other papers by Chia-Wei Lan in
Current site
Google Scholar
PubMed
Close
,
Yu-Chiao Liang aDepartment of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan

Search for other papers by Yu-Chiao Liang in
Current site
Google Scholar
PubMed
Close
, and
Min-Hui Lo aDepartment of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan

Search for other papers by Min-Hui Lo in
Current site
Google Scholar
PubMed
Close
https://orcid.org/0000-0002-8653-143X
Restricted access

Abstract

The annual range (AR) of precipitation in the Amazon River basin has increased steadily since 1979. This increase may have resulted from natural variability and/or anthropogenic forcing, such as local land-use changes and global warming, which has yet to be explored. In this study, climate model experiments using the Community Earth System Model, version 2 (CESM2), were conducted to examine the relative contributions of sea surface temperatures (SSTs) variability and anthropogenic forcings to the AR changes in the Amazon rainfall. With CESM2, we design several factorial simulations, instead of actual model projection. We found that the North Atlantic SSTs fluctuation dominantly decreases the precipitation AR trend over the Amazon by −85%. In contrast, other factors, including deforestation and carbon dioxide, contributed to the trend changes, ranging from 25% to 35%. The dynamic component, specifically the tendency of vertical motion, made negative contributions, along with the vertical profiles of moist static energy (MSE) tendency. Seasonal-dependent changes in atmospheric stability could be associated with variations in precipitation. It is concluded that surface ocean warming associated with the North Atlantic natural variability and global warming is the key factor in the increased precipitation AR over the Amazon from 1979 to 2014. The continuous local land-use changes may potentially influence the precipitation AR in the future.

Significance Statement

The annual range (AR) in precipitation, the difference between wet- and dry-season precipitation, has increased from 1979 to 2014 in the Amazon. This increase may have resulted from global warming, deforestation, and sea surface temperature variability in North Atlantic and Pacific. To explore the role of each of these factors in altering the Amazon precipitation AR, five experiments were designed in the climate model (CESM). Among these experiment results, the effect of North Atlantic SSTs was the strongest. In the future, deforestation, global warming, and different ocean temperature states in the North Atlantic and Pacific may become increasingly influential on the changes in precipitation. Further investigation is needed to ascertain how the AR of precipitation in the Amazon will change.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Min-Hui Lo, minhuilo@ntu.edu.tw

Abstract

The annual range (AR) of precipitation in the Amazon River basin has increased steadily since 1979. This increase may have resulted from natural variability and/or anthropogenic forcing, such as local land-use changes and global warming, which has yet to be explored. In this study, climate model experiments using the Community Earth System Model, version 2 (CESM2), were conducted to examine the relative contributions of sea surface temperatures (SSTs) variability and anthropogenic forcings to the AR changes in the Amazon rainfall. With CESM2, we design several factorial simulations, instead of actual model projection. We found that the North Atlantic SSTs fluctuation dominantly decreases the precipitation AR trend over the Amazon by −85%. In contrast, other factors, including deforestation and carbon dioxide, contributed to the trend changes, ranging from 25% to 35%. The dynamic component, specifically the tendency of vertical motion, made negative contributions, along with the vertical profiles of moist static energy (MSE) tendency. Seasonal-dependent changes in atmospheric stability could be associated with variations in precipitation. It is concluded that surface ocean warming associated with the North Atlantic natural variability and global warming is the key factor in the increased precipitation AR over the Amazon from 1979 to 2014. The continuous local land-use changes may potentially influence the precipitation AR in the future.

Significance Statement

The annual range (AR) in precipitation, the difference between wet- and dry-season precipitation, has increased from 1979 to 2014 in the Amazon. This increase may have resulted from global warming, deforestation, and sea surface temperature variability in North Atlantic and Pacific. To explore the role of each of these factors in altering the Amazon precipitation AR, five experiments were designed in the climate model (CESM). Among these experiment results, the effect of North Atlantic SSTs was the strongest. In the future, deforestation, global warming, and different ocean temperature states in the North Atlantic and Pacific may become increasingly influential on the changes in precipitation. Further investigation is needed to ascertain how the AR of precipitation in the Amazon will change.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Min-Hui Lo, minhuilo@ntu.edu.tw

Supplementary Materials

    • Supplemental Materials (PDF 0.1575 MB)
Save
  • Adler, R. F., and Coauthors, 2003: The Version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). J. Hydrometeor., 4, 11471167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Agarwal, N., R. J. Small, F. O. Bryan, I. Grooms, and P. J. Pegion, 2023: Impact of stochastic ocean density corrections on air-sea flux variability. Geophys. Res. Lett., 50, e2023GL104248, https://doi.org/10.1029/2023GL104248.

