Atmospheric Infrared Sounder Radiances Research Articles

Sensitivity of low‐tropospheric Arctic temperatures to assimilation of AIRS cloud‐cleared radiances: Impact on midlatitude waves

AbstractIn this work it is shown that the prediction of individual midlatitude waves in a global forecast framework may benefit from the assimilation of cloud‐cleared radiances (CCRs) from the Atmospheric Infrared Sounder (AIRS). The assimilation of CCRs, relative to clear‐sky radiances, provides more information in high‐latitude areas affected by broken low‐level stratus clouds, which are common over north polar latitudes during the summer and autumn seasons. This added information in cloudy regions produces slightly lower low‐level temperatures and lower mid‐tropospheric heights (through hydrostatic adjustment) over the Arctic and part of northeastern Siberia. In areas that are both dynamically unstable (with the potential for rapid error growth) and data void (as observed by clear‐sky radiances), the assimilation of CCRs provides valuable information that can improve the representation of individual baroclinic waves and their subsequent forecasts. The assimilation of AIRS CCRs slightly modifies the geopotential height gradients between the Arctic and the midlatitudes, leading to improvements in the forecast of individual baroclinic waves, as is shown through three case‐studies. The set of observing system experiments (OSEs) is performed with the NASA Goddard Earth Observing System (GEOS) data assimilation and forecast system during boreal autumn 2014. AIRS CCRs are thinned to approximately one quarter the density of operationally assimilated AIRS radiances, consistent with their higher information content. Global 6‐hourly analyses are produced from 01 September to 10 November 2014 and seven‐day forecasts are initialized at 0000 UTC daily. Since the CCR methodology is widely applicable, these findings are also relevant to other infrared sensors.

Ten Years of Satellite Infrared Radiance Monitoring With the Met Office NWP Model

Satellite sounder infrared radiances are among the most important contributions to the global observing system and have been assimilated into global numerical weather prediction (NWP) analyses for many years. They are also used as fundamental climate data records for climate monitoring. Prior to assimilation or producing climate records, the radiances should have all residual instrument biases removed. One way of estimating the mean biases is to continuously monitor the measured radiances against the NWP model equivalent radiances. This article is an extension of one published in 2012 which documented these biases for three years but now the time span of the monitoring has extended to beyond ten years, allowing the long-term stability of the instruments to be assessed. Data from high-resolution infrared sounder (HIRS), Advanced Along Track Scanning Radiometer (AATSR), and Spinning Enhanced Visible and Infrared Imager (SEVIRI), radiometers; atmospheric infrared sounder (AIRS), a spectrometer; and infrared atmospheric sounding interferometer (IASI), an interferometer, were included. Changes in mean biases and standard deviations were used to investigate the temporal stability of the bias and radiometric noise of the instruments over ten years. A double difference technique was employed to remove the effect of changes or deficiencies in the NWP system and radiative transfer (RT) model, which can contribute to the biases. The IASI and AIRS radiances were stable but with a different bias between the two instruments due to different versions of the RT model used. The SEVIRI radiometers were stable in most channels with the exception of the 13.4 μm channel. The HIRS instruments were subject to sudden changes in bias and increases in standard deviation compared with NWP simulations during the past decade.

Stratospheric Gravity Wave Products from Satellite Infrared Nadir Radiances in the Planning, Execution, and Validation of Aircraft Measurements during DEEPWAVE

AbstractGravity wave perturbations in 15-μm nadir radiances from the Atmospheric Infrared Sounder (AIRS) and Cross-Track Infrared Sounder (CrIS) informed scientific flight planning for the Deep Propagating Gravity Wave Experiment (DEEPWAVE). AIRS observations from 2003 to 2011 identified the South Island of New Zealand during June–July as a “natural laboratory” for observing deep-propagating gravity wave dynamics. Near-real-time AIRS and CrIS gravity wave products monitored wave activity in and around New Zealand continuously within 10 regions of scientific interest, providing nowcast guidance and validation for flight planners. A novel technique used these gravity wave products to validate upstream forecasts of nonorographic gravity waves with 1–2-day lead times, providing time to plan flight intercepts as tropospheric westerlies brought forecast source regions into range. Postanalysis verifies the choice of 15μm radiances for nowcasting, since 4.3-μm gravity wave products yielded spurious diurnal cycles, provided no altitude sensitivity, and proved relatively insensitive to deep gravity wave activity over the South Island. Comparisons of DEEPWAVE flight tracks with AIRS and CrIS gravity wave maps highlight successful repeated vectoring of the aircraft into regions of deep orographic and nonorographic gravity wave activity, and how background winds control the amplitude of waves in radiance perturbation maps. We discuss how gravity wave information in AIRS and CrIS radiances might be directly assimilated into future operational forecasting systems.

