Modeling seasonal vegetation variation and its validation against Moderate Resolution Imaging Spectroradiometer (MODIS) observations over North America

Yeonjoo Kim, Guiling Wang

Research output: Contribution to journalArticle

33 Citations (Scopus)

Abstract

Seasonal variability of vegetation, determined by plant phenology, impacts the seasonality of surface and atmospheric water cycles as well as the seasonality of surface energy budget. At the same time, leaf seasonal variations respond to both cumulative and concurrent hydrometeorological conditions. In order to account for this vegetation feedback at the seasonal timescale, a predictive phenology scheme for various plant functional types is developed on the basis of previous studies, and a methodology for crop simulations is proposed and implemented* to supplement this phenology scheme. The phenology scheme is then incorporated into the Community Land Model (CLM). The geographic focus of this study is on the United States where the need for seasonal prediction is urgent and vegetation seasonal characteristics have been shown to significantly influence summer precipitation and temperature. Comparison of the model simulation with Moderate Resolution Imaging Spectroradiometer (MODIS)-derived leaf area index data indicates that our model reproduces the observed vegetation seasonality reasonably well. Subsequent experiments demonstrate the interannual variability of vegetation phenology and its impact on surface water and energy budgets using the 1988 drought and 1993 flood in the U.S. Midwest as examples.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalJournal of Geophysical Research D: Atmospheres
Volume110
Issue number4
DOIs
Publication statusPublished - 2005 Feb 27

Fingerprint

phenology
MODIS (radiometry)
moderate resolution imaging spectroradiometer
vegetation
MODIS
Imaging techniques
seasonality
energy budgets
modeling
surface energy
energy budget
surface water
Interfacial energy
seasonal variation
leaf area index
hydrological cycle
drought
hydrologic cycle
Drought
crops

All Science Journal Classification (ASJC) codes

  • Oceanography
  • Astronomy and Astrophysics
  • Atmospheric Science
  • Space and Planetary Science
  • Earth and Planetary Sciences (miscellaneous)
  • Geophysics
  • Geochemistry and Petrology

Cite this

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abstract = "Seasonal variability of vegetation, determined by plant phenology, impacts the seasonality of surface and atmospheric water cycles as well as the seasonality of surface energy budget. At the same time, leaf seasonal variations respond to both cumulative and concurrent hydrometeorological conditions. In order to account for this vegetation feedback at the seasonal timescale, a predictive phenology scheme for various plant functional types is developed on the basis of previous studies, and a methodology for crop simulations is proposed and implemented* to supplement this phenology scheme. The phenology scheme is then incorporated into the Community Land Model (CLM). The geographic focus of this study is on the United States where the need for seasonal prediction is urgent and vegetation seasonal characteristics have been shown to significantly influence summer precipitation and temperature. Comparison of the model simulation with Moderate Resolution Imaging Spectroradiometer (MODIS)-derived leaf area index data indicates that our model reproduces the observed vegetation seasonality reasonably well. Subsequent experiments demonstrate the interannual variability of vegetation phenology and its impact on surface water and energy budgets using the 1988 drought and 1993 flood in the U.S. Midwest as examples.",
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AU - Kim, Yeonjoo

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N2 - Seasonal variability of vegetation, determined by plant phenology, impacts the seasonality of surface and atmospheric water cycles as well as the seasonality of surface energy budget. At the same time, leaf seasonal variations respond to both cumulative and concurrent hydrometeorological conditions. In order to account for this vegetation feedback at the seasonal timescale, a predictive phenology scheme for various plant functional types is developed on the basis of previous studies, and a methodology for crop simulations is proposed and implemented* to supplement this phenology scheme. The phenology scheme is then incorporated into the Community Land Model (CLM). The geographic focus of this study is on the United States where the need for seasonal prediction is urgent and vegetation seasonal characteristics have been shown to significantly influence summer precipitation and temperature. Comparison of the model simulation with Moderate Resolution Imaging Spectroradiometer (MODIS)-derived leaf area index data indicates that our model reproduces the observed vegetation seasonality reasonably well. Subsequent experiments demonstrate the interannual variability of vegetation phenology and its impact on surface water and energy budgets using the 1988 drought and 1993 flood in the U.S. Midwest as examples.

AB - Seasonal variability of vegetation, determined by plant phenology, impacts the seasonality of surface and atmospheric water cycles as well as the seasonality of surface energy budget. At the same time, leaf seasonal variations respond to both cumulative and concurrent hydrometeorological conditions. In order to account for this vegetation feedback at the seasonal timescale, a predictive phenology scheme for various plant functional types is developed on the basis of previous studies, and a methodology for crop simulations is proposed and implemented* to supplement this phenology scheme. The phenology scheme is then incorporated into the Community Land Model (CLM). The geographic focus of this study is on the United States where the need for seasonal prediction is urgent and vegetation seasonal characteristics have been shown to significantly influence summer precipitation and temperature. Comparison of the model simulation with Moderate Resolution Imaging Spectroradiometer (MODIS)-derived leaf area index data indicates that our model reproduces the observed vegetation seasonality reasonably well. Subsequent experiments demonstrate the interannual variability of vegetation phenology and its impact on surface water and energy budgets using the 1988 drought and 1993 flood in the U.S. Midwest as examples.

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