Collaborative Research: Quantifying the impacts of atmospheric and land surface heterogeneity and scale on soil moisture-precipitation feedbacks

合作研究:量化大气和地表异质性和规模对土壤湿度-降水反馈的影响

基本信息

  • 批准号:
    1035843
  • 负责人:
  • 金额:
    $ 22.93万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-01-01 至 2013-12-31
  • 项目状态:
    已结题

项目摘要

This project studies the potential feedback between soil moisture and precipitation. A positive feedback would mean that enhanced soil moisture leads to enhanced precipitation, as a wetter surface provides a source of evaporation for subsequent rainfall. In that case, precipitation would lead to wetter soil, which would in turn lead to further precipitation, while a lack of precipitation could lead to a lack of soil moisture and hence further reductions in precipitation leading to prolonged drought. This study assesses the influence of atmospheric and land surface heterogeneity and spatial scale on soil moisture-precipitation coupling, principally at daily timescales, through two interconnected approaches: 1) diagnostic analysis of available observations, reanalysis products, and global climate model (GCM) output; and 2) conceptual modeling of land-atmosphere interactions using process-based idealized models expresed as analytic equations as well as atmospheric column models coupled to simple soil models (eg "bucket" models). A primary objective of this activity is the development of robust, physically-based metrics for quantifying and comparing intraday soil moisture/precipitation coupling in models and observations.The issues addressed in this project have relevance to society as well as science, as drought duration and intensity have substantial consequences for agriculture. In addition, the project will support and train a postdoctoral researcher, thereby helping to support and train the next generation of scientists.
该项目研究土壤水分和降水之间的潜在反馈。 正反馈意味着土壤湿度的增加导致降水量的增加,因为更潮湿的表面为随后的降雨提供了蒸发源。 在这种情况下,降水将导致土壤更加湿润,这反过来又会导致进一步的降水,而降水不足可能导致土壤水分不足,从而导致降水进一步减少,导致长期干旱。本研究通过两种相互关联的方法评估了大气和陆面异质性和空间尺度对土壤水分-降水耦合的影响,主要是在日时间尺度上:1)对现有观测、再分析产品和全球气候模式(GCM)输出进行诊断分析;(2)陆-气相互作用的概念模型,基于理想化的模型表示为解析方程以及大气柱模型耦合到简单的土壤模型(如“桶”模型)。这项活动的主要目标是发展强大的,物理为基础的量化和比较模型和observations.The在这个项目中所解决的问题有相关的社会以及科学,干旱的持续时间和强度对农业的影响重大的一天土壤水分/降水耦合的指标。 此外,该项目将支持和培训一名博士后研究人员,从而帮助支持和培训下一代科学家。

项目成果

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Pierre Gentine其他文献

Two for one: Partitioning COsub2/sub fluxes and understanding the relationship between solar-induced chlorophyll fluorescence and gross primary productivity using machine learning
二合一:利用机器学习划分二氧化碳通量并理解太阳诱导叶绿素荧光与总初级生产力之间的关系
  • DOI:
    10.1016/j.agrformet.2022.108980
  • 发表时间:
    2022-06-15
  • 期刊:
  • 影响因子:
    5.700
  • 作者:
    Weiwei Zhan;Xi Yang;Youngryel Ryu;Benjamin Dechant;Yu Huang;Yves Goulas;Minseok Kang;Pierre Gentine
  • 通讯作者:
    Pierre Gentine
Estimating evapotranspiration using remotely sensed solar-induced fluorescence measurements
  • DOI:
    10.1016/j.agrformet.2021.108800
  • 发表时间:
    2022-03-01
  • 期刊:
  • 影响因子:
    5.700
  • 作者:
    Kai Zhou;Quan Zhang;Lihua Xiong;Pierre Gentine
  • 通讯作者:
    Pierre Gentine
Emissions rebound from the COVID-19 pandemic
  • DOI:
    10.1038/s41558-022-01332-6
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    30.7
  • 作者:
    Steven J. Davis;Zhu Liu;Zhu Deng;Biqing Zhu;Piyu Ke;Taochun Sun;Rui Guo;Chaopeng Hong;Bo Zheng;Yilong Wang;Olivier Boucher;Pierre Gentine;Philippe Ciais
  • 通讯作者:
    Philippe Ciais
GEOSIF: A continental-scale sub-daily reconstructed solar-induced fluorescence derived from OCO-3 and GK-2A over Eastern Asia and Oceania
GEOSIF:源自东亚和大洋洲 OCO-3 和 GK-2A 的大陆尺度次日重建太阳诱导荧光
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    13.5
  • 作者:
    Sungchan Jeong;Youngryel Ryu;Xing Li;Benjamin Dechant;Jiangong Liu;Juwon Kong;Wonseok Choi;Jianing Fang;Xu Lian;Pierre Gentine
  • 通讯作者:
    Pierre Gentine
The k−1 scaling of air temperature spectra in atmospheric surface layer flows
大气表层流中空气温度谱的 k−1 标度

Pierre Gentine的其他文献

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{{ truncateString('Pierre Gentine', 18)}}的其他基金

STC: Center for Learning the Earth with Artificial Intelligence and Physics (LEAP)
STC:利用人工智能和物理学习地球中心 (LEAP)
  • 批准号:
    2019625
  • 财政年份:
    2021
  • 资助金额:
    $ 22.93万
  • 项目类别:
    Cooperative Agreement
Collaborative Research: HDR Elements: Software for a new machine learning based parameterization of moist convection for improved climate and weather prediction using deep learning
合作研究:HDR Elements:基于新机器学习的湿对流参数化软件,利用深度学习改进气候和天气预报
  • 批准号:
    1835769
  • 财政年份:
    2018
  • 资助金额:
    $ 22.93万
  • 项目类别:
    Standard Grant
Collaborative Research: Role of Cloud Albedo and Land-Atmosphere Interactions on Continental Tropical Climates
合作研究:云反照率和陆地-大气相互作用对大陆热带气候的作用
  • 批准号:
    1734156
  • 财政年份:
    2017
  • 资助金额:
    $ 22.93万
  • 项目类别:
    Standard Grant
Collaborative Research: Dynamics of Unsaturated Downdrafts, Cold Pools, and Their Roles in Convective Initiation and Organization
合作研究:不饱和下降气流、冷池的动力学及其在对流引发和组织中的作用
  • 批准号:
    1649770
  • 财政年份:
    2017
  • 资助金额:
    $ 22.93万
  • 项目类别:
    Continuing Grant
CAREER: Departure from Monin-Obukhov Similarity Theory (MOST) using high-resolution turbulence models
职业生涯:使用高分辨率湍流模型偏离 Monin-Obukhov 相似理论 (MOST)
  • 批准号:
    1552304
  • 财政年份:
    2016
  • 资助金额:
    $ 22.93万
  • 项目类别:
    Continuing Grant
Summer School in Land-atmosphere Interactions
陆地-大气相互作用暑期学校
  • 批准号:
    1522174
  • 财政年份:
    2015
  • 资助金额:
    $ 22.93万
  • 项目类别:
    Standard Grant

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