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J. L. Haferman, W. F. Krajewski, and T. F. Smith


Several multifrequency techniques for passive microwave estimation of precipitation based on the absorption and scattering properties of hydrometeors have been proposed in the literature. In the present study, plane-parallel limitations are overcome by using a model based on the discrete-ordinates method to solve the radiative transfer equation in three-dimensional rectangular domains. This effectively accounts for the complexity and variety of radiation problems encountered in the atmosphere. This investigation presents results for plane-parallel and three-dimensional radiative transfer for a precipitating system, discusses differences between these results, and suggests possible explanations for these differences.

Microphysical properties were obtained from the Colorado State University Regional Atmospheric Modeling System and represent a hailstorm observed during the 1986 Cooperative Huntsville Meteorological Experiment. These properties are used as input to a three-dimensional radiative transfer model in order to simulate satellite observation of the storm. The model output consists of upwelling brightness temperatures at several of the frequencies on the Special Sensor Microwave/Imager. The radiative transfer model accounts for scattering and emission of atmospheric gases and hydrometeors in liquid and ice phases.

Brightness temperatures obtained from the three-dimensional model of this investigation indicate that horizontal inhomogeneities give rise to brightness temperature fields that can be quite different from fields obtained using plane-parallel radiative transfer theory. These differences are examined for various resolutions of the satellite sensor field of view. In addition, the issue of boundary conditions for three-dimensional atmospheric radiative transfer is addressed.

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J. L. Haferman, E. N. Anagnostou, D. Tsintikidis, W. F. Krajewski, and T. F. Smith


A precipitation retrieval algorithm based on the application of a 3D radiative transfer model to a hybrid physical-stochastic 3D cloud model is described. The cloud model uses a statistical rainfall clustering scheme to generate 3D cloud structure while ensuring that the stochastically generated quantities remain physically plausible. The radiative transfer model is applied to the cloud structures to simulate satellite remotely sensed upwelling microwave brightness temperatures TB's. Regression-derived relationships between model TB's and surface rainfall rates for Special Sensor Microwave/Imager (SSM/I) frequencies are used as the foundation of the retrieval algorithm, which is valid over oceans. A case study calibrates the retrieval algorithm to the European Centre for Medium-Range Weather Forecasts (ECMWF) numerical weather prediction model and applies the algorithm to SSM/I data obtained during the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. Comparisons between the satellite-derived precipitation amounts and radar-derived amounts, at a spatial resolution of approximately 55 km, give correlations of about 0.7 for instantaneous rain rates and 0.634 for monthly accumulations. Although the satellite-derived totals are reasonably well correlated with the radar totals, they also appear to contain a relatively large positive bias, which may in part be due to the ECMWF tuning. However, optical rain gauge measurements are lager than both the satellite- and radar-derived amounts, casting uncertainty into the level of bias of the satellite algorithm. Finally, an important aspect of 3D radiative transfer in precipitating systems is illustrated by demonstrating that satellite viewing angle effects realized in the simulation framework also appear to be present in empirical relations between SSM/I TB's and radar-derived surface rainfall rates.

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H. W. Loescher, J. M. Jacobs, O. Wendroth, D. A. Robinson, G. S. Poulos, K. McGuire, P. Reed, B. P. Mohanty, J. B. Shanley, and W. Krajewski

The Consortium of Universities for the Advancement of Hydrologic Sciences, Inc., established the Hydrologic Measurement Facility to transform watershed-scale hydrologic research by facilitating access to advanced instrumentation and expertise that would not otherwise be available to individual investigators. We outline a committee-based process that determined which suites of instrumentation best fit the needs of the hydrological science community and a proposed mechanism for the governance and distribution of these sensors. Here, we also focus on how these proposed suites of instrumentation can be used to address key scientific challenges, including scaling water cycle science in time and space, broadening the scope of individual subdisciplines of water cycle science, and developing mechanistic linkages among these subdisciplines and spatiotemporal scales.

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Steven V. Vasiloff, Dong-Jun Seo, Kenneth W. Howard, Jian Zhang, David H. Kitzmiller, Mary G. Mullusky, Witold F. Krajewski, Edward A. Brandes, Robert M. Rabin, Daniel S. Berkowitz, Harold E. Brooks, John A. McGinley, Robert J. Kuligowski, and Barbara G. Brown

Accurate quantitative precipitation estimates (QPE) and very short term quantitative precipitation forecasts (VSTQPF) are critical to accurate monitoring and prediction of water-related hazards and water resources. While tremendous progress has been made in the last quarter-century in many areas of QPE and VSTQPF, significant gaps continue to exist in both knowledge and capabilities that are necessary to produce accurate high-resolution precipitation estimates at the national scale for a wide spectrum of users. Toward this goal, a national next-generation QPE and VSTQPF (Q2) workshop was held in Norman, Oklahoma, on 28–30 June 2005. Scientists, operational forecasters, water managers, and stakeholders from public and private sectors, including academia, presented and discussed a broad range of precipitation and forecasting topics and issues, and developed a list of science focus areas. To meet the nation's needs for the precipitation information effectively, the authors herein propose a community-wide integrated approach for precipitation information that fully capitalizes on recent advances in science and technology, and leverages the wide range of expertise and experience that exists in the research and operational communities. The concepts and recommendations from the workshop form the Q2 science plan and a suggested path to operations. Implementation of these concepts is expected to improve river forecasts and flood and flash flood watches and warnings, and to enhance various hydrologic and hydrometeorological services for a wide range of users and customers. In support of this initiative, the National Mosaic and Q2 (NMQ) system is being developed at the National Severe Storms Laboratory to serve as a community test bed for QPE and VSTQPF research and to facilitate the transition to operations of research applications. The NMQ system provides a real-time, around-the-clock data infusion and applications development and evaluation environment, and thus offers a community-wide platform for development and testing of advances in the focus areas.

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