Spatial and Temporal Scales of Boundary Layer Wind Predictability in Response to Small-Amplitude Land Surface UncertaintySource: Journal of the Atmospheric Sciences:;2010:;Volume( 067 ):;issue: 001::page 217Author:Hacker, Joshua P.
DOI: 10.1175/2009JAS3162.1Publisher: American Meteorological Society
Abstract: Predictability experiments with the Weather Research and Forecast (WRF) model as a proxy for the atmosphere are analyzed to quantify the spatial and temporal scales of boundary layer wind response to land surface perturbations. Soil moisture is chosen as the land surface variable subject to uncertainty because the atmosphere is known to be sensitive to its state. A range of experiments with spatially correlated, small-amplitude perturbations to soil moisture leads to results that show the dependence of predictability on atmospheric conditions. The primary conclusions are as follows: 1) atmospheric conditions, including static instability and the presence of deep convection, determine whether large errors and local loss of predictability are possible in response to soil moisture errors; 2) the scale of soil moisture uncertainty determines scales of PBL wind predictability when the atmosphere is resistant to upscale error transfer, but when the atmosphere is sensitive the scale and magnitude of soil moisture uncertainty are not important after a few hours; and 3) nonlinear error growth is present whether or not the atmosphere is relatively sensitive to soil moisture uncertainty, leading to doubling times of minutes to hours for finite-sized perturbations. Similar results could be expected from other land surface variables or parameters that exert time-dependent forcing on the atmosphere that is similar in magnitude and scale to that of soil moisture.
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contributor author | Hacker, Joshua P. | |
date accessioned | 2017-06-09T16:28:33Z | |
date available | 2017-06-09T16:28:33Z | |
date copyright | 2010/01/01 | |
date issued | 2010 | |
identifier issn | 0022-4928 | |
identifier other | ams-68540.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4210109 | |
description abstract | Predictability experiments with the Weather Research and Forecast (WRF) model as a proxy for the atmosphere are analyzed to quantify the spatial and temporal scales of boundary layer wind response to land surface perturbations. Soil moisture is chosen as the land surface variable subject to uncertainty because the atmosphere is known to be sensitive to its state. A range of experiments with spatially correlated, small-amplitude perturbations to soil moisture leads to results that show the dependence of predictability on atmospheric conditions. The primary conclusions are as follows: 1) atmospheric conditions, including static instability and the presence of deep convection, determine whether large errors and local loss of predictability are possible in response to soil moisture errors; 2) the scale of soil moisture uncertainty determines scales of PBL wind predictability when the atmosphere is resistant to upscale error transfer, but when the atmosphere is sensitive the scale and magnitude of soil moisture uncertainty are not important after a few hours; and 3) nonlinear error growth is present whether or not the atmosphere is relatively sensitive to soil moisture uncertainty, leading to doubling times of minutes to hours for finite-sized perturbations. Similar results could be expected from other land surface variables or parameters that exert time-dependent forcing on the atmosphere that is similar in magnitude and scale to that of soil moisture. | |
publisher | American Meteorological Society | |
title | Spatial and Temporal Scales of Boundary Layer Wind Predictability in Response to Small-Amplitude Land Surface Uncertainty | |
type | Journal Paper | |
journal volume | 67 | |
journal issue | 1 | |
journal title | Journal of the Atmospheric Sciences | |
identifier doi | 10.1175/2009JAS3162.1 | |
journal fristpage | 217 | |
journal lastpage | 233 | |
tree | Journal of the Atmospheric Sciences:;2010:;Volume( 067 ):;issue: 001 | |
contenttype | Fulltext |