Significant Findings

AIRS data contributed to these significant findings in climate variability and change. They are organized by focus area and time period and only periodically updated.

Climate Variability and Trends
Climate Model and Reanalysis Validation
Climate Processes
Internal Gravity Waves
Various Climate Topics

Climate Variability and Trends

Findings from 2017–2019

Ground-based GNSS measurements are used to assess the quality of satellite-based total column water vapor from MODIS, AIRS and SCIAMACHY in the Arctic. Among all the satellite data, AIRS shows the best agreement with GNSS time series.

Alraddawi, D., Sarkissian, A., Keckhut, P., Bock, O., Noël, S., Bekki, S., Irbah, A., Meftah, M., and Claud, C.: Comparison of total water vapour content in the Arctic derived from GNSS, AIRS, MODIS and SCIAMACHY, Atmos. Meas. Tech., 11, 2949-2965, https://doi.org/10.5194/amt-11-2949-2018, 2018.

With 15 years of tropical AIRS observations, the probability of the deep convective cloud process as a function of sea surface temperature is derived. Based on this, the frequency of extreme deep convection will increase about 21% per 1 K of warming of the tropical oceans.

Aumann, H. H., Behrangi, A., & Wang, Y. (2018). Increased Frequency of Extreme Tropical Deep Convection: AIRS Observations and Climate Model Predictions. Geophysical Research Letters, 45. https://doi.org/10.1029/2018GL079423.

An innovative approach is presented to estimate vapor flux on the Greenland ice sheet, using AIRS skin temperature, air temperature, relative humidity and geopotential height.

Boisvert, L. N., J. N. Lee, J. T. M. Lenaerts, B. Noël, M. R. van den Broeke, and A. W. Nolin (2016), Using remotely sensed data from AIRS to estimate the vapor flux on the Greenland ice sheet: Comparisons with observations and a regional climate model, J. Geophys. Res. Atmos., 122, doi:10.1002/2016JD025674.

Variability of temperature and specific humidity across length-scales is derived in terms of power law scaling exponents, using AIRS profiles. A novel Monte-Carlo approach for variance scaling yields insights into scale-dependent behavior and processes within individual tropical and extratropical systems.

Dorrestijn, J., Kahn, B. H., Teixeira, J., and Irion, F. W.: Instantaneous variance scaling of AIRS thermodynamic profiles using a circular area Monte Carlo approach (2018) Atmos. Meas. Tech., 11, 2717-2733. https://doi.org/10.5194/amt-11-2717-2018.

AIRS thermodynamic-phase and ice cloud property retrievals are characterized with respect to different cloud scenes that are classified using CloudSat observations.

Guillaume, A., Kahn, B. H., Fetzer, E. J., Yue, Q., Manipon, G. J., Wilson, B. D., & Hua, H. (2019), Footprint-scale cloud type mixtures and their impacts on Atmospheric Infrared Sounder cloud property retrievals, Atmospheric Measurement Techniques, 12(8), 4361-4377. https://doi.org/10.5194/amt-12-4361-2019

Response of the lower troposphere to Water Vapor Intrusions into the Arctic is estimated with NASA’s A-Train satellite data, including AIRS temperature profiles. The intrusions are associated with a surface warming of 5.3 K (2.3 K) in winter (summer), lead to additional cloud radiative heating and weaken stability in the lower troposphere, preconditioning accelerated ice melt in the Arctic.

Johansson, E., A. Devasthale, M. Tjernstrom, A. M. L. Ekman, and T. L'Ecuyer (2017), Response of the lower troposphere to moisture intrusions into the Arctic, Geophysical Research Letters, 44(5), 2527-2536. https://dx.doi.org/10.1002/2017gl072687.

Combined reanalysis and satellite data sets, including AIRS, reveal global-scale patterns of subtropical marine boundary layer clouds.

Kahn, B. H., G. Matheou, Q. Yue, T. Fauchez, E. J. Fetzer, M. Lebsock, J. Martins, M. M. Schreier, K. Suzuki, and J. Teixeira (2017), An A-train and MERRA view of cloud, thermodynamic, and dynamic variability within the subtropical marine boundary layer, Atmos. Chem. Phys., 17, 9451–9468, https://doi.org/10.5194/acp-17-9451-2017.

The Atmospheric Infrared Sounder (AIRS) satellite instrument shows statistically significant global trends in ice cloud properties between September 2002 and August 2016.

