Vegetation response to climate variability in India from 2001 to 2010

Hirofumi Hashimoto, CSUMB/NASA ARC, hirofumi.hashimoto@gmail.com (Presenter)
Cristina Milesi, CSUMB/NASA ARC, cristina.milesi@gmail.com
Weile Wang, CSUMB/NASA ARC, weile.wang@gmail.com
Sangram Ganguly, NASA ARC, sangramganguly@gmail.com
Andrew Michaelis, CSUMB/NASA ARC, amac@hyperplane.org
Ramakrishna R. Nemani, NASA ARC, rama.nemani@nasa.gov

Food supply in India is a critical issue in sustaining a large population,

and more accurate predictability of agricultural productivity is

necessary for policy makers.

After the Green revolution, the productivity in India has increased

dramatically,

but the leveling-off of the productivity was expected in the near future.

Decreasing of ground water was already observed

and some climate models predict a higher frequency of drought in the

21st century.

For a better understanding of vegetation response to climate change,

we analyzed the satellite images of India from 2001 to 2010.

MODIS satellite imagery shows high spatial variability in vegetation

indices in response to climate variability.

In this study we scrutinize the cause and mechanism of the spatial

variability in vegetation growth in India.

First, we tried to find the corresponding climate variability from

re-analysis data (MERRA and NCEP-NCAR reanalysis data)

and satellite imagery such as TRMM, GIMMS, and MODIS,

as well as interpolated climate observation data (CRU).

Although the precipitation variability due to ENSO has the strongest

impact on vegetation growth,

the other climate variability, such as shortwave radiation, also

perturbed the vegetation response to climate changes.

Second, we proved our hypothesis explaining the vegetation growth trend

by running the Terrestrial Observation and Prediction System (TOPS) model.

The model results were compared with satellite images

and showed reasonable spatial pattern of net primary production

to explain the observed vegetation growth variability to climate change.

Those results can contribute to a more profound understanding of the

mechanism of vegetation growth in India toward future prediction in

food supply.

Presentation Type:  Poster

Session:  Other   (Tue 11:30 AM)

Associated Project(s): 

• Myneni, Ranga: Global Products of Leaf Area Index and Fraction Vegetation Absorbed PAR from the Terra/Aqua MODIS and NPP VIIRS Sensors: Algorithm Refinement and Cal/Val for ESDR Proposal ...details

Poster Location ID: 204