Literature DB >> 26324902

Fog and rain in the Amazon.

Usama Anber1, Pierre Gentine2, Shuguang Wang3, Adam H Sobel4.   

Abstract

The diurnal and seasonal water cycles in the Amazon remain poorly simulated in general circulation models, exhibiting peak evapotranspiration in the wrong season and rain too early in the day. We show that those biases are not present in cloud-resolving simulations with parameterized large-scale circulation. The difference is attributed to the representation of the morning fog layer, and to more accurate characterization of convection and its coupling with large-scale circulation. The morning fog layer, present in the wet season but absent in the dry season, dramatically increases cloud albedo, which reduces evapotranspiration through its modulation of the surface energy budget. These results highlight the importance of the coupling between the energy and hydrological cycles and the key role of cloud albedo feedback for climates over tropical continents.

Entities:  

Keywords:  Amazon; cloud-resolving models; fog; hydrologic cycle; land−atmosphere interactions

Year:  2015        PMID: 26324902      PMCID: PMC4577161          DOI: 10.1073/pnas.1505077112

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  5 in total

1.  Forest productivity and water stress in Amazonia: observations from GOSAT chlorophyll fluorescence.

Authors:  Jung-Eun Lee; Christian Frankenberg; Christiaan van der Tol; Joseph A Berry; Luis Guanter; C Kevin Boyce; Joshua B Fisher; Eric Morrow; John R Worden; Salvi Asefi; Grayson Badgley; Sassan Saatchi
Journal:  Proc Biol Sci       Date:  2013-05-01       Impact factor: 5.349

2.  Drought sensitivity of Amazonian carbon balance revealed by atmospheric measurements.

Authors:  L V Gatti; M Gloor; J B Miller; C E Doughty; Y Malhi; L G Domingues; L S Basso; A Martinewski; C S C Correia; V F Borges; S Freitas; R Braz; L O Anderson; H Rocha; J Grace; O L Phillips; J Lloyd
Journal:  Nature       Date:  2014-02-06       Impact factor: 49.962

3.  Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability.

Authors:  Peter M Cox; David Pearson; Ben B Booth; Pierre Friedlingstein; Chris Huntingford; Chris D Jones; Catherine M Luke
Journal:  Nature       Date:  2013-02-06       Impact factor: 49.962

4.  Climate extremes and the carbon cycle.

Authors:  Markus Reichstein; Michael Bahn; Philippe Ciais; Dorothea Frank; Miguel D Mahecha; Sonia I Seneviratne; Jakob Zscheischler; Christian Beer; Nina Buchmann; David C Frank; Dario Papale; Anja Rammig; Pete Smith; Kirsten Thonicke; Marijn van der Velde; Sara Vicca; Ariane Walz; Martin Wattenbach
Journal:  Nature       Date:  2013-08-15       Impact factor: 49.962

5.  Reconciling spatial and temporal soil moisture effects on afternoon rainfall.

Authors:  Benoit P Guillod; Boris Orlowsky; Diego G Miralles; Adriaan J Teuling; Sonia I Seneviratne
Journal:  Nat Commun       Date:  2015-03-05       Impact factor: 14.919

  5 in total
  5 in total

1.  Water, Energy, and Carbon with Artificial Neural Networks (WECANN): A statistically-based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence.

Authors:  Seyed Hamed Alemohammad; Bin Fang; Alexandra G Konings; Filipe Aires; Julia K Green; Jana Kolassa; Diego Miralles; Catherine Prigent; Pierre Gentine
Journal:  Biogeosciences       Date:  2017-09-20       Impact factor: 4.295

2.  Regionally strong feedbacks between the atmosphere and terrestrial biosphere.

Authors:  Julia K Green; Alexandra G Konings; Seyed Hamed Alemohammad; Joseph Berry; Dara Entekhabi; Jana Kolassa; Jung-Eun Lee; Pierre Gentine
Journal:  Nat Geosci       Date:  2017-05-29       Impact factor: 16.908

3.  Land-atmospheric feedbacks during droughts and heatwaves: state of the science and current challenges.

Authors:  Diego G Miralles; Pierre Gentine; Sonia I Seneviratne; Adriaan J Teuling
Journal:  Ann N Y Acad Sci       Date:  2018-06-25       Impact factor: 5.691

4.  Hydrologic resilience and Amazon productivity.

Authors:  Anders Ahlström; Josep G Canadell; Guy Schurgers; Minchao Wu; Joseph A Berry; Kaiyu Guan; Robert B Jackson
Journal:  Nat Commun       Date:  2017-08-30       Impact factor: 14.919

5.  Reconstructed Solar-Induced Fluorescence: A Machine Learning Vegetation Product Based on MODIS Surface Reflectance to Reproduce GOME-2 Solar-Induced Fluorescence.

Authors:  P Gentine; S H Alemohammad
Journal:  Geophys Res Lett       Date:  2018-04-13       Impact factor: 4.720

  5 in total

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