A high-resolution radar data assimilation system is presented for high-resolution numerical weather prediction models. The system is under development at the Naval Research Laboratory for the Navy’s Coupled Ocean–Atmosphere Mesoscale Prediction System. A variational approach is used to retrieve three-dimensional dynamical fields of atmospheric conditions from multiple-Doppler radar observations of radial velocity within a limited area. The methodology is described along with a preliminary evaluation of the impact of assimilated radar data on model forecasts using a case study of a squall line that occurred along the east coast of the United States on 9 May 2003. Results from the experiments show a significant impact from the assimilated radar radial velocity data on the model forecast of not just dynamical but also hydrological fields at all model levels for the duration of the storm. A verification system has also been developed to assess the radar data assimilation impact, and the results show improvements in the three-dimensional wind forecasts but relatively small changes in the prediction of storm locations. This study highlights the need to develop a continuous radar data assimilation system to maximize the impact of the data.
The NOAA/NWS/NCEP/Tropical Prediction Center/National Hurricane Center has sought techniques that use single-Doppler radar data to estimate the tropical cyclone wind field. A cooperative effort with NOAA/Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division and NCAR has resulted in significant progress in developing a method whereby radar display data are used as a proxy for a full-resolution base data and in improving and implementing existing wind retrieval and center-finding techniques. These techniques include the ground-based velocity track display (GBVTD), tracking radar echoes by correlation (TREC), GBVTDsimplex, and the principal component analysis (PCA) methods. The GBVTD and TREC algorithms are successfully applied to the Weather Surveillance Radar-1988 Doppler (WSR-88D) display data of Hurricane Bret (1999) and Tropical Storm Barry (2001). GBVTD analyses utilized circulation center estimates provided by the GBVTD-simplex and PCA methods, whereas TREC analyses utilized wind center estimates provided by radar imagery and aircraft measurements. GBVTD results demonstrate that the use of the storm motion as a proxy for the mean wind is not always appropriate and that results are sensitive to the accuracy of the circulation center estimate. TREC results support a previous conjecture that the use of polar coordinates would produce improved wind retrievals for intense tropical cyclones. However, there is a notable effect in the results when different wind center estimates are used as the origin of coordinates. The overall conclusion is that GBVTD and TREC have the ability to retrieve the intensity of a tropical cyclone with an accuracy of ϳ2 m s Ϫ1 or better if the wind intensity estimates from individual analyses are averaged together.
A high-resolution data assimilation system is under development at the Naval Research Laboratory (NRL). The objective of this development is to assimilate high-resolution data, especially those from Doppler radars, into the U.S. Navy’s Coupled Ocean–Atmosphere Mesoscale Prediction System to improve the model’s capability and accuracy in short-term (0–6 h) prediction of hazardous weather for nowcasting. A variational approach is used in this system to assimilate the radar observations into the model. The system is upgraded in this study with new capabilities to assimilate not only the radar radial-wind data but also reflectivity data. Two storm cases are selected to test the upgraded system and to study the impact of radar data assimilation on model forecasts. Results from the data assimilation experiments show significant improvements in storm prediction especially when both radar radial-wind and reflectivity observations are assimilated and the analysis incremental fields are adequately constrained by the model’s dynamics and properly adjusted to satisfy the model’s thermodynamical balance.
Atmospheric remote sensing has played a pivotal role in the increasingly sophisticated representation of clouds in the numerical models used to assess global and regional climate change. This has been accomplished because the underlying bulk cloud properties can be derived from a statistical analysis of the returned microwave signals scattered by a diverse ensemble comprised of numerous cloud hydrometeors. A new Doppler radar, previously used to track small debris particles shed from the NASA space shuttle during launch, is shown to also have the capacity to detect individual cloud hydrometeors in the free atmosphere. Similar to the traces left behind on film by subatomic particles, larger cloud particles were observed to leave a well-defined radar signature (or streak), which could be analyzed to infer the underlying particle properties. We examine the unique radar and environmental conditions leading to the formation of the radar streaks and develop a theoretical framework which reveals the regulating role of the background radar reflectivity on their observed characteristics. This main expectation from theory is examined through an analysis of the drop properties inferred from radar and in situ aircraft measurements obtained in two contrasting regions of an observed multicellular storm system. The observations are placed in context of the parent storm circulation through the use of the radar's unique high-resolution waveforms, which allow the bulk and individual hydrometeor properties to be inferred at the same time.microphysics | convection | cumulonimbus | backscatter
Descriptions of the experimental design and research highlights obtained from a series of four multiagency field projects held near Cape Canaveral, Florida, are presented. The experiments featured a 3 MW, dual-polarization, C-band Doppler radar that serves in a dual capacity as both a precipitation and cloud radar. This duality stems from a combination of the radar’s high sensitivity and extremely small-resolution volumes produced by the narrow 0.22° beamwidth and the 0.543 m along-range resolution. Experimental highlights focus on the radar’s real-time aircraft tracking capability as well as the finescale reflectivity and eddy structure of a thin nonprecipitating stratus layer. Examples of precipitating storm systems focus on the analysis of the distinctive and nearly linear radar reflectivity signatures (referred to as “streaks”) that are caused as individual hydrometeors traverse the narrow radar beam. Each streak leaves a unique radar reflectivity signature that is analyzed with regard to estimating the underlying particle properties such as size, fall speed, and oscillation characteristics. The observed along-streak reflectivity oscillations are complex and discussed in terms of diameter-dependent drop dynamics (oscillation frequency and viscous damping time scales) as well as radar-dependent factors governing the near-field Fresnel radiation pattern and inferred drop–drop interference.
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