How Well Can Infrared Sounders Observe the Atmosphere and Surface Through Clouds?

Infrared sounders, such as the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), and the Cross-track Infrared sounder (CrIS), have a cloud-impenetrable disadvantage in observing the atmosphere and surface under opaque cloudy conditions. However, recent studies indicate that hyperspectral, infrared sounders have the ability to detect cloud effective-optical and microphysical properties and to penetrate optically thin clouds in observing the atmosphere and surface to a certain degree. We have developed a retrieval scheme dealing with atmospheric conditions with cloud presence. This scheme can be used to analyze the retrieval accuracy of atmospheric and surface parameters under clear and cloudy conditions. In this paper, we present the surface emissivity results derived from IASI global measurements under both clear and cloudy conditions. The accuracy of surface emissivity derived under cloudy conditions is statistically estimated in comparison with those derived under clear sky conditions. The retrieval error caused by the clouds is shown as a function of cloud optical depth, which helps us to understand how well infrared sounders can observe the atmosphere and surface through clouds

Ultraspectral Sounding Retrieval Error Budget and Estimation

The ultraspectral infrared radiances obtained from satellite observations provide atmospheric, surface, and/or cloud information. The intent of the measurement of the thermodynamic state is the initialization of weather and climate models. Great effort has been given to retrieving and validating these atmospheric, surface, and/or cloud properties. Error Consistency Analysis Scheme (ECAS), through fast radiative transfer model (RTM) forward and inverse calculations, has been developed to estimate the error budget in terms of absolute and standard deviation of differences in both spectral radiance and retrieved geophysical parameter domains. The retrieval error is assessed through ECAS without assistance of other independent measurements such as radiosonde data. ECAS re-evaluates instrument random noise, and establishes the link between radiometric accuracy and retrieved geophysical parameter accuracy. ECAS can be applied to measurements of any ultraspectral instrument and any retrieval scheme with associated RTM. In this paper, ECAS is described and demonstration is made with the measurements of the METOP-A satellite Infrared Atmospheric Sounding Interferometer (IASI).

Hyperspectrally-Resolved Surface Emissivity Derived Under Optically Thin Clouds

Surface spectral emissivity derived from current and future satellites can and will reveal critical information about the Earth s ecosystem and land surface type properties, which can be utilized as a means of long-term monitoring of global environment and climate change. Hyperspectrally-resolved surface emissivities are derived with an algorithm utilizes a combined fast radiative transfer model (RTM) with a molecular RTM and a cloud RTM accounting for both atmospheric absorption and cloud absorption/scattering. Clouds are automatically detected and cloud microphysical parameters are retrieved; and emissivity is retrieved under clear and optically thin cloud conditions. This technique separates surface emissivity from skin temperature by representing the emissivity spectrum with eigenvectors derived from a laboratory measured emissivity database; in other words, using the constraint as a means for the emissivity to vary smoothly across atmospheric absorption lines. Here we present the emissivity derived under optically thin clouds in comparison with that under clear conditions

Inter-comparison between AIRS and IASI through Retrieved Parameters

A State-of-the-art retrieval algorithm dealing with all-weather conditions has been applied to satellite/aircraft instruments retrieving cloud/surface and atmospheric conditions. High quality retrievals have been achieved from IASI data. Surface, cloud, and atmospheric structure and variation are well captured by IASI measurements and/or retrievals. The same retrieval algorithm is also applied to AIRS for retrieval inter-comparison. Both AIRS and IASI have a similar FOV size but AIRS has a higher horizontal resolution. AIRS data can be interpolated to IASI horizontal resolution for inter-comparison at the same geophysical locations, however a temporal variation between AIRS and IASI observations need to be considered. JAIVEx has employed aircraft to obtain the atmospheric variation filling the temporal gap between two satellites. First results show that both AIRS and IASI have a very similar vertical resolving power, atmospheric conditions are well captured by both instruments, and radiances are well calibrated. AIRS data shown in retrievals (e.g., surface emissivity and moisture) have a relatively higher noise level. Since the this type of retrieval is very sensitive to its radiance quality, retrieval products inter-comparison is an effective way to identify/compare their radiance quality, in terms of a combination of spectral resolution and noise level, and to assess instrument performance. Additional validation analyses are needed to provide more-definitive conclusions

Cloud and Thermodynamic Parameters Retrieved from Satellite Ultraspectral Infrared Measurements

Atmospheric-thermodynamic parameters and surface properties are basic meteorological parameters for weather forecasting. A physical geophysical parameter retrieval scheme dealing with cloudy and cloud-free radiance observed with satellite ultraspectral infrared sounders has been developed and applied to the Infrared Atmospheric Sounding Interferometer (IASI) and the Atmospheric InfraRed Sounder (AIRS). The retrieved parameters presented herein are from radiance data gathered during the Joint Airborne IASI Validation Experiment (JAIVEx). JAIVEx provided intensive aircraft observations obtained from airborne Fourier Transform Spectrometer (FTS) systems, in-situ measurements, and dedicated dropsonde and radiosonde measurements for the validation of the IASI products. Here, IASI atmospheric profile retrievals are compared with those obtained from dedicated dropsondes, radiosondes, and the airborne FTS system. The IASI examples presented here demonstrate the ability to retrieve fine-scale horizontal features with high vertical resolution from satellite ultraspectral sounder radiance spectra

