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P. B. Roohr and T. H. Vonder Haar

Abstract

Lightning Positioning and Tracking System (LPATS) data received by the Cooperative Institute for Research in the Atmosphere via a real-time weather data network were used to study the temporal variability of lightning for a frontal system and hurricane that affected the United States in 1989. Our comparison of these data with GOES-7 imagery revealed that lightning data can help define the development, linearity, and maximum intensity of a frontal band as seen with the correlation of currents discharged by lightning to ground with associated IR temperature fields. Lightning data also revealed a dramatic increase in convection equatorward of Hurricane Chantal's vortex upon her rapid intensification and landfall, and the heavy rainfall amounts associated with the tropical storm correlated to areas of rather frequent lightning activity west of Galveston, Texas, on 1 August 1989.

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V. E. Suomi and T. H. Vonder Haar

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No abstract available.

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T. H. Vonder Haar and K. J. Hanson

Abstract

A combination of measurements from satellites and surface stations show that, although more solarenergy is absorbed in tropical regions than previously believed, most of this energy is added to the oceanrather than the atmosphere.

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T. Vukicevic, M. Sengupta, A. S. Jones, and T. Vonder Haar

Abstract

This study addresses the problem of four-dimensional (4D) estimation of a cloudy atmosphere on cloud-resolving scales using satellite remote sensing measurements. The motivation is to develop a methodology for accurate estimation of cloud properties and the associated atmospheric environment on small spatial scales but over large regions to aid in better understanding of the clouds and their role in the atmospheric system. The problem is initially approached by the study of the assimilation of the Geostationary Operational Environmental Satellite (GOES) imager observations into a cloud-resolving model with explicit bulk cloud microphysical parameterization. A new 4D variational data assimilation (4DVAR) research system with the cloud-resolving capability is applied to a case of a multilayered cloud evolution without convection. In the experiments the information content of the IR window channels is addressed as well as the sensitivity of estimation to lateral boundary condition errors, model first guess, decorrelation length in the background statistical error model, and the use of a generic linear model error. The assimilation results are compared with independent observations from the Atmospheric Radiation Measurement (ARM) central facility archive.

The modeled 3D spatial distribution and short-term evolution of the ice cloud mass is significantly improved by the assimilation of IR window channels when the model already contains conditions for the ice cloud formation. The assimilated ice cloud in this case is in good agreement with the independent cloud radar measurements. The simulation of liquid clouds below thick ice clouds is not influenced by the IR window observations. The assimilation results clearly demonstrate that increasing the observational constraint from individual to combined channel measurements and from less to more frequent observation times systematically improves the assimilation results. The experiments with the model error indicate that the current specification of this error in the form of a generic linear forcing, which was adopted from other data assimilation studies, is not suitable for the cloud-resolving data assimilation. Instead, a parameter estimation approach may need to be explored in the future. The experiments with varying decorrelation lengths suggest the need to use the model horizontal grid spacing that is several times smaller than the GOES imager native resolution to achieve equivalent spatial variability in the assimilation.

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B. C. Carissimo, A. H. Oort, and T. H. Vonder Haar

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The poleward energy transports in the atmosphere–ocean system are estimated for the annual mean and the four seasons based on satellite measurements of the net radiation balance at the top of the atmosphere, atmospheric transports of energy at the north or south poles various types of corrections had to be made, so that the global balances are maintained. This also enabled us to estimate the uncertainties in the procedures used. The uncertainties found are similar to those reported by Hastenrath based on different satellite data sets but using the same correction method.

Finally, oceanic heat transports are computed for the annual mean and seasons. One of the crucial terms in the heat budget, the interseasonal storage of energy in the oceans, is estimated for three different layers 0–112, 0–552 and 0–550 m, enabling a further error estimate in the inferred oceanic heat transports.

The present results confirm the presence of a strong annual cycle in the transport of energy by the oceans.

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T. Vukicevic, T. Greenwald, M. Zupanski, D. Zupanski, T. Vonder Haar, and A. S. Jones

Abstract

This study focuses on cloudy atmosphere state estimation from high-resolution visible and infrared satellite remote sensing measurements and a mesoscale model with explicit cloud prediction. The cloud state is defined as 3D spatially distributed hydrometeors characterized with microphysical properties: mixing ratio, number concentration, and size distribution. The Geostationary Operational Environmental Satellite-9 (GOES-9) imager visible and infrared measurements were used in a new four-dimensional variational data assimilation (4DVAR) mesoscale algorithm for a warm continental stratus cloud system case to test the impact of these observations on the cloud simulation. The new data assimilation algorithm includes the Regional Atmospheric Modeling System (RAMS) with explicit cloud state prediction, the associated adjoint system, and an observational operator for forward and adjoint integrations of the GOES radiances. The results show positive impact of GOES imager measurements on the 3D cloud short-term simulation during and after the assimilation. The impact was achieved through sensitivity of the radiances to the cloud droplet mixing ratio at observation time and a 4D correlation between the cloud and atmospheric thermal and dynamical environment in the forecast model. The dynamical response to the radiance observations was through enhanced large mesoscale vertical mixing while horizontal advection was weak in the case of stable continental stratus evolution.