Using AIRS and ARM SGP Clear‐Sky Observations to Evaluate Meteorological Reanalyses: A Hyperspectral Radiance Closure Approach

AbstractUsing the ground‐based measurements from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site and spectral radiance from the Atmospheric Infrared Sounder (AIRS) on National Aeronautics and Space Administration Aqua, we evaluate the temperature and humidity profiles from European Center for Medium Range Weather Forecasting ERA‐Interim and Modern‐Era Retrospective analysis for Research and Applications Version 2 reanalyses. Four sets of synthetic AIRS spectra are calculated using 51 clear‐sky sounding profiles from the ARM SGP observations, the collocated AIRS L2 retrievals and the two reanalyses, respectively. A subset of AIRS channels sensitive to temperature, CO2, or H2O but not to other trace gases is chosen and further categorized into different groups according to the peak altitudes of their weighting functions. Synthetic radiances are then compared to the observed AIRS radiances for each group. For all groups, the observed AIRS radiances agree well with the synthetic ones based on the ARM SGP soundings or the AIRS L2 retrievals. The brightness temperature (BT) differences are within ±0.5 K. For two reanalyses, BT differences in all temperature‐sensitive groups are generally within ±0.5 K; but the mean BT differences in all groups sensitive to both T and H2O are negative. Together, they suggest a wet bias in the free troposphere in both reanalyses. Moreover, such BT differences can be seen in the analysis of AIRS clear‐sky radiances over the entire 30–40°N zone. A grid‐search retrieval suggests that 9–30% reduction for reanalysis humidity between 200 and 800 hPa is needed to correct such wet bias.

Assimilation of atmospheric infrared sounder radiances with WRF-GSI for improving typhoon forecast

The Atmospheric Infrared Sounder (AIRS) can provide the profile information on atmospheric temperature and humidity in high vertical resolution. The assimilation of its radiances has been proven to improve the Numerical Weather Prediction (NWP) in global models. In this study, regional assimilation of AIRS radiances was carried out in a community assimilation system, using Gridpoint Statistical Interpolation (GSI) coupled with the Weather Research and Forecasting (WRF) model. The AIRS channel selection, quality control, and radiances bias correction were examined and illustrated for optimized assimilation. The bias correction scheme in the regional model showed that corrections on most of the channels produce satisfactory results except for several land surface channels. The assimilation and forecast experiments were carried out for three typhoon cases (Saola, Damrey, and Haikui in 2012) with and without including AIRS radiances. Results show that the assimilation of AIRS radiances into the WRF/GSI model improves both the typhoon track and intensity in a 72-hour forecast.

Impact of adaptively thinned AIRS cloud-cleared radiances on tropical cyclone representation in a global data assimilation and forecast system.

A simple adaptive thinning methodology for Atmospheric Infrared Sounder (AIRS) radiances is evaluated through a combination of Observing System Experiments (OSEs) and adjoint methodologies. The OSEs are performed with the NASA Goddard Earth Observing System (GEOS, version 5) data assimilation and forecast model. In addition, the adjoint-based forecast sensitivity observation impact technique is applied to assess fractional contributions of sensors in different thinning configurations. The adaptive strategy uses a denser AIRS coverage in a moving domain centered around tropical cyclones (TCs), sparser everywhere else. The OSEs consist of two sets of data assimilation runs that cover the period from September 1st to 10 November 2014, with the first 20 days discarded for spin-up. Both sets assimilate all conventional and satellite observations used operationally. In addition, one ingests clear-sky AIRS radiances, the other cloud-cleared radiances, each comprising multiple thinning strategies. Daily 7-day forecasts are initialized from all these analyses and evaluated with focus on TCs over the Atlantic and the Pacific. Evidence is provided on the effectiveness of this simple TC-centered adaptive radiance thinning strategy, in full agreement with previous theoretical studies. Specifically, global skill increases, and tropical cyclone representation is substantially improved. The improvement is particularly strong when cloud-cleared radiances are assimilated. Finally, the article suggests that cloud-cleared radiances, if thinned more aggressively than the currently used clear-sky radiances, could successfully replace them with large improvements in TC forecasting and no loss of global skill.