Retrieval with Infrared Atmospheric Sounding Interferometer and Validation during JAIVEx

A state-of-the-art IR-only retrieval algorithm has been developed with an all-season-global EOF Physical Regression and followed by 1-D Var. Physical Iterative Retrieval for IASI, AIRS, and NAST-I. The benefits of this retrieval are to produce atmospheric structure with a single FOV horizontal resolution (approx. 15 km for IASI and AIRS), accurate profiles above the cloud (at least) or down to the surface, surface parameters, and/or cloud microphysical parameters. Initial case study and validation indicates that surface, cloud, and atmospheric structure (include TBL) are well captured by IASI and AIRS measurements. Coincident dropsondes during the IASI and AIRS overpasses are used to validate atmospheric conditions, and accurate retrievals are obtained with an expected vertical resolution. JAIVEx has provided the data needed to validate the retrieval algorithm and its products which allows us to assess the instrument ability and/or performance. Retrievals with global coverage are under investigation for detailed retrieval assessment. It is greatly desired that these products be used for testing the impact on Atmospheric Data Assimilation and/or Numerical Weather Prediction

Analysis of AIRS and IASI System Performance Under Clear and Cloudy Conditions

The radiometric and spectral system performance of space-borne infrared radiometers is generally specified and analyzed under strictly cloud-free, spatially uniform and warm conditions, with the assumption that the observed performance applies to the full dynamic range under clear and cloudy conditions and that random noise cancels for the evaluation of the radiometric accuracy. Such clear conditions are found in only one percent of the data. Ninety nine percent of the data include clouds, which produce spatially highly non-uniform scenes with 11 micrometers window brightness temperatures as low as 200K. We use AIRS and IASI radiance spectra to compare system performance under clear and a wide range of cloudy conditions. Although the two instruments are in polar orbits, with the ascending nodes separated by four hours, daily averages already reveal surprisingly similar measurements. The AIRS and IASI radiometric performance based on the mean of large numbers of observation is comparable and agrees within 200 mK over a wide range of temperatures. There are also some unexpected differences at the 200 -500 mK level, which are of significance for climate applications. The results were verified with data from July 2007 through January 2010, but many can already be gleaned from the analysis of a single day of data

Near‐Global CFC‐11 Trends as Observed by Atmospheric Infrared Sounder From 2003 to 2018

Recent studies have indicated a slowdown of the decline of CFC‐11 concentration since 2012. Ground‐based observations used in such studies have their limitations in terms of global coverage. Here we show that the CFC‐11 time‐varying behaviors can be seen by double differencing nadir‐view, clear‐sky brightness temperatures of four AIRS (Atmospheric Infrared Sounder) channels in an infrared CFC‐11 absorption band. Assuming that CFC‐11 is vertically well mixed through the troposphere, we retrieve CFC‐11 surface concentration and its secular trend using such AIRS observations over the near globe (55°S to 55°N) from January 2003 to December 2018. The retrieved trends of CFC‐11 at the 11 ground sites agree well with the trends derived from in situ measurements at those sites. Our results show that, from 55°S to 55°N, the CFC‐11 trends from January 2003 to December 2012 are all negative, ranging from −2.5 to −1 ppt/year. The trends from January 2003 to December 2018 are less negative by as much as ~0.5–1 ppt/year over the Shandong peninsula, the Arabian Peninsula, and north India and Nepal area, and such differences in the trends are statistically significant. Factors other than the CFC‐11 that can affect the retrievals and trends are also discussed. These findings can help us depict the near‐global spatial distribution of the CFC‐11 trends from 2003 to 2018. The analysis described here has the potential to be used with current and future hyperspectral sounders to help monitor the CFC‐11 from space.Key PointsCFC‐11 long‐term signals can be extracted from the nadir‐viewed infrared sounders such as AIRS using a double differential methodCFC‐11 long‐term trends over each 30° by 10° grid from 55°S to 55°N are estimated from the AIRS clear‐sky radiances from 2003 to 2018The result suggested possible regional slowdowns of the CFC‐11 trend since 2013Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163636/2/jgrd56600_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163636/1/jgrd56600.pd

Atmospheric Infrared Fast Transmittance Models: A Comparison of Two Approaches

The next generation of atmospheric temperature and humidity sounders will have thousands of radiometrically accurate spectral channels throughout the infrared. The retrieval of atmospheric parameters from these radiances will stress both the accuracy and efficiency of forward model radiative transfer algorithms. We are developing a forward model for the Atmospheric Infrared Sounder (AIRS) which will fly on the EOS PM platform. The work presented here is based on algorithms developed over a number of years by McMillin, Fleming, and others for low resolution infrared sounders (HIRS) and microwave sounders. We have developed two "high-resolution" AIRS forward model algorithms for water vapor, one based on atmospheric layers with fixed pressures and variable water amounts, and another based on layers of fixed absorber amount but with variable pressures. These algorithms are compared for speed, accuracy, ease of development, and other factors that must be considered in developing a complex ..