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R. J. Hung and R. E. Smith

Abstract

Gravity waves with wave periods of 13 to 15 min and horizontal phase velocities of 90 to 220 m s−1 were present in ground-based observations of the upper atmosphere during time periods when tornadoes were occurring and gravity waves with wave periods of 20 to 25 min and horizontal phase velocities of 100 to 200 m s−1 were detected when a hurricane was present. Combinations of available neutral atmosphere data and model parameter values were used with a group ray tracing technique in an attempt to locate the sources of these waves. Computed sources of the waves with periods of 13 to 15 min were located within 50 km of the locations where tornadoes touched down from 2 to 4 h later. In the case of the waves with periods of 20 to 25 min it was found that the computed location of the source was roughly where the hurricane would be located 3 h after the waves were excited. The applicability of the present study to a tornado and hurricane warning system is noted.

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R. E. Smith and R. J. Hung

Abstract

A three-dimensional, nine-element, high-frequency cw Doppler sounder array has been used to detect ionospheric disturbances during periods of severe weather, particularly during periods with severe thunderstorms and tornadoes. One typical disturbance recorded during a period of severe thunderstorm activity and one during a period of tornado activity have been chosen for analysis in this note. The observations indicate that wave-like disturbances possibly generated by the severe weather have wave periods in the range 2–8 min which place them in the infrasonic wave category.

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R. J. Hung, T. Phan, and R. E. Smith

Abstract

Penetrative convection, thunderstorms, squall lines, etc., all generate atmospheric gravity waves which can be observed by a ground-based ionospheric Doppler sounder array. Sources of these waves can be determined from reverse ray tracing computations. Case studies of gravity waves associated with isolated tornadic storms on 13 January 1976 were summarized to establish the minimum data sampling time required for correct spectral analysis and ray tracing computations. It was concluded that the data sampling time can be reduced to two to three times the wave period while still obtaining a reasonably good power spectral density. It was also demonstrated that the data sampling time can be reduced to two to three times the time delay of the wave arrival between two station pairs while still obtaining a justifiably good cross-spectral analysis. Computed source locations of the observed gravity waves are compared with conventional and satellite meteorological data.

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R. J. Hung, T. Phan, D. C. Lin, R. E. Smith, R. R. Jayroe, and S. West

Abstract

Enhanced convection-initiated gravity waves associated with an isolated tornado in the absence of a squall line are investigated. Ray-tracing computations based on data observed on 29 May 1977 indicated that the wave sources were located in north-central Oklahoma. Comparison with a radar echo map during the time period when the waves were excited showed that the waves were generated by an isolated cloud with enhanced convection. GOES infrared digital data during the time period from wave excitation to tornado touchdown were analyzed. Results showed that the cloud where the gravity waves were excited was characterized by both a very low temperature at the cloud top and a very high expansion rate of the cold cloud-top area. The lead time between the excitation of the gravity waves and the tornado touchdown is discussed in conjunction with the growth rate of the clouds associated with the tornado.

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Jason A. Otkin, Derek J. Posselt, Erik R. Olson, Hung-Lung Huang, James E. Davies, Jun Li, and Christopher S. Velden

Abstract

A novel application of numerical weather prediction (NWP) models within an end-to-end processing system used to demonstrate advanced hyperspectral satellite technologies and instrument concepts is presented. As part of this system, sophisticated NWP models are used to generate simulated atmospheric profile datasets with fine horizontal and vertical resolution. The simulated datasets, which are treated as the “truth” atmosphere, are subsequently passed through a sophisticated forward radiative transfer model to generate simulated top-of-atmosphere (TOA) radiances across a broad spectral region. Atmospheric motion vectors and temperature and water vapor retrievals generated from the TOA radiances are then compared with the original model-simulated atmosphere to demonstrate the potential utility of future hyperspectral wind and retrieval algorithms. Representative examples of TOA radiances, atmospheric motion vectors, and temperature and water vapor retrievals are shown to illustrate the use of the simulated datasets.