Radiance Preprocessing for Assimilation in the Hourly Updating Rapid Refresh Mesoscale Model: A Study Using AIRS Data

Abstract This study describes the initial application of radiance bias correction and channel selection in the hourly updated Rapid Refresh model. For this initial application, data from the Atmospheric Infrared Sounder (AIRS) are used; this dataset gives atmospheric temperature and water vapor information at higher vertical resolution and accuracy than previously launched low-spectral resolution satellite systems. In this preliminary study, data from AIRS are shown to add skill to short-range weather forecasts over a relatively data-rich area. Two 1-month retrospective runs were conducted to evaluate the impact of assimilating clear-sky AIRS radiance data on 1–12-h forecasts using a research version of the National Oceanic and Atmospheric Administration (NOAA) Rapid Refresh (RAP) regional mesoscale model already assimilating conventional and other radiance [AMSU-A, Microwave Humidity Sounder (MHS), HIRS-4] data. Prior to performing the assimilation, a channel selection and bias-correction spinup procedure was conducted that was appropriate for the RAP configuration. RAP forecasts initialized from analyses with and without AIRS data were verified against radiosonde, surface atmosphere, precipitation, and satellite radiance observations. Results show that the impact from AIRS radiance data on short-range forecast skill in the RAP system is small but positive and statistically significant at the 95% confidence level. The RAP-specific channel selection and bias correction procedures described in this study were the basis for similar applications to other radiance datasets now assimilated in version 3 of RAP implemented at NOAA’s National Centers for Environmental Prediction (NCEP) in August 2016.

The Stratospheric Changes Inferred from 10 Years of AIRS and AMSU-A Radiances

Global-mean radiances observed by the Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Sounding Unit A (AMSU-A) are analyzed from 2003 to 2012. The focus of this study is on channels sensitive to emission and absorption in the stratosphere. Optimal fingerprinting is used to obtain estimates of changes of stratospheric temperature in five vertical layers due to external forcing in the presence of natural variability. Natural variability is estimated using synthetic radiances based on the 500-yr GFDL CM3 and 240-yr HadGEM2-CC control runs. The results show a cooling rate of 0.65 ± 0.11 (2 σ) K decade−1 in the upper stratosphere above 6 hPa, approximately 0.46 ± 0.24 K decade−1 in two midstratospheric layers between 6 and 30 hPa, and 0.39 ± 0.32 K decade−1 in the lower stratosphere (30–60 hPa). The cooling rate in the lowest part of the stratosphere (60–100 hPa) is −0.014 ± 0.22 K decade−1, which is smallest among all five layers and statistically insignificant. The synergistic use of well-calibrated passive infrared and microwave radiances permits disambiguation of trends of carbon dioxide and stratospheric temperature, increases vertical resolution of detected stratospheric temperature trends, and effectively reduces uncertainties of estimated temperature trends.

Estimation of Near-Real-Time Outgoing Longwave Radiation from Cross-Track Infrared Sounder (CrIS) Radiance Measurements

