Development of satellite green vegetation fraction time series for use in mesoscale modeling: application to the European heat wave 2006

Joakim Refslund Nielsen, Ebba Dellwik, Andrea N. Hahmann, Michael J. Barlage, Eva Boegh

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

A method is presented for development of satellite green vegetation fraction (GVF) time series for use in the Weather Research and Forecasting (WRF) model. The GVF data is in the WRF model used to describe the temporal evolution of many land surface parameters, in addition to the evolution of vegetation. Several high-resolution GVF products, derived from high-quality satellite retrievals from Moderate Resolution Imaging Spectroradiometer images, were produced and their performance was evaluated in long-term WRF simulations. The atmospheric conditions during the 2006 heat wave year over Europe were simulated since significant interannual variability in vegetation seasonality was found. Such interannual variability is expected to increase in the coming decades due to climatic changes. The simulation using a quadratic normalized difference vegetation index to GVF relationship resulted in consistent improvements of modeled temperatures. The model mean temperature cold bias was reduced by 10 % for the whole domain and by 20–45 % in areas affected by the heat wave. The study shows that WRF simulations during heat waves and droughts, when vegetation conditions deviate from the climatology, require concurrent land surface properties in order to produce accurate results.
Original languageEnglish
JournalTheoretical and Applied Climatology
Volume117
Issue number3-4
Pages (from-to)377-392
ISSN0177-798X
DOIs
Publication statusPublished - 2014

Cite this

@article{053fbcad124d4bcfa018ef5dd3e20a20,
title = "Development of satellite green vegetation fraction time series for use in mesoscale modeling: application to the European heat wave 2006",
abstract = "A method is presented for development of satellite green vegetation fraction (GVF) time series for use in the Weather Research and Forecasting (WRF) model. The GVF data is in the WRF model used to describe the temporal evolution of many land surface parameters, in addition to the evolution of vegetation. Several high-resolution GVF products, derived from high-quality satellite retrievals from Moderate Resolution Imaging Spectroradiometer images, were produced and their performance was evaluated in long-term WRF simulations. The atmospheric conditions during the 2006 heat wave year over Europe were simulated since significant interannual variability in vegetation seasonality was found. Such interannual variability is expected to increase in the coming decades due to climatic changes. The simulation using a quadratic normalized difference vegetation index to GVF relationship resulted in consistent improvements of modeled temperatures. The model mean temperature cold bias was reduced by 10 {\%} for the whole domain and by 20–45 {\%} in areas affected by the heat wave. The study shows that WRF simulations during heat waves and droughts, when vegetation conditions deviate from the climatology, require concurrent land surface properties in order to produce accurate results.",
author = "Nielsen, {Joakim Refslund} and Ebba Dellwik and Hahmann, {Andrea N.} and Barlage, {Michael J.} and Eva Boegh",
year = "2014",
doi = "10.1007/s00704-013-1004-z",
language = "English",
volume = "117",
pages = "377--392",
journal = "Theoretical and Applied Climatology",
issn = "0177-798X",
publisher = "Springer Wien",
number = "3-4",

}

Development of satellite green vegetation fraction time series for use in mesoscale modeling: application to the European heat wave 2006. / Nielsen, Joakim Refslund; Dellwik, Ebba; Hahmann, Andrea N.; Barlage, Michael J. ; Boegh, Eva .

In: Theoretical and Applied Climatology, Vol. 117, No. 3-4, 2014, p. 377-392.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Development of satellite green vegetation fraction time series for use in mesoscale modeling: application to the European heat wave 2006

AU - Nielsen, Joakim Refslund

AU - Dellwik, Ebba

AU - Hahmann, Andrea N.

AU - Barlage, Michael J.

AU - Boegh, Eva

PY - 2014

Y1 - 2014

N2 - A method is presented for development of satellite green vegetation fraction (GVF) time series for use in the Weather Research and Forecasting (WRF) model. The GVF data is in the WRF model used to describe the temporal evolution of many land surface parameters, in addition to the evolution of vegetation. Several high-resolution GVF products, derived from high-quality satellite retrievals from Moderate Resolution Imaging Spectroradiometer images, were produced and their performance was evaluated in long-term WRF simulations. The atmospheric conditions during the 2006 heat wave year over Europe were simulated since significant interannual variability in vegetation seasonality was found. Such interannual variability is expected to increase in the coming decades due to climatic changes. The simulation using a quadratic normalized difference vegetation index to GVF relationship resulted in consistent improvements of modeled temperatures. The model mean temperature cold bias was reduced by 10 % for the whole domain and by 20–45 % in areas affected by the heat wave. The study shows that WRF simulations during heat waves and droughts, when vegetation conditions deviate from the climatology, require concurrent land surface properties in order to produce accurate results.

AB - A method is presented for development of satellite green vegetation fraction (GVF) time series for use in the Weather Research and Forecasting (WRF) model. The GVF data is in the WRF model used to describe the temporal evolution of many land surface parameters, in addition to the evolution of vegetation. Several high-resolution GVF products, derived from high-quality satellite retrievals from Moderate Resolution Imaging Spectroradiometer images, were produced and their performance was evaluated in long-term WRF simulations. The atmospheric conditions during the 2006 heat wave year over Europe were simulated since significant interannual variability in vegetation seasonality was found. Such interannual variability is expected to increase in the coming decades due to climatic changes. The simulation using a quadratic normalized difference vegetation index to GVF relationship resulted in consistent improvements of modeled temperatures. The model mean temperature cold bias was reduced by 10 % for the whole domain and by 20–45 % in areas affected by the heat wave. The study shows that WRF simulations during heat waves and droughts, when vegetation conditions deviate from the climatology, require concurrent land surface properties in order to produce accurate results.

U2 - 10.1007/s00704-013-1004-z

DO - 10.1007/s00704-013-1004-z

M3 - Journal article

VL - 117

SP - 377

EP - 392

JO - Theoretical and Applied Climatology

JF - Theoretical and Applied Climatology

SN - 0177-798X

IS - 3-4

ER -