Case study results demonstrate that the numerical models are able to realistically simulate mesoscale cloud, temperature, and water vapor structures present in the real atmosphere. Because real hyperspectral radiance measurements with high spatial and temporal resolution are not available for large geographical domains, the simulated TOA radiance datasets are the only viable alternative that can be used to demonstrate the new hyperspectral technologies and capabilities. As such, sophisticated mesoscale models are critically important for the demonstration of the future end-to-end processing system.

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Thomas J. Greenwald, R. Bradley Pierce, Todd Schaack, Jason Otkin, Marek Rogal, Kaba Bah, Allen Lenzen, Jim Nelson, Jun Li, and Hung-Lung Huang

Abstract

In support of the Geostationary Operational Environmental Satellite R series (GOES-R) program, the Cooperative Institute for Meteorological Satellite Studies (CIMSS) at the University of Wisconsin–Madison is generating high quality simulated Advanced Baseline Imager (ABI) radiances and derived products in real time over the continental United States. These data are mainly used for testing data-handling systems, evaluating ABI-derived products, and providing training material for forecasters participating in GOES-R Proving Ground test bed activities. The modeling system used to generate these datasets consists of advanced regional and global numerical weather prediction models in addition to state-of-the-art radiative transfer models, retrieval algorithms, and land surface datasets. The system and its generated products are evaluated for the 2014 Pacific Northwest wildfires; the 2013 Moore, Oklahoma, tornado; and Hurricane Sandy. Simulated aerosol optical depth over the Front Range of Colorado during the Pacific Northwest wildfires was validated using high-density Aerosol Robotic Network (AERONET) measurements. The aerosol, cloud, and meteorological modeling system used to generate ABI radiances was found to capture the transport of smoke from the Pacific wildfires into the Front Range of Colorado and true-color imagery created from these simulated radiances provided visualization of the smoke plumes. Evaluation of selected simulated ABI-derived products for the Moore tornado and Hurricane Sandy cases was done using real-time GOES sounder/imager products produced at CIMSS. Results show that simulated ABI moisture and atmospheric stability products, cloud products, and red–green–blue (RGB) airmass composite imagery are well suited as proxy ABI data for user preparedness.

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Yi-Hung Kuo, J. David Neelin, Chih-Chieh Chen, Wei-Ting Chen, Leo J. Donner, Andrew Gettelman, Xianan Jiang, Kuan-Ting Kuo, Eric Maloney, Carlos R. Mechoso, Yi Ming, Kathleen A. Schiro, Charles J. Seman, Chien-Ming Wu, and Ming Zhao

Abstract

To assess deep convective parameterizations in a variety of GCMs and examine the fast-time-scale convective transition, a set of statistics characterizing the pickup of precipitation as a function of column water vapor (CWV), PDFs and joint PDFs of CWV and precipitation, and the dependence of the moisture–precipitation relation on tropospheric temperature is evaluated using the hourly output of two versions of the GFDL Atmospheric Model, version 4 (AM4), NCAR CAM5 and superparameterized CAM (SPCAM). The 6-hourly output from the MJO Task Force (MJOTF)/GEWEX Atmospheric System Study (GASS) project is also analyzed. Contrasting statistics produced from individual models that primarily differ in representations of moist convection suggest that convective transition statistics can substantially distinguish differences in convective representation and its interaction with the large-scale flow, while models that differ only in spatial–temporal resolution, microphysics, or ocean–atmosphere coupling result in similar statistics. Most of the models simulate some version of the observed sharp increase in precipitation as CWV exceeds a critical value, as well as that convective onset occurs at higher CWV but at lower column RH as temperature increases. While some models quantitatively capture these observed features and associated probability distributions, considerable intermodel spread and departures from observations in various aspects of the precipitation–CWV relationship are noted. For instance, in many of the models, the transition from the low-CWV, nonprecipitating regime to the moist regime for CWV around and above critical is less abrupt than in observations. Additionally, some models overproduce drizzle at low CWV, and some require CWV higher than observed for strong precipitation. For many of the models, it is particularly challenging to simulate the probability distributions of CWV at high temperature.