Kahn, B. H., H. Takahashi, G. L. Stephens, Q. Yue, J. Delanoë, G. Manipon, E. M. Manning, and A. J. Heymsfield (2018), Ice cloud microphysical trends observed by the Atmospheric Infrared Sounder, Atmospheric Chemistry and Physics, 18(14), 10715-10739. https://www.atmos-chem-phys.net/18/10715/2018/

Trends in AIRS zonal mean stratospheric temperature are compared with Radio Occultation and reanalysis data and causes of discrepancies identified.

Leroy, S. S., Ao, C. O., & Verkhoglyadova, O. P. (2018), Temperature Trends and Anomalies in Modern Satellite Data: Infrared Sounding and GPS Radio Occultation, Journal of Geophysical Research-Atmospheres, 123(20), 11431-11444. https://doi.org/10.1029/2018jd028990.

AIRS, MODIS and reanalysis data are used to compute the dependence of the observed variability of Low Cloud Cover (LCC) on various predictor variables. Increasing sea surface temperature and drying of the free troposphere are associated with a decrease in LCC. Increased estimated inversion strength is associated with increased LCC.

McCoy, D. T., R. Eastman, D. L. Hartmann, and R. Wood (2017), The change in low cloud cover in a warmed climate inferred from AIRS, MODIS, and ERA-interim, Journal of Climate, 30(10), 3609-3620. https://dx.doi.org/10.1175/JCLI-D-15-0734.1.

Building a long-term climate record of the earth’s thermal emission spectra from similar hyperspectral infrared sounders, relies on the translation of channel radiances from one sounder to another. A novel deconvolution-based method for AIRS-to-CrIS translation is shown to be more accurate than conventional interpolation or regression.

Motteler, H. E., & Strow, L. L. (2018), AIRS Deconvolution and the Translation of AIRS-to-CrIS Radiances With Applications for the IR Climate Record. https://doi.org/10.1109/TGRS.2018.2869170.

Optimal fingerprinting is applied to AIRS and AMSU-A data from 2003-2012, to detect decadal changes in stratospheric temperature and carbon dioxide that are unexplained by natural variability within 2σ uncertainty. Cooling rates are estimated in five stratospheric layers.

Pan, F., X. Huang, S.S. Leroy, P. Lin, L.L. Strow, Y. Ming, and V. Ramaswamy, 2017: The Stratospheric Changes Inferred from 10 Years of AIRS and AMSU-A Radiances. J. Climate, 30, 6005–6016, https://doi.org/10.1175/JCLI-D-17-0037.1

AIRS near-surface air temperature and specific humidity is calibrated against buoy data and used with other observations to construct a data set on daily radiative and turbulent heat fluxes over the Indian Ocean. This is used to study subseasonal variability in the tropical Indian Ocean.

Parampil, S. R., G. N. Bharathraj, M. Harrison, and D. Sengupta (2016), Observed subseasonal variability of heat flux and the SST response of the tropical Indian Ocean, Journal of Geophysical Research-Oceans, 121(10), 7290-7307. https://dx.doi.org/10.1002/2016jc011948.

For the first time, observational trends of spectrally resolved radiative flux across the entire long-wave spectrum in the Arctic are examined using 14 years of AIRS and CERES observations. Results support previous findings that the Arctic climate is shifting to a warmer and wetter state, and highlight the need to understand the changes in each season separately instead of a simple examination of annual mean statistics.

Peterson, C. A., Chen, X., Yue, Q., & Huang, X. (2019), The Spectral Dimension of Arctic Outgoing Longwave Radiation and Greenhouse Efficiency Trends From 2003 to 2016, Journal of Geophysical Research. Atmospheres, 124(15), 8467-8480. https://doi.org/10.1029/2019JD030428

AIRS temperature and humidity profiles are used to study the evolution of the summer intra-seasonal oscillation in the Bay of Bengal. Association of temperature and humidity anomalies with phases of the evolution and ocean temperatures from GODAS analysis, shows an active role of subsurface ocean temperatures on the intra-seasonal time scale.

Rahaman, H., Bharath Raj, G. N., & Ravichandran, M. (2019), Coupled Ocean–Atmosphere Summer Intraseasonal Oscillation over the Bay of Bengal, Pure & Applied Geophysics, 1-15. https://doi.org/10.1007/s00024-019-02275-4

Minimum detection times (MDT) for global and regional precipitable water vapor (PWV) trends are estimated, combining predicted GCM trends over 2000-2100 with uncertainty estimates from AIRS and IASI. The median value of PWV has an MDT of 15 years or less over all scales, while extreme dry and wet PWV conditions have higher measurement uncertainty and corresponding larger MDTs.

