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Patrick Minnis and Mandana M. Khaiyer

Abstract

The land skin temperature, an important feature for agricultural monitoring, convective processes, and the earth’s radiation budget, is monitored from limited-view satellite imagers. The angular dependence of this parameter is examined using simultaneous views of clear areas from up to three geostationary satellites. Daytime temperatures from different satellites differed by up to 6 K and varied as a function of the time of day. Larger differences are expected to occur but were not measured because of limited viewing angles. These differences suggest that biases may occur in both the magnitude and phase of the diurnal cycle of skin temperature and its mean value whenever geostationary satellite data are used to determine skin temperature. The temperature differences were found over both flat and mountainous regions with some slight dependence on vegetation. The timing and magnitude of the temperature differences provide some initial validation for relatively complex model calculations of skin temperature variability. The temperature differences are strongly correlated with terrain and the anisotropy of reflected solar radiation for typical land surfaces. These strong dependencies suggest the possibility for the development of a simple empirical approach for characterizing the temperature anisotropy. Additional research using a much greater range of viewing angles is required to confirm the potential of the suggested empirical approach.

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H. Wang, R. T. Pinker, P. Minnis, and M. M. Khaiyer

Abstract

Solar radiation reaching the earth’s surface provides the primary forcing of the climate system, and thus, information on this parameter is needed at a global scale. Several satellite-based estimates of surface radiative fluxes are available, but they differ from each other in many aspects. The focus of this study is to highlight one aspect of such differences, namely, the way satellite-observed radiances are used to derive information on cloud optical properties and the impact this has on derived parameters such as surface radiative fluxes. Frequently, satellite visible radiance in a single channel is used to infer cloud transmission; at times, several spectral channels are utilized to derive cloud optical properties and use these to infer cloud transmission. In this study, an evaluation of these two approaches will be performed in terms of impact on the accuracy in surface radiative fluxes. The University of Maryland Satellite Radiation Budget (UMD/SRB) model is used as a tool to perform such an evaluation over the central United States. The estimated shortwave fluxes are evaluated against ground observations at the Atmospheric Radiation Measurement Program (ARM) Central Facility and at four ARM extended sites. It is shown that the largest differences between these two approaches occur during the winter season when snow is on the ground.

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K. Van Weverberg, A. M. Vogelmann, W. Lin, E. P. Luke, A. Cialella, P. Minnis, M. Khaiyer, E. R. Boer, and M. P. Jensen

Abstract

This paper presents a detailed analysis of convection-permitting cloud simulations, aimed at increasing the understanding of the role of parameterized cloud microphysics in the simulation of mesoscale convective systems (MCSs) in the tropical western Pacific (TWP). Simulations with three commonly used bulk microphysics parameterizations with varying complexity have been compared against satellite-retrieved cloud properties. An MCS identification and tracking algorithm was applied to the observations and the simulations to evaluate the number, spatial extent, and microphysical properties of individual cloud systems. Different from many previous studies, these individual cloud systems could be tracked over larger distances because of the large TWP domain studied.

The analysis demonstrates that the simulation of MCSs is very sensitive to the parameterization of microphysical processes. The most crucial element was found to be the fall velocity of frozen condensate. Differences in this fall velocity between the experiments were more related to differences in particle number concentrations than to fall speed parameterization. Microphysics schemes that exhibit slow sedimentation rates for ice aloft experience a larger buildup of condensate in the upper troposphere. This leads to more numerous and/or larger MCSs with larger anvils. Mean surface precipitation was found to be overestimated and insensitive to the microphysical schemes employed in this study. In terms of the investigated properties, the performances of complex two-moment schemes were not superior to the simpler one-moment schemes, since explicit prediction of number concentration does not necessarily improve processes such as ice nucleation, the aggregation of ice crystals into snowflakes, and their sedimentation characteristics.

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Tarah M. Sharon, Bruce A. Albrecht, Haflidi H. Jonsson, Patrick Minnis, Mandana M. Khaiyer, Timothy M. van Reken, John Seinfeld, and Rick Flagan

