Single-footprint retrievals of temperature, water vapor and cloud properties from AIRS

Irion, F. W.; Kahn, Brian H.; Schreier, M. M.; Fetzer, Eric J.; Fishbein, Evan; Fu, Dejian; Kalmus, P.; Wilson, R. C.; Wong, Sun; Yue, Qing

doi:10.5194/amt-11-971-2018

Cited by 50 publications

(48 citation statements)

References 55 publications

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“…There are retrieval methods that attempt to directly solve for clouds using single footprint infrared radiances [68,69] but these are experimental at best and do not quantify or propagate cloud uncertainty rigorously enough for ECVs at global scales. The CLIMCAPS inversion system, instead, adopts a "cloud clearing" approach, which was developed in the 1970s [70][71][72] and is still operational today [2,29].…”

Section: Cloud Clearingmentioning

confidence: 99%

Uncertainty Characterization and Propagation in the Community Long-Term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS)

2019

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The Community Long-term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS) retrieves multiple Essential Climate Variables (ECV) about the vertical atmosphere from hyperspectral infrared measurements made by the Atmospheric InfraRed Sounder (AIRS, 2002–present) and its successor, the Cross-track Infrared Sounder (CrIS, 2011–present). CLIMCAPS ECVs are profiles of temperature and water vapor, column amounts of greenhouse gases (CO2, CH4), ozone (O3) and precursor gases (CO, SO2) as well as cloud properties. AIRS (and CrIS) spectral measurements are highly correlated signals of many atmospheric state variables. CLIMCAPS inverts an AIRS (and CrIS) measurement into a set of discrete ECVs by employing a sequential Bayesian approach in which scene-dependent uncertainty is rigorously propagated. This not only linearizes the inversion problem but explicitly accounts for spectral interference from other state variables so that the correlation among ECVs (and their uncertainty) may be minimized. Here, we outline the CLIMCAPS retrieval methodology with specific focus given to its sequential scene-dependent uncertainty propagation system. We conclude by demonstrating continuity in two CLIMCAPS ECVs across AIRS and CrIS so that a long-term data record may be generated to study the feedback cycles characterizing our climate system.

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Section: Cloud Clearingmentioning

confidence: 99%

Uncertainty Characterization and Propagation in the Community Long-Term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS)

2019

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“…Kahn et al 2008;Posselt et al, 2008), systematic uncertainties and approximations taken in the forward model (e.g. Wang et al, 2016;Irion et al, 2018), and instrument calibration drift (e.g. Pagano et al, 2012;Yue et al, 2017a;Manning and Aumann, 2017).…”

Section: Introductionmentioning

confidence: 99%

Ice cloud microphysical trends observed by the Atmospheric Infrared Sounder

et al. 2018

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Abstract. We use the Atmospheric Infrared Sounder (AIRS) version 6 ice cloud property and thermodynamic phase retrievals to quantify variability and 14-year trends in ice cloud frequency, ice cloud top temperature (T ci ), ice optical thickness (τ i ) and ice effective radius (r ei ). The trends in ice cloud properties are shown to be independent of trends in information content and χ 2 . Statistically significant decreases in ice frequency, τ i , and ice water path (IWP) are found in the SH and NH extratropics, but trends are of much smaller magnitude and statistically insignificant in the tropics. However, statistically significant increases in r ei are found in all three latitude bands. Perturbation experiments consistent with estimates of AIRS radiometric stability fall significantly short of explaining the observed trends in ice properties, averaging kernels, and χ 2 trends. Values of r ei are larger at the tops of opaque clouds and exhibit dependence on surface wind speed, column water vapour (CWV) and surface temperature (T sfc ) with changes up to 4-5 µm but are only 1.9 % of all ice clouds. Non-opaque clouds exhibit a much smaller change in r ei with respect to CWV and T sfc . Comparisons between DARDAR and AIRS suggest that r ei is smallest for singlelayer cirrus, larger for cirrus above weak convection, and largest for cirrus above strong convection at the same cloud top temperature. This behaviour is consistent with enhanced particle growth from radiative cooling above convection or large particle lofting from strong convection.

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“…There is potential in the near future to further enhance the spatial (and possibly vertical) resolution and to otherwise enhance the information content of backtraced profiles via 1) AIRS soundings at 13.5 km resolution that are produced for targeted studies (Irion et al 2018); 2) 3-km HRRR winds to drive HYSPLIT; (Kruskal and Wallis, 1952). ''NO'' symbolizes that the test did not pass (p value .0.05), while ''YES'' symbolizes that the test did pass (p value ,0.05).…”

Section: Discussionmentioning

confidence: 99%

Trajectory-Enhanced AIRS Observations of Environmental Factors Driving Severe Convective Storms

Kalmus

Kahn

Freeman

et al. 2019

Monthly Weather Review

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We investigate environmental factors of severe convective weather using temperature and moisture retrievals from the Atmospheric Infrared Sounder (AIRS) that lie along parcel trajectories traced from tornado, large hail, and severe wind producing events in the central United States. We create AIRS proximity soundings representative of the storm environment by calculating back trajectories from storm times and locations at levels throughout the troposphere, using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model forced with the 32-km North American Regional Reanalysis (NARR) and 12-km North American Mesoscale Forecast System (NAM12). The proximity soundings are calculated for severe weather events including tornadoes, hail ≥2 in. diameter, and wind gusts >65 mph (29 m s−1) specified in the NCEI Storm Events database. Box-and-whisker diagrams exhibit more realistic values of enhanced convective available potential energy (CAPE) and suppressed convective inhibition (CIN) relative to conventional “nearest neighbor” (NN) soundings; however, differences in lifting condensation level (LCL), level of free convection (LFC), and significant tornado parameter (STP) from the HYSPLIT-adjusted back traced soundings are more similar to NN soundings. This methodology should be extended to larger swaths of soundings, and to other operational infrared sounders, to characterize the large-scale environment in severe convective events.

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Single-footprint retrievals of temperature, water vapor and cloud properties from AIRS

Cited by 50 publications

References 55 publications

Uncertainty Characterization and Propagation in the Community Long-Term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS)

Uncertainty Characterization and Propagation in the Community Long-Term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS)

Ice cloud microphysical trends observed by the Atmospheric Infrared Sounder

Trajectory-Enhanced AIRS Observations of Environmental Factors Driving Severe Convective Storms

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