Roman, J., R. Knuteson, S. Ackerman, and H. Revercomb (2016), Estimating Minimum Detection Times for Satellite Remote Sensing of Trends in Mean and Extreme Precipitable Water Vapor, Journal of Climate, 29(22), 8211-8230. https://dx.doi.org/10.1175/jcli-d-16-0303.1.

AIRS data are included in the GEWEX archive of water vapor products which is used to quantify the current state of the art in water vapour products being constructed for climate applications and to support the selection process of suitable water vapour products for production of globally consistent water and energy cycle products.

Schröder, M., Lockhoff, M., Fell, F., Forsythe, J., Trent, T., Bennartz, R., Borbas, E., Bosilovich, M. G., Castelli, E., Hersbach, H., Kachi, M., Kobayashi, S., Kursinski, E. R., Loyola, D., Mears, C., Preusker, R., Rossow, W. B., and Saha, S.: The GEWEX Water Vapor Assessment archive of water vapour products from satellite observations and reanalyses, Earth Syst. Sci. Data, 10, 1093-1117,2018 https://doi.org/10.5194/essd-10-1093-2018

AIRS thermodynamic profiles, skin temperature and outgoing longwave radiation are used to study the climate over the summer Arctic. A relationship is identified between large‐scale circulation variability and changing cloud properties permitting longwave radiation at both the surface and top of the atmosphere to respond to variability in atmospheric thermodynamics. Driven by anomalous advection of warm air, the corresponding enhanced OLR cooling signal on monthly time scales represents an important buffer to regional Arctic warming.

Sedlar, J., and M. Tjernström (2017), Clouds, warm air, and a climate cooling signal over the summer Arctic, Geophys. Res. Lett., 44, doi:10.1002/ 2016GL071959

Global cloud climatologies are built from 13 years of AIRS and 8 years of IASI observations. Infrared sounders are found to be particularly advantageous to retrieve upper-tropospheric cloud properties, with a reliable cirrus identification, day and night.

Stubenrauch, C. J., Feofilov, A. G., Protopapadaki, S. E., and Armante, R.: Cloud climatologies from the infrared sounders AIRS and IASI: strengths and applications, Atmos. Chem. Phys., 17, 13625-13644, https://doi.org/10.5194/acp-17-13625-2017, 2017.

AIRS and other infrared sounding measurements are used to recalibrate infrared and water vapor channels of instruments onboard the historical geostationary satellites of the Japan Meteorological Agency.

Tabata, T., John, V. O., Roebeling, R. A., Hewison, T., & Schulz, J. (2019), Recalibration of over 35 years of infrared and water vapor channel radiances of the JMA geostationary satellites, Remote Sensing, 11(10). https://doi.org/10.3390/rs11101189

Findings from 2006–2016

Finding of a repeatable annual cycle in relative humidity over the polar continent and super saturation with respect to ice, particularly in winter, where it might occur almost half the time in the troposphere. This may affect the quantity and isotopic composition of ice over Antarctica.

Gettelman, A., V. P. Walden, L. M. Miloshevich, W. L. Roth, and B. Halter (2006), Relative humidity over Antarctica from radiosondes, satellites, and a general circulation model, J. Geophys. Res., 111, D09S13, doi:10.1029/2005JD006636

Climate Model and Reanalysis Validation

Findings from 2017–2019

AIRS spectral radiances are used to find a wet bias in the free troposphere in both ERA-Interim and MERRA reanalysis profiles.

Chen, X. H., Huang, X. L., Dong, X. Q., Xi, B. K., Dolinar, E. K., Loeb, N. G., et al. (2018), Using AIRS and ARM SGP Clear-Sky Observations to Evaluate Meteorological Reanalyses: A Hyperspectral Radiance Closure Approach, Journal of Geophysical Research-Atmospheres, 123(20), 11720-11734. https://doi.org/10.1029/2018jd028850.

AIRS/AMSU-A surface temperature data is used with station measurements to find that surface and near-surface temperatures from MERRA-2 reanalysis show improvements over MERRA temperatures.

