ali behrangi stephanie granger - airs · sept june. airs helps understand drought development...
TRANSCRIPT
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AIRS Application for drought and fire:Current status and future plans
Ali BehrangiStephanie Granger
Jet Propulsion Laboratory, California Institute of Technology
Thanks to: Steve Licata, Yixin Wen, Alireza Farahmand
NASA sounder science team meeting, Oct 24-26, 2017, Greenbelt, MD.
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Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
A. Behrangi NASA sounder science team meeting, Oct 24-26, 2017, Greenbelt, MD
(VPD= es-e) will increase over land
Why AIRS data ?
SVPDI>1.5This suggests that
VPD=Vapor pressure deficit
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Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
A. Behrangi NASA sounder science team meeting, Oct 24-26, 2017, Greenbelt, MD
Drought formation: A processS
tand
ardi
zed
inde
x
Behrangi et al. (2016)
AIRS
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AIRS and US drought monitor (USDM )March 2016
VPD Anomaly RH Anomaly
US drought monitor
VP
D A
nom
aly
RH Anomaly *-1
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Case study
USDM• 2011 Texas Drought 2011 drought was the worst one-year drought in Texas since 1895.
• 2012 US Midwest Drought
• 2014 California Drought
• 2010-11 East Africa Drought
caused $12 billion in damages mainly from agricultural losses [Henderson and Kauffman, 2012].
Sept
Sept
June
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AIRS helps understand drought development processes
Behrangi, A., P. Loikith, E. Fetzer, H. Nguyen, and S. Granger, 2015: Utilizing Humidity and Temperature Data to Advance Monitoring and Prediction of Meteorological Drought. Climate, 3, 999-1017.
2012 drought
Behrangi et al. (2015)
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VPD anomaly
Fire occurrence : hectares burned
VPD and FireAugust 2012
The national fire danger rating system (NFDRS) energy release component (ERC)
Annual burned forest area v. mean March–August VPD in SW forest area during 1894–2013. The figure is from Williams et al. (2014a)
June
July
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Collaboration withThe National Drought Mitigation Center (NDMC)
U.S. Drought Monitor (USDM)
20160519
USDM
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AIRS Drought Percentile Products – Processing Flow
Producing ½ degree ; Near real-time percentiles for T, RH, VPD
Credit:Stephanie GrangerSteve Licata
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Assessing the impact of AMSU loss on drought analysisComparing MW-IR and IR-only retrievals over Midwest drought
VPD Anomaly
Loss of AMSU A2:
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Current Status
�Automated near real-time production of T, RH and VPD as percentiles for USDM
(delivered every Monday; USDM automatically pulls from our ftp site)
�Since May 2017 - USDM incorporates AIRS drought products into data stack for authors– 7 , 28, and 56 day window
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Case study: Recent drought over Montana, N&S Dakota
Sept 10th 2017
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USDM
VPD percentile
RH percentile 2017 05 15
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USDM
VPD percentile
RH percentile
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USDM
VPD percentile
RH percentile
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June 6
USDM
VPD percentile
RH percentile
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USDM
VPD percentile
RH percentile
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USDM
VPD percentile
RH percentile
June 19th, 2017
Vegetation health NOAA START
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USDM
VPD percentile
RH percentile
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USDM
VPD percentile
RH percentile
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USDM
VPD percentile
RH percentile
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USDM
VPD percentile
RH percentile
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USDM
VPD percentile
RH percentile
USDM:July 24th, 2017
AIRS: June 19th
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Drought dynamics
• T RH VPD
• Precipitation
Environment:
• Soil Moisture
Vegetation:• SIF• NDVI
SIF: solar-induced chlorophyll fluorescence Credit: Yixin Wen
Drought development is a process:Relating VPD, NDVI, SIF , PRECIP, Soil moisture,
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Case 1: Central plain drought in 2012
USDMVPD
VegDRI QuickDRI
Example: Timing of the peak drought conditions in 2012Using VPD anomaly, USDM, VegDRI and QuickDRI
July 1, 2012 August 28, 2012
Sep 2, 2012 July 15, 2012
Wen, et al. In prep
+2 month
+2 month +1/2 month
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Future Work• Continue to work with National Drought Mitigation Center
(USDM) to refine products• Assessing irrigated/non-irrigated regions• Combining the AIRS data with other related observations
(e.g., VPD and Soil moisture)• Utilize our results in decision making process:
Concept submitted to WWAO to support Missouri Basin Drought Early Warning System (Granger/Behrangi/Svoboda)
• Sustainability of data record (e.g., via NPP, etc.)