    • Search Google Scholar
    • Export Citation
  • Almeida, C. T., J. F. Oliveira-Júnior, R. C. Delgado, P. Cubo, and M. C. Ramos, 2017: Spatiotemporal rainfall and temperature trends throughout the Brazilian Legal Amazon, 1973–2013. Int. J. Climatol., 37, 20132026, https://doi.org/10.1002/joc.4831.

    • Search Google Scholar
    • Export Citation
  • Bagley, J. E., A. R. Desai, K. J. Harding, P. K. Snyder, and J. A. Foley, 2014: Drought and deforestation: Has land cover change influenced recent precipitation extremes in the Amazon? J. Climate, 27, 345361, https://doi.org/10.1175/JCLI-D-12-00369.1.

    • Search Google Scholar
    • Export Citation
  • Boisier, J. P., P. Ciais, A. Ducharne, and M. Guimberteau, 2015: Projected strengthening of Amazonian dry season by constrained climate model simulations. Nat. Climate Change, 5, 656660, https://doi.org/10.1038/nclimate2658.

    • Search Google Scholar
    • Export Citation
  • Brando, P. M., and Coauthors, 2014: Abrupt increases in Amazonian tree mortality due to drought–fire interactions. Proc. Natl. Acad. Sci. USA, 111, 63476352, https://doi.org/10.1073/pnas.1305499111.

    • Search Google Scholar
    • Export Citation
  • Chen, C.-C., and Coauthors, 2019: Thermodynamic and dynamic responses to deforestation in the Maritime Continent: A modeling study. J. Climate, 32, 35053527, https://doi.org/10.1175/JCLI-D-18-0310.1.

    • Search Google Scholar
    • Export Citation
  • Chen, H.-C., and M.-H. Lo, 2023: Contrasting responses of surface heat fluxes to tropical deforestation. J. Geophys. Res. Atmos., 128, e2022JD038118, https://doi.org/10.1029/2022JD038118.

    • Search Google Scholar
    • Export Citation
  • Choat, B., T. J. Brodribb, C. R. Brodersen, R. A. Duursma, R. López, and B. E. Medlyn, 2018: Triggers of tree mortality under drought. Nature, 558, 531539, https://doi.org/10.1038/s41586-018-0240-x.

    • Search Google Scholar
    • Export Citation
  • Chou, C., and C.-W. Lan, 2012: Changes in the annual range of precipitation under global warming. J. Climate, 25, 222235, https://doi.org/10.1175/JCLI-D-11-00097.1.

    • Search Google Scholar
    • Export Citation
  • Chou, C., J. C. H. Chiang, C.-W. Lan, C.-H. Chung, Y.-C. Liao, and C.-J. Lee, 2013: Increase in the range between wet and dry season precipitation. Nat. Geosci., 6, 263267, https://doi.org/10.1038/ngeo1744.

    • Search Google Scholar
    • Export Citation
  • Correia, F. W. S., R. C. S. Alvalá, and A. O. Manzi, 2008: Modeling the impacts of land cover change in Amazonia: A Regional Climate Model (RCM) simulation study. Theor. Appl. Climatol., 93, 225244, https://doi.org/10.1007/s00704-007-0335-z.

    • Search Google Scholar
    • Export Citation
  • Cox, P. M., and Coauthors, 2008: Increasing risk of Amazonian drought due to decreasing aerosol pollution. Nature, 453, 212215, https://doi.org/10.1038/nature06960.