Hearty, T.J., J.N. Lee, D.L. Wu, R. Cullather, J.M. Blaisdell, J. Susskind, and S.M. Nowicki, 2018: Intercomparison of Surface Temperatures from AIRS, MERRA, and MERRA-2 with NOAA and GC-Net Weather Stations at Summit, Greenland. J. Appl. Meteor. Climatol., 57, 1231¬1245, https://doi.org/10.1175/JAMC-D-17-0216.1

Monthly mean tropospheric air temperature, specific and relative humidity products are included in a new AIRS Obs4MIPs dataset for use in the evaluation of state-of-the-art climate models. The new dataset updates and extends the previous version and adds relative humidity.

Tian, B., E. J. Fetzer, and E. M. Manning, 2019: The Atmospheric Infrared Sounder Obs4MIPs version 2 data set, Earth and Space Science, 6, https://doi.org/10.1029/2018EA000508.

AIRS brightness temperatures are used with other satellite measurements in an evaluation of six stratospheric reanalyses, finding tighter correlation between reanalyses than with observations, and suggesting possible over-tuning.

Wright, C. J., & Hindley, N. P. (2018), How well do stratospheric reanalyses reproduce high-resolution satellite temperature measurements? Atmospheric Chemistry And Physics, 18(18), 13703-13731. https://doi.org/10.5194/acp-18-13703-2018.

Findings from 2006–2015

The AIRS monthly mean tropospheric air temperature and specific humidity products are an essential part of the Obs4MIPs project and were used to evaluate the state-of-the-art climate models from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Based on the AIRS data, the CMIP5 models were found to have a tropospheric cold bias (around 2 K), especially in the extratropical upper troposphere, and a double-ITCZ bias in the troposphere from 1000 hPa to 300 hPa, especially in the tropical Pacific. The AIRS water vapor data also help to constrain climate sensitivity and reduce its large uncertainty range in climate models.

Tian, B. (2015), Spread of model climate sensitivity linked to double-Intertropical Convergence Zone bias, Geophys. Res. Lett., 42(10), 4133-4141, https://doi.org/10.1002/2015gl064119.

Tian, B., E. J. Fetzer, B. H. Kahn, J. Teixeira, E. Manning, and T. Hearty (2013), Evaluating CMIP5 models using AIRS tropospheric air temperature and specific humidity climatology, J. Geophys. Res., 118(1), 114-134, 10.1029/2012jd018607.

The existence of radiance biases of opposite signs in different spectral regions suggests that the apparent good agreement of a climate model's broadband longwave flux with observations may be due to a fortuitous cancellation of spectral errors.

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

AIRS moisture fields differ from 6 major climate models such that the models are too dry below 800 mb in the tropics compared with AIRS, and too moist between 300 mb and 600 mb especially in the extra-tropics. This affects model predictions of future climate warming.

John, V.O. and Soden, B. J., (2007), Temperature and humidity biases in global climate models and their impact on climate feedbacks, Geophys.Res. Lett., 34, L18704, doi:10.1029/2007GL030429

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.

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

Climate Processes

Findings from 2017–2019

AIRS temperature and water vapor is used to infer magnitudes of short-term and long-term water vapor feedback and compare to CMIP5 model simulations.

Liu, R., Su, H., Liou, K.-N., Jiang, J. H., Gu, Y., Liu, S. C. & Shiu, C.-J. (2018). An assessment of tropospheric water vapor feedback using radiative kernels. Journal of Geophysical Research: Atmospheres, 123. https://doi.org/10.1002/2017JD027512

Cloud-top phase partitioning observed by AIRS indicates that phase transitions may be driving increases in liquid water path in the poleward half of extratropical cyclones. These increases are important in the context of the negative extratropical shortwave cloud feedback predicted by climate models.

McCoy, D. T., Field, P. R., Elsaesser, G. S., Bodas-Salcedo, A., Kahn, B. H., Zelinka, M. D., et al. (2019), Cloud feedbacks in extratropical cyclones: insight from long-term satellite data and high-resolution global simulations, Atmospheric Chemistry And Physics, 19(2), 1147-1172. https://doi.org/10.5194/acp-19-1147-2019.

The existence of a negative greenhouse effect over the Antarctic Plateau is verified and attributed to unique local climatological conditions--a strong surface-based temperature inversion and scarcity of free tropospheric water vapor.

