Transcript Alys Thomas Hydrology and Climate Research Group Dept. of

Using the G.R.A.C.E. Satellites’
Water Storage Anomaly Dataset
to Identify Regional Scale
Drought Conditions
Alys Thomas
Hydrology and Climate Research Group
Dept. of Earth System Science
University of California, Irvine
2013 AMS Annual Meeting, Austin
cm eqv. water height
Objective

The GRACE mission provides monthly, global maps of
Earth's gravity and how it changes as the mass
distribution shifts

Large scale gravity changes attributed to mass movement
of water on and beneath the surface

Helps us understand how water moves from the land to
the ocean and back again
DATASET
•Release 5 Land data from Uni. Texas Center for
Space Research (CSR)
•Monthly time steps: March 2003- August 2012
•Mean is removed to produce terrestrial water
storage anomalies (TWSA) on 1° grids
•Units: CM of equivalent water thickness
Courtesy of CSR & JPL, http://www.csr.utexas.edu/grace/gallery/
The Gravity Recovery And Climate Experiment

Back to the basics:


Once variable (i.e. rainfall, streamflow, water storage, etc.) crosses a given
threshold, it enters into a dry/drought period
The length of time it stays under and deviates from that threshold give us
the severity of the drought event
Examples:
Yevjevich (1967)
Keyantash and Dracup (2002)
Characterizing drought with GRACE data
Mishra et al. (2009)

Amazon River Basin




Hydrologically-defined
Area: ~6,100,000 km2
Two well-documented meteorological
droughts during GRACE period (2005
& 2010)
High Plains Region (U.S.)


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Not hydrologically defined
Area: ~2,000,000 km2
Two documented droughts during
GRACE period (Severest drought late
2010 to present)
Study Areas

Processing of GRACE data:

Global 1° gridded GRACE product downloaded

Scale factors (provided) and interpolation of missing months

Monthly climatology (TWSA) calculated using ~9 years of TWSA data

GRACE anomalies converted from ‘cm’ to ‘km’ of eqv. water height

Masks for study areas used to calculate the spatial averages

Regional average storage anomalies (km) were then multiplied by the
region’s area (km2) resulting in:
regional-average water storage volume change (km3)
Methodology
Storage Temporal Characteristics: AMAZON
Storage Temporal Characteristics: HIGH PLAINS
Water storage with the climatology removed:
Assign a dryness
threshold (zero)
based on storage
values with monthly
climatology
removed
Negative =
dry/drought
Positive =
wet/flood
Determining Drought Severity
Drought Magnitude & Duration: AMAZON
-2406
-3874
-1293
Drought Severity: AMAZON
-3458 (DEFICIT)
Drought Magnitude & Duration: HIGH PLAINS
-622
-2323
(DEFICIT)
Drought Severity: HIGH PLAINS
-3827
Average volume of water missing from region per drought event:

①
Amazon:

Dec 2004 – Dec 2005 drought
~ 298 km3
①
Severest mo. (Aug2005): 499 km3
②
Southern Plains:
Oct 2010 – Aug 2012 drought
~ 166 km3
Severest mo. (Jun2012): 348 km3
Feb 2010 – Mar 2011 drought
~ 247 km3
Severest mo. (Oct2010): 463 km3
Drought: Impacts on Water Storage
THIS IS WHAT
GRACE SAW . . .
Monthly observations of terrestrial water storage variability from
GRACE satellites reveal extended periods of relatively dry conditions:
A.
Amazon River Basin in 2005 and 2010
B.
Southern Plains region in 2006 and 2010-present
A.
Analyzing water storage anomalies without their 9-year monthly climatology
allow us to define a dryness threshold for each region
B.
We can then determine GRACE-identified drought magnitude, duration, and
severity in units of volume of water “missing” from the system during drought
and how much is needed to “recover”
C.
D.
Future work:
A.
Spatial characteristics within these regions
B.
Linking “missing” water storage numbers with water management
C.
Application to other regions
Summary

Funding: NASA Graduate Student Research Project

Many thanks to:

Jay Famiglietti, J.T. Reager, Matt Rodell, Bailing Li, Caroline de Linage,
Hiroko Beaudoing
Hydrospheric and Biospheric Sciences
•
Keyantash, J. A., and J. A. Dracup, 2002: The quantification of drought: An evaluation of drought indices. Bull. Amer. Meteor. Soc., 83, 1167–1180
•
Landerer F.W. and S. C. Swenson, Accuracy of scaled GRACE terrestrial water storage estimates. Water Resources Research 2012.
•
Mishra, K., V. P. Singh, and V. R. Desai, Drought characterization: a probabilistic approach, Stoch Environ Res Risk Assess (2009) 23:41–55, DOI
10.1007/s00477-007-0194-2.
•
Swenson S.C , D. P. Chambers, and J. Wahr: Estimating geocenter variations from a combination of GRACE and ocean model output. J Geophys. Res.Solid Earth, Vol 113, Issue: B8, Article B08410. 2008.
Contact Alys Thomas: [email protected]
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