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X-ray Variability Constraints on Compton Cloud Models of Cygnus X-1

We have now completed this work, and all related publications have either appeared in print or are currently in press. A list of these publications is given below. There have been essentially three works that have arisen from this proposal. Spectral analysis of the data is presented in Dove et al. (1998a). Timing analysis is presented in Nowak et al. (1999a). Theoretical implications of the data analysis are discussed in Nowak et al. (1999b). Preliminary versions of all these works were presented at various conferences, and are reported in Nowak et al. (1997, 1998), Wilms et al. (1997), and Dove et al. (1998b). The grant was predominantly used for salary support for Dr. Michael Nowak, Dr. James Dove, and Dr. J. Wilms during the course of these projects. Grant funds were also used for Dr. Nowak to travel to Caltech to perform data analysis with Dr. Brian Vaughan, and for Dr. Wilms to visit JILA, University of Colorado, where much of this work was performed.

Vaughan, Brian↗

Parameterization of the Vertical Variability of Tropical Cirrus Cloud Microphysical and Optical Properties

Cloud Integrating Nephelometers (CIN) were flown on the U. North Dakota Citation aircraft and the NASA WB-57 aircraft for the purpose of measuring in-situ the optical extinction coefficient and the asymmetry parameter (g) at a wavelength of 635 nm of primarily ice particles encountered during the NASA CRYSTAL-FACE study of large cumulus clouds (Cu) and their anvils found in the southern Florida region. The probes performance was largely successful and produced archived data for vertical profiles of extinction, asymmetry parameter, and effective radius (Re), the latter being obtained by combining CIN and CVI (total water; Oregon State U.) measurements. Composites of the CIN and CVI data describing the average microphysical and optical behavior of the Cu and their anvils showed the following: The extinction increases with height as a result of the size of the particles also decreasing with height as shown by the Re measurements; near the top of anvils the size of the primary ice particles is about 10-um radius; and the value of g does not vary significantly with height and has a mean value of about 0.73 consistent with the idea that ambient ice crystals are primarily of complex shape and reflect solar radiation more efficiently than particles of pristine crystal shape. Other observations include: The g measurements were found to be an indicator of the phase of the cloud permitting identification of the clouds with water droplets, rain, and ice; visual ranges as small as several tens of meters were occasionally found in "extinction cores" that coincided with strong updraft cores; and comparison of the cloud probes on the Citation showed significant disagreement.

Gerber, Hermann E.↗

Parameterizations of the Vertical Variability of Tropical Cirrus Cloud Microphysical and Optical Properties

Our multi-investigator effort was targeted at the following areas of interest to CRYSTAL-FACE: (1) the water budgets of anvils, (2) parameterizations of the particle size distributions and related microphysical and optical properties (3) characterizations of the primary ice particle habits, (4) the relationship of the optical properties to the microphysics and particle habits, and (5) investigation of the ice-nuclei types and mechanisms in anvil cirrus. Dr. Twohy's effort focused on (l), (2), and (5), with the measurement and analysis of ice water content and cirrus residual nuclei using the counterflow virtual impactor (CVI).

Twohy, Cynthia↗

Understanding Seasonal Variability in Thin Cirrus Clouds from Continuous MPLNET Observations at GSFC in 2012

Optically thin cirrus cloud (optical depth < 0.3) net radiative forcing represents one of the primary uncertainties in climate feedback, as sub-visible clouds play a fundamental role in atmospheric radiation balance and climate change. A lidar is a very sensitive optical device to detect clouds with an optical depth as low as 10-4. In this paper we assess the daytime net radiative forcing of sub-visible cirrus clouds detected at Goddard Space Flight Center, a permanent observational site of the NASA Micro Pulse Lidar Network in 2012. Depending on their height, season and hour of the day, the solar albedo effect can outweigh the infrared greenhouse effect, cooling the earth atmosphere system rather than warming it exclusively. As result, based on latitude, the net forcing of sub-visible cirrus clouds can be more accurately parameterized in climate models.

Lolli, Simone↗

Cloud-encounter and particle-concentration variabilities from GASP data

Summary statistics, tabulations, and variability studies are presented for cloud encounter and particle concentration data taken as part of the NASA global atmospheric sampling program. Cloud encounter was experienced in about 15 percent of the data samples; however, the percentage varies with season, latitude, and altitude (particularly distance from the tropopause). In agreement with classical storm models, the data show more clouds in the upper troposphere in anticyclones than in cyclones. The concentration of particles with a diameter greater than 3 micron also varies with time and location, depending primarily on the horizontal extent of cloudiness. Some examples of the application of the statistical data to the estimation of the frequency of cloud encounter and laminar flow loss to be expected on long range airline routes are also presented.