Sejas, S.A., Taylor, P.C. and Cai, M., 2018: Unmasking the negative greenhouse effect over the Antarctic Plateau. npj Climate and Atmospheric Science, 1(1), p.17. https://www.nature.com/articles/s41612-018-0031-y

Identification of a strong, positive feedback on tropical convection, associated with the short-term climate variations of the El Nino/Southern Oscillation. The feedback is a result of coupled dynamical‐radiative processes that combine to produce intensification of the tropical hydrological cycle that is more than twice that expected from commonly used Clausius-Clapeyron theory.

Stephens, G. L., M. Z. Hakuba, M. Webb, M. Lebsock, Q. Yue, B. H. Kahn, S. Hristova-Veleva, A. Rapp, C. Stubenrauch, G. S. Elsasser, and J. Slingo (2018), Regional intensification of the tropical hydrological cycle during ENSO, Geophys. Res. Lett., 45, https://doi.org/10.1029/2018GL077598

It is shown that tightening of the ascending branch of the Hadley Circulation coupled with a decrease in tropical high cloud fraction is key in modulating precipitation response to surface warming.

Su H, Jiang JH, Neelin JD, Shen TJ, Zhai C, Yue Q, Wang Z, Huang L, Choi YS, Stephens GL, Yung YL. Tightening of tropical ascent and high clouds key to precipitation change in a warmer climate. Nature communications. 2017 Jun 7;8:15771, http://dx.doi.org/10.1038/ncomms15771

AIRS-based tropical Outgoing Longwave Radiation (OLR) shows a decreasing trend between 2003-2013 due to the El Nino-Southern Oscillation. This holds for both daytime and nighttime but the daytime OLR decreases faster.

Su, W. Y., N. G. Loeb, L. S. Liang, N. N. Liu, and C. T. Liu (2017), The El Nino-Southern Oscillation effect on tropical outgoing longwave radiation: A daytime versus nighttime perspective, Journal of Geophysical Research-Atmospheres, 122(15), 7820-7833.https://dx.doi.org/10.1002/2017jd027002.

Multiple datasets, including AIRS effective cloud fraction, are used to show that low clouds increase across a broad expanse of the North Pacific in response to the poleward shift of the midlatitude jet under global warming. This is demonstrated to be primarily driven by anomalous surface temperature advection.

Zelinka, M.D., Grise, K.M., Klein, S.A., Zhou, C., DeAngelis, A.M. and Christensen, M.W., 2018: Drivers of the Low Cloud Response to Poleward Jet Shifts in the North Pacific in Observations and Models. Journal of Climate. doi:10.1175/JCLI-D-18-0114.1, https://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-18-0114.1

Findings from 2006–2016

The transient convective events in the Asian summer monsoon anticyclone are associated with the vertical transport of low ozone and high water vapor into the upper troposphere-lower stratosphere region.

Randel W. J., M. Park (2006), Deep convective influence on the Asian summer monsoon anticyclone and associated tracer variability observed with Atmospheric Infrared Sounder (AIRS), J. Geophys. Res., 111, D12314, doi:10.1029/2005JD006490.

Madden-Julian Oscillation

Findings from 2006-2018

Discovery of the Madden-Julian Oscillation (MJO) signal in tropical mid-tropospheric CO2 and its dynamical cause. Large-scale variations in tropical CO2, determined from AIRS retrievals, are modulated by the MJO. The correlation structure between CO2, rainfall, and vertical velocity indicate that positive (negative) anomalies in CO2 arise due to upward (downward) large-scale vertical motions in the lower troposphere associated with the MJO. These findings can help to elucidate how various processes can organize, transport, and mix CO2, and they provide a robustness test for coupled carbon-climate models.

Li, K.-F. (2018), An Intraseasonal Variability in CO₂Over the Arctic Induced by the Madden-Julian Oscillation. https://dx.doi.org/10.1002/2017GL076544.

Li, K. F., B. Tian, D. E. Waliser, and Y. L. Yung, 2010: Tropical mid-tropospheric CO2 variability driven by the Madden-Julian oscillation, PNAS, 107 (45), 19171- 19175, doi:10.1073/pnas.1008222107.

Discovery of a trimodal temperature vertical structure and a low-level moisture and temperature preconditioning associated with the Madden-Julian Oscillation (MJO). Discovery of the poor representation of the low-level moisture and temperature structure associated with the MJO in the NCEP/NCAR, NCEP/DOE and ERA-Interim reanalyses which have been widely used as 'true' observations to validate MJO theories and model simulations.