    • Search Google Scholar
    • Export Citation
  • Cui, J., S. Piao, C. Huntingford, X. Wang, X. Lian, A. Chevuturi, A. G. Turner, and G. J. Kooperman, 2020: Vegetation forcing modulates global land monsoon and water resources in a CO2-enriched climate. Nat. Commun., 11, 5184, https://doi.org/10.1038/s41467-020-18992-7.

    • Search Google Scholar
    • Export Citation
  • Danabasoglu, G., and Coauthors, 2020: The Community Earth System Model version 2 (CESM2). J. Adv. Model. Earth Syst., 12, e2019MS001916, https://doi.org/10.1029/2019MS001916.

    • Search Google Scholar
    • Export Citation
  • Devaraju, N., G. Bala, and A. Modak, 2015: Effects of large-scale deforestation on precipitation in the monsoon regions: Remote versus local effects. Proc. Natl. Acad. Sci. USA, 112, 32573262, https://doi.org/10.1073/pnas.1423439112.

    • Search Google Scholar
    • Export Citation
  • Duffy, P. B., P. Brando, G. P. Asner, and C. B. Field, 2015: Projections of future meteorological drought and wet periods in the Amazon. Proc. Natl. Acad. Sci. USA, 112, 13 17213 177, https://doi.org/10.1073/pnas.1421010112.

    • Search Google Scholar
    • Export Citation
  • Eyring, V., S. Bony, G. A. Meehl, C. A. Senior, B. Stevens, R. J. Stouffer, and K. E. Taylor, 2016: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev., 9, 19371958, https://doi.org/10.5194/gmd-9-1937-2016.

    • Search Google Scholar
    • Export Citation
  • Ffield, A., 2007: Amazon and Orinoco River plumes and NBC rings: Bystanders or participants in hurricane events? J. Climate, 20, 316333, https://doi.org/10.1175/JCLI3985.1.

    • Search Google Scholar
    • Export Citation
  • Friedman, A. R., M. A. Bollasina, G. Gastineau, and M. Khodri, 2021: Increased Amazon Basin wet-season precipitation and river discharge since the early 1990s driven by tropical Pacific variability. Environ. Res. Lett., 16, 034033, https://doi.org/10.1088/1748-9326/abd587.

    • Search Google Scholar
    • Export Citation
  • Fu, R., R. E. Dickinson, M. Chen, and H. Wang, 2001: How do tropical sea surface temperatures influence the seasonal distribution of precipitation in the equatorial Amazon? J. Climate, 14, 40034026, https://doi.org/10.1175/1520-0442(2001)014<4003:HDTSST>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Fu, R., and Coauthors, 2013: Increased dry-season length over southern Amazonia in recent decades and its implication for future climate projection. Proc. Natl. Acad. Sci. USA, 110, 18 11018 115, https://doi.org/10.1073/pnas.1302584110.

    • Search Google Scholar
    • Export Citation
  • García-García, D., and C. C. Ummenhofer, 2015: Multidecadal variability of the continental precipitation annual amplitude driven by AMO and ENSO. Geophys. Res. Lett., 42, 526535, https://doi.org/10.1002/2014GL062451.

    • Search Google Scholar
    • Export Citation
  • Gatti, L. V., and Coauthors, 2021: Amazonia as a carbon source linked to deforestation and climate change. Nature, 595, 388393, https://doi.org/10.1038/s41586-021-03629-6.

    • Search Google Scholar
    • Export Citation
  • Gouveia, N. A., D. F. M. Gherardi, and L. E. O. C. Aragão, 2019: The role of the Amazon River plume on the intensification of the hydrological cycle. Geophys. Res. Lett., 46, 12 22112 229, https://doi.org/10.1029/2019GL084302.

    • Search Google Scholar
    • Export Citation
  • Grodsky, S. A., and Coauthors, 2012: Haline hurricane wake in the Amazon/Orinoco plume: AQUARIUS/SACD and SMOS observations. Geophys. Res. Lett., 39, L20603, https://doi.org/10.1029/2012GL053335.

    • Search Google Scholar
    • Export Citation
  • Hurrell, J. W., J. J. Hack, D. Shea, J. M. Caron, and J. Rosinski, 2008: A new sea surface temperature and sea ice boundary dataset for the Community Atmosphere Model. J. Climate, 21, 51455153, https://doi.org/10.1175/2008JCLI2292.1.

