J. F. Kimpel

Bio: J. F. Kimpel is an academic researcher. The author has contributed to research in topics: Radar engineering details & Phased array. The author has an hindex of 1, co-authored 1 publications receiving 225 citations.

Agile-Beam Phased Array Radar for Weather Observations

Abstract: Weather radars with conventional antenna cannot provide desired volume scan updates at intervals of one minute or less, which is essential for significant improvement in warning lead time of impending storm hazards. The agile-beam multimission phased array radar (MPAR) discussed herein is one potential candidate that can provide faster scanning. It also offers a unique potential for multipurpose use to not only sample weather, but support air traffic needs and track noncooperative airplanes, thus making it an affordable option. After introducing the basic idea behind electronic beam steering, the needs for frequent observations of convective weather are explained. Then, advantages of the phased array radar (PAR) for weather monitoring and improving data quality are examined. To explore and develop weather-related applications of the PAR, a National Weather Radar Testbed (NWRT) has been established in Norman, Oklahoma. The NWRT's main purpose is to address the advanced capabilities anticipated within the n...

Convective-scale warn-on-forecast system: A vision for 2020

Abstract: The National Oceanic and Atmospheric Administration's (NOAA's) National Weather Service (NWS) issues warnings for severe thunderstorms, tornadoes, and flash floods because these phenomena are a threat to life and property. These warnings are presently based upon either visual confirmation of the phenomena or the observational detection of proxy signatures that are largely based upon radar observations. Convective-scale weather warnings are unique in the NWS, having little reliance on direct numerical forecast guidance. Because increasing severe thunderstorm, tornado, and flash-flood warning lead times are a key NOAA strategic mission goal designed to reduce the loss of life, injury, and economic costs of these high-impact weather phenomena, a new warning paradigm is needed in which numerical model forecasts play a larger role in convective-scale warnings. This new paradigm shifts the warning process from warn on detection to warn on forecast, and it has the potential to dramatically increase warning lead ...

Confronting the Challenge of Modeling Cloud and Precipitation Microphysics

Abstract: In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth's atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle-based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next-generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process-level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle-based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.

Rapid Sampling of Severe Storms by the National Weather Radar Testbed Phased Array Radar

Abstract: A key advantage of the National Weather Radar Testbed Phased Array Radar (PAR) is the capability to adaptively scan storms at higher temporal resolution than is possible with the Weather Surveillance Radar-1988 Doppler (WSR-88D): 1 min or less versus 4.1 min, respectively. High temporal resolution volumetric radar data are a necessity for rapid identification and confirmation of weather phenomena that can develop within minutes. The purpose of this paper is to demonstrate the PAR’s ability to collect rapid-scan volumetric data that provide more detailed depictions of quickly evolving storm structures than the WSR-88D. Scientific advantages of higher temporal resolution PAR data are examined for three convective storms that occurred during the spring and summer of 2006, including a reintensifying supercell, a microburst, and a hailstorm. The analysis of the reintensifying supercell (58-s updates) illustrates the capability to diagnose the detailed evolution of developing and/or intensifying areas ...

The Tornado Warning Process: A Review of Current Research, Challenges, and Opportunities

Abstract: With the unusually violent tornado season of 2011, there has been a renewed national interest, through such programs as NOAA's Weather Ready Nation initiative, to reevaluate and improve our tornado warning process. This literature review provides an interdisciplinary, end-to-end examination of the tornado warning process. Following the steps outlined by the Integrated Warning System, current research in tornado prediction and detection, the warning decision process, warning dissemination, and public response are reviewed, and some of the major challenges for improving each stage are highlighted. The progress and challenges in multi-day to short-term tornado prediction are discussed, followed by an examination of tornado detection, focused primarily upon the contributions made by weather radar and storm spotters. Next is a review of the warning decision process and the challenges associated with dissemination of the warning, followed by a discussion of the complexities associated with understanding public ...

A Mobile, Phased-Array Doppler Radar For The Study of Severe Convective Storms

Abstract: A mobile X-band, phased-array Doppler radar was acquired from the U.S. Army by the Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS) at the Naval Postgraduate School and adapted for meteorological use by ProSensing, Inc. The radar was used during field experiments conducted in the Southern Plains by faculty and students from the School of Meteorology at the University of Oklahoma during the spring storm seasons of 2007 and 2008. During these field experiments, storm-scale, rapid-scan, volumetric, Doppler-radar observations were obtained in tornadic and nontornadic supercells, quasilinear mesoscale convective systems, and in both boundary layer–based and elevated ordinary convective cells. A case is made for the use of the radar for studies of convective weather systems and other weather phenomena that evolve on time scales as short as tens of seconds.