Identification

Title

Assessing impacts of integrating MODIS vegetation data in the Weather Research and Forecasting (WRF) Model coupled to two different canopy-resistance approaches

Abstract

The impact of 8-day-averaged data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor-namely, the 1-km leaf area index, absorbed photosynthetic radiation, and land-use data-is investigated for use in the Weather Research and Forecasting (WRF) model for regional weather prediction. These high-resolution, near-real-time MODIS data are hypothesized to enhance the representation of land–atmosphere interactions and to potentially improve the WRF model forecast skill for temperature, surface moisture, surface fluxes, and soil temperature. To test this hypothesis, the impact of using MODIS-based land surface data on surface energy and water budgets was assessed within the “Noah” land surface model with two different canopy-resistance schemes. An ensemble of six model experiments was conducted using the WRF model for a typical summertime episode over the U.S. southern Great Plains that occurred during the International H₂O Project (IHOP_2002) field experiment. The six model experiments were statistically analyzed and showed some degree of improvement in surface latent heat flux and sensible heat flux, as well as surface temperature and moisture, after land use, leaf area index, and green vegetation fraction data were replaced by remotely sensed data. There was also an improvement in the WRF-simulated temperature and boundary layer moisture with MODIS data in comparison with the default U.S. Geological Survey land-use and leaf area index inputs. Overall, analysis suggests that recalibration and improvements to both the input data and the land model help to improve estimation of surface and soil parameters and boundary layer moisture and led to improvement in simulating convection in WRF runs. Incorporating updated land conditions provided the most notable improvements, and the mesoscale model performance could be further enhanced when improved land surface schemes become available.

Resource type

document

Resource locator

Unique resource identifier

code

http://n2t.net/ark:/85065/d7j67hwp

codeSpace

Dataset language

eng

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code identifying the spatial reference system

Classification of spatial data and services

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geoscientificInformation

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Text

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title

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reference date

date type

publication

effective date

2016-01-01T00:00:00Z

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publication

effective date

2014-06-01T00:00:00Z

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Copyright 2014 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be "fair use" under Section 107 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Law (17 USC, as revised by P.L. 94-553) does not require the Society's permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statements, requires written permission or license from the AMS. Additional details are provided in the AMS Copyright Policies, available from the AMS at 617-227-2425 or amspubs@ametsoc.org. Permission to place a copy of this work on this server has been provided by the AMS. The AMS does not guarantee that the copy provided here is an accurate copy of the published work.

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None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

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