Abstract

A cloud rift is characterized as a large-scale, persistent area of broken, low-reflectivity stratocumulus clouds usually surrounded by a solid deck of stratocumulus. A rift observed off the coast of California was investigated using an instrumented aircraft to compare the aerosol, cloud microphysical, and thermodynamic properties in the rift with those of the surrounding solid stratocumulus deck. The microphysical characteristics in the solid stratocumulus deck differ substantially from those of a broken, cellular rift where cloud droplet concentrations are a factor of 2 lower than those in the solid cloud. Furthermore, cloud condensation nuclei (CCN) concentrations were found to be about 3 times greater in the solid-cloud area compared with those in the rift. Although drizzle was observed near cloud top in parts of the solid stratocumulus cloud, the largest drizzle rates were associated with the broken clouds within the rift area and with extremely large effective droplet sizes retrieved from satellite data. Minimal thermodynamic differences between the rift and solid cloud deck were observed. In addition to marked differences in particle concentrations, evidence of a mesoscale circulation near the solid cloud–rift boundary is presented. This mesoscale circulation may provide a mechanism for maintaining a rift, but further study is required to understand the initiation of a rift and the conditions that may cause it to fill. A review of results from previous studies indicates similar microphysical characteristics in rift features sampled serendipitously. These observations indicate that cloud rifts are depleted of aerosols through the cleansing associated with drizzle and are a manifestation of natural processes occurring in marine stratocumulus.

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Aaron D. Kennedy, Xiquan Dong, Baike Xi, Patrick Minnis, Anthony D. Del Genio, Audrey B. Wolf, and Mandana M. Khaiyer

Abstract

Three years of surface and Geostationary Operational Environmental Satellite (GOES) data from the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site are used to evaluate the NASA GISS Single Column Model (SCM) simulated clouds from January 1999 to December 2001. The GOES-derived total cloud fractions for both 0.5° and 2.5° grid boxes are in excellent agreement with surface observations, suggesting that ARM point observations can represent large areal observations. Low (<2 km), middle (2–6 km), and high (>6 km) levels of cloud fractions, however, have negative biases as compared to the ARM results due to multilayer cloud scenes that can either mask lower cloud layers or cause misidentifications of cloud tops. Compared to the ARM observations, the SCM simulated most midlevel clouds, overestimated low clouds (4%), and underestimated total and high clouds by 7% and 15%, respectively. To examine the dependence of the modeled high and low clouds on the large-scale synoptic patterns, variables such as relative humidity (RH) and vertical pressure velocity (omega) from North American Regional Reanalysis (NARR) data are included. The successfully modeled and missed high clouds are primarily associated with a trough and ridge upstream of the ARM SGP, respectively. The PDFs of observed high and low occurrence as a function of RH reveal that high clouds have a Gaussian-like distribution with mode RH values of ∼40%–50%, whereas low clouds have a gammalike distribution with the highest cloud probability occurring at RH ∼75%–85%. The PDFs of modeled low clouds are similar to those observed; however, for high clouds the PDFs are shifted toward higher values of RH. This results in a negative bias for the modeled high clouds because many of the observed clouds occur at RH values below the SCM-specified stratiform parameterization threshold RH of 60%. Despite many similarities between PDFs derived from the NARR and ARM forcing datasets for RH and omega, differences do exist. This warrants further investigation of the forcing and reanalysis datasets.

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D. D. Turner, A. M. Vogelmann, R. T. Austin, J. C. Barnard, K. Cady-Pereira, J. C. Chiu, S. A. Clough, C. Flynn, M. M. Khaiyer, J. Liljegren, K. Johnson, B. Lin, C. Long, A. Marshak, S. Y. Matrosov, S. A. McFarlane, M. Miller, Q. Min, P. Minimis, W. O'Hirok, Z. Wang, and W. Wiscombe

Many of the clouds important to the Earth's energy balance, from the Tropics to the Arctic, contain small amounts of liquid water. Longwave and shortwave radiative fluxes are very sensitive to small perturbations of the cloud liquid water path (LWP), when the LWP is small (i.e., < 100 g m−2; clouds with LWP less than this threshold will be referred to as “thin”). Thus, the radiative properties of these thin liquid water clouds must be well understood to capture them correctly in climate models. We review the importance of these thin clouds to the Earth's energy balance, and explain the difficulties in observing them. In particular, because these clouds are thin, potentially mixed phase, and often broken (i.e., have large 3D variability), it is challenging to retrieve their microphysical properties accurately. We describe a retrieval algorithm intercomparison that was conducted to evaluate the issues involved. The intercomparison used data collected at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site and included 18 different algorithms to evaluate their retrieved LWP, optical depth, and effective radii. Surprisingly, evaluation of the simplest case, a single-layer overcast stratocumulus, revealed that huge discrepancies exist among the various techniques, even among different algorithms that are in the same general classification. This suggests that, despite considerable advances that have occurred in the field, much more work must be done, and we discuss potential avenues for future research.)

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