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1 U M D - E S S I C C o o p e r a t e I n s t i t u t e O f S a t e l l i t e E a r t h S y s t e m S t u d i e s ( C I S E S S )2 N O A A N E S D I S C e n t e r F o r S a t e l l i t e A p p l i c a t i o n s A n d R e s e a r c h3 N A S A M a r s h a l l S p a c e F l i g h t C e n t e r4 U S D A - A R S H y d r o l o g y A n d R e m o t e S e n s i n g L a b o r a t o r y

Evapotranspiration Data Product from NESDIS GET-D System Upgraded for GOES-16 ABI

Observations

CISESS Science Meeting, UMD, 2019

Li Fang 1,2,*, Xiwu Zhan 2, Mitchell Schull 1,2, Jifu Yin 1,2, Satya Kalluri 2

Peng Yu 1,2, Istvan Laszlo 2Corinne Carter 1,2

Christopher Hain 3Martha Anderson 4

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Background & Objectives

Accurate estimates ofevapotranspiration (ET) arecritical for numerical weather andclimate prediction models

GOES Imager-based ET andDrought (GET-D) product systemhas been operational sinceSeptember 2016

Continuation of GET-D operationusing the current high-resolutionGOES-R series satellites is in highdemand

GET-D system will be upgradedto ingest ABI from GOES- 16 andGOES 17

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Outline

Background & Objectives Theoretic Basis of ALEXI Model Upgraded GET-D System ET product & Product Consistency Validation Summary & Future work

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Theoretic Basis-ALEXI Model

Atmosphere-Land Exchange Inversion (ALEXI) model exploits the mid-morningrise in LST from GOES to deduce the land surface fluxes, includingevapotranspiration (ET)

Implementation of the two-source energy balance model which balancescomponents of energy budgets for the soil and canopy components separately

From Martha Anderson

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Anderson et al. 1997, 2007

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Upgraded GET-D System for GOES-16

Background

ALEXI

GET-D

ET product

Validation

Summary & Future work

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System Inputs of Upgraded GET-D

Background

ALEXI

GET-D

ET product

Validation

Summary & Future work

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System Outputs of Upgraded GET-D

Background

ALEXI

GET-D

ET product

Validation

Summary & Future work

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ET from GET-D Based on GOES-16 ABI Data

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ET from GET-D Based on GOES-16 ABI Data

GOES-16 based 8 km; aggregated from 2kmGOES-13/15 based -- 8 km

GOES-16 based -- 2 km

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ET from GET-D Based on GOES-16 ABI Data

GOES-13/15 based -- 8 km GOES-16 based 8 km; aggregated from 2km

GOES-16 based -- 2 km

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ET from GET-D Based on GOES-16 ABI Data

GOES-13/15 based -- 8 km

GOES-16 based -- 2 km

GOES-16 based 8 km; aggregated from 2km

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ET from GET-D Based on GOES-16 ABI Data

GOES-13/15 based -- 8 km GOES-16 based 8 km; aggregated from 2km

GOES-16 based -- 2 km

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Spatial correlation over CONUS domain is

0.946CONSISTENT!

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Validation over MEAD, NE

1km

Suyker, A.E.; Verma, S.B. Coupling of carbon dioxide and water vapor exchanges of irrigated and rainfed maize–soybean cropping systems and water productivity. Agric.For. Meteorol. 2010, 150, 553–563.Agricultural Research and Development Center, University of Nebraska.

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Validation over MEAD sites, NE

Background

ALEXI

GET-D

ET product

Validation

Summary & Future work

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Error statistics of GET-D ET estimates (mm/day)validated against in situ measurements in MEAD, NE

GOES-16 based

GOES-13 based

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GET-D is upgraded successfully togenerate ET at 2km spatial resolutionusing GOES-16 ABI observations

Upgraded ET product is validatedagainst independent data sets (MEADin situ observations)

GOES-16 based ET product isconsistent with current operationalGOES-13 based product

GOES-16 based GET-D ET has finerspatial resolution (2km vs 8km) andhigher correlation with in situ ETmeasurements compared to GOES-13based one

Summary

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GOES-17 ABI data will be tested withthe upgraded GET-D software

Combined GOES-16 and -17 ABIobservations will be used in thesystem

Comprehensive validation of ETfrom the upgraded GET-D systemwith more in situ measurements

Build GOES-16/17 based ETclimatology together with the legacyGOES-13/15 ET

Evaporative Stress Index (ESI) will becomputed from the GET-D ET and itsclimatology for drought monitoring

Conclusion Future Work

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Evapotranspiration Data Product from NESDIS GET-D System Upgraded for GOES-16 ABI Observations

Li Fang *, Xiwu Zhan, Mitchell Schull, Satya KalluriIstvan Laszlo, Peng Yu, Corinne Carter

Christopher Hain, Martha Anderson

Li Fang li.fang@noaa.gov

Acknowledgments: Research reported in this paper was supported by the NOAA NESDIS GOES-R Risk Reduction (GOES-R3) program for project #488

The end