Although the current experiments show measurable positive impact of the cloudy radiance measurements on the stratus cloud simulation, they clearly suggest the need to further address the problem of negative cloud cover forecast errors. These errors were only weakly corrected in the current study because of the small sensitivity of the visible and infrared window radiances to the cloud-free atmosphere.

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T. Koyama, T. Vukicevic, M. Sengupta, T. Vonder Haar, and A. S. Jones

Abstract

Information content analysis of the Geostationary Operational Environmental Satellite (GOES) sounder observations in the infrared was conducted for use in satellite data assimilation. Information content is defined as a first-order response of the top-of-atmosphere brightness temperature to perturbations of simulated temperature and humidity profiles, obtained from a cloud-resolving model, both in the presence and absence of clouds. Sensitivity to the perturbations was numerically evaluated using an observational operator for visible and infrared radiative transfer developed within a research satellite data assimilation system. The vertical distribution of the sensitivities was analyzed as a function of cloud optical thickness covering the range from a cloud-free scene to an optically thick cloud. The clear-sky sensitivities to temperature and humidity perturbations for each channel are representative of the corresponding channel weighting functions for a clear-sky case. For optically thin–moderate ice clouds, the vertical distributions of the sensitivities resemble clear-sky results, indicating that the use of infrared sounding observations in data assimilation can potentially improve temperature and humidity profiles below those clouds. This result is significant, as GOES infrared sounder data have until now only been used in cloud-cleared scenes. It is expected that the use of sounder data in data assimilation, even in the presence of optically thin to moderate high clouds, will help reduce errors in temperature and water vapor mixing ratio profiles below the clouds.

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T. H. Vonder Haar, A. C. Meade, R. J. Craig, and D. L. Reinke

Abstract

Advanced software routines have been developed for digital imaging systems to obtain three- and four- dimensional computer-generated images from meteorological satellite, radar, and conventional data. Time sequences of these digital images provide a truly four-dimensional view of evolving atmospheric conditions. Applications of this technique for convective storms research and teaching, for forecaster information, and for pilot briefing are presented.

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John M. Forsythe, Jason B. Dodson, Philip T. Partain, Stanley Q. Kidder, and Thomas H. Vonder Haar

Abstract

The NOAA operational total precipitable water (TPW) anomaly product is available to forecasters to display percentage of normal TPW in real time for applications like heavy precipitation forecasts. In this work, the TPW anomaly is compared to multilayer cloud frequency and vertical structure. The hypothesis is tested that the TPW anomaly is reflective of changes in cloud vertical distribution, and that anomalously moist atmospheres have more and deeper clouds, while dry atmospheres have fewer and thinner clouds. Cloud vertical occurrence profiles from the CloudSat 94-GHz radar and the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) are composited according to TPW anomaly for summer and winter from 2007 to 2010. Three geographic regions are examined: the North Pacific (NPAC), the tropical east Pacific (Niño), and the Mississippi Valley (MSVL), which is a land-only region. Cloud likelihood increases as TPW anomaly values increase beyond 100% over MSVL and Niño. Over NPAC, shallow boundary layer cloud occurrence is not a function of TPW anomaly, while high clouds and deep clouds throughout the troposphere are more likely at higher TPW anomalies. In the Niño region, boundary layer clouds grow vertically as the TPW anomaly increases, and the anomaly range is smaller than in the midlatitudes. In summer, the MSVL region resembles Niño, but boundary layer clouds are observed less frequently than expected. The wintertime MSVL results do not show any compelling relationship, perhaps because of the difficulties in computing TPW anomaly in a very dry atmosphere.

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T. H. Vonder Haar, C. F. Shih, D. L. Randel, J. J. Toth, D. N. Allen, R. A. Pielke, and R. Green

A new weather laboratory for teaching and applied research has been developed at Colorado State University (CSU). The laboratory uses DEC workstations and also hosts various microcomputers via a local area network to interface with the Cooperative Institute for Research in the Atmosphere (CIRA) computer system shared by the Department of Atmospheric Science. This computer system centers on a cluster of VAX 700-class computers and includes several user-interactive subsystems, such as the Interactive Research Imaging System (IRIS), Direct Readout Satellite Earth Station (DRSES), and a weather display system (using General Meteorological Software Package [GEMPAK]). Through direct communication lines, the VAX 700-class computer cluster is linked to the mainframe computers of CSU, National Center for Atmospheric Research (NCAR), and National Oceanic and Atmospheric Administration/Environmental Research Laboratory (NOAA/ERL). Since the computer system has such broad interface with other computer systems, a unique feature of the new weather laboratory is its capability to provide not only current weather data but also real-time satellite, radar, mesonet, and profiler data. Examples of the products of the new weather laboratory are presented. Options and trade-offs encountered in the design of the new weather laboratory are discussed.

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