A ground-based Fourier transform spectrometer has been developed to measure the atmospheric downwelling infrared radiance spectrum at the earth's surface with high absolute accuracy. The Atmospheric ...Emitted Radiance Interferometer (AERI) instrument was designed and fabricated by the University of Wisconsin Space Science and Engineering Center (UW-SSEC) for the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program. This paper emphasizes the key features of the UW-SSEC instrument design that contribute to meeting the AERI instrument requirements for the ARM Program. These features include a highly accurate radiometric calibration system, an instrument controller that provides continuous and autonomous operation, an extensive data acquisition system for monitoring calibration temperatures and instrument health, and a real-time data processing system. In particular, focus is placed on design issues crucial to meeting the ARM requirements for radiometric calibration, spectral calibration, noise performance, and operational reliability. The detailed performance characteristics of the AERI instruments built for the ARM Program are described in a companion paper. PUBLICATION ABSTRACT
Abstract
The Atmospheric Emitted Radiance Interferometer (AERI) instrument was developed for the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program by the University of ...Wisconsin Space Science and Engineering Center (UW-SSEC). The infrared emission spectra measured by the instrument have the sensitivity and absolute accuracy needed for atmospheric remote sensing and climate studies. The instrument design is described in a companion paper. This paper describes in detail the measured performance characteristics of the AERI instruments built for the ARM Program. In particular, the AERI systems achieve an absolute radiometric calibration of better than 1% (3σ) of ambient radiance, with a reproducibility of better than 0.2%. The knowledge of the AERI spectral calibration is better than 1.5 ppm (1σ) in the wavenumber range 400– 3000 cm−1.
The Atmospheric Infrared Sounder (AIRS) is the first of a new generation of advanced satellite‐based atmospheric sounders with the capability of obtaining high–vertical resolution profiles of ...temperature and water vapor. The high‐accuracy retrieval goals of AIRS (e.g., 1 K RMS in 1 km layers below 100 mbar for air temperature, 10% RMS in 2 km layers below 100 mbar for water vapor concentration), combined with the large temporal and spatial variability of the atmosphere and difficulties in making accurate measurements of the atmospheric state, necessitate careful and detailed validation using well‐characterized ground‐based sites. As part of ongoing AIRS Science Team efforts and a collaborative effort between the NASA Earth Observing System (EOS) project and the Department of Energy Atmospheric Radiation Measurement (ARM) program, data from various ARM and other observations are used to create best estimates of the atmospheric state at the Aqua overpass times. The resulting validation data set is an ensemble of temperature and water vapor profiles created from radiosondes launched at the approximate Aqua overpass times, interpolated to the exact overpass time using time continuous ground‐based profiles, adjusted to account for spatial gradients within the Advanced Microwave Sounding Unit (AMSU) footprints, and supplemented with limited cloud observations. Estimates of the spectral surface infrared emissivity and local skin temperatures are also constructed. Relying on the developed ARM infrastructure and previous and ongoing characterization studies of the ARM measurements, the data set provides a good combination of statistics and accuracy which is essential for assessment of the advanced sounder products. Combined with the collocated AIRS observations, the products are being used to study observed minus calculated AIRS spectra, aimed at evaluation of the AIRS forward radiative transfer model, AIRS observed radiances, and temperature and water vapor profile retrievals. This paper provides an introduction to the ARM site best estimate validation products and characterizes the accuracy of the AIRS team version 4 atmospheric temperature and water vapor retrievals using the ARM products. The AIRS retrievals over tropical ocean are found to have very good accuracy for both temperature and water vapor, with RMS errors approaching the theoretical expectation for clear sky conditions, while retrievals over a midlatitude land site have poorer performance. The results demonstrate the importance of using specialized “truth” sites for accurate assessment of the advanced sounder performance and motivate the continued refinement of the AIRS science team retrieval algorithm, particularly for retrievals over land.
