David O. Gill

Bio: David O. Gill is an academic researcher from National Center for Atmospheric Research. The author has contributed to research in topics: Weather Research and Forecasting Model & Storm. The author has an hindex of 8, co-authored 11 publications receiving 3404 citations. Previous affiliations of David O. Gill include Cooperative Institute for Research in Environmental Sciences.

A Description of the Advanced Research WRF Version 2

Abstract: : The development of the Weather Research and Forecasting (WRF) modeling system is a multiagency effort intended to provide a next-generation mesoscale forecast model and data assimilation system that will advance both the understanding and prediction of mesoscale weather and accelerate the transfer of research advances into operations. The model is being developed as a collaborative effort ort among the NCAR Mesoscale and Microscale Meteorology (MMM) Division, the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental Prediction (NCEP) and Forecast System Laboratory (FSL), the Department of Defense's Air Force Weather Agency (AFWA) and Naval Research Laboratory (NRL), the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma, and the Federal Aviation Administration (FAA), along with the participation of a number of university scientists. The WRF model is designed to be a flexible, state-of-the-art, portable code that is an efficient in a massively parallel computing environment. A modular single-source code is maintained that can be configured for both research and operations. It offers numerous physics options, thus tapping into the experience of the broad modeling community. Advanced data assimilation systems are being developed and tested in tandem with the model. WRF is maintained and supported as a community model to facilitate wide use, particularly for research and teaching, in the university community. It is suitable for use in a broad spectrum of applications across scales ranging from meters to thousands of kilometers. Such applications include research and operational numerical weather prediction (NWP), data assimilation and parameterized-physics research, downscaling climate simulations, driving air quality models, atmosphere-ocean coupling, and idealized simulations (e.g boundary-layer eddies, convection, baroclinic waves).

The Weather Research and Forecasting Model: Overview, System Efforts, and Future Directions

Abstract: Since its initial release in 2000, the Weather Research and Forecasting (WRF) Model has become one of the world’s most widely used numerical weather prediction models. Designed to serve both research and operational needs, it has grown to offer a spectrum of options and capabilities for a wide range of applications. In addition, it underlies a number of tailored systems that address Earth system modeling beyond weather. While the WRF Model has a centralized support effort, it has become a truly community model, driven by the developments and contributions of an active worldwide user base. The WRF Model sees significant use for operational forecasting, and its research implementations are pushing the boundaries of finescale atmospheric simulation. Future model directions include developments in physics, exploiting emerging compute technologies, and ever-innovative applications. From its contributions to research, forecasting, educational, and commercial efforts worldwide, the WRF Model has made a s...

The weather research and forecast model: software architecture and performance

Abstract: The first non-beta release of the Weather Research and Forecast (WRF) modeling system in May, 2004 represented a key milestone in the effort to design and implement a fullyfunctioning, next-generation modeling system for the atmospheric research and operational NWP user communities. With efficiency, portability, maintainability, and extensibility as bedrock requirements, the WRF software framework has allowed incremental and reasonably rapid development while maintaining overall consistency and adherence to the architecture and its interfaces. The WRF 2.0 release supports the fullrange of functionality envisioned for the model including efficient scalable performance on a range of high-performance computing platforms, multiple dynamic cores and physics options, low-overhead two-way interactive nesting, moving nests, model coupling, and interoperability with other common model infrastructure efforts such as ESMF.

Numerical Simulation of Urban Heat Island Effect by the WRF Model with 4-km Grid Increment: An Inter-Comparison Study between the Urban Canopy Model and Slab Model

Abstract: The present study applies the WRF model involving the single-layer urban canopy model (hereafter, WRF_UCM) to urban climate simulation of the Tokyo metropolitan area for August (2004–2007) and compare results to (a) observations, and (b) the WRF model involving the slab urban model (hereafter, WRF_SLAB). In this urban area, WRF_UCM accurately captures the observed monthly mean daytime and nocturnal UHI, whereas WRF_SLAB does not show a nocturnal UHI. Moreover, the observed diurnal variations of the surface air temperature for central Tokyo and Kumagaya, a nearby inland city, are reproduced well by WRF_UCM. However, WRF_SLAB exhibits both a 1-hr phase shift and a 6.2 � C excess oscillation magnitude over observations. In addition, WRF_UCM accurately reproduces the frequency distribution of surface air temperatures, showing a maximum at 27 � C, whereas WRF_SLAB produce a bimodal distribution, with double peaks at 23 and 33 � C. Finally, WRF_UCM does a much better job than WRF_SLAB at modeling the relative humidity.

