Scientific Theme: Advanced Modeling and Observing Systems

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Theme report: Advanced Modeling and Observing Systems running the model backwards in time, as is required for the DFI, so considerable development effort has been necessary. Such a capability was, in fact, developed in 2005 for WRF v2.1. Work to extend this capability to WRF v2.2 has turned out to be decidedly nontrivial, but it is progressing. MILESTONE GSD01.2: Incorporate enhancements to Gridpoint Statistical Interpolation (GSI) code to improve use of surface weather observations (METARs) and introduce GSD-developed procedures into GSI to incorporate three-dimensional, high-frequency National Weather Service WSR-88D radar data in the initialization of cloud and precipitation hydrometeors. ACCOMPLISHMENTS FOR GSD01.2: Work on GSI at GSD was begun in 2005. After some very basic code adjustments, work started to concentrate on features important for RR applications, particularly those required for one-hour cycling and assimilation of hydrometeors. (GSI has heretofore been used only with models cycling every six hours and without assimilation of hydrometeor information.) The two most important of these features are usage of surface observations, including ceiling height and present weather, and analysis of hydrometeors. One of the strengths of the present Rapid Update Cycle (RUC) is the handling of surface data in the RUC analysis. The difference between the surface observation of virtual potential temperature, water-vapor mixing ratio and horizontal wind components and the one-hour background forecast of these quantities is spread vertically through the mixed-layer (but only if there is such a mixed-layer) in the one-hour background forecast by generating ―pseudoobservations‖ within the mixed-layer, but not above. For the time being, a different approach is taken in the GSI, using anisotropic background error covariance information in an adaptive way. The premise is to apply the PBL depth of the background forecast as computed in the present RUC and use this to constrain the scale of vertical correlation in the background error. This approach is combined with a model for anisotropic background error developed and implemented in GSI by NCEP. The present code employs the background virtual potential temperature when computing the vertical correlation of background error. Present work is directed toward introduction and intense testing of this approach in the real-time one-hour RR cycle soon to begin on the new ESRL supercomputer (see Milestone GSD01.1). The existing operational RUC cloud analysis is done outside the variational framework of the RUC 3dVAR. It uses NESDIS cloud products (cloud top pressure and temperature) and METARs to decide the location of cloud top and clear area and then adds a thin layer of cloud under the cloud top and clears the column above cloud top. (The whole column is cleared of hydrometeors if the column is identified as being clear by the RUC cloud analysis.) Versions of GSI released by NCEP have yet to incorporate any cloud analysis procedures. Therefore, an enhanced version of the existing RUC cloud-analysis procedure within the GSI software framework was incorporated, but as with RUC, outside the variational parts of the code. A systematic approach toward introducing the RUC cloud analysis into GSI has been pursued, including a) building onto the GSI framework to accommodate the cloud analysis, b) ingesting cloud observations, c) building the cloud analysis driver, and d) incorporating RUC cloud analysis into GSI. All the programming work has been finished including parallelization of the cloud-analysis code. Preliminary results show successful performance. The code will be further tested in the real time RR cycle. A new procedure for assimilation of three-dimensional high-frequency National Weather Service WSR-88D radar data is being tested in real-time RUC cycles at GSD. Briefly summarized, this procedure uses the 1-km Q2 Mosaic radar-reflectivity product developed at the National Severe Storms Lab of NOAA, plus some additional quality control, to identify volumes of the atmosphere having radar reflectivity due to hydrometeors. In areas where radar data are absent, lightning is used to identify volumes likely to possess hydrometeors. The procedure also identifies areas where the one-hour background forecast has hydrometeors that do not exist in reality. In order to render the initial mass and momentum fields more consistent with these implied hydrometeor fields, the diabatic digital filter initialization is employed. After the initial adiabatic backward stage of the DFI, there follows the diabatic forward step. During this forward step, the potential temperature tendencies from the microphysics and convection parameterization schemes are replaced by tendencies specified based on the mixing ratios of the hydrometeors. In this way an initial divergent component of the wind field is introduced that has some measure of consistency with the hydrometeor fields and allows a much improved forecast of precipitation through the first three to six hours of the model forecast. Introduction of this procedure into the RR cycling later this year is planned, once a version of 32
Theme report: Advanced Modeling and Observing Systems WRF with a diabatic digital filter initialization is developed. This will thus be implemented, at least initially, outside the GSI framework. GSD03: Verification Techniques for the Evaluation of Aviation Weather Forecasts GOAL: Design and evaluate new verification approaches and tools that will provide information about the quality of aviation forecasts and their value to aviation decision makers. MILESTONE GSD03.1: Participate in the redesign of the Real-Time Verification System (RTVS) by enhancing the functionality of the database, web-interface, and real-time processing modules of the system to support verification of aviation parameters, such as icing, turbulence, and convective weather. ACCOMPLISHMENTS FOR GSD03.1: Upgrades to the turbulence and icing verification modules were added to the RTVS operations, and researchers participated in the development of the conceptual design for the reengineered RTVS. MILESTONE GSD03.2: Investigate and develop new verification techniques for evaluating the accuracy of convective echo tops, high resolution automated convective probabilistic forecasts, and ceiling and visibility forecast lead times. ACCOMPLISHMENTS FOR GSD03.2: A Terminal Aerodrome Forecast (TAF) lead-time metric and a prototype web interface for access to the TAF leadtime metric statistics and diagnostic