Research funded by the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program has led to significant improvements in longwave radiative transfer modeling over the last decade. ...These improvements, which have generally come in small incremental changes, were made primarily in the water vapor self- and foreign-broadened continuum and the water vapor absorption line parameters. These changes, when taken as a whole, result in up to a 6 W m-2 improvement in the modeled clear-sky downwelling longwave radiative flux at the surface and significantly better agreement with spectral observations. This paper provides an overview of the history of ARM with regard to clear-sky longwave radiative transfer, and analyzes remaining related uncertainties in the ARM state-of-the-art Line-by-Line Radiative Transfer Model (LBLRTM). A quality measurement experiment (QME) for the downwelling infrared radiance at the ARM Southern Great Plains site has been ongoing since 1994. This experiment has three objectives: 1) to validate and improve the absorption models and spectral line parameters used in line-by-line radiative transfer models, 2) to assess the ability to define the atmospheric state, and 3) to assess the quality of the radiance observations that serve as ground truth for the model. Analysis of data from 1994 to 1997 made significant contributions to optimizing the QME, but is limited by small but significant uncertainties and deficiencies in the atmospheric state and radiance observations. This paper concentrates on the analysis of QME data from 1998 to 2001, wherein the data have been carefully selected to address the uncertainties in the 1994-97 dataset. Analysis of this newer dataset suggests that the representation of self-broadened water vapor continuum absorption is 3%-8% too strong in the 750-1000 cm-1 region. The dataset also provides information on the accuracy of the self- and foreign-broadened continuum absorption in the 1100-1300 cm-1 region. After accounting for these changes, remaining differences in modeled and observed downwelling clear-sky fluxes are less than 1.5 W m-2 over a wide range of atmospheric states.
Thousands of comparisons between total precipitable water vapor (PWV) obtained from radiosonde (Vaisala RS80-H) profiles and PWV retrieved from a collocated microwave radiometer (MWR) were made at ...the Atmospheric Radiation Measurement (ARM) Program's Southern Great Plains Cloud and Radiation Testbed (SGP CART) site in northern Oklahoma from 1994 to 2000. These comparisons show that the RS80-H radiosonde has an approximate 5% dry bias compared to the MWR. This observation is consistent with interpretations of Vaisala RS80 radiosonde data obtained during the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). In addition to the dry bias, analysis of the PWV comparisons as well as of data obtained from dual-sonde soundings done at the SGP show that the calibration of the radiosonde humidity measurements varies considerably both when the radiosondes come from different calibration batches and when the radiosondes come from the same calibration batch. This variability can result in peak-to-peak differences between radiosondes of greater than 25% in PWV. Because accurate representation of the vertical profile of water vapor is critical for ARM's science objectives, an empirical method for correcting the radiosonde humidity profiles is developed based on a constant scaling factor. By using an independent set of observations and radiative transfer models to test the correction, it is shown that the constant humidity scaling method appears both to improve the accuracy and reduce the uncertainty of the radiosonde data. The ARM data are also used to examine a different, physically based, correction scheme that was developed recently by scientists from Vaisala and the National Center for Atmospheric Research (NCAR). This scheme, which addresses the dry bias problem as well as other calibration-related problems with the RS80-H sensor, results in excellent agreement between the PWV retrieved from the MWR and integrated from the corrected radiosonde. However, because the physically based correction scheme does not address the apparently random calibration variations observed, it does not reduce the variability either between radiosonde calibration batches or within individual calibration batches.