AbstractThis study describes the algorithm for deriving near-real-time outgoing longwave radiation (OLR) from Cross-Track Infrared Sounder (CrIS) hyperspectral infrared sounder radiance measurements. The estimation of OLR on a near-real-time basis provides a unique perspective for studying the variability of Earth’s current atmospheric radiation budget. CrIS-derived OLR values are estimated as a weighted linear combination of CrIS-adjusted “pseudochannel” radiances. The algorithm uses the Atmospheric Infrared Sounder (AIRS) as the transfer instrument, and a least squares regression algorithm is applied to generate two sets of regression coefficients. The first set of regression coefficients is derived from collocated Clouds and the Earth’s Radiant Energy System (CERES) OLR on Aqua and pseudochannel radiances calculated from AIRS radiances. The second set of coefficients is derived to adjust the CrIS pseudochannel radiance to account for the differences in pseudochannel radiances between AIRS and CrIS. The CrIS-derived OLR is then validated by using a limited set of available CERES SNPP OLR observations over 1° × 1° global grids, as well as monthly OLR mean and interannual differences against CERES OLR datasets from SNPP and Aqua. The results show that the bias of global CrIS OLR estimation is within ±2 W m−2 and that the standard deviation is within 5 W m−2 for all conditions, and ±1 and 3 W m−2 for homogeneous scenes. The interannual CrIS-derived OLR differences agree well with Aqua CERES interannual OLR differences on a 1° × 1° spatial scale, with only a small drift of the global mean of these two datasets of around 0.004 W m−2.

Deriving clear-sky longwave spectral flux from spaceborne hyperspectral radiance measurements: a case study with AIRS observations

Abstract. Previous studies have shown that longwave (LW) spectral fluxes have unique merit in climate studies. Using Atmospheric Infrared Sounder (AIRS) radiances as a case study, this study presents an algorithm to derive the entire LW clear-sky spectral fluxes from spaceborne hyperspectral observations. No other auxiliary observations are needed in the algorithm. A clear-sky scene is identified using a three-step detection method. The identified clear-sky scenes are then categorized into different sub-scene types using information about precipitable water, lapse rate and surface temperature inferred from the AIRS radiances at six selected channels. A previously established algorithm is then used to invert AIRS radiances to spectral fluxes over the entire LW spectrum at 10 cm−1 spectral interval. Accuracy of the algorithms is evaluated against collocated Clouds and the Earth's Radiant Energy System (CERES) observations. For nadir-view observations, the mean difference between outgoing longwave radiation (OLR) derived by this algorithm and the collocated CERES OLR is 1.52 Wm−2 with a standard deviation of 2.46 Wm−2. When the algorithm is extended for viewing zenith angle up to 45°, the performance is comparable to that for nadir-view results.

A case study of typhoon‐induced gravity waves and the orographic impacts related to Typhoon Mindulle (2004) over Taiwan

AbstractAtmospheric gravity waves (GWs) significantly influence global circulation. Deep convection, particularly that associated with typhoons, is believed to be an important source of gravity waves. Stratospheric gravity waves induced by Typhoon Mindulle (2004) were detected by the Atmospheric Infrared Sounder (AIRS). Semicircular GWs with horizontal wavelengths of 100–400 km were found over Taiwan through an inspection of AIRS radiances at 4.3 μm. Characteristics of the stratospheric gravity waves generated by Typhoon Mindulle were investigated using the Weather Research and Forecasting (WRF) model. The initial and boundary data were determined by the high‐resolution European Center for Medium‐Range Weather Forecasts reanalysis data. The WRF simulation reproduces the main features of Typhoon Mindulle and the significant GWs. The simulated GWs with horizontal wavelengths of 100–400 km match the AIRS observations: they propagate upward and eastward, and the westward components are mostly filtered in the stratosphere. By comparing the measured waves with a WRF simulation in the absent of orography (WRF‐FLAT), we find that the orographic gravity waves (OGWs) generated by the flow of Typhoon Mindulle over the Central Mountain Range (CMR) in Taiwan account for approximately 50% of the total wave momentum flux in the troposphere. The dominant orientation of the OGW wave fronts is parallel to the CMR rideline. When entering into the stratosphere, OGW propagation is determined by the position of the typhoon center relative to the CMR.

