Significant Science Findings

Weather and Weather Forecasting ›
Climate Variability and Change ›
Atmospheric Composition and Carbon Cycle ›
Air Quality ›


 

Weather and Weather Forecasting


Assimilating even small amounts of AIRS data improves forecast significantly: Less than 1% of AIRS spectra extends the NCEP global 6-day forecast by 6 hours in both hemispheres. AIRS data are now used routinely by major weather forecast centers around the world, including NCEP (US) and ECMWF (Europe).

Le Marshall, J., J. Jung, J. Derber, M. Chahine, R. Treadon, S. J. Lord, M. Goldberg, W. Wolfc, H. C. Liu, J. Joiner, J. Woollen, R. Todling, P. van Delst, and Y. Tahara (2006), "Improving Global Analysis and Forecasting with AIRS", Bulletin of the American Meteorological Society, 87, 891-894, doi: 10.1175/BAMS-87-7-891

McNally, A.P., Watts, P.D., Smith, J.A., Engelen, R., Kelly, G.A., Thepaut, J.N., and Matricardi, M., 2006, The assimilation of AIRS radiance data at ECMWF, QJR Meteorol. Soc., 132, 935-957. doi: 10.1256/qj.04.171

Chahine et al. (2006), 'The Atmospheric Infrared Sounder (AIRS): improving weather forecasting and providing new insights into climate', Bulletin of the American Meteorological Society, 87, 911-926, DOI: 10.1175/BAMS-87-7-911


Assimilation of AIRS retrieved temperature profiles into the FVDAS improves the prediction of the intensity and location of cyclones in the Southern Hemisphere. 

Atlas, R. (2005a), The impact of AIRS data on weather prediction, Proc. SPIE Int. Soc. Opt. Eng., 5806, 599? 606,doi:10.1117/12.602540.


Assimilation of the AIRS Level 2 product into the MM5 model shows that the Saharan Air Layer (SAL) may have delayed the formation of Hurricane Isabel and inhibited the development of another tropical disturbance to the East. 

Wu L., S. A. Braun, J. J. Qu, X. Hao (2006), Simulating the formation of Hurricane Isabel (2003) with AIRS data, Geophys. Res. Lett., 33, L04804, doi:10.1029/2005GL024665.


The assimilation of AIRS derived temperature profiles in partially cloud contaminated areas can significantly increase weather forecast skill in a global model and forecasting system.

Reale, O., J. Susskind, R. Rosenberg, E. Brin, E. Liu, L. P. Riishojgaard, J. Terry, and J. C. Jusem (2008), Improving forecast skill by assimilation of quality-controlled AIRS temperature retrievals under partially cloudy conditions, Geophys. Res. Lett., 35, L08809, doi:10.1029/2007GL033002.

 

Climate Variability and Change


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.


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.

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.

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

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


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


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 


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.


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 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.


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, 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


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.

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.


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.


4-D assimilation of observations from the major humidity observing systems show improvements in simulated wind and temperature fields. AIRS is shown to have an especially significant impact in simulations of the upper troposphere.

Andersson, E., E. Holm, P. Bauer, A. Bejaars, G. A. Kelly, A. P. McNally, A. J. Simmons, J.-N. Thepaut, and A. M. Tompkins (2007), Analysis and forecast impact of the main humidity observing systems. Quart. J. Royal. Met. Soc., 133, 1473-1485.


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.


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.

 

Atmospheric Composition and Carbon Cycle


AIRS retrieved CO2 shows the distribution of middle tropospheric carbon dioxide is strongly influenced by surface source and large-scale circulations such as the mid-latitude jet streams and by synoptic weather systems, most notably in the summer hemisphere.

Chahine, M.T. et al., (2008), Satellite Remote Sounding of Mid-Tropospheric CO2, Geophys. Res. Lett., 35, SEPTEMBER, doi:10.1029/2008GL035022


Detailed, daily global observation of transport of mid-tropospheric carbon monoxide from biomass burning emissions. 

McMillan W. W., C. Barnet, L. Strow, M. T. Chahine, M. L. McCourt, J. X. Warner, P. C. Novelli, S. Korontzi, E. S. Maddy, S. Datta (2005), "Daily global maps of carbon monoxide from NASA's Atmospheric Infrared Sounder", Geophys. Res. Lett., 32, L11801, doi:10.1029/2004GL021821.


First remote retrieval of mid-tropospheric carbon dioxide under cloudy conditions directly from cloud-cleared radiance spectra with an accuracy of 0.43 1.20 ppmv.

Chahine M., C. Barnet, E. T. Olsen, L. Chen, E. Maddy (2005), On the determination of atmospheric minor gases by the method of vanishing partial derivatives with application to CO 2, Geophys. Res. Lett., 32, L22803, doi:10.1029/2005GL024165.


First assimilation of AIRS carbon dioxide as a tracer in a full 4D-Var ECMWF transport model. 

Engelen R. J., A. P. McNally (2005), Estimating atmospheric CO 2 from advanced infrared satellite radiances within an operational four-dimensional variational (4D-Var) data assimilation system: Results and validation, J. Geophys. Res., 110, D18305, doi:10.1029/2005JD005982.


Significant differences between simulated and observed carbon dioxide abundance outside of the tropics, which raises questions about the lower-to-upper troposphere transport pathways in current models. 

Tiwari Y. K., M. Gloor, R. J. Engelen, F. Chevallier, C. Rdenbeck, S. Krner, P. Peylin, B. H. Braswell, M. Heimann (2006), Comparing CO 2 retrieved from Atmospheric Infrared Sounder with model predictions: Implications for constraining surface fluxes and lower-to-upper troposphere transport, J. Geophys. Res., 111, D17106, doi:10.1029/2005JD006681.


AIRS shortwave mid-tropospheric temperature sounding channels can be used to deduce a 2.2 0.4 ppmv/year increase in the carbon dioxide abundance under clear tropical ocean conditions.

Aumann H. H., D. Gregorich, S. Gaiser (2005), AIRS hyper-spectral measurements for climate research: Carbon dioxide and nitrous oxide effects, Geophys. Res. Lett., 32, L05806, doi:10.1029/2004GL021784. 


Inclusion of AIRS SO2 information can improve measurements of volcanic SO2 and ash loading in the troposphere, and to refine our understanding of volcanic cloud composition, structure and evolution. 

Wright,R., Carn,S. A., Flynn,L. P. (2005), A satellite chronology of the May-June 2003 eruption of Anatahan volcano, Journal of Volcanology and Geothermal Research, 146, 102-116. doi: 10.1016/j.jvolgeores.2004.10.021.

 

Air Quality


AIRS carbon monoxide retrievals validate the plume rise mechanism in simulations of the transport of carbon monoxide in the mid-troposphere. 

Freitas S. R., K. M. Longo, M. O. Andreae (2006), Impact of including the plume rise of vegetation fires in numerical simulations of associated atmospheric pollutants, Geophys. Res. Lett., 33, L17808, doi:10.1029/2006GL026608.