Strange IndiaStrange India


  • Lawrence, D. & Vandecar, K. Effects of tropical deforestation on climate and agriculture. Nat. Clim. Change 5, 27–36 (2015).

    Article 
    ADS 

    Google Scholar 

  • Spracklen, D. V., Baker, J. C. A., Garcia-Carreras, L. & Marsham, J. H. The effects of tropical vegetation on rainfall. Annu. Rev. Environ. Resour. 43, 193–218 (2018).

    Article 

    Google Scholar 

  • Bonan, G. B. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449 (2008).

    Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 

  • Spracklen, D. V., Arnold, S. R. & Taylor, C. M. Observations of increased tropical rainfall preceded by air passage over forests. Nature 489, 282–285 (2012).

    Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 

  • Staal, A. et al. Forest-rainfall cascades buffer against drought across the Amazon. Nat. Clim. Change 8, 539–543 (2018).

    Article 
    ADS 

    Google Scholar 

  • Baker, J. C. A. & Spracklen, D. V. Divergent representation of precipitation recycling in the Amazon and the Congo in CMIP6 models. Geophys. Res. Lett. 49, e2021GL095136 (2022).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Guan, K. et al. Photosynthetic seasonality of global tropical forests constrained by hydroclimate. Nat. Geosci. 8, 284–289 (2015).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Staal, A. et al. Hysteresis of tropical forests in the 21st century. Nat. Commun. 11, 4978 (2020).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Zemp, D. C. et al. Self-amplified Amazon forest loss due to vegetation-atmosphere feedbacks. Nat. Commun. 8, 14681 (2017).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–854 (2013).

    Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 

  • Chagnon, F. J. F. & Bras, R. L. Contemporary climate change in the Amazon. Geophys. Res. Lett. 32, L13703 (2005).

    Article 
    ADS 

    Google Scholar 

  • Khanna, J., Medvigy, D., Fueglistaler, S. & Walko, R. Regional dry-season climate changes due to three decades of Amazonian deforestation. Nat. Clim. Change 7, 200–204 (2017).

    Article 
    ADS 

    Google Scholar 

  • Garcia-Carreras, L. & Parker, D. J. How does local tropical deforestation affect rainfall? Geophys. Res. Lett. 38, L19802 (2011).

    Article 
    ADS 

    Google Scholar 

  • Leite-Filho, A. T., Soares-Filho, B. S., Davis, J. L., Abrahão, G. M. & Börner, J. Deforestation reduces rainfall and agricultural revenues in the Brazilian Amazon. Nat. Commun. 12, 2591 (2021).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • McAlpine, C. A. et al. Forest loss and Borneo’s climate. Environ. Res. Lett. 13, 044009 (2018).

  • Chapman, S. et al. Compounding impact of deforestation on Borneo’s climate during El Niño events. Environ. Res. Lett. 15, 084006 (2020).

  • Spracklen, D. V. & Garcia-Carreras, L. The impact of Amazonian deforestation on Amazon basin rainfall. Geophys. Res. Lett. 42, 9546–9552 (2015).

    Article 
    ADS 

    Google Scholar 

  • Jiang, Y. et al. Modeled response of South American climate to three decades of deforestation. J. Clim. 34, 2189–2203 (2021).

    Article 
    ADS 

    Google Scholar 

  • Harris, I., Osborn, T. J., Jones, P. & Lister, D. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Sci. Data 7, 109 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Fassoni-Andrade, A. C. et al. Amazon hydrology from space: scientific advances and future challenges. Rev. Geophys. 59, e2020RG000728 (2021).

    Article 
    ADS 

    Google Scholar 

  • Haiden, T., Janousek, M., Vitart, F., Ferranti, L. & Prates, F. Evaluation of ECMWF Forecasts, Including the 2019 Upgrade. ECMWF Technical Memorandum No. 853 (ECMWF, 2019).

