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Xiaoqing Wu, William D. Hall, Wojciech W. Grabowski, Mitchell W. Moncrieff, William D. Collins, and Jeffrey T. Kiehl

Abstract

A two-dimensional cloud-resolving model with a large domain is integrated for 39 days during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) to study the effects of ice phase processes on cloud properties and cloud radiative properties. The ice microphysical parameterization scheme is modified based on microphysical measurements from the Central Equatorial Pacific Experiment. A nonlocal boundary layer diffusion scheme is included to improve the simulation of the surface heat fluxes. The modified ice scheme produces fewer ice clouds during the 39-day simulation. The cloud radiative properties show significant improvement and compare well with various observations. Both the 39-day mean value (202 W m−2) and month-long evolution of outgoing longwave radiative flux from the model are comparable with satellite observations. The 39-day mean surface shortwave cloud forcing is −110 W m−2, consistent with other estimates obtained for TOGA COARE. The 39-day mean values of surface net longwave, shortwave, latent, and sensible fluxes are −46.2, 182.9, −109.9, and −7.8 W m −2, respectively, in line with the IMET buoy data (−54.6, 178.2, −102.7, and −10.6 W m−2).

The offline radiation calculations as well as the cloud-interactive radiation simulations demonstrate that a doubled effective radius of ice particles and enhanced shortwave cloud absorption strongly affect the radiative flux and cloud radiative forcing but have little impact on the cloud properties. The modeled albedo is sensitive to the effective radius of ice particles and/or the shortwave cloud absorption in the radiation scheme. More complete satellite observations and theoretical studies are required to fully understand the physical processes involved.

The results suggest that the ice microphysical parameterization plays an important role in the long-term simulation of cloud properties and cloud radiative properties. Future field observations should put more weight on the microphysical properties, cloud properties, and high-quality radiative properties in order to further improve the cloud-resolving modeling of cloud systems and the understanding of cloud–radiation interaction.

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B. P. LeClair, A. E. Hamielec, H. R. Pruppacher, and W. D. Hall

Abstract

Four theoretical approaches are presented for quantitatively determining the intensity of the internal circulation and the flow patterns inside and outside liquid water spheres falling at terminal velocity in air. The first approach assumes creeping flow outside and inside a water sphere, the second assumes potential flow outside and inviscid motion inside a water sphere, the third makes use of boundary layer theory, and the fourth approach uses a numerical method to solve the full Navier-Stokes equation of motion inside and outside a water sphere. The theoretical predictions are compared with data obtained from new quantitative wind tunnel experiments on spherical and deformed water drops. The results show that the creeping flow analysis greatly underestimates the strength of the internal velocity while the inviscid flow analysis greatly overestimates it. On the other hand, the results of the boundary layer approach and of the numerical approach agree reasonably well with the experimental data for drops with radii <500 μ. For larger drops the results of the boundary layer approach greatly overestimate the strength of the internal circulation and predict a completely wrong trend of the variation of the internal velocity with drop size, while the numerical results, although somewhat overestimating the circulation strength, predict the trend correctly. Reasonably good agreement is also found between the observed flow patterns inside the drop and those numerically predicted. In two appendices the effect of the internal circulation on drop shape and hydrodynamic drag is discussed.

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Chad W. Thackeray, Alex Hall, Mark D. Zelinka, and Christopher G. Fletcher

Abstract

An emergent constraint (EC) is a popular model evaluation technique, which offers the potential to reduce intermodel variability in projections of climate change. Two examples have previously been laid out for future surface albedo feedbacks (SAF) stemming from loss of Northern Hemisphere (NH) snow cover (SAFsnow) and sea ice (SAFice). These processes also have a modern-day analog that occurs each year as snow and sea ice retreat from their seasonal maxima, which is strongly correlated with future SAF across an ensemble of climate models. The newly released CMIP6 ensemble offers the chance to test prior constraints through out-of-sample verification, an important examination of EC robustness. Here, we show that the SAFsnow EC is equally strong in CMIP6 as it was in past generations, while the SAFice EC is also shown to exist in CMIP6, but with different, slightly weaker characteristics. We find that the CMIP6 mean NH SAF exhibits a global feedback of 0.25 ± 0.05 W m−2 K−1, or ~61% of the total global albedo feedback, largely in line with prior generations despite its increased climate sensitivity. The NH SAF can be broken down into similar contributions from snow and sea ice over the twenty-first century in CMIP6. Crucially, intermodel variability in seasonal SAFsnow and SAFice is largely unchanged from CMIP5 because of poor outlier simulations of snow cover, surface albedo, and sea ice thickness. These outliers act to mask the noted improvement from many models when it comes to SAFice, and to a lesser extent SAFsnow.