analysis capabilities were developed. These capabilities were demonstrated to NWS HQ staff. The capability to evaluate convective echo top forecasts was added to the RTVS. Statistics are being used this season to evaluate forecast accuracy. An ―audit trail‖ verification capability was developed within RTVS to track the forecast quality of operationally significant convective weather forecasts. A user-based verification technique for evaluating convective forecasts was developed. This technique incorporates strategic decision points, operational flight sectors, and high-impact weather events. MILESTONE GSD03.3: Summarize results from statistical evaluations of turbulence and convective weather forecasts in written reports. ACCOMPLISHMENTS FOR GSD03.3: The statistical generation, analysis of results, and writing of the following reports were developed: Forecast Icing Product (FIP) Calibration study Graphical Turbulence Guidance version 2 supplemental report Monthly summary report for the Collaborative Convective Forecast Product. Analysis of results for the National Ceiling and Visibility Analysis product was also completed. NGDC03: Space Weather GOAL: Assess the current state of the space environment from the surface of the sun to the upper atmosphere; use datadriven physical models to construct a realistic and authoritative gridded database of the space environment; and place that description into its long-term climatological perspective. 33
Page 1 and 2: COOPERATIVE INSTITUTE FOR RESEARCH
Page 3: Table of Contents Letter from the D
Page 7 and 8: Executive Summary and Research High
Page 13 and 14: Chemical Sciences Division (CSD) CI
Page 15 and 16: CIRES in 2006-2007: Administration
Page 17 and 18: CIRES in 2006-2007: Contributions t
Page 19 and 20: CIRES in 2006-2007: Creating a Dyna
Page 25 and 26: Theme report: Advanced Modeling and
Page 37: GSD01: Numerical Weather Prediction
Page 51 and 52: Theme report: Climate System Variab
Page 73 and 74: NOAA Operation Model NOAA Optimally
Page 75 and 76: Scientific Theme: Geodynamics This
Page 77 and 78: Scientific Theme: Geodynamics MILES
Page 79 and 80: Scientific Theme: Integrating Activ
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Scientific Theme: Integrating Activ
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Scientific Theme: Planetary Metabol
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Scientific Theme: Planetary Metabol
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Scientific Theme: Regional Processe
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CSD08: Regional Air Quality Scienti
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k 1(T) (10 -11 cm 3 molecule -1 s -
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Global Snow Cover Mapping Richard A
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Complementary Research: Faculty Fel
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Land Surface Hydrology and Global C
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The Arctic's Shrinking Sea Ice Cove
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Laboratory Studies of Clouds and Ae
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Complementary Research: Education a
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Center for the Study of Earth from
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Complementary Research: CIRES Scien
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National Snow and Ice Data Center C
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Center for Limnology Complementary
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Climate Diagnostics Center Compleme
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Complementary Research: Innovative
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Complementary Research: CIRES Fello
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Complementary Research: CIRES Fello
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CIRES’ Leadership Konrad Steffen:
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Appendices: Governance and Manageme
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Appendices: Student Diversity Progr
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Appendices: Publications Publicatio
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Appendices: Publications Beaver, M.
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Appendices: Publications Cimini, D.
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Appendices: Publications standard u
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Appendices: Publications Garrett, T
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Appendices: Publications Holland, M
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Appendices: Publications Li, S., G.
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Appendices: Publications Mcguire, A
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Appendices: Publications Olsen, N.,
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Appendices: Publications Regonda, S
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Appendices: Publications Sierau, B.
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Appendices: Publications Turnbull,
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Appendices: Publications Yoon, S.C.
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Appendices: Publications Maus, S.,
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Appendices: Publications Miller, J.
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Appendices: Publications Chernogor,
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Appendices: Publications Petropavlo
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Appendices: Publications Refereed J
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Appendices: Honors and Awards Honor
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Appendices: Honors and Awards Maure
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Appendices: Service Service: Calend
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Appendices: Service Army Office of
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Appendices: Acronyms Acronyms and A
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Appendices: Acronyms DOE Department
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Appendices: Acronyms MBBDB MultiBea
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Appendices: Acronyms SHEBA Surface
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Scientific Theme: Advanced Modeling and Observing Systems

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