  • Esquivel-Muelbert, A. et al. Compositional response of Amazon forests to climate change. Glob. Change Biol. 25, 39–56 (2019).

    Article 
    ADS 

    Google Scholar 

  • Brum, M. et al. ENSO effects on the transpiration of eastern Amazon trees. Philos. Trans. R. Soc. B 373, 20180085 (2018).

    Article 

    Google Scholar 

  • Bagley, J. E., Desai, A. R., Harding, K. J., Snyder, P. K. & Foley, J. A. Drought and deforestation: has land cover change influenced recent precipitation extremes in the Amazon? J. Clim. 27, 345–361 (2014).

    Article 
    ADS 

    Google Scholar 

  • Wunderling, N. et al. Recurrent droughts increase risk of cascading tipping events by outpacing adaptive capacities in the Amazon rainforest. Proc. Natl Acad. Sci. USA 119, e2120777119 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Fu, R. & Li, W. The influence of the land surface on the transition from dry to wet season in Amazonia. Theor. Appl. Climatol. 78, 97–110 (2004).

    Article 
    ADS 

    Google Scholar 

  • Leite-Filho, A. T., de Sousa Pontes, V. Y. & Costa, M. H. Effects of deforestation on the onset of the rainy season and the duration of dry spells in southern Amazonia. J. Geophys. Res. Atmos. 124, 5268–5281 (2019).

    Article 
    ADS 

    Google Scholar 

  • Negri, A. J., Adler, R. F., Xu, L. & Surratt, J. The Impact of Amazonian deforestation on dry season rainfall. J. Clim. 17, 1306–1319 (2004).

    2.0.CO;2″ data-track-action=”article reference” href=”https://doi.org/10.1175%2F1520-0442%282004%29017%3C1306%3ATIOADO%3E2.0.CO%3B2″ aria-label=”Article reference 28″ data-doi=”10.1175/1520-0442(2004)017<1306:TIOADO>2.0.CO;2″>Article 
    ADS 

    Google Scholar 

  • Chagnon, F. J. F., Bras, R. L. & Wang, J. Climatic shift in patterns of shallow clouds over the Amazon. Geophys. Res. Lett. 31, L24212 (2004).

    Article 
    ADS 

    Google Scholar 

  • Chambers, J. Q. & Artaxo, P. Biosphere–atmosphere interactions: deforestation size influences rainfall. Nat. Clim. Change 7, 175–176 (2017).

    Article 
    ADS 

    Google Scholar 

  • Baudena, M., Tuinenburg, O. A., Ferdinand, P. A. & Staal, A. Effects of land-use change in the Amazon on precipitation are likely underestimated. Glob. Change Biol. 27, 5580–5587 (2021).

    Article 
    CAS 

    Google Scholar 

  • Duku, C. & Hein, L. The impact of deforestation on rainfall in Africa: a data-driven assessment. Environ. Res. Lett. 16, 064044 (2021).

  • Akkermans, T., Thiery, W. & Van Lipzig, N. P. M. The regional climate impact of a realistic future deforestation scenario in the Congo basin. J. Clim. 27, 2714–2734 (2014).

    Article 
    ADS 

    Google Scholar 

  • Staal, A. et al. Feedback between drought and deforestation in the Amazon. Environ. Res. Lett. 15, 044024 (2020).

  • Xu, X. et al. Deforestation triggering irreversible transition in Amazon hydrological cycle. Environ. Res. Lett. 17, 034037 (2022).

  • Kooperman, G. J. et al. Forest response to rising CO2 drives zonally asymmetric rainfall change over tropical land. Nat. Clim. Change 8, 434–440 (2018).

    Article 
    ADS 

    Google Scholar 

  • Chen, Z. et al. Global land monsoon precipitation changes in CMIP6 projections. Geophys. Res. Lett. 47, e2019GL086902 (2020).

