Alys Thomas Alys Thomas Hydrology and Climate Research Group Hydrology and Climate Research Group Dept. of Earth System Science Dept. of Earth System Science University of California, Irvine University of California, Irvine 2013 AMS Annual 2013 AMS Annual Meeting, Austin Meeting, Austin Using the Using the G.R.A.C.E. G.R.A.C.E. Satellites’ Water Satellites’ Water Storage Anomaly Dataset Storage Anomaly Dataset to Identify Regional to Identify Regional Scale Drought Conditions Scale Drought Conditions
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Alys ThomasAlys ThomasHydrology and Climate Research GroupHydrology and Climate Research GroupDept. of Earth System ScienceDept. of Earth System ScienceUniversity of California, IrvineUniversity of California, Irvine 2013 AMS Annual 2013 AMS Annual Meeting, AustinMeeting, Austin
Using the Using the G.R.A.C.E.G.R.A.C.E. Satellites’ Water Storage Satellites’ Water Storage
Anomaly Dataset to Anomaly Dataset to Identify Regional Scale Identify Regional Scale
Drought ConditionsDrought Conditions
ObjectiveObjective
cm eqv. water height
The GRACE mission provides monthly, global The GRACE mission provides monthly, global maps of Earth's gravity and how it changes as maps of Earth's gravity and how it changes as the mass distribution shiftsthe mass distribution shifts
Large scale gravity changes attributed to mass Large scale gravity changes attributed to mass movement of water on and beneath the surfacemovement of water on and beneath the surface
Helps us understand how water moves from the Helps us understand how water moves from the land to the ocean and back againland to the ocean and back again
The The GGravity ravity RRecovery ecovery AAnd nd CClimate limate
EExperimentxperiment
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 thicknessCourtesy of CSR & JPL, http://www.csr.utexas.edu/grace/gallery/
Back to the basics:Back to the basics: Once variable (i.e. rainfall, streamflow, water storage, etc.) Once variable (i.e. rainfall, streamflow, water storage, etc.)
crosses a given threshold, it enters into a dry/drought periodcrosses a given threshold, it enters into a dry/drought period The length of time it stays under and deviates from that The length of time it stays under and deviates from that
threshold give us the threshold give us the severityseverity of the drought event of the drought event
Characterizing drought with GRACE dataCharacterizing drought with GRACE data
Mishra et al. (2009)
Yevjevich (1967)
Keyantash and Dracup (2002)
Examples:
Amazon River BasinAmazon River Basin Hydrologically-definedHydrologically-defined Area: ~6,100,000 kmArea: ~6,100,000 km22
Two well-documented Two well-documented meteorological droughts during meteorological droughts during GRACE period (2005 & 2010)GRACE period (2005 & 2010)
High Plains Region (U.S.)High Plains Region (U.S.) Not hydrologically definedNot hydrologically defined Area: ~2,000,000 kmArea: ~2,000,000 km22
Two documented droughts during Two documented droughts during GRACE period (Severest drought GRACE period (Severest drought late 2010 to present)late 2010 to present)
Study AreasStudy Areas
Processing of GRACE data:Processing of GRACE data:
Scale factors (Scale factors (providedprovided) and interpolation of missing months) and interpolation of missing months
Monthly climatology (TWSA) calculated using ~9 years of TWSA Monthly climatology (TWSA) calculated using ~9 years of TWSA datadata
GRACE anomalies converted from ‘cm’ to ‘GRACE anomalies converted from ‘cm’ to ‘kmkm’ of eqv. water ’ of eqv. water heightheight
Masks for study areas used to calculate the spatial averagesMasks for study areas used to calculate the spatial averages
Regional average storage anomalies (km) were then multiplied Regional average storage anomalies (km) were then multiplied by the region’s area (kmby the region’s area (km22) resulting in:) resulting in:
regional-average water storage volume change regional-average water storage volume change (km(km33))
THIS IS WHAT THIS IS WHAT GRACEGRACE SAW . . . SAW . . .
A.A.Monthly observations of terrestrial water storage variability from GRACE Monthly observations of terrestrial water storage variability from GRACE satellites reveal extended periods of relatively dry conditions:satellites reveal extended periods of relatively dry conditions:
A.A. Amazon River Basin in 2005 and 2010Amazon River Basin in 2005 and 2010B.B. Southern Plains region in 2006 and 2010-presentSouthern Plains region in 2006 and 2010-present
B.B.Analyzing water storage anomalies without their 9-year monthly climatology allow us Analyzing water storage anomalies without their 9-year monthly climatology allow us to define a dryness threshold for each regionto define a dryness threshold for each region
C.C.We can then determine GRACE-identified drought magnitude, duration, and severity We can then determine GRACE-identified drought magnitude, duration, and severity in units of volume of water “in units of volume of water “missingmissing” from the system during drought and how much ” from the system during drought and how much is needed to “is needed to “recoverrecover””
D.D.Future work:Future work:
A.A. Spatial characteristics within these regionsSpatial characteristics within these regions
B.B. Linking “missing” water storage numbers with water managementLinking “missing” water storage numbers with water management
C.C. Application to other regionsApplication to other regions
Funding:Funding: NASA Graduate Student Research Project NASA Graduate Student Research Project
Many thanks to:Many thanks to: Jay Famiglietti, J.T. Reager, Jay Famiglietti, J.T. Reager, Matt Rodell, Bailing Li, Caroline Matt Rodell, Bailing Li, Caroline
de Linage, Hiroko Beaudoingde Linage, Hiroko Beaudoing
• 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.