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P. A. Romashkin, D. F. Hurst, J. W. Elkins, G. S. Dutton, D. W. Fahey, R. E. Dunn, F. L. Moore, R. C. Myers, and B. D. Hall

Abstract

Detailed information on the four-channel Airborne Chromatograph for Atmospheric Trace Species (ACATS-IV), used to measure long-lived atmospheric trace gases, is presented. Since ACATS-IV was last described in the literature, the temporal resolution of some measurements was tripled during 1997–99, chromatography was significantly changed, and data processing improved. ACATS-IV presently measures CCl3F [chlorofluorocarbon (CFC)-11], CCl2FCClF2 (CFC-113), CH3CCl3 (methyl chloroform), CCl4 (carbon tetrachloride), CH4 (methane), H2 (hydrogen), and CHCl3 (chloroform) every 140 s, and N2O (nitrous oxide), CCl2F2 (CFC-12), CBrClF2 (halon-1211), and SF6 (sulfur hexafluoride) every 70 s. An in-depth description of the instrument operation, standardization, calibration, and data processing is provided, along with a discussion of precision and uncertainties of ambient air measurements for several airborne missions.

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Matt C. Wilbanks, Sandra E. Yuter, Simon P. de Szoeke, W. Alan Brewer, Matthew A. Miller, Andrew M. Hall, and Casey D. Burleyson

Abstract

Density currents (i.e., cold pools or outflows) beneath marine stratocumulus clouds are characterized using 30 days of ship-based observations obtained during the 2008 Variability of American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx) in the southeast Pacific. An air density increase criterion applied to the Improved Meteorological (IMET) sensor data identified 71 density current front, core (peak density), and tail (dissipating) zones. The similarity in speeds of the mean density current propagation speed (1.8 m s−1) and the mean cloud-level advection relative to the surface layer wind (1.9 m s−1) allowed drizzle cells to deposit elongated density currents in their wakes. Scanning Doppler lidar captured prefrontal updrafts with a mean intensity of 0.91 m s−1 and an average vertical extent of 800 m. Updrafts were often surmounted by low-lying shelf clouds not connected to the overlying stratocumulus cloud. The observed density currents were 5–10 times thinner and weaker than typical continental thunderstorm cold pools. Nearly 90% of density currents were identified when C-band radar estimated areal average rain rates exceeded 1 mm day−1 over a 30-km diameter. Rather than peaking when rain rates were highest overnight, density current occurrence peaks between 0600 and 0800 local solar time when enhanced local drizzle co-occurred with shallow subcloud dry and stable layers. The dry layers may have contributed to density current formation by enhancing subcloud evaporation of drizzle. Density currents preferentially occurred in a large region of predominantly open cells but also occurred in regions of closed cells.

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W. J. Koshak, R. J. Solakiewicz, R. J. Blakeslee, S. J. Goodman, H. J. Christian, J. M. Hall, J. C. Bailey, E. P. Krider, M. G. Bateman, D. J. Boccippio, D. M. Mach, E. W. McCaul, M. F. Stewart, D. E. Buechler, W. A. Petersen, and D. J. Cecil

Abstract

Two approaches are used to characterize how accurately the north Alabama Lightning Mapping Array (LMA) is able to locate lightning VHF sources in space and time. The first method uses a Monte Carlo computer simulation to estimate source retrieval errors. The simulation applies a VHF source retrieval algorithm that was recently developed at the NASA Marshall Space Flight Center (MSFC) and that is similar, but not identical to, the standard New Mexico Tech retrieval algorithm. The second method uses a purely theoretical technique (i.e., chi-squared Curvature Matrix Theory) to estimate retrieval errors. Both methods assume that the LMA system has an overall rms timing error of 50 ns, but all other possible errors (e.g., anomalous VHF noise sources) are neglected. The detailed spatial distributions of retrieval errors are provided. Even though the two methods are independent of one another, they nevertheless provide remarkably similar results. However, altitude error estimates derived from the two methods differ (the Monte Carlo result being taken as more accurate). Additionally, this study clarifies the mathematical retrieval process. In particular, the mathematical difference between the first-guess linear solution and the Marquardt-iterated solution is rigorously established thereby explaining why Marquardt iterations improve upon the linear solution.

