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A. Guillaume, B. H. Kahn, Q. Yue, E. J. Fetzer, S. Wong, G. J. Manipon, H. Hua, and B. D. Wilson

Abstract

A method is described to characterize the scale dependence of cloud chord length using cloud-type classification reported with the 94-GHz CloudSat radar. The cloud length along the CloudSat track is quantified using horizontal and vertical structures of cloud classification separately for each cloud type and for all clouds independent of cloud type. While the individual cloud types do not follow a clear power-law behavior as a function of horizontal or vertical scale, a robust power-law scaling of cloud chord length is observed when cloud type is not considered. The exponent of horizontal length is approximated by β ≈ 1.66 ± 0.00 across two orders of magnitude (~10–1000 km). The exponent of vertical thickness is approximated by β ≈ 2.23 ± 0.03 in excess of one order of magnitude (~1–14 km). These exponents are in agreement with previous studies using numerical models, satellites, dropsondes, and in situ aircraft observations. These differences in horizontal and vertical cloud scaling are consistent with scaling of temperature and horizontal wind in the horizontal dimension and with scaling of buoyancy flux in the vertical dimension. The observed scale dependence should serve as a guide to test and evaluate scale-cognizant climate and weather numerical prediction models.

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J. C. Kaimal, R. A. Eversole, D. H. Lenschow, B. B. Stankov, P. H. Kahn, and J. A. Businger

Abstract

The paper describes a convective boundary layer experiment conducted in April 1978 at the Boulder Atmospheric Observatory, and examines the spectral behavior of wind velocity and temperature from the Observatory's 300 m tower, from aircraft flights alongside the tower and from a surface network of anemometers, for evidence of terrain influence on turbulence structure. The gently rolling terrain at the site does not seem to affect the turbulence spectra from the tower in any perceptible manner, except for minor shifts in the vertical velocity and temperature spectral peaks. The aircraft vertical velocity spectra showed different shapes for alongwind and crosswind sampling directions, as in earlier measurements over ocean surfaces, and their peaks are displaced to higher wavenumbers compared with the tower spectra. Long-term spectra of horizontal wind components from surface stations around the tower exhibit no particular sensitivity to site selection. Under near-stationary conditions the peak of the spectrum of the streamwise component tends to reflect more closely the predominant boundary layer. convective scales than does the peak of the lateral wind component. The problem of identifying those scales in the presence of large shifts in wind direction is discussed.

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Qing Yue, K. N. Liou, S. C. Ou, B. H. Kahn, P. Yang, and G. G. Mace

Abstract

A thin cirrus cloud thermal infrared radiative transfer model has been developed for application to cloudy satellite data assimilation. This radiation model was constructed by combining the Optical Path Transmittance (OPTRAN) model, developed for the speedy calculation of transmittances in clear atmospheres, and a thin cirrus cloud parameterization using a number of observed ice crystal size and shape distributions. Numerical simulations show that cirrus cloudy radiances in the 800–1130-cm−1 thermal infrared window are sufficiently sensitive to variations in cirrus optical depth and ice crystal size as well as in ice crystal shape if appropriate habit distribution models are selected a priori for analysis. The parameterization model has been applied to the Atmospheric Infrared Sounder (AIRS) on board the Aqua satellite to interpret clear and thin cirrus spectra observed in the thermal infrared window. Five clear and 29 thin cirrus cases at nighttime over and near the Atmospheric Radiation Measurement program (ARM) tropical western Pacific (TWP) Manus Island and Nauru Island sites have been chosen for this study. A χ2-minimization program was employed to infer the cirrus optical depth and ice crystal size and shape from the observed AIRS spectra. Independent validation shows that the AIRS-inferred cloud parameters are consistent with those determined from collocated ground-based millimeter-wave cloud radar measurements. The coupled thin cirrus radiative transfer parameterization and OPTRAN, if combined with a reliable thin cirrus detection scheme, can be effectively used to enhance the AIRS data volume for data assimilation in numerical weather prediction models.

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M. M. Schreier, B. H. Kahn, A. Eldering, D. A. Elliott, E. Fishbein, F. W. Irion, and T. S. Pagano

Abstract

The combination of multiple satellite instruments on a pixel-by-pixel basis is a difficult task, even for instruments collocated in space and time, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) on board the Earth Observing System (EOS) Aqua. Toward the goal of an improved collocation methodology, the channel- and scan angle–dependent spatial response functions of AIRS that were obtained from prelaunch measurements and calculated impacts from scan geometry are shown within the context of radiance comparisons. The AIRS spatial response functions are used to improve the averaging of MODIS radiances to the AIRS footprint, and the variability of brightness temperature differences (ΔTb) between MODIS and AIRS are quantified on a channel-by-channel basis. To test possible connections between ΔTb and the derived level 2 (L2) datasets, cloud characteristics derived from MODIS are used to highlight correlations between these quantities and ΔTb, especially for ice clouds in H2O and CO2 bands. Furthermore, correlations are quantified for temperature lapse rate (dT/dp) and the magnitude of water vapor mixing ratio (q) obtained from AIRS L2 retrievals. Larger values of dT/dp and q correlate well to larger values of ΔTb in the H2O and CO2 bands. These correlations were largely eliminated or reduced after the MODIS spectral response functions were shifted by recommended values. While this investigation shows that the AIRS spatial response functions are necessary to reduce the variability and skewness of ΔTb within heterogeneous scenes, improved knowledge about MODIS spectral response functions is necessary to reduce biases in ΔTb.

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B. H. Kahn, J. Teixeira, E. J. Fetzer, A. Gettelman, S. M. Hristova-Veleva, X. Huang, A. K. Kochanski, M. Köhler, S. K. Krueger, R. Wood, and M. Zhao

Abstract

Observations of the scale dependence of height-resolved temperature T and water vapor q variability are valuable for improved subgrid-scale climate model parameterizations and model evaluation. Variance spectral benchmarks for T and q obtained from the Atmospheric Infrared Sounder (AIRS) are compared to those generated by state-of-the-art numerical weather prediction “analyses” and “free-running” climate model simulations with spatial resolution comparable to AIRS. The T and q spectra from both types of models are generally too steep, with small-scale variance up to several factors smaller than AIRS. However, the two model analyses more closely resemble AIRS than the two free-running model simulations. Scaling exponents obtained for AIRS column water vapor (CWV) and height-resolved layers of q are also compared to the superparameterized Community Atmospheric Model (SP-CAM), highlighting large differences in the magnitude of CWV variance and the relative flatness of height-resolved q scaling in SP-CAM. Height-resolved q spectra obtained from aircraft observations during the Variability of the American Monsoon Systems Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx) demonstrate changes in scaling exponents that depend on the observations’ proximity to the base of the subsidence inversion with scale breaks that occur at approximately the dominant cloud scale (~10–30 km). This suggests that finer spatial resolution requirements must be considered for future satellite observations of T and q than those currently planned for infrared and microwave satellite sounders.

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