Assimilation of thermodynamic information from advanced infrared sounders under partially cloudy skies for regional NWP

AbstractGenerally, only clear‐infrared spectral radiances (not affected by clouds) are assimilated in weather analysis systems. This is due to difficulties in modeling cloudy radiances as well as in observing their vertical structure from space. To take full advantage of the thermodynamic information in advanced infrared (IR) sounder observations requires assimilating radiances from cloud‐contaminated regions. An optimal imager/sounder cloud‐clearing technique has been developed by the Cooperative Institute for Meteorological Satellite Studies at the University of Wisconsin‐Madison. This technique can be used to retrieve clear column radiances through combining collocated multiband imager IR clear radiances and the sounder cloudy radiances; no background information is needed in this method. The imager/sounder cloud‐clearing technique is similar to that of the microwave/IR cloud clearing in the derivation of the clear‐sky equivalent radiances. However, it retains the original IR sounder resolution, which is critical for regional numerical weather prediction applications. In this study, we have investigated the assimilation of cloud‐cleared IR sounder radiances using Atmospheric Infrared Sounder (AIRS)/Moderate Resolution Imaging Spectroradiometer for three hurricanes, Sandy (2012), Irene (2011), and Ike (2008). Results show that assimilating additional cloud‐cleared AIRS radiances reduces the 48 and 72 h temperature forecast root‐mean‐square error by 0.1–0.3 K between 300 and 850 hPa. Substantial improvement in reducing track forecasts errors in the range of 10 km to 50 km was achieved.

One-dimensional variational (1D-Var) retrieval of middle to upper tropospheric humidity using AIRS radiance data

A one-dimensional variational analysis (1D-Var retrieval) of tropospheric humidity was conducted using hyper-spectral radiance data from the Atmospheric Infrared Sounder (AIRS). For the vertical range of the atmosphere between 200 and 600 hPa, the same high-resolution retrieval of humidity profiles as for clear-sky conditions was possible over low clouds if the cloud height was lower than 800 hPa. Global analyses from a global data assimilation system were used for initial profiles, and clear conditions over 800 hPa height were determined from AIRS radiance data. Results of analyses for 50 days of global radiosonde matchup data from 21 December 2008 to 8 February 2009 revealed that our 1D-Var calculations derived humidity profiles were closer to the sonde profiles than those of a global analysis at a height over 600 hPa. Furthermore, the results of 1D-Var retrieval often represented high and supersaturated relative humidity around the supposed ice clouds. The altitudes of the high humidity region agreed with the height of ice clouds that had been detected by CloudSat/CALIPSO. As well as possibly improving the humidity profiles in a numerical model by data assimilation, it is expected that these humidity analyses using AIRS radiance data will provide additional information for the study of ice clouds in the middle to upper troposphere.

Assimilation of clear sky Atmospheric Infrared Sounder radiances in short-term regional forecasts using community models

Regional assimilation experiments of clear-sky Atmospheric Infrared Sounder (AIRS) radiances were performed using the gridpoint statistical interpolation three-dimensional variational assimilation system coupled to the weather research and forecasting model. The data assimilation system and forecast model used in this study are separate community models; it cannot be assumed that the coupled systems work optimally. Tuning was performed on the data assimilation system and forecast model. Components tuned included the background error covariance matrix, the satellite radiance bias correction, the quality control procedures for AIRS radiances, the forecast model resolution, and the infrared channel selection. Assimilation metrics and diagnostics from the assimilation system were used to identify problems when combining separate systems. Forecasts initiated from analyses after assimilation were verified with model analyses, rawinsondes, nonassimilated satellite radiances, and 24 h–accumulated precipitation. Assimilation of clear sky AIRS radiances showed the largest improvement in temperature and radiance brightness temperature bias when compared with rawinsondes and satellite observations, respectively. Precipitation skill scores displayed minor changes with AIRS radiance assimilation. The 00 and 12 coordinated universal time (UTC) forecasts were typically of better quality than the 06 and 18 UTC forecasts, possibly due to the amount of AIRS data available for each assimilation cycle.