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P. J. Sellers, B. W. Meeson, J. Closs, J. Collatz, F. Corprew, D. Dazlich, F. G. Hall, Y. Kerr, R. Koster, S. Los, K. Mitchell, J. McManus, D. Myers, K.-J. Sun, and P. Try

A comprehensive series of global datasets for land-atmosphere models has been collected, formatted to a common grid, and released on a set of CD-ROMs. This paper describes the motivation for and the contents of the dataset.

In June of 1992, an interdisciplinary earth science workshop was convened in Columbia, Maryland, to assess progress in land-atmosphere research, specifically in the areas of models, satellite data algorithms, and field experiments. At the workshop, representatives of the land-atmosphere modeling community defined a need for global datasets to prescribe boundary conditions, initialize state variables, and provide near-surface meteorological and radiative forcings for their models. The International Satellite Land Surface Climatology Project (ISLSCP), a part of the Global Energy and Water Cycle Experiment, worked with the Distributed Active Archive Center of the National Aeronautics and Space Administration Goddard Space Flight Center to bring the required datasets together in a usable format. The data have since been released on a collection of CD-ROMs.

The datasets on the CD-ROMs are grouped under the following headings: vegetation; hydrology and soils; snow, ice, and oceans; radiation and clouds; and near-surface meteorology. All datasets cover the period 1987–88, and all but a few are spatially continuous over the earth's land surface. All have been mapped to a common 1° × 1° equal-angle grid. The temporal frequency for most of the datasets is monthly. A few of the near-surface meteorological parameters are available both as six-hourly values and as monthly means.

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David P. Bacon, Nash’at N. Ahmad, Zafer Boybeyi, Thomas J. Dunn, Mary S. Hall, Pius C. S. Lee, R. Ananthakrishna Sarma, Mark D. Turner, Kenneth T. Waight III, Steve H. Young, and John W. Zack

Abstract

The Operational Multiscale Environment Model with Grid Adaptivity (OMEGA) and its embedded Atmospheric Dispersion Model is a new atmospheric simulation system for real-time hazard prediction, conceived out of a need to advance the state of the art in numerical weather prediction in order to improve the capability to predict the transport and diffusion of hazardous releases. OMEGA is based upon an unstructured grid that makes possible a continuously varying horizontal grid resolution ranging from 100 km down to 1 km and a vertical resolution from a few tens of meters in the boundary layer to 1 km in the free atmosphere. OMEGA is also naturally scale spanning because its unstructured grid permits the addition of grid elements at any point in space and time. In particular, unstructured grid cells in the horizontal dimension can increase local resolution to better capture topography or the important physical features of the atmospheric circulation and cloud dynamics. This means that OMEGA can readily adapt its grid to stationary surface or terrain features, or to dynamic features in the evolving weather pattern. While adaptive numerical techniques have yet to be extensively applied in atmospheric models, the OMEGA model is the first model to exploit the adaptive nature of an unstructured gridding technique for atmospheric simulation and hence real-time hazard prediction. The purpose of this paper is to provide a detailed description of the OMEGA model, the OMEGA system, and a detailed comparison of OMEGA forecast results with data.

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Brian A. Klimowski, Robert Becker, Eric A. Betterton, Roelof Bruintjes, Terry L. Clark, William D. Hall, Brad W. Orr, Robert A. Kropfli, Paivi Piironen, Roger F. Reinking, Dennis Sundie, and Taneil Uttal

The 1995 Arizona Program was a field experiment aimed at advancing the understanding of winter storm development in a mountainous region of central Arizona. From 15 January through 15 March 1995, a wide variety of instrumentation was operated in and around the Verde Valley southwest of Flagstaff, Arizona. These instruments included two Doppler dual-polarization radars, an instrumented airplane, a lidar, microwave and infrared radiometers, an acoustic sounder, and other surface-based facilities. Twenty-nine scientists from eight institutions took part in the program. Of special interest was the interaction of topographically induced, storm-embedded gravity waves with ambient upslope flow. It is hypothesized that these waves serve to augment the upslope-forced precipitation that falls on the mountain ridges. A major thrust of the program was to compare the observations of these winter storms to those predicted with the Clark-NCAR 3D, nonhydrostatic numerical model.

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W. J. Gutowski Jr, P. A. Ullrich, A. Hall, L. R. Leung, T. A. O’Brien, C. M. Patricola, R. W. Arritt, M. S. Bukovsky, K. V. Calvin, Z. Feng, A. D. Jones, G. J. Kooperman, E. Monier, M. S. Pritchard, S. C. Pryor, Y. Qian, A. M. Rhoades, A. F. Roberts, K. Sakaguchi, N. Urban, and C. Zarzycki

ABSTRACT

Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions.

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