Tian, B., D. E. Waliser, E. J. Fetzer, and Y. L. Yung (2010), Vertical moist thermodynamic structure of the Madden-Julian Oscillation in Atmospheric Infrared Sounder retrievals: An update and a comparison to ECMWF interim re-analysis, Mon. Wea. Rev., 138(12), 4576-4582, 10.1175/2010mwr3486.1.

Tian, B., D. E. Waliser, E. J. Fetzer, B. H. Lambrigtsen, Y. Yung, and B. Wang (2006), Vertical moist thermodynamic structure and spatial-temporal evolution of the MJO in AIRS observations,. J. Atmos. Sci., 63, 2462-2485 (2006). DOI: 10.1175/JAS3782.1

Discovery of the Madden-Julian Oscillation (MJO) signal in tropical total-column ozone and its dynamical cause.

Tian B., Y. L. Yung, D. E. Waliser, T. Tyranowski, L. Kuai, E. J. Fetzer, F. W. Irion (2007), Intraseasonal variations of the tropical total ozone and their connection to the Madden-Julian Oscillation, Geophys. Res. Lett., 34, L08704, doi:10.1029/2007GL029451.

Internal Gravity Waves

Findings from 2017-2019

Model experiments suggest that stratospheric long vertical wavelength gravity waves, revealed by AIRS brightness temperature variations, follow precipitation sources of the Madden-Julian Oscillation, and drive intraseasonal stratospheric zonal wind anomalies through drag effects.

Alexander M.J., A.W. Grimsdell, C.C. Stephan, and L. Hoffmann(2017), MJO-related intraseasonal variation in the stratosphere: Gravity waves and zonal winds, J. Geophys. Res., 122, doi:https://doi.org/10.1002/2017JD027620.

Using five years of AIRS brightness temperature measurements with other sources, it is concluded that convective activity to the west of the Great Lakes is the dominant source of gravity waves over the central and eastern United States, both at ground level and in the stratosphere.

de Groot-Hedlin, C. D., Hedlin, M. A. H., Hoffmann, L., Joan Alexander, M. & Stephan, C. C. (2017). Relationships between Gravity Waves Observed at Earth's Surface and in the Stratosphere over the Central and Eastern United States. Journal of Geophysical Research: Atmospheres, 122. https://doi.org/10.1002/2017JD027159.

Gravity wave momentum flux vectors are derived from AIRS temperature data. Resulting distributions of wave amplitudes and momentum fluxes highlight the importance of gravity waves in the polar vortex and the summertime subtropics.

Ern, M., L. Hoffmann, and P. Preusse (2017), Directional gravity wave momentum fluxes in the stratosphere derived from high-resolution AIRS temperature data. http://dx.doi.org/10.1002/2016GL072007.

13.5 years of AIRS observations of stratospheric gravity waves along with tropical cyclone data, provide evidence that stratospheric gravity wave activity is associated with the intensification of tropical cyclones, and may become an important future indicator of storm intensification.

Hoffmann L., X. Wu, and M.J. Alexander (2018), Satellite Observations of Stratospheric Gravity Waves Associated with the Intensification of Tropical Cyclones, Geophys. Res. Lett., 44, https://doi.org/10.1002/2017GL076123.

A record of gravity wave activity in the lower stratosphere is introduced, based on AIRS brightness temperature variances from 2003-2012, revealing a strong seasonal cycle, wave sources and triggering of polar stratospheric cloud formation.

Hoffmann, L., R. Spang, A. Orr, M. J. Alexander, L. A. Holt, and O. Stein (2017), A decadal satellite record of gravity wave activity in the lower stratosphere to study polar stratospheric cloud formation, Atmospheric Chemistry and Physics, 17(4), 2901-2920. http://dx.doi.org/10.5194/acp-17-2901-2017.

AIRS observations are used to validate gravity waves in GEOS-5 high-resolution climate model simulations.

Holt, L. A., M. J. Alexander, L. Coy, C. Liu, A. Molod, W. Putman, and S. Pawson (2017), An evaluation of gravity waves and gravity wave sources in the Southern Hemisphere in a 7 km global climate simulation, Quarterly Journal of the Royal Meteorological Society, 143(707), 2481-2495. https://dx.doi.org/10.1002/qj.3101.

Gravity wave observations based on AIRS brightness temperature are used in a case study, focusing on gravity waves generated by a small island.