  • Stickler, C. M. et al. Dependence of hydropower energy generation on forests in the Amazon Basin at local and regional scales. Proc. Natl Acad. Sci. USA 110, 9601–9606 (2013).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Challinor, A. J. et al. A meta-analysis of crop yield under climate change and adaptation. Nat. Clim. Change 4, 287–291 (2014).

    Article 
    ADS 

    Google Scholar 

  • Strand, J. et al. Spatially explicit valuation of the Brazilian Amazon forest’s ecosystem services. Nat. Sustain. 1, 657–664 (2018).

    Article 

    Google Scholar 

  • Potapov, P. et al. Global maps of cropland extent and change show accelerated cropland expansion in the twenty-first century. Nat. Food 3, 19–28 (2022).

    Article 

    Google Scholar 

  • Li, Y. et al. Deforestation-induced climate change reduces carbon storage in remaining tropical forests. Nat. Commun. 13, 1964 (2022).

    Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Aragão, L. E. O. C. et al. Interactions between rainfall, deforestation and fires during recent years in the Brazilian Amazonia. Philos. Trans. R. Soc. B 363, 1779–1785 (2008).

    Article 

    Google Scholar 

  • Marengo, J. A. et al. Changes in climate and land use over the Amazon region: current and future variability and trends. Front. Earth Sci. https://doi.org/10.3389/feart.2018.00228 (2018).

  • Jiang, Y. et al. Widespread increase of boreal summer dry season length over the Congo rainforest. Nat. Clim. Change https://doi.org/10.1038/s41558-019-0512-y (2019).

  • Van Der Ent, R. J. & Savenije, H. H. G. Length and time scales of atmospheric moisture recycling. Atmos. Chem. Phys. 11, 1853–1863 (2011).

    Article 
    ADS 

    Google Scholar 

  • Sorí, R., Nieto, R., Vicente-Serrano, S. M., Drumond, A. & Gimeno, L. A Lagrangian perspective of the hydrological cycle in the Congo River basin. Earth Syst. Dyn. 8, 653–675 (2017).

    Article 
    ADS 

    Google Scholar 

  • van der Ent, R. J., Savenije, H. H. G., Schaefli, B. & Steele-Dunne, S. C. Origin and fate of atmospheric moisture over continents. Water Resour. Res. 46, W09525 (2010).

    ADS 

    Google Scholar 

  • Feng, Y. et al. Doubling of annual forest carbon loss over the tropics during the early twenty-first century. Nat. Sustain. 4, 441–451 (2022).

    Google Scholar 

  • Tuinenburg, O. A., Bosmans, J. H. C. & Staal, A. The global potential of forest restoration for drought mitigation. Environ. Res. Lett. 17, 034045 (2022).

  • Met Office. Cartopy: a cartographic python library with a Matplotlib interface 2010–2015. Met Office https://scitools.org.uk/cartopy (2022).

  • Hoyer, S. & Hamman, J. xarray: N-D labeled arrays and datasets in Python. J. Open Res. Softw. https://doi.org/10.5334/jors.148 (2017).

  • Zhuang, J. xESMF. Zenodo https://doi.org/10.5281/zenodo.1134365 (2022).

  • Baker, J. C. A. & Spracklen, D. V. Climate benefits of intact Amazon forests and the biophysical consequences of disturbance. Front. For. Glob. Change https://doi.org/10.3389/ffgc.2019.00047 (2019).

  • Schaaf, C. & Wang, Z. MCD43A3 MODIS/Terra+Aqua BRDF/Albedo Daily L3 Global – 500m V006. NASA EOSDIS Land Processes DAAC https://doi.org/10.5067/modis/mcd43a3.006 (2015).

  • Waskom, M. Seaborn: statistical data visualization. J. Open Source Softw. 6, 3021 (2021).