    • Search Google Scholar
    • Export Citation
  • Joetzjer, E., and Coauthors, 2014: Predicting the response of the Amazon rainforest to persistent drought conditions under current and future climates: A major challenge for global land surface models. Geosci. Model Dev., 7, 29332950, https://doi.org/10.5194/gmd-7-2933-2014.

    • Search Google Scholar
    • Export Citation
  • Kayano, M. T., R. V. Andreoli, and R. A. F. de Souza, 2020: Pacific and Atlantic multidecadal variability relations to the El Niño events and their effects on the South American rainfall. Int. J. Climatol., 40, 21832200, https://doi.org/10.1002/joc.6326.

    • Search Google Scholar
    • Export Citation
  • Kirschbaum, M. U. F., and A. M. S. McMillan, 2018: Warming and elevated CO2 have opposing influences on transpiration. Which is more important? Curr. For. Rep., 4, 5171, https://doi.org/10.1007/s40725-018-0073-8.

    • Search Google Scholar
    • Export Citation
  • Kleidon, A., and M. Heimann, 2000: Assessing the role of deep rooted vegetation in the climate system with model simulations: Mechanism, comparison to observations and implications for Amazonian deforestation. Climate Dyn., 16, 183199, https://doi.org/10.1007/s003820050012.

    • Search Google Scholar
    • Export Citation
  • Kosaka, Y., and S.-P. Xie, 2013: Recent global-warming hiatus tied to equatorial Pacific surface cooling. Nature, 501, 403407, https://doi.org/10.1038/nature12534.

    • Search Google Scholar
    • Export Citation
  • Kosaka, Y., and S.-P. Xie, 2016: The tropical Pacific as a key pacemaker of the variable rates of global warming. Nat. Geosci., 9, 669673, https://doi.org/10.1038/ngeo2770.

    • Search Google Scholar
    • Export Citation
  • Lan, C.-W., M.-H. Lo, C.-A. Chen, and J.-Y. Yu, 2019: The mechanisms behind changes in the seasonality of global precipitation found in reanalysis products and CMIP5 simulations. Climate Dyn., 53, 41734187, https://doi.org/10.1007/s00382-019-04781-6.

    • Search Google Scholar
    • Export Citation
  • Liang, Y.-C., M.-H. Lo, C.-W. Lan, H. Seo, C. C. Ummenhofer, S. Yeager, R.-J. Wu, and J. D. Steffen, 2020: Amplified seasonal cycle in hydroclimate over the Amazon River basin and its plume region. Nat. Commun., 11, 4390, https://doi.org/10.1038/s41467-020-18187-0.

    • Search Google Scholar
    • Export Citation
  • Marengo, J. A., and Coauthors, 2012: Recent developments on the South American monsoon system. Int. J. Climatol., 32 (1), 121, https://doi.org/10.1002/joc.2254.

    • Search Google Scholar
    • Export Citation
  • Olivares, I., J.-C. Svenning, P. M. van Bodegom, and H. Balslev, 2015: Effects of warming and drought on the vegetation and plant diversity in the Amazon basin. Bot. Rev., 81, 4269, https://doi.org/10.1007/s12229-014-9149-8.

    • Search Google Scholar
    • Export Citation
  • O’Neill, B. C., and Coauthors, 2016: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci. Model Dev., 9, 34613482, https://doi.org/10.5194/gmd-9-3461-2016.

    • Search Google Scholar
    • Export Citation
  • Parsons, L. A., 2020: Implications of CMIP6 projected drying trends for 21st century Amazonian drought risk. Earth’s Future, 8, e2020EF001608, https://doi.org/10.1029/2020EF001608.

    • Search Google Scholar
    • Export Citation
  • Rezende, L. F. C., and Coauthors, 2022: Impacts of land use change and atmospheric CO2 on Gross Primary Productivity (GPP), evaporation, and climate in Southern Amazon. J. Geophys. Res. Atmos., 127, e2021JD034608, https://doi.org/10.1029/2021JD034608.