Jackson, D.R., A. Gadian, N.P. Hindley, L. Hoffmann, J. Hughes, J. King, T. Moffat-Griffin, A.C. Moss, A.N. Ross, S.B. Vosper, C.J. Wright, and N.J. Mitchell, 2018: The South Georgia Wave Experiment: A Means for Improved Analysis of Gravity Waves and Low-Level Wind Impacts Generated from Mountainous Islands. Bull. Amer. Meteor. Soc., 99, 1027–1040, https://doi.org/10.1175/BAMS-D-16-0151.1

Two events with stratospheric trailing gravity waves over New Zealand, revealed by AIRS measurements, are examined.

Jiang, Q., J.D. Doyle, S.D. Eckermann, and B.P. Williams (2019), Stratospheric Trailing Gravity Waves from New Zealand, J. Atmos. Sci., 76, 1565–1586, https://doi.org/10.1175/JAS-D-18-0290.1

AIRS gravity wave signatures based on brightness temperature perturbation retrievals at 4.3 μm, most sensitive at 30-40 km altitude, agree well with near-coincident but higher altitude measurements from the CIPS instrument. The results suggest the power of combining these measurements to investigate gravity wave filtering and vertical propagation.

Randall, C. E., et al. (2017), New AIM/CIPS global observations of gravity waves near 50–55 km, Geophys. Res. Lett., 44, 7044–7052, https://doi.org/10.1002/2017GL073943.

A strong thunderstorm in Northern China excited a concentric gravity wave. The background conditions, excitation and propagation into the stratosphere and mesosphere are investigated with multiple instruments, with the stratospheric temperature perturbation observed by AIRS.

Wen, Y.; Zhang, Q.; Gao, H.; Xu, J.; Li, Q. (2018). A Case Study of the Stratospheric and Mesospheric Concentric Gravity Waves Excited by Thunderstorm in Northern China. Atmosphere, 9, 489. https://doi.org/10.3390/atmos9120489

A novel spectral analysis technique, applied to AIRS temperature data over 20-60 km altitude, provides a 3-D view of many gravity wave properties. They include height/direction-resolved momentum fluxes, and phase and group velocity vectors, never previously measured from an individual satellite instrument. The method is demonstrated on the region around the Southern Andes and Antarctic Peninsula.

Wright, C. J., N. P. Hindley, L. Hoffmann, M. J. Alexander, and N. J. Mitchell (2017), Exploring gravity wave characteristics in 3-D using a novel S-transform technique: AIRS/Aqua measurements over the Southern Andes and Drake Passage, Atmospheric Chemistry and Physics, 17(13), 8553-8575. http://dx.doi.org/10.5194/acp-17-8553-2017.

The first comprehensive satellite analysis of gravity wave propagation generated by a. hurricane event from the troposphere through the stratosphere and mesosphere into the ionosphere, includes multiple AIRS-derived stratospheric gravity wave signals from hurricane Matthew. The analysis shows significant dynamical coupling between the troposphere and the entire middle and upper atmosphere via the gravity waves.

Xu, S., Yue, J., Xue, X. H., Vadas, S. L., Miller, S. D., Azeem, I., et al. (2019), Dynamical Coupling Between Hurricane Matthew and the middle to Upper Atmosphere via Gravity Waves, Journal of Geophysical Research-Space Physics, 124(5), 3589-3608. https://doi.org/10.1029/2018ja026453

Findings from 2006-2016

AIRS provides global observational constraints on fast internal gravity wave in the middle atmosphere, complementing data from a variety of other sources. These gravity waves, with their high vertical group velocities, are important in the momentum budget of the stratosphere and mesosphere.

Alexander, J. and C. Barnet 2007. Using satellite observations to constrain parameterizations of gravity wave effects for global models. J. Atmos. Sci. v.64 p.1652-1665.

Various Climate Topics

Findings from 2003–2013

These studies used the AIRS data to show that surface warming leads to an increase in water vapor. This water vapor acts as a greenhouse gas and amplifies the surface warming. The AIRS observations are also consistent with warming predicted by numerical climate models, increasing confidence in model predictions of future warming.

Dessler, A. E., Z. Zhang, and P. Yang (2008), Water-vapor climate feedback inferred from climate fluctuations, 2003'2008, Geophys. Res. Lett., 35, L20704, doi:10.1029/2008GL035333.