Usage of differential absorption method in the thermal IR: A case study of quick estimate of clear-sky column water vapor

The concept of differential absorption has been widely used in UV and shortwave remote sensing. This study explores how to extend such concept to the thermal-IR for fast estimation of the total column water vapor (CWV) from clear-sky IR radiances. Using Atmospheric Infrared Sounder (AIRS) radiances as a case study, double difference of radiances at two pairs of pre-selected AIRS channels can be used to suppress the influence of continuum absorption and to highlight contrasts due to weak water vapor line absorptions. To take emission into account, another two AIRS channels are used as surrogates of surface temperature and lapse rate in the lower troposphere. As a result, a three-dimensional look-up table (LUT) can be constructed based on training data sets. Such LUT enables us a fast estimate of CWV directly from the spectral radiances without any a prior information or formal retrieval. The performance of the method is tested using synthetic AIRS radiances based on reanalysis as well as actual sounding profiles. It is also tested against AIRS L2 cloud-cleared radiances and CWV retrievals. The comparisons show that the mean bias of this method is within ±0.07cm and the root-mean-square fractional error is about 33%.

Simultaneous observations of convective gravity waves from a ground‐based airglow imager and the AIRS satellite experiment

We report the first joint observations of convectively generated gravity waves (GWs) using an OH airglow imager in Colorado and the Atmospheric Infrared Sounder (AIRS) onboard the Aqua satellite. Convective GWs, appearing as concentric rings, are observed over the western Great Plain regions of North America in the evening of 3 June 2008 in the airglow images. Inspecting both weather radars and AIRS radiances at 8.1 µm, strong convective clouds are found near the center of the concentric rings. The AIRS data at 4.3 µm show semicircular GWs with horizontal wavelengths of 60–80 km at 0900 UT, whereas the airglow imager observed circular GWs with horizontal wavelengths of ~44 km and airglow emission perturbation of ~6% at the same geographic location at 0910 UT. Large‐scale GWs (horizontal wavelengths greater than 100 km) emanating northwestward can be seen in both AIRS data and airglow images at different times. The imager observed small‐scale ripples associated with unstable concentric GWs in the mesopause in the early evening. Given that the brightness temperature perturbation of the GWs in the AIRS data is about 0.16 K and assuming that the GWs propagate without dissipation from the stratosphere to the upper mesosphere, the expected airglow emission perturbation caused by the GWs would be 4%–17%. Ray tracing simulations are performed to demonstrate that the GWs seen in AIRS and in the imager were likely excited by the same convective system.

Assimilation of Infrared Radiances in the Context of Observing System Simulation Experiments

AbstractThe Observing System Simulation Experiment (OSSE) capability developed at Environment Canada allows simulation of all observation types currently used operationally as well as future data types. Its infrastructure, based on the operational global data assimilation system used at the Canadian Meteorological Centre, was recently enhanced to conduct data assimilation experiments for two future satellite missions. This study presents a subcomponent of that system, focusing on the assimilation of infrared radiances from the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) instruments. The goal is to realistically simulate the radiance observations and to reproduce statistical characteristics of these data seen in the real system, notably background and analysis departures. Care is taken to emulate the operational quality control procedures leading to the assimilation of clear radiances, which implies radiance simulation for all-sky conditions. It is found that the standard deviation of the Gaussian random perturbation applied to the simulated observations should be close to that of the radiometric noise level for sounding channels in the 13.0–14.5-μm region but that it should be significantly higher for water vapor channels in the 5.5–6.7-μm region. The study also allows evaluation of residual biases linked to cloud contamination. For atmospheric window channels, that bias can reach −0.4 K. It reduces rapidly with peak height of the channel response function. This suggests that improvements are needed in low-cloud detection. The realism of the OSSE is further demonstrated through the shown impact consistency of AIRS and IASI radiance assimilation in forecasts up to 5 days from the separate use of simulated and real observations.

View‐angle‐dependent AIRS cloudiness and radiance variance: Analysis and interpretation

