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Kenneth W. Johnson

Abstract

Development of a methodology for the optimal placement of multivariate sensors as an aid in the design of geophysical field experiments is shown. The optimal placement methodology relies on spatial correlation estimates, interpolation error estimates as provided by a multivariate optimal interpolation scheme, and optimization techniques using nonlinear programming. Atmospheric fields and their associated statistics are simulated by analytic functions to demonstrate the capabilities of the methodology. These include the ability to design new networks, to add sensors optimally to existing networks, and to place restrictions on the region in which sensors can be located by introducing physical and economical constraints on the nonlinear programming problem. It is demonstrated that the mean and variance of the interpolation error for all fields is generally smaller for analyses whose input is derived from optimal sampling locations rather than from subjectively chosen locations.

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Ying Lin, Peter S. Ray, and Kenneth W. Johnson

Abstract

A method is developed to initialize convective storm simulations with Doppler radar-derived fields. Input fields for initialization include velocity, rainwater derived from radar reflectivity, and pressure and temperature fields obtained through thermodynamic retrieval. A procedure has been developed to fill in missing wind data, followed by a variational adjustment to the filled wind field to minimize “shocks” that would otherwise cause the simulated fields to deteriorate rapidly.

A series of experiments using data from a simulated storm establishes the feasibility of the initialization method. Multiple-Doppler radar observations from the 20 May 1977 Del City tornadic storm are used for the initialization experiments. Simulation results are shown and compared to observations taken at a later time. The simulated storm shows good agreement with the subsequent observations, though the simulated storm appears to be evolving faster than observed. Possible reasons for the discrepancies are discussed.

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Kenneth W. Johnson, Peter S. Ray, Brenda C. Johnson, and Robert P. Davies-Jones

Abstract

Observations of the 20 May 1977 tornadic storms are used to evaluate recent theories on the initiation of rotation at mid-and low levels and to verify recent thermodynamic retrieval results. Using the lengthy data record from a variety of sensors available for this day, it appears that the mechanism that initiates low-level rotation is different from that at midlevels. Attempts to identify the source of the low-level rotation as vertical tilting baroclinically generated horizontal vorticity were inconclusive.

The recent thermodynamic retrieval results of Hane and Ray and of Brandes for these storms are in good agreement with independent measurements where available. However, verification is hindered by the sparseness of these measurements. Noticeable differences in the region of the rear-flank downdraft suggest that there is room for improvement in the retrieval methods.

Investigation of the cyclic generation of rotation along gust fronts indicates that the source of low-level rotation is not derived from baroclinically generated horizontal vorticity as seems to be the case with the initial mesocyclone core. Instead, vertical vorticity amplification along the gust front leading to successive generation of mesocyclone cores and discrete mesocyclone propagation is the result of the concentration of low-level preexisting vertical vorticity through convergence.

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William W. Kellogg, David Atlas, David S. Johnson, Richard J. Reed, and Kenneth C. Spengler
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Kenneth W. Johnson, Jeff Bauer, Gregory A. Riccardi, Kelvin K. Droegemeier, and Ming Xue

Abstract

This paper describes the parallelization of a mesoscale-cloud-scale numerical weather prediction model and experiments conducted to assess its performance. The model used is the Advanced Regional Prediction System (ARPS), a limited-area nonhydrostatic model suitable for cloud-scale and mesoscale studies. Because models such as ARPS are usually memory and CPU bound, the motivation here is to decrease the computer time required for running the model and/or increase the size of the problem that can be run. A domain decomposition strategy using a network of workstations produced a significant decrease in elapsed time and increase in problem size relative to a single-workstation run. The performance of the resulting program is described by deprived formulas (collectively known as a performance model), which predict the execution time and speedup for different numbers of processors and problem sizes. The interprocessor communication speeds are shown to be the major obstacle to achieving full processor use. The effect of faster communication networks on parallel performance is predicted based on this performance model. Parallelization experiments using the ARPS code were run on a cluster of IBM RS6000 workstations connected via Ethernet. The message-passing paradigm implemented here made use of the library of routines from the Parallel Virtual Machine software package.