Open access
P. Joe, S. Belair, N.B. Bernier, V. Bouchet, J. R. Brook, D. Brunet, W. Burrows, J.-P. Charland, A. Dehghan, N. Driedger, C. Duhaime, G. Evans, A.-B. Filion, R. Frenette, J. de Grandpré, I. Gultepe, D. Henderson, A. Herdt, N. Hilker, L. Huang, E. Hung, G. Isaac, C.-H. Jeong, D. Johnston, J. Klaassen, S. Leroyer, H. Lin, M. MacDonald, J. MacPhee, Z. Mariani, T. Munoz, J. Reid, A. Robichaud, Y. Rochon, K. Shairsingh, D. Sills, L. Spacek, C. Stroud, Y. Su, N. Taylor, J. Vanos, J. Voogt, J. M. Wang, T. Wiechers, S. Wren, H. Yang, and T. Yip

Abstract

The Pan and Parapan American Games (PA15) are the third largest sporting event in the world and were held in Toronto in the summer of 2015 (10–26 July and 7–15 August). This was used as an opportunity to coordinate and showcase existing innovative research and development activities related to weather, air quality (AQ), and health at Environment and Climate Change Canada. New observational technologies included weather stations based on compact sensors that were augmented with black globe thermometers, two Doppler lidars, two wave buoys, a 3D lightning mapping array, two new AQ stations, and low-cost AQ and ultraviolet sensors. These were supplemented by observations from other agencies, four mobile vehicles, two mobile AQ laboratories, and two supersites with enhanced vertical profiling. High-resolution modeling for weather (250 m and 1 km), AQ (2.5 km), lake circulation (2 km), and wave models (250-m, 1-km, and 2.5-km ensembles) were run. The focus of the science, which guided the design of the observation network, was to characterize and investigate the lake breeze, which affects thunderstorm initiation, air pollutant transport, and heat stress. Experimental forecasts and nowcasts were provided by research support desks. Web portals provided access to the experimental products for other government departments, public health authorities, and PA15 decision-makers. The data have been released through the government of Canada’s Open Data Portal and as a World Meteorological Organization’s Global Atmospheric Watch Urban Research Meteorology and Environment dataset.

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Eric D. Maloney, Andrew Gettelman, Yi Ming, J. David Neelin, Daniel Barrie, Annarita Mariotti, C.-C. Chen, Danielle R. B. Coleman, Yi-Hung Kuo, Bohar Singh, H. Annamalai, Alexis Berg, James F. Booth, Suzana J. Camargo, Aiguo Dai, Alex Gonzalez, Jan Hafner, Xianan Jiang, Xianwen Jing, Daehyun Kim, Arun Kumar, Yumin Moon, Catherine M. Naud, Adam H. Sobel, Kentaroh Suzuki, Fuchang Wang, Junhong Wang, Allison A. Wing, Xiaobiao Xu, and Ming Zhao

Abstract

Realistic climate and weather prediction models are necessary to produce confidence in projections of future climate over many decades and predictions for days to seasons. These models must be physically justified and validated for multiple weather and climate processes. A key opportunity to accelerate model improvement is greater incorporation of process-oriented diagnostics (PODs) into standard packages that can be applied during the model development process, allowing the application of diagnostics to be repeatable across multiple model versions and used as a benchmark for model improvement. A POD characterizes a specific physical process or emergent behavior that is related to the ability to simulate an observed phenomenon. This paper describes the outcomes of activities by the Model Diagnostics Task Force (MDTF) under the NOAA Climate Program Office (CPO) Modeling, Analysis, Predictions and Projections (MAPP) program to promote development of PODs and their application to climate and weather prediction models. MDTF and modeling center perspectives on the need for expanded process-oriented diagnosis of models are presented. Multiple PODs developed by the MDTF are summarized, and an open-source software framework developed by the MDTF to aid application of PODs to centers’ model development is presented in the context of other relevant community activities. The paper closes by discussing paths forward for the MDTF effort and for community process-oriented diagnosis.

Open access