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D. D. Turner, E. J. Mlawer, and H. E. Revercomb
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L. A. Sromovsky, H. E. Revercomb, V. E. Suomi, S. S. Limaye, and R. J. Krauss

Abstract

Previous Voyager 1 and 2 Jovian circulation measurements exhibit a large positive correlation between eddy momentum transports and the meridional shear of the zonal wind component, implying a very large rate of conversion of eddy kinetic energy into kinetic energy of the zonal jets. Examination of the vectors mainly responsible for the correlation in our recent Voyager 2 global measurements indicates that it is probably caused by a biased sampling of prominent cloud features associated with circulating eddies. Intensive diagnostic measurements with more nearly uniform spatial sampling show no significant correlation in regions where our original measurements showed strong correlations. If the sampling bias mechanism is fully accounted for in all Jovian circulation measurements, the estimated eddy-to-mean-flow kinetic energy conversion rate may be reduced significantly.

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W. F. Feltz, W. L. Smith, H. B. Howell, R. O. Knuteson, H. Woolf, and H. E. Revercomb

Abstract

The Department of Energy Atmospheric Radiation Measurement Program (ARM) has funded the development and installation of five ground-based atmospheric emitted radiance interferometer (AERI) systems at the Southern Great Plains (SGP) site. The purpose of this paper is to provide an overview of the AERI instrument, improvement of the AERI temperature and moisture retrieval technique, new profiling utility, and validation of high-temporal-resolution AERI-derived stability indices important for convective nowcasting. AERI systems have been built at the University of Wisconsin—Madison, Madison, Wisconsin, and deployed in the Oklahoma–Kansas area collocated with National Oceanic and Atmospheric Administration 404-MHz wind profilers at Lamont, Vici, Purcell, and Morris, Oklahoma, and Hillsboro, Kansas. The AERI systems produce absolutely calibrated atmospheric infrared emitted radiances at one-wavenumber resolution from 3 to 20 μm at less than 10-min temporal resolution. The instruments are robust, are automated in the field, and are monitored via the Internet in near–real time. The infrared radiances measured by the AERI systems contain meteorological information about the vertical structure of temperature and water vapor in the planetary boundary layer (PBL; 0–3 km). A mature temperature and water vapor retrieval algorithm has been developed over a 10-yr period that provides vertical profiles at less than 10-min temporal resolution to 3 km in the PBL. A statistical retrieval is combined with the hourly Geostationary Operational Environmental Satellite (GOES) sounder water vapor or Rapid Update Cycle, version 2, numerical weather prediction (NWP) model profiles to provide a nominal hybrid first guess of temperature and moisture to the AERI physical retrieval algorithm. The hourly satellite or NWP data provide a best estimate of the atmospheric state in the upper PBL; the AERI radiances provide the mesoscale temperature and moisture profile correction in the PBL to the large-scale GOES and NWP model profiles at high temporal resolution. The retrieval product has been named AERIplus because the first guess used for the mathematical physical inversion uses an optimal combination of statistical climatological, satellite, and numerical model data to provide a best estimate of the atmospheric state. The AERI physical retrieval algorithm adjusts the boundary layer temperature and moisture structure provided by the hybrid first guess to fit the observed AERI downwelling radiance measurement. This provides a calculated AERI temperature and moisture profile using AERI-observed radiances “plus” the best-known atmospheric state above the boundary layer using NWP or satellite data. AERIplus retrieval accuracy for temperature has been determined to be better than 1 K, and water vapor retrieval accuracy is approximately 5% in absolute water vapor when compared with well-calibrated radiosondes from the surface to an altitude of 3 km. Because AERI can monitor the thermodynamics where the atmosphere usually changes most rapidly, atmospheric stability tendency information is readily available from the system. High-temporal-resolution retrieval of convective available potential energy, convective inhibition, and PBL equivalent potential temperature θ e are provided in near–real time from all five AERI systems at the ARM SGP site, offering a unique look at the atmospheric state. This new source of meteorological data has shown excellent skill in detecting rapid synoptic and mesoscale meteorological changes within clear atmospheric conditions. This method has utility in nowcasting temperature inversion strength and destabilization caused by θ e advection. This high-temporal-resolution monitoring of rapid atmospheric destabilization is especially important for nowcasting severe convection.

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W. L. Smith, H. E. Revercomb, R. O. Knuteson, F. A. Best, R. Dedecker, H. B. Howell, and H. M. Woolf

Abstract

The characteristics of the ER-2 aircraft and ground-based High Resolution Interferometer Sounder (HIS) instruments deployed during FIRE II are described. A few example spectra are given to illustrate the HIS cloud and molecular atmosphere remote sensing capabilities.

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Steven A. Ackerman, W. L. Smith, H. E. Revercomb, and J. D. Spinhirne

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Lidar and high spectral resolution infrared radiance observations taken on board the ER-2 on 28 October 1986 are used to study the radiative properties of cirrus cloud in the 8–12 μm window region. Measurements from the High-spectral resolution Interferometer Sounder (HIS) indicate that the spectral variation of the equivalent blackbody temperature across the window can be greater than 5°C for a given cirrus cloud. This difference is attributed to the presence of small particles.

A method for detecting cirrus clouds using 8 μm, 11 μm, and 12 μm bands is presented. The 8 μm band is centered on a weak water-vapor absorption line while the 11 μm and 12 μm bands are between absorption lines. The brightness temperature difference between the 8 and 11 μm bands is negative for clear regions, while for ice clouds it is positive. Differences in the 11 and 12 μm channels are positive, whether viewing a cirrus cloud or a clear region. Inclusion of the 8 μm channel therefore removes the ambiguity associated with the use of 11 and 12 μm channels alone. The method is based on the comparison of brightness temperatures observed in these three channels.