Nastrom, G. D.↗

A New Statistically based Autoconversion rate Parameterization for use in Large-Scale Models

The autoconversion rate is a key process for the formation of precipitation in warm clouds. In climate models, physical processes such as autoconversion rate, which are calculated from grid mean values, are biased, because they do not take subgrid variability into account. Recently, statistical cloud schemes have been introduced in large-scale models to account for partially cloud-covered grid boxes. However, these schemes do not include the in-cloud variability in their parameterizations. In this paper, a new statistically based autoconversion rate considering the in-cloud variability is introduced and tested in three cases using the Canadian Single Column Model (SCM) of the global climate model. The results show that the new autoconversion rate improves the model simulation, especially in terms of liquid water path in all three case studies.

Lin, Bing↗

Clouds in ECMWF's 30 KM Resolution Global Atmospheric Forecast Model (TL639)

Global models of the general circulation of the atmosphere resolve a wide range of length scales, and in particular cloud structures extend from planetary scales to the smallest scales resolvable, now down to 30 km in state-of-the-art models. Even the highest resolution models do not resolve small-scale cloud phenomena seen, for example, in Landsat and other high-resolution satellite images of clouds. Unresolved small-scale disturbances often grow into larger ones through non-linear processes that transfer energy upscale. Understanding upscale cascades is of crucial importance in predicting current weather, and in parameterizing cloud-radiative processes that control long term climate. Several movie animations provide examples of the temporal and spatial variation of cloud fields produced in 4-day runs of the forecast model at the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, England, at particular times and locations of simultaneous measurement field campaigns. model resolution is approximately 30 km horizontally (triangular truncation TL639) with 31 vertical levels from surface to stratosphere. Timestep of the model is about 10 minutes, but animation frames are 3 hours apart, at timesteps when the radiation is computed. The animations were prepared from an archive of several 4-day runs at the highest available model resolution, and archived at ECMWF. Cloud, wind and temperature fields in an approximately 1000 km X 1000 km box were retrieved from the archive, then approximately 60 Mb Vis5d files were prepared with the help of Graeme Kelly of ECMWF, and were compressed into MPEG files each less than 3 Mb. We discuss the interaction of clouds and radiation in the model, and compare the variability of cloud liquid as a function of scale to that seen in cloud observations made in intensive field campaigns. Comparison of high-resolution global runs to cloud-resolving models, and to lower resolution climate models is leading to better understanding of the upscale cascade and suggesting new cloud-radiation parameterizations for climate models.

Cahalan, R. F.↗

An Overview of Atmospheric Features Over the Western North Atlantic Ocean and North American East Coast—Part 2: Circulation, Boundary Layer, and Clouds

The Western North Atlantic Ocean (WNAO) is a complex land-ocean-atmosphere system that experiences a wide range of atmospheric phenomena, which in turn drive unique aerosol transport pathways, cloud morphologies, and boundary layer variability. This work, Part 2 of a 2-part paper series, provides an overview of the atmospheric circulation, boundary layer variability, three-dimensional cloud structure, and precipitation over the WNAO; the companion paper (Part 1) focused on chemical characterization of aerosol, gas, and wet deposition. Seasonal changes in the circulation and sea surface temperature explain a clear transition in cloud morphologies from small shallow cumulus clouds, convective clouds, and tropical storms in summer, to stratus/stratocumulus and multi-layer cloud systems associated with winter storms. Synoptic variability in cloud fields is estimated using satellite-based weather states, and the role of postfrontal conditions (cold-air outbreaks) in the development of stratiform clouds is further analyzed. Precipitation is persistent over the ocean, with a regional peak over the Gulf Stream path, where offshore sea surface temperature gradients are large and surface fluxes reach a regional peak. Satellite data show a clear annual cycle in cloud droplet number concentration along the coast in winter, and minima in summer, suggesting a marked annual cycle in aerosol-cloud interactions. The performance of four climate models are assessed against satellite cloud retrievals. The models qualitatively reproduce the annual cycle in cloud cover and liquid water path, but with large discrepancies across models, especially in the extra-tropics. The paper concludes with a summary of outstanding issues and recommendations for future work.

54 ENVIRONMENTAL SCIENCES↗

An Overview of Atmospheric Features Over the Western North Atlantic Ocean and North American East Coast – Part 2: Circulation, Boundary Layer, and Clouds

The Western North Atlantic Ocean (WNAO) is a complex land-ocean-atmosphere system that experiences a broad range of atmospheric phenomena, which in turn drive unique aerosol transport pathways, cloud morphologies, and boundary layer variability. This work, Part 2 of a 2-part paper series, provides an overview of the atmospheric circulation, boundary layer variability, three-dimensional cloud structure, and precipitation over the WNAO; the companion paper (Part 1) focused on chemical characterization of aerosols, gases, and wet deposition.Seasonal changes in atmospheric circulation and sea surface temperature explain a clear transition in cloud morphologies from small shallow cumulus clouds, convective clouds, and tropical storms in summer, to stratus/stratocumulus and multi-layer cloud systems associated with winter storms. Synoptic variability in cloud fields is estimated using satellite-based weather states, and the role of postfrontal conditions (cold-air outbreaks) in the development of stratiform clouds is further analyzed. Precipitation is persistent over the ocean, with a regional peak over the Gulf Stream path, where offshore sea surface temperature gradients are large and surface fluxes reach a regional peak. Satellite data show a clear annual cycle in cloud droplet number concentration with maxima (minima) along the coast in winter (summer), suggesting a marked annual cycle in aerosol-cloud interactions. Compared with satellite cloud retrievals, four climate models qualitatively reproduce the annual cycle in cloud cover and liquid water path, but with large discrepancies across models, especially in the extra-tropics. The paper concludes with a summary of outstanding issues and recommendations for future work.

