Uses of AIRS Data for Weather, Climate and Atmospheric Composition
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Transcript of Uses of AIRS Data for Weather, Climate and Atmospheric Composition
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
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Uses of AIRS Data for Weather, Climate and Atmospheric Composition
Eric FetzerJet Propulsion Laboratory / California Institute of
Technology
Satellite Hyperspectral Sensor Workshop, University of Miami
March 29 -31, 2011
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
In Memory of Dr. Mous Chahine
AIRS Science Team Leader and Friend
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National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
AIRS Project Overview
Salient Features
Spacecraft – Instruments:EOS Aqua – AIRS/AMSU/HSBLaunch Date: May 4, 2002Launch Vehicle: Boeing Delta II, Intermediate ELV
Mission Life: 6 yearsCategory: 2Risk Class: AInstruments Operational: August 2002Team Leader: Moustafa T. Chahine
Science
• Improve Weather Prediction
• AIRS data are assimilated into the operational forecast system at NWP centers worldwide
• AIRS Improves Forecast and Tropical Cyclone Prediction
• Improve Climate Prediction
• Measure the Water Cycle, Temperature Trends, Dust and Cloud Properties
• Measure Important Trace Gases: CO, O3, CO2, CH4, SO2
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
AIRS Key Products and Science Areas
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Atmospheric Water VaporOzone
Cloud Properties
Dust
CO
EmissivityMethane
Atmospheric Temperature
CO2
Greenhouse Gas Forcing
Cloud and Water Vapor Processes
SO2
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
~400 AIRS Peer-Reviewed Publications
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National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
Question 1
• How are current hyperspectral IR sounders such as the NASA JPL AIRS and CNES & EUMETSAT IASI used?
– What are the deficiencies?– What improved information is needed by the user?
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AIRS Improves Weather Operations and Research
SAL 4SAL 3SAL 2
AEW 1
Polar 1
SAL 1Irene
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Polar 2
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Mixing Ratio (g kg-1)
Pre
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hP
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GPS Sonde
Jordan
AIRS
NCEP Operational Improvement
Regional Forecast Improvement
Pressure RainfallNOAA Hurricane Center
Saharan Air Layer Hurricane Suppression
AIRS Research Validates Models
6 hrs on 6 day forecast
J. Fu, U of Hawaii
J. Dunion, NOAAB. Zavodsky, NASA SPoRT
J. LeMarshall, JCSDA
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AIRS Finds Biases in Climate Model Moisture & Temperature
• AIRS finds major climate models are too dry below 800 mb in the tropics, and too moist between 300 mb and 600 mb especially in the extra-tropics. (Pierce, John, Gettleman); too cold above.
• Radiance biases of opposite signs in different spectral regions suggests that the apparent good agreement of a climate model's broadband longwave flux and total water with observations may be due to a fortuitous cancellation of spectral errors (Huang).
1. Pierce D. W., T. P. Barnett, E. J. Fetzer, P. J. Gleckler (2006), Three-dimensional tropospheric water vapor in coupled climate models compared with observations from the AIRS satellite system, Geophys. Res. Lett., 33, L21701, doi:10.1029/2006GL027060.
2. John, V.O. and Soden, B. J., Temperature and humidity biases in global climate models and their impact on climate feedbacks, Geophys.Res. Lett., 34, L18704, doi:10.1029/2007GL030429
3. Gettleman, Collins, Fetzer, Eldering, Irion (2006), “Climatology of Upper-Tropospheric Relative Humidity from the Atmospheric Infrared Sounder and Implications for Climate”, J. Climate, 19, 6104-6121. DOI: 10.1175/JCLI3956.1
4. Huang, Y., Ramaswamy, V., Huang, X.L., Fu, Q., Bardeen, C., A strict test in climate modeling with spectrally resolved radiances: GCM simulation versus AIRS observations, Geophys. Res. Lett., 2007, 34, 24, L24707
Water Vapor Vertical Climatology
(Pierce, Scripps)
Outgoing Longwave Radiation(Huang, Univ. of Michigan)
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
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AIRS H2O Data used as “Truth” toImprove Parameterizations in Climate Models
• Tim Barnett: Scripps, UCSD– Coupled Climate Models show >50%
bias errors in H2O vapor. Models worst at mid altitude and mid latitude.