    • Search Google Scholar
    • Export Citation
  • Ritchie, P. D. L., I. Parry, J. J. Clarke, C. Huntingford, and P. M. Cox, 2022: Increases in the temperature seasonal cycle indicate long-term drying trends in Amazonia. Commun. Earth Environ., 3, 199, https://doi.org/10.1038/s43247-022-00528-0.

    • Search Google Scholar
    • Export Citation
  • Ritter, F., M. Berkelhammer, and C. Garcia-Eidell, 2020: Distinct response of gross primary productivity in five terrestrial biomes to precipitation variability. Commun. Earth Environ., 1, 34, https://doi.org/10.1038/s43247-020-00034-1.

    • Search Google Scholar
    • Export Citation
  • Ruiz-Vásquez, M., P. A. Arias, J. A. Martínez, and J. C. Espinoza, 2020: Effects of Amazon basin deforestation on regional atmospheric circulation and water vapor transport towards tropical South America. Climate Dyn., 54, 41694189, https://doi.org/10.1007/S00382-020-05223-4.

    • Search Google Scholar
    • Export Citation
  • Sampaio, G., and Coauthors, 2021: CO2 physiological effect can cause rainfall decrease as strong as large-scale deforestation in the Amazon. Biogeosciences, 18, 25112525, https://doi.org/10.5194/bg-18-2511-2021.

    • Search Google Scholar
    • Export Citation
  • Schneider, U., A. Becker, P. Finger, A. Meyer-Christoffer, B. Rudolf, and M. Ziese, 2011: GPCC full data reanalysis version 6.0 at 1.0°: Monthly land-surface precipitation from rain-gauges built on GTS-based and historic data. Accessed 1 September 2020, https://doi.org/10.5676/DWD_GPCC/FD_M_V7_100.

  • Shimizu, M. H., J. A. Anochi, and M. T. Kayano, 2022: Precipitation patterns over northern Brazil basins: Climatology, trends, and associated mechanisms. Theor. Appl. Climatol., 147, 767783, https://doi.org/10.1007/s00704-021-03841-4.

    • Search Google Scholar
    • Export Citation
  • Silva Junior, C. H. L., A. C. M. Pessôa, N. S. Carvalho, J. B. C. Reis, L. O. Anderson, and L. E. O. C. Aragão, 2021: The Brazilian Amazon deforestation rate in 2020 is the greatest of the decade. Nat. Ecol. Evol., 5, 144145, https://doi.org/10.1038/s41559-020-01368-x.

    • Search Google Scholar
    • Export Citation
  • Spracklen, D. V., and L. Garcia-Carreras, 2015: The impact of Amazonian deforestation on Amazon basin rainfall. Geophys. Res. Lett., 42, 95469552, https://doi.org/10.1002/2015GL066063.

    • Search Google Scholar
    • Export Citation
  • Wang, C., and S. Dong, 2010: Is the basin-wide warming in the North Atlantic Ocean related to atmospheric carbon dioxide and global warming? Geophys. Res. Lett., 37, L08707, https://doi.org/10.1029/2010GL042743.

    • Search Google Scholar
    • Export Citation
  • Wang, X.-Y., X. Li, J. Zhu, and C. A. S. Tanajura, 2018: The strengthening of Amazonian precipitation during the wet season driven by tropical sea surface temperature forcing. Environ. Res. Lett., 13, 094015, https://doi.org/10.1088/1748-9326/aadbb9.

    • Search Google Scholar
    • Export Citation
  • Wang, Y., J. Xiao, X. Li, and S. Niu, 2022: Global evidence on the asymmetric response of gross primary productivity to interannual precipitation changes. Sci. Total Environ., 814, 152786, https://doi.org/10.1016/j.scitotenv.2021.152786.

    • Search Google Scholar
    • Export Citation
  • Yoon, J.-H., and N. Zeng, 2010: An Atlantic influence on Amazon rainfall. Climate Dyn., 34, 249264, https://doi.org/10.1007/s00382-009-0551-6.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 494 494 219
Full Text Views 141 141 57
PDF Downloads 151 151 65