Shu-Hua Chen

Bio: Shu-Hua Chen is an academic researcher from University of California, Davis. The author has contributed to research in topics: Weather Research and Forecasting Model & Data assimilation. The author has an hindex of 24, co-authored 81 publications receiving 4034 citations. Previous affiliations of Shu-Hua Chen include National Center for Atmospheric Research & Water Resources University.

A Revised Approach to Ice Microphysical Processes for the Bulk Parameterization of Clouds and Precipitation

Abstract: A revised approach to cloud microphysical processes in a commonly used bulk microphysics parameterization and the importance of correctly representing properties of cloud ice are discussed. Several modifications are introduced to more realistically simulate some of the ice microphysical processes. In addition to the assumption that ice nuclei number concentration is a function of temperature, a new and separate assumption is developed in which ice crystal number concentration is a function of ice amount. Related changes in ice microphysics are introduced, and the impact of sedimentation of ice crystals is also investigated. In an idealized thunderstorm simulation, the distribution of simulated clouds and precipitation is sensitive to the assumptions in microphysical processes, whereas the impact of the sedimentation of cloud ice is small. Overall, the modifications introduced to microphysical processes play a role in significantly reducing cloud ice and increasing snow at colder temperatures and ...

A One-dimensional Time Dependent Cloud Model

Abstract: A one-dimensional prognostic cloud model has been developed for possible use in a Cumulus Parameterization Scheme (CPS). In this model, the nonhydrostatic pressure, entrainment, cloud microphysics, lateral eddy mixing and vertical eddy mixing are included, and their effects are discussed. The inclusion of the nonhydrostatic pressure can (1) weaken vertical velocities, (2) help the cloud develop sooner, (3) help maintain a longer mature stage, (4) produce a stronger overshooting cooling, and (5) approximately double the precipitation amount. The pressure perturbation consists of buoyancy pressure and dynamic pressure, and the simulation results show that both of them are important. We have compared our simulation results with those from Ogura and Takahashi's one-dimensional cloud model, and those from the three-dimensional Weather Research and Forecast (WRF) model. Our model, including detailed cloud microphysics, generates stronger maximum vertical velocity than Ogura and Takahashi's results. Furthermore, the results illustrate that this one-dimensional model is capable of reproducing the major features of a convective cloud that are produced by the three-dimensional model when there is no ambient wind shear.

Effects of Moist Froude Number and CAPE on a Conditionally Unstable Flow over a Mesoscale Mountain Ridge

Abstract: In this study, idealized simulations are performed for a conditionally unstable flow over a two-dimensional mountain ridge in order to investigate the propagation and types of cloud precipitation systems controlled by the unsaturated moist Froude number (Fw) and the convective available potential energy (CAPE). A two-dimensional moist flow regime diagram, based on Fw and CAPE, is proposed for a conditionally unstable flow passing over a two-dimensional mesoscale mountain ridge. The characteristics of these flow regimes are 1) regime I: flow with an upstream-propagating convective system and an early, slowly moving convective system over the mountain; 2) regime II: flow with a long-lasting orographic convective system over the mountain peak, upslope, or lee slope; 3) regime III: flow with an orographic convective or mixed convective and stratiform precipitation system over the mountain and a downstream-propagating convective system; and 4) regime IV: flow with an orographic stratiform precipitatio...

Identifying PM2.5 and PM0.1 sources for epidemiological studies in California.

Abstract: The University of California-Davis_Primary (UCD_P) model was applied to simultaneously track ∼ 900 source contributions to primary particulate matter (PM) in California for seven continuous years (January 1st, 2000 to December 31st, 2006). Predicted source contributions to primary PM2.5 mass, PM1.8 elemental carbon (EC), PM1.8 organic carbon (OC), PM0.1 EC, and PM0.1 OC were in general agreement with the results from previous source apportionment studies using receptor-based techniques. All sources were further subjected to a constraint check based on model performance for PM trace elemental composition. A total of 151 PM2.5 sources and 71 PM0.1 sources contained PM elements that were predicted at concentrations in general agreement with measured values at nearby monitoring sites. Significant spatial heterogeneity was predicted among the 151 PM2.5 and 71 PM0.1 source concentrations, and significantly different seasonal profiles were predicted for PM2.5 and PM0.1 in central California vs southern California. Population-weighted concentrations of PM emitted from various sources calculated using the UCD_P model spatial information differed from the central monitor estimates by up to 77% for primary PM2.5 mass and 148% for PM2.5 EC because the central monitor concentration is not representative of exposure for nearby population. The results from the UCD_P model provide enhanced source apportionment information for epidemiological studies to examine the relationship between health effects and concentrations of primary PM from individual sources.

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...

Climate Change 2007: The Physical Science Basis.

Abstract: Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.

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).