A Containerized Mesoscale Model and Analysis Toolkit to Accelerate Classroom Learning, Collaborative Research, and Uncertainty Quantification

Abstract: Numerical weather prediction (NWP) experiments can be complex and time consuming; results depend on computational environments and numerous input parameters. Delays in learning and obtaining research results are inevitable. Students face disproportionate effort in the classroom or beginning graduate-level NWP research. Published NWP research is generally not reproducible, introducing uncertainty and slowing efforts that build on past results. This work exploits the rapid emergence of software container technology to produce a transformative research and education environment. The Weather Research and Forecasting (WRF) Model anchors a set of linked Linux-based containers, which include software to initialize and run the model, to analyze results, and to serve output to collaborators. The containers are demonstrated with a WRF simulation of Hurricane Sandy. The demonstration illustrates the following: 1) how the often-difficult exercise in compiling the WRF and its many dependencies is eliminated, 2...

A Description of the Advanced Research WRF Version 3

Abstract: The Technical Note series provides an outlet for a variety of NCAR manuscripts that contribute in specialized ways to the body of scientific knowledge but which are not suitable for journal, monograph, or book publication. Reports in this series are issued by the NCAR Scientific Divisions ; copies may be obtained on request from the Publications Office of NCAR. Designation symbols for the series include: Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation.

A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes

Abstract: This paper proposes a revised vertical diffusion package with a nonlocal turbulent mixing coefficient in the planetary boundary layer (PBL). Based on the study of Noh et al. and accumulated results of the behavior of the Hong and Pan algorithm, a revised vertical diffusion algorithm that is suitable for weather forecasting and climate prediction models is developed. The major ingredient of the revision is the inclusion of an explicit treatment of entrainment processes at the top of the PBL. The new diffusion package is called the Yonsei University PBL (YSU PBL). In a one-dimensional offline test framework, the revised scheme is found to improve several features compared with the Hong and Pan implementation. The YSU PBL increases boundary layer mixing in the thermally induced free convection regime and decreases it in the mechanically induced forced convection regime, which alleviates the well-known problems in the Medium-Range Forecast (MRF) PBL. Excessive mixing in the mixed layer in the presenc...

Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model [presentation]

Abstract: Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

A Description of the Advanced Research WRF Version 2

Abstract: : The development of the Weather Research and Forecasting (WRF) modeling system is a multiagency effort intended to provide a next-generation mesoscale forecast model and data assimilation system that will advance both the understanding and prediction of mesoscale weather and accelerate the transfer of research advances into operations. The model is being developed as a collaborative effort ort among the NCAR Mesoscale and Microscale Meteorology (MMM) Division, the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental Prediction (NCEP) and Forecast System Laboratory (FSL), the Department of Defense's Air Force Weather Agency (AFWA) and Naval Research Laboratory (NRL), the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma, and the Federal Aviation Administration (FAA), along with the participation of a number of university scientists. The WRF model is designed to be a flexible, state-of-the-art, portable code that is an efficient in a massively parallel computing environment. A modular single-source code is maintained that can be configured for both research and operations. It offers numerous physics options, thus tapping into the experience of the broad modeling community. Advanced data assimilation systems are being developed and tested in tandem with the model. WRF is maintained and supported as a community model to facilitate wide use, particularly for research and teaching, in the university community. It is suitable for use in a broad spectrum of applications across scales ranging from meters to thousands of kilometers. Such applications include research and operational numerical weather prediction (NWP), data assimilation and parameterized-physics research, downscaling climate simulations, driving air quality models, atmosphere-ocean coupling, and idealized simulations (e.g boundary-layer eddies, convection, baroclinic waves).