A principal component noise filter has been applied to ground-based high-spectral-resolution infrared radiance observations collected by the Atmospheric Emitted Radiance Interferometers (AERIs) ...deployed by the Atmospheric Radiation Measurement (ARM) program. The technique decomposes the radiance observations into their principal components, selects the ones that describe the most variance in the data, and reconstructs the data from these components. An empirical function developed for chemical analysis is utilized to determine the number of principal components to be used in the reconstruction of the data. Statistical analysis of the noise-filtered minus original radiance data, as well as side-by-side analysis of data from two AERI systems utilizing different temporal sampling, demonstrates the ability of the noise filter using this empirical function to retain most of the atmospheric signal above the AERI noise level in the filtered data. The noise filter is applied to data collected at ARM's tropical, midlatitude, and Arctic sites, demonstrating that the random variability in the data is reduced by 5% to over 450%, depending on the spectral element and location of the instrument. A seasonal analysis of the number of principal components required by the noise filter for each site shows a strong seasonal dependence in the atmospheric variability at the Arctic and midlatitude sites but not at the tropical site. PUBLICATION ABSTRACT
AIRS and MODIS on the EOS Aqua spacecraft collect global observations of the Earth's upwelling infrared radiance for numerous remote sensing and climate related applications. This paper presents ...comparisons of the AIRS and MODIS radiance observations and illustrates the utility of using high–spectral resolution observations to create a highly accurate assessment of broadband sensor calibration. In the analysis, the high–spectral resolution AIRS spectra are reduced to MODIS spectral resolution, and the high–spatial resolution MODIS data are reduced to AIRS spatial resolution for global data collected on 6 September 2002 and 18 February 2004. Spatially uniform scenes are selected, and the observed differences are characterized as a function of several parameters including scene temperature, sensor scan (view) angle, and solar zenith angle. The comparisons are in general very good with respect to the expected radiometric accuracies of the sensors, with mean brightness temperature differences of 0.1 K or less for many of the MODIS bands. Uncertainties of these determinations range from near 0 K for window region bands to as large as 0.2 K for other bands. For MODIS water vapor bands 27 (6.8 μm) and 28 (7.3 μm) and temperature sounding bands 34 (13.7 μm), 35 (13.9 μm), and 36 (14.2 μm), the differences exhibit a dependence on scene temperature, with peak differences exceeding 1 K for bands 27 and 36. Differences as a function of scan angle are 0.4 K or less for all bands, and scan angles but clear trends are defined. Results for the 2 days demonstrate good reproducibility with changes in mean differences of 0.1 K or less for most bands.
This paper describes the application of principal component analysis to reduce the random noise present in the hyperspectral infrared observations. Within a set of spectral observations the number of ...components needed to characterize the atmosphere is far less than the number of wavelengths observed, typically by a factor between 50 and 70. The higher‐order components, which mainly serve to characterize noise, can be eliminated along with the noise that they characterize. The results obtained depend on the variability of the selected sets of observations and on specific instrument characteristics such as spectral resolution and noise statistics. For a set of 10,000 Fourier transform spectrometer (FTS) simulated spectra, whose standard deviation is about 10% of the mean, we were able to obtain noise reduction factors between 5 and 8. Results obtained from real FTS, with standard deviation of about 10% of the mean, indicated practical noise reduction between 5 and 6. To avoid loss of information in the presence of highly deviant observations, it is necessary to use a conservative number of principal components higher than the optimum to maximum noise reduction. However, even then, noise reduction factors of 4 are still achievable.
Upper air temperature is defined as an essential climate variable by the World Meteorological Organization. Two remote sensing technologies being promoted for monitoring stratospheric temperatures ...are GPS radio occultation (RO) and spectrally resolved IR radiances. This study assesses RO and hyperspectral IR sounder derived temperature products within the stratosphere by comparing IR spectra calculated from GPS RO and IR sounder products to coincident IR observed radiances, which are used as a reference standard. RO dry temperatures from the University Corporation for Atmospheric Research (UCAR) Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission are compared to NASA Atmospheric Infrared Sounder (AIRS) retrievals using a previously developed profile‐to‐profile collocation method and vertical temperature averaging kernels. Brightness temperatures (BTs) are calculated for both COSMIC and AIRS temperature products and are then compared to coincident AIRS measurements. The COSMIC calculated minus AIRS measured BTs exceed the estimated 0.5 K measurement uncertainty for the winter time extratropics around 35 hPa. These differences are attributed to seasonal UCAR COSMIC biases. Unphysical vertical oscillations are seen in the AIRS L2 temperature product in austral winter Antarctic regions, and results imply a small AIRS tropical warm bias around ~35 hPa in the middle stratosphere.
Key Points
Demonstrates method for validating stratospheric temperature profile products using hyperspectral infrared radiance observations
UCAR COSMIC RO and NASA AIRS v6 hyperspectral IR sounder temperatures and calculated radiances are compared
AIRS L2 product found to contain unphysical structures in polar winters and a COSMIC warm bias found in the UTLS polar winters
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