1. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California 1 Uses of AIRS Data for Weather, Climate and Atmospheric Composition Eric Fetzer Jet Propulsion Laboratory / California Institute of Technology Satellite Hyperspectral Sensor Workshop, University of Miami March 29 -31, 2011

2. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California In Memory of Dr. Mous Chahine AIRS Science Team Leader and Friend 2

3. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California AIRS Project Overview Salient Features Spacecraft – Instruments: EOS Aqua – AIRS/AMSU/HSB Launch Date: May 4, 2002 Launch Vehicle: Boeing Delta II, Intermediate ELV Mission Life: 6 years Category:2 Risk Class:A Instruments Operational: August 2002 Team 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, O 3, CO 2, CH 4, SO 2

4. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California AIRS Key Products and Science Areas 4 Atmospheric Water Vapor Ozone Cloud Properties Dust CO Emissivity Methane Atmospheric Temperature CO2 Greenhouse Gas Forcing Cloud and Water Vapor Processes SO2

5. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California ~400 AIRS Peer-Reviewed Publications 5

6. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, 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? 6

7. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California 7 AIRS Improves Weather Operations and Research SAL 4 SAL 3 SAL 2 AEW 1 Polar 1 SAL 1 Irene 5 10 20 15 1 Polar 2 NCEP Operational Improvement Regional Forecast Improvement Pressure Rainfall NOAA Hurricane Center Saharan Air Layer Hurricane Suppression AIRS Research Validates Models 6 hrs on 6 day forecast J. Fu, U of Hawaii J. Dunion, NOAA B. Zavodsky, NASA SPoRT J. LeMarshall, JCSDA

8. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California 8 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)

9. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California 9 AIRS H 2 O Data used as “Truth” to Improve 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

10. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California 10 Atmospheric Composition: Influence of Madden-Julian Oscillation on AIRS CO 2 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]

11. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, 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 11

12. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Information from AIRS Retrievals in Cloudy Regions Improves Tropical Cyclone Forecast 5 of the 7 forecasts’ error at landfall is less than 50km No Cyclone Good landfall location Good 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

13. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Full utilization of existing data. Specifically: – Constituents Sulfur dioxide (volcanoes). Dust (aerosols). HDO (hydrologic cycle) Ammonia (nitrogen cycle; aerosols). Etc… 13 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?

14. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Improved horizontal resolution. 14 Current AIRS Status -- What are the deficiencies? -- What improved information is needed by the user?

15. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Horizontal resolution needs driven by rapid improvements in global models. 15

16. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Higher Spatial Resolution will Improve Process Studies of Clouds and Water Vapor 16 Current (AIRS) Water Vapor 15 km 50 km Bretherton et al (2004) Sub Gridscale Resolution Needed to Constrain Cloud Physics Parameterizations

17. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, 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 (Hyperspectral) 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

18. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, 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

19. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California IR sounding and cumulus boundary layer vertical structure: AIRS and RICO experiment 19 AIRS Support Product provides realistic info on vertical structure

20. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Improved spectral coverage – Carbon monoxide – Methane 3.33 micron band. 20 Current AIRS Status -- What are the deficiencies? -- What improved information is needed by the user?

21. National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, 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. 21