David Painemal↗

Cloud-screening for Africa using a geographically and seasonally variable infrared threshold

A spatially variable monthly, infrared cloud-threshold data base has been used to screen cloud-contaminated observations from radiances measured by the NOAA-9 AVHRR over Africa. Cloud-screening through a monthly average infrared threshold based on measured surface air temperature, which is geographically dependent, shows an improvement over using a seasonally and geographically independent thermal cloud threshold of 287 K. It is found that differences in cloud-screening for these two thresholds occur for cases of lower altitude clouds or subpixel clouds where the radiative temperature is higher than the 287 K infrared threshold, yet colder than the variable threshold developed by Stowe et al. (1988) for the Nimbus-7 global cloud climatology. The variable IR threshold is shown to be effective over persistently cloud-covered regions, such as the coastal region of the Gulf of Guinea, but may introduce some erroneous cloud identifications over mountains.

Eck, T. F.↗

July 16, 1987 revisited: Lessons for modelers

A cross pattern was flown by the NCAR Electra in the restricted air space around San Nicolas Island (SNI). There was available a LANDSAT image coincident with the mission. The variability of cloud thickness along the flight track is discussed. The evidence points to variability in the water vapor content above the inversion as the controlling factor. This compounds the difficulty of parameterizing these clouds in General Circulation Models (GCMs). The importance of specifying correctly the upper boundary condition in cloud models is stressed. Particularly, in GCMs, calculating the humidity in the lower layers of the model is crucial for successful parameterization of marine stratocumulus clouds.

Hanson, Howard P.↗

Monte Carlo Bayesian Inference on a Statistical Model of Sub-gridcolumn Moisture Variability Using High-resolution Cloud Observations : Sensitivity Tests and Results - Part II

Part I presented a Monte Carlo Bayesian method for constraining a complex statistical model of GCM sub-gridcolumn moisture variability using high-resolution MODIS cloud data, thereby permitting large-scale model parameter estimation and cloud data assimilation. This part performs some basic testing of this new approach, verifying that it does indeed significantly reduce mean and standard deviation biases with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud top pressure, and that it also improves the simulated rotational-Ramman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the OMI instrument. Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows finite jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. This paper also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in the cloud observables on cloud vertical structure, beyond cloud top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard (1998) provides some help in this respect, by better honoring inversion structures in the background state.

Monte Carlo Bayesian inference↗

Cloud cover estimation: Use of GOES imagery in development of cloud cover data base for insolation assessment

The potential of using digital satellite data to establish a cloud cover data base for the United States, one that would provide detailed information on the temporal and spatial variability of cloud development are studied. Key elements include: (1) interfacing GOES data from the University of Wisconsin Meteorological Data Facility with the Jet Propulsion Laboratory's VICAR image processing system and IBIS geographic information system; (2) creation of a registered multitemporal GOES data base; (3) development of a simple normalization model to compensate for sun angle; (4) creation of a variable size georeference grid that provides detailed cloud information in selected areas and summarized information in other areas; and (5) development of a cloud/shadow model which details the percentage of each grid cell that is cloud and shadow covered, and the percentage of cloud or shadow opacity. In addition, comparison of model calculations of insolation with measured values at selected test sites was accomplished, as well as development of preliminary requirements for a large scale data base of cloud cover statistics.

Huning, J. R.↗

ISCCP results for the FIRE IFO regions and times

The ISCCP analysis of cloud conditions during and in the vicinity of the FIRE cirrus and marine stratus Intensive Field Observations (IFOs) is presented in two forms: the standard climatology product, which is averaged to a nominal 250 km resolution and a pixel-by-pixel version that samples the original data at about 30 km spacing every three hours. These results are based on NOAA-9 and GOES-6 images covering October to November 1986 and July 1987 for the FIRE Extended Area. Comparisons of these results with other FIRE observations will serve to check the accuracy of the clear sky radiances inferred by the ISCCP analysis, which determines the accuracy of the cloud detections. Of more interest is the exploration of the dependence of the inferred cloud properties for direct evaluation of the role of small scale variability of cloud properties on the radiation field. This is illustrated by preliminary results obtained for the scales contained in the ISCCP data. The ISCCP analysis also sets the larger scale context of the FIRE data: (1) comparisons of the clouds occurring in the FIRE IFOs with nearby locations and times are presented, and (2) comparisons of the cloud conditions for the same month in other years are shown.

Rossow, William B.↗