AbstractUpper tropospheric clouds play an important role in the global energy budget and hydrological cycle. Significant view‐angle asymmetry has been observed in upper‐level tropical clouds derived from 8 years of Atmospheric Infrared Sounder (AIRS) 15 µm radiances. Here we find that the asymmetry also exists in the extratropics. It is larger during day than that during night, more prominent near elevated terrain, and closely associated with deep convection and wind shear. The cloud radiance variance, a proxy for cloud inhomogeneity, has consistent characteristics of the asymmetry to those in the AIRS cloudiness. The leading causes of the view‐dependent cloudiness asymmetry are the local time difference and small‐scale organized cloud structures. The local time difference (1–1.5 h) of upper‐level clouds between two AIRS outermost views can create parts of the observed asymmetry. On the other hand, small‐scale tilted and banded structures of the upper‐level clouds can induce about half of the observed view‐angle‐dependent differences in the AIRS cloud radiances and their variances. This estimate is inferred from analogous study using microwave humidity sounder radiances observed during the period of time when there were simultaneous measurements at two different view‐angles from NOAA‐18 and NOAA‐19 satellites. The existence of tilted cloud structures and asymmetric 15 µm and 6.7 µm cloud radiances implies that cloud statistics would be view‐angle‐dependent, and should be taken into account in radiative transfer calculations, measurement uncertainty evaluations and cloud climatology investigations. In addition, the momentum forcing in the upper troposphere from tilted clouds is also likely asymmetric, which can affect atmospheric circulation anisotropically.

Retrieval of Cirrus Cloud Properties From the Atmospheric Infrared Sounder: The K-Coefficient Approach Using Cloud-Cleared Radiances as Input

We have developed a k-coefficient retrieval approach for Atmospheric Infrared Sounder (AIRS) observations, using AIRS cloud-cleared radiances (ACCRs) as input. This new approach takes advantage of the available ACCR, reduces computational expense, offers an efficient and accurate cirrus cloud retrieval alternative for hyperspectral infrared (IR) observations, and is potentially applicable to the compilation of a long-term cirrus cloud climatology from hyperspectral IR observations. The retrieval combines a lookup-table method coupled to a residual minimization scheme using observed cloudy and cloud-cleared AIRS radiances as input. Six AIRS channels between 766 and 832 cm-1 with minimal water vapor absorption/emission have been selected, and their spectral radiances have been demonstrated to be sensitive to both cirrus cloud optical depth (τc) and ice crystal effective particle size (De). The capability of the k-coefficient approach is demonstrated by comparison with a more accurate retrieval program, which combines the delta-four stream (D4S) approximation with the currently operational Stand-alone AIRS Radiative Transfer Algorithm (SARTA). The distribution patterns and the range of retrieved cloud parameters from the k-coefficient approach are nearly identical to those from SARTA+D4S retrievals, with minor differences traced to uncertainties in parameterized cloudy radiances in the k-coefficient approach and in the ACCR. The k -coefficient approach has also been applied to four AIRS granules over North Central China, Mongolia, and Siberia containing a significant presence of cirrus clouds, and its results are quantitatively compared to simultaneous Moderate Resolution Imaging Spectroradiometer/Aqua cirrus cloud retrievals. Finally, AIRS retrieved τc and De are consistent with the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat derived values for semitransparent cirrus clouds, with more significant differences in thicker cirrus and multilayer clouds.

A global view of stratospheric gravity wave hotspots located with Atmospheric Infrared Sounder observations

The main aim of this study is to find and classify hotspots of stratospheric gravity waves on a global scale. The analysis is based on a 9 year record (2003 to 2011) of radiance measurements by the Atmospheric Infrared Sounder (AIRS) aboard NASA's Aqua satellite. We detect gravity waves based on 4.3 µm brightness temperature variances. Our method focuses on peak events, i.e., strong gravity wave events for which the local variance considerably exceeds background levels. We estimate the occurrence frequencies of these peak events for different seasons and time of day and use the results to find local maxima or “hotspots.” In addition, we use AIRS radiances at 8.1 µm to simultaneously detect convective events, including deep convection in the tropics and mesoscale convective systems at middle latitudes. We classify the gravity wave sources based on seasonal occurrence frequencies for convection, but also by means of time series analyses and topographic data. Our study reproduces well‐known hotspots of gravity waves, e.g., the Andes and the Antarctic Peninsula. However, the high horizontal resolution of the AIRS observations also allows us to locate numerous mesoscale hotspots, which are partly unknown or poorly studied so far. Most of these mesoscale hotspots are found near orographic features like mountain ranges, coasts, lakes, deserts, or isolated islands. This study will help to select promising regions and seasons for future case studies of gravity waves.