Observational Evidence of State‐Dependent Positive and Negative Land Surface Feedback on Afternoon Deep Convection Over the Southern Great Plains
Abstract
Abstract The detection of soil moisture‐precipitation feedback is complicated by the dependence of feedback sign on atmospheric state and cloud types. We evaluated responses of convective clouds to changes in surface evaporative fraction (EF) from satellite and ground‐based measurements over the Southern Great Plains in summer months. Strong responses to EF were inferred only after accounting for tropospheric states supporting systematically positive or negative responses. State dependence (inferred from controlled model experiments) explains the weak response found in previous studies. The probability of transitions from shallow to deep cumulus, and subsequent precipitation onset, increases by 58% over drier surfaces in weakly stratified environments having deeper boundary layers. Boundary layer dynamics play a more important role than low‐level relative humidity in these environments. Wetter surfaces yield increased deep convection in moist and thermally stratified environments. The distinct pathways of convective initiation over dry and wet land surfaces can play important roles in drought onset and termination.
- Authors:
-
[1];
[1]
- Climate and Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA USA
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1603827
- Grant/Contract Number:
- DEAC02‐05CH11231
- Resource Type:
- Publisher's Accepted Manuscript
- Journal Name:
- Geophysical Research Letters
- Additional Journal Information:
- Journal Name: Geophysical Research Letters Journal Volume: 47 Journal Issue: 5; Journal ID: ISSN 0094-8276
- Publisher:
- American Geophysical Union (AGU)
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Qiu, Shaoyue, and Williams, Ian N. Observational Evidence of State‐Dependent Positive and Negative Land Surface Feedback on Afternoon Deep Convection Over the Southern Great Plains. United States: N. p., 2020.
Web. doi:10.1029/2019GL086622.
Qiu, Shaoyue, & Williams, Ian N. Observational Evidence of State‐Dependent Positive and Negative Land Surface Feedback on Afternoon Deep Convection Over the Southern Great Plains. United States. https://doi.org/10.1029/2019GL086622
Qiu, Shaoyue, and Williams, Ian N. Tue .
"Observational Evidence of State‐Dependent Positive and Negative Land Surface Feedback on Afternoon Deep Convection Over the Southern Great Plains". United States. https://doi.org/10.1029/2019GL086622.
@article{osti_1603827,
title = {Observational Evidence of State‐Dependent Positive and Negative Land Surface Feedback on Afternoon Deep Convection Over the Southern Great Plains},
author = {Qiu, Shaoyue and Williams, Ian N.},
abstractNote = {Abstract The detection of soil moisture‐precipitation feedback is complicated by the dependence of feedback sign on atmospheric state and cloud types. We evaluated responses of convective clouds to changes in surface evaporative fraction (EF) from satellite and ground‐based measurements over the Southern Great Plains in summer months. Strong responses to EF were inferred only after accounting for tropospheric states supporting systematically positive or negative responses. State dependence (inferred from controlled model experiments) explains the weak response found in previous studies. The probability of transitions from shallow to deep cumulus, and subsequent precipitation onset, increases by 58% over drier surfaces in weakly stratified environments having deeper boundary layers. Boundary layer dynamics play a more important role than low‐level relative humidity in these environments. Wetter surfaces yield increased deep convection in moist and thermally stratified environments. The distinct pathways of convective initiation over dry and wet land surfaces can play important roles in drought onset and termination.},
doi = {10.1029/2019GL086622},
journal = {Geophysical Research Letters},
number = 5,
volume = 47,
place = {United States},
year = {Tue Mar 10 00:00:00 EDT 2020},
month = {Tue Mar 10 00:00:00 EDT 2020}
}
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