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Rainer Bleck, Renate Brummer, and Melvyn A. Shapiro

Abstract

Ground-based remote sensing devices have recently been developed which provide high-resolution tropospheric wind measurements and coarse-resolution radiometric temperature measurements under most weather conditions. A variational analysis scheme for inferring missing details in the three-dimensional temperature field from concurrent wind observations is proposed. The scheme is based on the solution of a three-dimensional boundary value problem and thus requires input from a network of profilers, rather than one individual instrument. Since observing networks of this kind do not presently exist, the scheme is tested on objectively analyzed, thermally degraded radiosonde data. The ultimate purpose of the thermal enhancement procedure is to improve the dynamic balance between mass and wind fields observed by future ground- or space-based profiler networks and to lessen the initialization shock if these data are used in numerical prediction models.

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Stanley G. Benjamin, Keith A. Brewster, Renate Brümmer, Brian F. Jewett, Thomas W. Schlatter, Tracy L. Smith, and Peter A. Stamus

Abstract

A 3-h intermittent data assimilation system (Mesoscale Analysis and Prediction System—MAPS) configured in isentropic coordinates was developed and implemented in real-time operation. The major components of the system are data ingest, objective quality control of the observation, objective analysis, and a primitive equation forecast model, all using isentropic coordinates to take advantage of the improved resolution near frontal zones and greater spatial coherence of data that this coordinate system provides. Each 3-h forecast becomes the background for the subsequent analysis; in this manner, a four-dimensional set of observations can be assimilated.

The primary asynoptic data source used in current real-time operation of this system is air-craft data, most of it automated. Data from wind profilers, surface observations, and radiosondes are also included in MAPS.

Statistics were collected over the last half of 1989 and into 1990 to study the performance of MAPS and compare it with that of the Regional Analysis and Forecast System (RAFS), which is run operationally at the National Meteorological Center (NMC). Analyses generally fit mandatory-level observations more closely in MAPS than in RAFS. Three-hour forecasts from MAPS, incorporating asynoptic aircraft reports, improve on 12-h MAPS forecasts valid at the same time for all levels and variables, and also improve on 12-h RAFS forecasts of upper-level winds. This result is due to the quality and volume of the aircraft data as well as the effectiveness of the isentropic data assimilation used. Forecast fields at other levels are slightly poorer than those from RAFS. This may be largely due to the lack of diabatic and boundary-layer physics for the MAPS model used in this test period.

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Scott Longmore, Steven Miller, Dan Bikos, Daniel Lindsey, Edward Szoke, Debra Molenar, Donald Hillger, Renate Brummer, and John Knaff

Abstract

The increasing use of mobile phones (MPs) equipped with digital cameras and the ability to post images and information to the Internet in real time has significantly improved the ability to report events almost instantaneously. From the perspective of weather forecasters responsible for issuing severe weather warnings, the old adage holds that a picture is indeed worth a thousand words; a single digital image conveys significantly more information than a simple web-submitted text or phone-relayed report. Timely, quality-controlled, and value-added photography allows the forecaster to ascertain the validity and quality of storm reports. The posting of geolocated, time-stamped storm report photographs utilizing an MP application to U.S. National Weather Service (NWS) Weather Forecast Office (WFO) social media pages has generated recent positive feedback from forecasters. This study establishes the conceptual framework, architectural design, and pathway toward implementation of a formalized photo report (PR) system composed of 1) an MP application, 2) a processing and distribution system, and 3) the Advanced Weather Interactive Processing System II (AWIPS II) data plug-in software. The requirements and anticipated appearance of such a PR system are presented, along with considerations for possible additional features and applications that extend the utility of the system beyond the realm of severe weather applications.

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Isidora Jankov, Lewis D. Grasso, Manajit Sengupta, Paul J. Neiman, Dusanka Zupanski, Milija Zupanski, Daniel Lindsey, Donald W. Hillger, Daniel L. Birkenheuer, Renate Brummer, and Huiling Yuan

Abstract

The main purpose of the present study is to assess the value of synthetic satellite imagery as a tool for model evaluation performance in addition to more traditional approaches. For this purpose, synthetic GOES-10 imagery at 10.7 μm was produced using output from the Advanced Research Weather Research and Forecasting (ARW-WRF) numerical model. Use of synthetic imagery is a unique method to indirectly evaluate the performance of various microphysical schemes available within the ARW-WRF. In the present study, a simulation of an atmospheric river event that occurred on 30 December 2005 was used. The simulations were performed using the ARW-WRF numerical model with five different microphysical schemes [Lin, WRF single-moment 6 class (WSM6), Thompson, Schultz, and double-moment Morrison]. Synthetic imagery was created and scenes from the simulations were statistically compared with observations from the 10.7-μm band of the GOES-10 imager using a histogram-based technique. The results suggest that synthetic satellite imagery is useful in model performance evaluations as a complementary metric to those used traditionally. For example, accumulated precipitation analyses and other commonly used fields in model evaluations suggested a good agreement among solutions from various microphysical schemes, while the synthetic imagery analysis pointed toward notable differences in simulations of clouds among the microphysical schemes.

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Steven J. Goodman, James Gurka, Mark DeMaria, Timothy J. Schmit, Anthony Mostek, Gary Jedlovec, Chris Siewert, Wayne Feltz, Jordan Gerth, Renate Brummer, Steven Miller, Bonnie Reed, and Richard R. Reynolds

The Geostationary Operational Environmental Satellite R series (GOES-R) Proving Ground engages the National Weather Service (NWS) forecast, watch, and warning community and other agency users in preoperational demonstrations of the new and advanced capabilities to be available from GOES-R compared to the current GOES constellation. GOES-R will provide significant advances in observing capabilities but will also offer a significant challenge to ensure that users are ready to exploit the new 16-channel imager that will provide 3 times more spectral information, 4 times the spatial coverage, and 5 times the temporal resolution compared to the current imager. In addition, a geostationary lightning mapper will provide continuous and near-uniform real-time surveillance of total lightning activity throughout the Americas and adjacent oceans encompassing much of the Western Hemisphere. To ensure user readiness, forecasters and other users must have access to prototype advanced products within their operational environment well before launch. Examples of the advanced products include improved volcanic ash detection, lightning detection, 1-min-interval rapid-scan imagery, dust and aerosol detection, and synthetic cloud and moisture imagery. A key component of the GOES-R Proving Ground is the two-way interaction between the researchers who introduce new products and techniques and the forecasters who then provide feedback and ideas for improvements that can best be incorporated into NOAA's integrated observing and analysis operations. In 2012 and beyond, the GOES-R Proving Ground will test and validate display and visualization techniques, decision aids, future capabilities, training materials, and the data processing and product distribution systems to enable greater use of these products in operational settings.

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