    Article 
    ADS 

    Google Scholar 

  • Chen, M. et al. Global land use for 2015–2100 at 0.05° resolution under diverse socioeconomic and climate scenarios. Sci. Data 7, 320 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Funk, C. et al. The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Sci. Data 2, 150066 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Xie, P. et al. NOAA Climate Data Record (CDR) of CPC Morphing technique (CMORPH) high resolution global precipitation estimates, version 1. NOAA National Centers for Environmental Information https://doi.org/10.25921/w9va-q159 (2019).

  • Xie, P. et al. A gauge-based analysis of daily precipitation over East Asia. J. Hydrometeorol. 8, 607–626 (2007).

    Article 
    ADS 

    Google Scholar 

  • Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).

    Article 
    ADS 

    Google Scholar 

  • Elke, R., Hänsel, S., Finger, P., Schneider, U. & Ziese, M. GPCC Climatology Version 2022 at 0.25°: monthly land-surface precipitation climatology for every month and the total year from rain-gauges built on GTS-based and historical data. GPCC https://doi.org/10.5676/DWD_GPCC/CLIM_M_V2022_025 (2022).

  • Huffman, G. J. A., Behrangi, R. F., Adler, D. T., Bolvin, E. J. & Nelkin, G. G. Introduction to the new version 3 GPCP monthly global precipitation analysis. GPCP https://docserver.gesdisc.eosdis.nasa.gov/public/project/MEaSUREs/GPCP/Release_Notes.GPCPV3.2.pdf (2022).

  • Hou, A. Y. et al. The global precipitation measurement mission. Bull. Am. Meteorol. Soc. 95, 701–722 (2014).

    Article 
    ADS 

    Google Scholar 

  • Kobayashi, S. et al. The JRA-55 reanalysis: general specifications and basic characteristics. J. Meteorol. Soc. Japan 93, 5–48 (2015).

    Article 
    ADS 

    Google Scholar 

  • Gelaro, R. et al. The modern-era retrospective analysis for research and applications, version 2 (MERRA-2). J. Clim. 30, 5419–5454 (2017).

    Article 
    ADS 

    Google Scholar 

  • Chen, M., Xie, P. & Janowiak, J. E. Global land precipitation: a 50-yr monthly analysis based on gauge observations. J. Hydrometeorol. 3, 249–266 (2002).

    2.0.CO;2″ data-track-action=”article reference” href=”https://doi.org/10.1175%2F1525-7541%282002%29003%3C0249%3AGLPAYM%3E2.0.CO%3B2″ aria-label=”Article reference 67″ data-doi=”10.1175/1525-7541(2002)003<0249:GLPAYM>2.0.CO;2″>Article 
    ADS 

    Google Scholar 

  • Nguyen, P. et al. The CHRS data portal, an easily accessible public repository for PERSIANN global satellite precipitation data. Sci. Data 6, 1180296 (2019).

    Article 

    Google Scholar 

  • Ashouri, H. et al. PERSIANN-CDR: daily precipitation climate data record from multisatellite observations for hydrological and climate studies. Bull. Am. Meteorol. Soc. 96, 69–83 (2015).

    Article 
    ADS 

    Google Scholar 

  • Nguyen, P. et al. Persiann dynamic infrared–rain rate (PDIR-now): a near-real-time, quasi-global satellite precipitation dataset. J. Hydrometeorol. 21, 2893–2906 (2020).

    Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Sadeghi, M. et al. PERSIANN-CCS-CDR, a 3-hourly 0.04° global precipitation climate data record for heavy precipitation studies. Sci. Data 8, 157 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Huffman, G. J. et al. The TRMM Multisatellite Precipitation Analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J. Hydrometeorol. 8, 38–55 (2007).

    Article 
    ADS 

    Google Scholar 

  • Matsuura, K. & Willmott, C. J. Terrestrial precipitation: 1900-2017 gridded monthly time series. Global Precipitation Archive http://climate.geog.udel.edu/~climate/html_pages/Global2017/README.GlobalTsP2017.html (2018).



  • Source link

    By AUTHOR

    Leave a Reply

    Your email address will not be published. Required fields are marked *