The HIS and lidar observations were combined to derive the spectral effective beam emissivity (ε) of the cirrus clouds. Fifty percent of clouds on this day displayed a spectral variation of ε from 2–10%. These differences, in conjunction with large differences in the HIS observed brightness temperatures, indicate that cirrus clouds cannot be considered gray in the 8–12 μm window region.

The derived spectral transmittance of the cloud is used to infer the effective radii of the particle size distribution, assuming ice spheres. For 28 October 1986 the effective radius of cirrus cloud particle size distribution (r eff) was generally within the 30–40 μm range with 8% of the cases where 10 < r eff < 30 μm and 12% of the cases corresponding to r ref > 40 μm.

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William L. Smith, Xia Lin Ma, Steven A. Ackerman, H. E. Revercomb, and R. O. Knuteson

Abstract

A technique for estimating cloud radiative properties (i.e., spectral emissivity and reflectivity) in the infrared is developed based on observations at a spectral resolution of approximately 0.5 cm−1. The algorithm makes use of spectral radiance observations and theoretical calculations of the infrared spectra for clear and cloudy conditions along with lidar-determined cloud-base and cloud-top pressure. An advantage of the high spectral resolution observations is that the absorption effects of atmospheric gases are minimized by analyzing between gaseous absorption lines. The technique is applicable to both ground-based and aircraft-based platforms and derives the effective particle size and associated cloud water content required to satisfy, theoretically, the observed cloud infrared spectra. The algorithm is tested using theoretical simulations and applied to observations made with the University of Wisconsin's ground-based and NASA ER-2 aircraft High-Resolution Infrared Spectrometer instruments.

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D. D. Turner, S. A. Ackerman, B. A. Baum, H. E. Revercomb, and P. Yang

Abstract

A new technique for ascertaining the thermodynamic cloud phase from high-spectral-resolution ground-based infrared measurements made by the Atmospheric Emitted Radiance Interferometer (AERI) is presented. This technique takes advantage of the differences in the index of refraction of ice and water between 11 and 19 μm. The differences in the refractive indices translate into differences in cloud emissivity at the various wavelengths, which are used to determine whether clouds contain only ice particles or only water particles, or are mixed phase. Simulations demonstrate that the algorithm is able to ascertain correctly the cloud phase under most conditions, with the exceptions occurring when the optical depth of the cloud is dominated by liquid water (>70%). Several examples from the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment are presented, to demonstrate the capability of the algorithm, in which a collocated polarization-sensitive lidar is used to provide insight to the true thermodynamic phase of the clouds. Statistical comparisons with this lidar during the SHEBA campaign demonstrate that the algorithm identifies the cloud as either an ice or mixed-phase cloud approximately 80% of time when a single-layer cloud with an average depolarization above 10% exists that is not opaque to the AERI. For single-layer clouds having depolarization of less than 10%, the algorithm identifies the cloud as a liquid water cloud over 50% of the time. This algorithm was applied to 7 months of data collected during SHEBA, and monthly statistics on the frequency of ice, water, and mixed-phase clouds are presented.

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D. D. Turner, R. O. Knuteson, H. E. Revercomb, C. Lo, and R. G. Dedecker

Abstract

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.

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S. A. Ackerman, W. L. Smith, A. D. Collard, X. L. Ma, H. E. Revercomb, and R. O. Knuteson

Abstract

This paper parts analysis of cloud observations by the High-Resolution Interferometer Sounder made from the NASA ER-2 aircraft during FIRE II. Clear and cloudy sky radiance spectra are presented in terms of differences between observations and radiative transfer model simulations.

Doubling/adding radiative transfer model simulations demonstrate that the magnitude of the brightness temperature differences (ΔBT) is a function of the cloud particle size distribution and the cloud ice water path. For effective radii greater than approximately 30 µm (size parameter of 18) there is little spectral variation in the brightness temperature (BT). An analysis of brightness temperature differences indicates that cirrus clouds over the FIRE II central site possessed a small-particle mode. The cases analyzed had similar appearances in a plot of ΔBT between 11 and 12 µm (BT11 – BT12) versus the observed ΔBT between 8 and 11 µm (BT8 – BT11), suggesting similarity in the microphysical properties of nongray cirrus. Brightness temperature differences between cirrus cloud over the central site and the Gulf of Mexico are presented to illustrate differences in the cirrus microphysical properties at the two different locations.

Cloud effective emissivities and effective radiative temperature were derived for observations over the FIRE central site using complementary lidar and radiosonde data. Small variations in these effective properties were seen on 5 December and 22 November. Although they had similar effective temperatures, the emissivities were very different. Very few clouds were observed to have an emissivity near unity.

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A. D. Collard, S. A. Ackerman, W. L. Smith, X. Ma, H. E. Revercomb, R. O. Knuteson, and S-C. Lee

Abstract

During FIRE II, cirrus clouds were observed in the wavelength range 3–19, µm with two High Resolution Interferometer Sounders as described in the Part I companion paper. One, known as AC-HIS, was mounted on the NASA ER-2 aircraft in order to look down on the clouds; these results are described in the Part II companion paper. The other, GB-HIS, also known as the Atmospheric Emitted Radiance Interferometer (AERI), was ground based. The AERI observations have been simulated, assuming scattering from spherical ice particles, using a single-layer doubling model for the cloud, for two atmospheric windows at 700–1250 and 2650–3000 cm−1. The second of these windows is affected by scattered sunlight, which has been included in the calculations. The sensitivity of the cloud signal to quantities such as the ice water path (IWP) and effective radius (r eff) have been determined. Using the cloud model, best fits have been derived for IWP and r eff, for both windows individually and together. Possible errors in these derivations have been investigated.

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