• Andrew Gettleman: NCAR– AIRS can provide insight on climate
forcings– Variability not well reproduced in
GCM/CAMS – Greenhouse effect appears to
increase with SST– Water vapor feedback positive: but
not as positive as constant RH would assume
• Andrew Dessler: Texas A&M– Simple trajectory model with fixed
RH limit does a good job of reproducing AIRS annual average water vapor
– Model shows that dehydration of mid-troposphere air occurs in three latitude bands
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National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
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Atmospheric Composition:Influence of Madden-Julian Oscillation on AIRS CO2
Contour line: TRMM Rain
AIRS CO2 data are modulated by the Madden-Julian Oscillation. The peak-to-peak amplitude of the MJO signal is ~ 1 ppm.
Li et al. [PNAS, 2010]
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
Current AIRS Status-- What are the deficiencies?-- What improved information is needed by the user?
• Full utilization of existing data. Specifically:– Cloudy scenes (and cloud information) into forecasts.– Constituents
• Sulfur dioxide (volcanoes).• Dust (aerosols).• HDO (hydrologic cycle)• Ammonia (nitrogen cycle; aerosols).• Etc…
• Improved spatial resolution
• Improved spectral coverage
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National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
Information from AIRS Retrievals in Cloudy RegionsImproves Tropical Cyclone Forecast
5 of the 7 forecasts’error at landfall is
less than 50km
No CycloneGood landfall locationGood landfall timing
AIRS Vis Image: Nargis, May 1, 2008
Reale, O., W. K. Lau, J. Susskind, E. Brin, E. Liu, L. P. Riishojgaard, M. Fuentes, and R. Rosenberg (2009), AIRS impact on the analysis and forecast track of tropical cyclone Nargis in a global data assimilation and forecasting system, Geophys. Res. Lett., 36, L06812, doi:10.1029/2008GL037122.http://www.agu.org/journals/gl/gl0906/2008GL037122/
Major Impact to Tropical Cyclone Nargis Hindcast
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
• Full utilization of existing data. Specifically:– Constituents
• Sulfur dioxide (volcanoes).• Dust (aerosols).• HDO (hydrologic cycle)• Ammonia (nitrogen cycle; aerosols).• Etc…
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Gangale, G., A. J. Prata, and L. Clarisse (2009), The infrared spectral signature of volcanic ash determined from high-spectral resolution satellite measurements, Remote Sensing of Environment, 114(2), 414-425.
Current AIRS Status-- What are the deficiencies?-- What improved information is needed by the user?
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
• Improved horizontal resolution.
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Current AIRS Status-- What are the deficiencies?-- What improved information is needed by the user?
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
Horizontal resolution needs driven by rapid improvements in global models.
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Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
Higher Spatial Resolution will Improve Process Studies of Clouds and
Water Vapor
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Current (AIRS)
Water Vapor
15 km
50 km
Bretherton et al (2004)
Sub Gridscale Resolution Needed to Constrain Cloud Physics
Parameterizations
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
Expect Improvement in Boundary Layer Accuracy and Yield over
Land with Higher Spatial Resolution
Joel Susskind, 2008
Land cases limited by inadequate surface emissivity knowledge.
One Month August 2005 Cloud-
cleared
AIRS(Hyperspectra
l)
One Month August August 2003
Cloud-Free Scenes
MODIS (Broadband)
50x50 km
ν = 1095 cm-1
5x5 km
ν = 1205 cm-1
S. Hook (JPL)
T. Pagano (JPL)
AIRS Yield and Accuracy Degrade Near Land
Surface
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
Fine Scale Structure Cumulus Boundary Layers Needed for Improved
Models
Small values of cloud cover ~ 5-30%
Stevens et al (2006)
Low cloud cover, deeper boundary layers and smoother vertical structures More detailed information from IR/MW sounding
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
IR sounding and cumulus boundary layer vertical structure: AIRS and
RICO experiment
19AIRS Support Product provides realistic info on vertical structure
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Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
• Improved spectral coverage– Carbon monoxide– Methane 3.33 micron band.
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Current AIRS Status-- What are the deficiencies?-- What improved information is needed by the user?
National Aeronautics and Space Administration
Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadena, California
Conclusions
• Much work has been done with AIRS– Reflected in ~400 publications in
• Weather.• Climate.• Atmospheric Composition.
• More to do– Exploit cloudy scenes in forecasts.– Extract more information about structure and
composition.
• The Future– Current and planned sounders will not keep up with
rapid improvements in model resolution.
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