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Kenneth S. Johnson, Luke J. Coletti, Hans W. Jannasch, Carole M. Sakamoto, Dana D. Swift, and Stephen C. Riser

Abstract

Reagent-free optical nitrate sensors [in situ ultraviolet spectrophotometer (ISUS)] can be used to detect nitrate throughout most of the ocean. Although the sensor is a relatively high-power device when operated continuously (7.5 W typical), the instrument can be operated in a low-power mode, where individual nitrate measurements require only a few seconds of instrument time and the system consumes only 45 J of energy per nitrate measurement. Operation in this mode has enabled the integration of ISUS sensors with Teledyne Webb Research's Autonomous Profiling Explorer (APEX) profiling floats with a capability to operate to 2000 m. The energy consumed with each nitrate measurement is low enough to allow 60 nitrate observations on each vertical profile to 1000 m. Vertical resolution varies from 5 m near the surface to 50 m near 1000 m, and every 100 m below that. Primary lithium batteries allow more than 300 vertical profiles from a depth of 1000 m to be made, which corresponds to an endurance near four years at a 5-day cycle time. This study details the experience in integrating ISUS sensors into Teledyne Webb Research's APEX profiling floats and the results that have been obtained throughout the ocean for periods up to three years.

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Fred V. Brock, Kenneth C. Crawford, Ronald L. Elliott, Gerrit W. Cuperus, Steven J. Stadler, Howard L. Johnson, and Michael D. Eilts

Abstract

The Oklahoma mesonet is a joint project of Oklahoma State University and the University of Oklahoma. It is an automated network of 108 stations covering the state of Oklahoma. Each station measures air temperature, humidity, barometric pressure, wind speed and direction, rainfall, solar radiation, and soil temperatures. Each station transmits a data message every 15 min via a radio link to the nearest terminal of the Oklahoma Law Enforcement Telecommunications System that relays it to a central site in Norman, Oklahoma. The data message comprises three 5-min averages of most data (and one 15-min average of soil temperatures). The central site ingests the data, runs some quality assurance tests, archives the data, and disseminates it in real time to a broad community of users, primarily through a computerized bulletin board system. This manuscript provides a technical description of the Oklahoma mesonet including a complete description of the instrumentation. Sensor inaccuracy, resolution, height with respect to ground level, and method of exposure are discussed.

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Molly Baringer, Mariana B. Bif, Tim Boyer, Seth M. Bushinsky, Brendan R. Carter, Ivona Cetinić, Don P. Chambers, Lijing Cheng, Sanai Chiba, Minhan Dai, Catia M. Domingues, Shenfu Dong, Andrea J. Fassbender, Richard A. Feely, Eleanor Frajka-Williams, Bryan A. Franz, John Gilson, Gustavo Goni, Benjamin D. Hamlington, Zeng-Zhen Hu, Boyin Huang, Masayoshi Ishii, Svetlana Jevrejeva, William E. Johns, Gregory C. Johnson, Kenneth S. Johnson, John Kennedy, Marion Kersalé, Rachel E. Killick, Peter Landschützer, Matthias Lankhorst, Tong Lee, Eric Leuliette, Feili Li, Eric Lindstrom, Ricardo Locarnini, Susan Lozier, John M. Lyman, John J. Marra, Christopher S. Meinen, Mark A. Merrifield, Gary T. Mitchum, Ben Moat, Didier Monselesan, R. Steven Nerem, Renellys C. Perez, Sarah G. Purkey, Darren Rayner, James Reagan, Nicholas Rome, Alejandra Sanchez-Franks, Claudia Schmid, Joel P. Scott, Uwe Send, David A. Siegel, David A. Smeed, Sabrina Speich, Paul W. Stackhouse Jr., William Sweet, Yuichiro Takeshita, Philip R. Thompson, Joaquin A. Triñanes, Martin Visbeck, Denis L. Volkov, Rik Wanninkhof, Robert A. Weller, Toby K. Westberry, Matthew J. Widlansky, Susan E. Wijffels, Anne C. Wilber, Lisan Yu, Weidong Yu, and Huai-Min Zhang
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