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Use of High Spectral Resolution Infrared Sounders to Validate Reanalyses Mitch Goldberg, Likun Wang NOAA/NESDIS/STAR Satellite Meteorology and Climatology Division 1
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Use of High Spectral Resolution Infrared Sounders to Validate Reanalyses

Feb 01, 2016

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Use of High Spectral Resolution Infrared Sounders to Validate Reanalyses. Mitch Goldberg, Likun Wang NOAA/NESDIS/STAR Satellite Meteorology and Climatology Division. Motivation. - PowerPoint PPT Presentation
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Page 1: Use of High Spectral Resolution Infrared Sounders to Validate Reanalyses

Use of High Spectral Resolution Infrared Sounders to Validate

ReanalysesMitch Goldberg, Likun Wang

NOAA/NESDIS/STARSatellite Meteorology and

Climatology Division

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Motivation• Many studies comparing AIRS, IASI and aircraft interferometer have

demonstrated the accuracy and stability of AIRS and IASI.

• Finally we have a very precise, accurate reference dataset to validate other datasets, such as radiosondes, model analyses, reanalyses, etc.

• Unlike GPS RO, the thermal infrared radiances are influenced by key essential climate variables:– CO2, CH4, O3, CO, Clouds, Aerosols, Temperature, Moisture.

• CLARREO mission is design to meet this objective, with onboard SI traceability.

• Climate Reanalyses are gaining recognition for providing historical climate information but each are different, why??

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Wide spread in Projections

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Need to improve model projections. With benchmark – reference satellite observations, we can insist that the models agree with the satellite observations

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AIRS Sensitivity to Atmospheric Change

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Approach

• Simulate AIRS IR radiances from Reanalyses and compare with observed AIRS.

• Limiting factors:– How good is AIRS?– How good is the radiative transfer model?

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01/29/2010 Task140 Brief 7

Double Difference versus SNOs

1) Indirect vs. Direct comparison

2) Warm scenes vs. cold scenes

Four channels

SNOs

Polar Regions

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01/29/2010 Task140 Brief 8

Results

GOES-AIRSGOES-IASI

SNO NorthSNO South

Double Difference

6.5µm

10.7µm

12.0µm

13.3µm

IASI-AIRS

Wang et al. 2010, manuscript for GRL

Zero line

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Statistical results

GOES-11 Ch3

GOES-11 Ch4

GOES-11 Ch5 GOES-12 Ch6

Central Wavelength (µm) 6.7 10.7 12.0 13.3

Double Differences

Sample number 694 688 691 626

Mean (K) -0.0707 -0.0262 -0.041 -0.0751

95% confidence level (K)

0.0052 0.0116 0.0135 0.0124

SNOs Sample number 228 * 228 228 228

Mean (K) -0.011 -0.0624 -0.010 -0.0124

95% confidence level (K)

0.0091 0.0300 0.0295 0.0211

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Temperature channel 1.5 mb peak

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Temerature channel 40 mb peak

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Temperature channel 300 mb peak

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Water vapor channel 300 mb peak

Increasing negative means increase in water vapor

DR = f( DT, DQ)

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ERA-Interim versus ECMWFTPW above 500hpa

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JRA versus ECMWFTPW above 500hpa

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MERRA versus ECMWFTPW above 500hpa

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Comparison with TWP ARM Site - Night time – September 2002-2005 N=22

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Summary

Datasets have been generated for 5 years data from January 2003:

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Summary/Recommendations• AIRS and IASI are reference quality instruments which

can be used to validate climate reanalyses and climate projections.

• Need to continue to improve radiative transfer models via better laboratory spectroscopy and ground truth data (e.g. GRUAN)

• Absolute observations and radiative transfer will allow measurements to be used as anchor points and will allow focus on improving model physics.

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ERA Interim Reanalysis - ECMWF Weather Analysis – September 2004

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ERA Interim Reanalysis - ECMWF Weather Analysis Sept. 2007

ECMWF 2003 – 2005 can be used to validate reanalyses

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ERAIM - JRA25 ECMWF - JRA25

JRA25 vs ECMWF and ERA Interim (above 500 mb)