Using MODIS Data to
Characterize Climate Model Land Surface Processes and The Impacts of Land
Use/Cover Change on Surface Hydrological Processes
Proposal
to NASA NRA-03-OES-03 Interdisciplinary Science In
the NASA Earth Science Enterprise
Principal Investigator: Robert E. Dickinson
Tel: 404-385-1509
Fax: 404-385-1510
Email: robted@eas.gatech.edu
Co-Investigators: Gordon B. Bonan2, Ruth Defries3, Mark Friedl4, Feng Gao4, Menglin Jin3, Juri Knyazikan4, Shunlin
Liang3, Wolfgang Lucht5, Ranga Myneni4, Bernard
Pinty6, Nikolay Shabanov4, Crystal Schaaf4, Yuhong Tian1, Elena Tsvetsinskaya4, Michel Verstraete6, Zong-Liang Yang7, Xubin Zeng8,
Liming Zhou1
Collaborators: Peter Cox9, Yongjiu
Dai10, Nadine Gobron6, Yves Govaerts11, Andrew Pitman12, Jan Polcher13, Jagadish Shukla14, Alan Strahler4, Kumiko
Takata15, Jean-Luc Widlowski6
Students: Zhuo Wang8, Mi Zhou1
Abstract
Abstract One of
the key science questions identified in the NRA is: “How are variations in
local weather, precipitation, and water resources related to global climate
variation?” The overall goal of this interdisciplinary proposal is to address
this question through a synthesis of MODIS data onboard the Terra and Aqua
satellites with land surface models as used in climate system models. Doing
so will advance our understanding as to two ESE key science questions: “How
does the Earth system respond to natural and human-induced changes?” and
“What are the consequences of change in the Earth system for human
civilization?”
This
investigation will be carried out by a multidisciplinary team who
collectively has considerable experience in climate modeling and in the
development of various MODIS algorithms that are now able to provide
important products to climate modelers. We will develop a quantitative basis
for assessing the consequences of land use/cover change in terms of climate
and hydrological changes, building on a climatology
of spectral albedos related to the plant functional
types (PFTs) of the NCAR Community Land Model
(CLM2). We will establish realistic radiative
models for these PFTs in the form of lookup table
spectral albedos depending on model parameters such
as LAI, fractional covers, and underlying surfaces. We will also use the
spectral albedos and other MODIS data to improve
descriptions of LAI, stem area index, fractional vegetation cover, fractional
snow cover, and emissivity/skin temperature in
CLM2. Relevant model processes will be reformulated so that they are
consistent with the MODIS observations. In particular, the atmospheric solar
radiation model will be modified to include the 7 MODIS land bands and the
land model will be improved by a new treatment of solar radiation for its PFTs in terms of the lookup tables that have been
generated.
We will
investigate change regions identified by MODIS land cover dynamic algorithms.
Such will be characterized in terms of changes of the spectral albedos and hence in terms of some combination of changes
of PFTs or of the other properties connected to a
particular PFT. This study will provide a basis for including year-to-year
changes of land use/cover in climate prediction models and establishing the
hydrological consequences of past and future land cover change.
The response of
the land climate system to forcing involves not only the climate system
sensitivity to TOA radiative fluxes, but also other
sensitivities that are orthogonal to the response to TOA radiative
flux changes. These other sensitivities are of comparable importance for
determining climate change over land, i.e. the changes of surface
temperatures and hydrological properties. The current theoretical framework
of sensitivity to TOA fluxes is largely inappropriate to quantify such
questions as what is the climate change resulting from land use changes since
it depends significantly on other dimensions in sensitivity space. Perhaps an
even more important question is the role of land in shorter time scale (e.g.
seasonal) climate prediction, and the processes relevant to this question are
largely orthogonal to TOA flux sensitivity. Hence the main objective of this
proposal will be to develop quantitatively an alternative paradigm, arguably
more appropriate for quantifying climate change at the land surface. Key
elements of the forcing of land are the statistics of surface solar radiation
fluxes and precipitation, and their interaction with the vegetation and soil.
The former are highly dependent on details of clouds and aerosol
distributions. High frequency temporal details are shown to be important. The
response has been known to depend on the partitioning of radiation between
canopy and soil and the partitioning of the precipitation between storage, evapotranspiration, and runoff. The new theme we will
develop is the division among different time scales of the evapotranspiration and runoff. For example, precipitation
that is immediately lost as runoff or evaporation is consequently not stored
in the soil and so does not contribute to predictability of soil moisture or
its feedbacks on precipitation. Hence, the correct modeling of these times
scales is key for representing the contribution of land to seasonal to interannual predictability. The proposed work will use
NASA satellite data for solar radiation, clouds and aerosols, and
precipitation albedo, and LAI/FPAR and through
their incorporation in a climate model quantify the processes involved and
contribute to the improvement of various land models.
Progress Report 2005
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