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Global Modeling and Assimilation Officegmao.gsfc.nasa.govGMAO

National Aeronautics and Space Administration

Continuing the Assessment of the Combined Impacts of AIRS, CrIS,

and IASI on Global Skill and Tropical Cyclone Representation

in the NASA GEOS-5Erica McGrath-Spangler1

Oreste Reale1, Will McCarty2, Dan Holdaway1, Ron Gelaro2, Manisha Ganeshan1

1 GESTAR/USRA and NASA/GMAO2NASA/GMAO



Statement of the problemAfter examining the problem of error correlation within AIRS data, we are going to examine the possibility of horizontal error correlations across infrared instruments (AIRS, CrIS, and IASI)Errors from different hyperspectral infrared datasets may not be independent, introducing cross-instrument correlation errors that are not accounted for in current data assimilation systemsCurrently, the instruments are assimilated independentlyShould they be considered together with a comprehensive thinning strategy?



Clear-sky AIRS radiance distribution

• Performed “bounding” experiments to explore various thinning levels for AIRS data only

• Found that these experiments affected assimilation of other hyperspectral infrared radiances

x ~4x ~1/4x



Clear-sky global adjoint results

Globally, reduced data density results in a higher fraction of observations being beneficial to the analysisCrIS: Affected by

changes in AIRS data density, even though CrIS assimilation NOT modified in these experiments!



Hyperspectral instrument orbit tracks

AIRS and CrIS are in very similar orbits, observations are collocated



Observations over H. GonzaloInstruments provide different information around the stormClear-sky data have gaps around center of the storm AIRS

IASI (Metop-A)

CrIS

IASI (Metop-B)



New ExperimentsGEOS-5 DAS version 5-13.0p1 run 1 Sep – 10 Nov 2014 with

10 day forecasts from 21 Sep – 31 Oct 2014

• RAD_noCrIS: AIRS clear-sky radiances, thinning 145 km, no CrIS data

• RAD_noIASI: AIRS clear-sky radiances, thinning 145 km, no IASI data

• CLD_noCrIS: AIRS cloud-cleared radiances, thinning 145 km, no CrIS

data

• CLD_noIASI: AIRS cloud-cleared radiances, thinning 145 km, no IASI

data

• RAD3_CrIS3_IASI3: AIRS clear-sky radiances, AIRS, CrIS, and IASI all

thinned 300 km

• CLD3_CrIS3_IASI3: AIRS cloud-cleared radiances, AIRS, CrIS, and

IASI all thinned 300 km



Global 500 hPa height anomaly correlation

Reference = OPS

More aggressive, comprehensive thinning across instruments improves global skill



AIRS clear-sky and cloud-cleared response

For clear-sky AIRS radiances, removing IASI has small positive impact at early forecast times, but degrades after 6 days

Reference = RAD Reference = RAD

However, for cloud-cleared AIRS radiances, removing IASI produces a significant improvement

Indication that error correlations among instruments are different if using clear-sky or cloud-cleared AIRS radiances



H. Edouard analysis

10 hPa



H. Edouard analysis

Vertical cross sectionWind magnitude (shaded)Temperature (°C, black)Temp. Anomaly (°C, red)

850 hPa winds (shaded)slp(contours)

Comprehensive thinning for both cases improves analyzed structure• Stronger wind

speed• Stronger warm

core



H. Edouard intensity forecast

Improvement in analysis structure translates to increases in forecast intensity



H. Gonzalo analysis

More aggressive, comprehensive thinning produces greater storm intensification



H. Gonzalo analysis

Vertical cross

section

Wind magnitude

(shaded)

Temperature (°C,

black)

Temp. Anomaly

(°C, red)

850 hPa winds

(shaded)

slp(contours)

Comprehensive

thinning results in

• Stronger warm core

• Increase in winds

• More symmetric

structure



H. Gonzalo intensity forecast

Intensity forecasts from 00Z analysis are stronger through 48 hours when thinning is comprehensive and more aggressive



H. Simon analysis

Short-lived storm that was difficult to represent in DAS



H. Simon analysis

Vertical cross sectionWind magnitude (shaded)Temperature (°C, black)Temp. Anomaly (°C, red)

850 hPa winds (shaded)slp(contours)

At time of maximum intensity, aggressive, comprehensive thinning of hyperspectral instruments showed substantial improvement• Deeper central

pressure• More symmetric

wind structure• Stronger warm

core• More compact

and narrow storm



H. Simon intensity forecast

Substantial improvement in intensity forecast for this difficult to predict storm



Summary• Evidence is presented suggesting that cross instrument

horizontal error correlations exist among hyperspectral soundersl• Data denial experiments in which CrIS and/or IASI are taken out

from a data assimilation experiment in which either AIRS clear-sky or AIRS cloud-cleared are used, produce a benefit

• This is suggestive of cross instrument correlation error

• However, two strategies of comprehensive thinning in which 1)clear-sky AIRS radiances are thinned together with CrIS and IASI or 2) cloud-cleared AIRS radiances are thinned together with CrIS and IASI BOTH produce improvement in forecast skill and TC representation

• This improvement is not as large as was found with adaptive thinning, but we are currently working to expand adaptive thinning strategy to CrIS and IASI



AcknowledgementsThanks to:

Dr. Ramesh Kakar for support of the current proposal ”Using AIRS data to understand processes affecting TC structure and extreme precipitation in a Global Data Assimilation and Forecasting Framework (2014-2017)” (PI: Dr. O. Reale)

Dr. Ramesh Kakar for support of the previously funded proposal “Using AIRS data to understand processes affecting Tropical Cyclone structure in a Global Data Assimilation and Forecasting Framework (2011-2014)”

Dr. Tsengdar Lee for generous allocations of NASA High End Computing resources

AIRS team at JPL and the Sounder Research Team at NASA GSFC

GES DISC for their outstanding service to the community

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