Gettelman, A., and Q. Fu, 2008: Observed and Simulated Upper-Tropospheric Water Vapor Feedback. J. Climate, 21, 3282'3289.

Discovery of the Madden-Julian Oscillation (MJO) signal in tropical total-column ozone and its dynamical cause.

Discovery of the Madden-Julian Oscillation (MJO) signal in tropical mid-troposheric CO2 and its dynamical cause.

Large-scale variations in tropical CO2, determined from AIRS retrievals, are modulated by the MJO. The correlation structure between CO2, rainfall, and vertical velocity indicate that positive (negative) anomalies in CO2 arise due to upward (downward) large-scale vertical motions in the lower troposphere associated with the MJO. These findings can help to elucidate how various processes can organize, transport, and mix CO2, and they provide a robustness test for coupled carbon-climate models.

Li, K. F., B. Tian, D. E. Waliser, and Y. L. Yung, 2010: Tropical mid-tropospheric CO2 variability driven by the Madden-Julian oscillation, PNAS, 107 (45), 19171- 19175, doi:10.1073/pnas.1008222107.

The onset of the severe thunderstorm activity lags the top-of-atmosphere incident solar flux by about two months, while the sea surface temperature lags by about three months.

Aumann, H.H., Gregorich, D., Broberg, S., Elliott, (2017), D.Seasonal correlations of SST, water vapor, and convective activity in tropical oceans: a new hyperspectral data set for climate modeling. Geophys. Res. Lett., 34, L15813, doi: 10.1029/2006GL029191

AIRS high-resolution spectra provides the first global view of small-particle-dominated cirrus clouds.

Kahn B. H., A. Eldering, S. A. Clough, E. J. Fetzer, E. Fishbein, M. R. Gunson, S.-Y. Lee, P. F. Lester, V. J. Realmuto (2003), Near micron-sized cirrus cloud particles in high-resolution infrared spectra: An orographic case study, Geophys. Res. Lett., 30 (8), 1441, doi:10.1029/2003GL01690

Correlations between ice cloud effective diameter, optical depth, and relative humidity in the tropical upper troposphere, results of which are consistent with many aircraft observations. Suggests that preferred ice crystal habit distributions explain the best-fit model simulations when fit to AIRS radiances.

Kahn, B. H., C. K. Liang, A. Eldering, A. Gettelman, Q. Yue, and K. N. Liou (2008), Tropical thin cirrus and relative humidity observed by the Atmospheric Infrared Sounder, Atmos. Chem. Phys., 8, 1501-1518.

Shows the feasibility of a fast radiative transfer model to retrieve ice cloud effective diameter and optical depth from AIRS radiances. Furthermore, this study shows that the high spectral resolution and coverage of AIRS will help constrain ice crystal size and habit distribution assumptions used in radiative transfer simulations of ice clouds.

Yue, Q., K. N. Liou, S. C. Ou, B. H. Kahn, P. Yang, and G. G. Mace (2007), Interpretation of AIRS data in thin cirrus atmospheres based on a fast radiative transfer model, J. Atmos. Sci. 64, 3827-3842.

AIRS water vapor observations reveal much larger tropospheric moisture perturbations associated with the Boreal Summer Intraseasonal Oscillation (BSISO) than those depicted in previous NCEP reanalysis and ECMWF analysis data sets. The AIRS data also reveal boundary layer moist preconditioning for the BSISO which is absent from conventional NCEP reanalysis.

Fu X., B. Wang, L. Tao (2006), Satellite data reveal the 3-D moisture structure of Tropical Intraseasonal Oscillation and its coupling with underlying ocean, Geophys. Res. Lett., 33, L03705, doi:10.1029/2005GL025074.

Yang, B., X. Fu, and B. Wang (2008), Atmosphere-ocean conditions jointly guide convection of the Boreal Summer Intraseasonal Oscillation: Satellite observations, J. Geophys. Res., 113, D11105, doi:10.1029/2007JD009276.

First demonstration that the local correlation of water vapor and temperature can reach values up to one order of magnitude higher than the Clausius-Clapeyron regime. This works highlight the presence of other mechanisms controlling water vapor, besides local temperature.

Gambacorta, A., C.D. Barnet, B. Soden and L. Strow 2008. An assessment of the tropical humidity-temperature covariance using AIRS. Geophys. Res. Lett. v.35 L10814 doi:10.1029/2008GL033805, 5 pgs.