Comparison of two land surface schemes in week-long cloud-system-resolving simulations of warm season precipitation

This paper presents a case study of the impact of land surface treatment on warm season precipitation simulations at convection-permitting grid resolution. Two surface schemes are tested: Dudhia’s five-layer soil model (FLSM) and the Noah land-surface model (NLSM). The experimentation case involves a 1-week episode of active summertime convection over the central United States. The overall precipitation features, such as the diurnal regeneration of zonally propagating rainfall episodes and the spatial distribution of accumulative rainfall, are adequately replicated by the two parameterizations. In comparison, NLSM produces roughly 12% more and broader rainfall than FLSM. This differential rainfall amount is consistent with the differential surface moisture fluxes between the two schemes, whereas the precipitation feedback plays a negligible role. It is also found that FLSM generates comparatively stronger sensible heat transports from the land surface and thus a warmer temperature near the surface.     

Testing GISS-MM5 physics configurations for use in regional impacts studies

The Mesoscale Modeling System Version 5 (MM5) was one-way nested to the Goddard Institute for Space Studies global climate model (GISS GCM), which provided the boundary conditions for present (1990s) and future (IPCC SRES A2 scenario, 2050s) five-summer “time-slice” simulations over the continental and eastern United States. Five configurations for planetary boundary layer, cumulus parameterization, and radiation scheme were tested, and one set was selected for use in the New York City Climate and Health Project—a multi-disciplinary study investigating the effects of climate change and land-use change on human health in the New York metropolitan region. Although hourly and daily data were used in the health project, in this paper we focus on long-term current and projected mean climate change. The GISS-MM5 was very sensitive to the choice of cumulus parameterization and planetary boundary layer scheme, leading to significantly different temperature and precipitation outcomes for the 1990s. These differences can be linked to precipitation type (convective vs. non-convective), to their effect on solar radiation received at the ground, and ultimately to surface temperature. The projected changes in climate (2050s minus 1990s) were not as sensitive to choice of model physics combination. The range of the projected surface temperature changes at a given grid point among the model versions was much less than the mean change for all five model configurations, indicating relative consensus for simulating surface temperature changes among the different model projections. The MM5 versions, however, offer less consensus regarding 1990s to 2050s changes in precipitation amounts. All of the projected 2050s temperature changes were found to be significant at the 95th percent confidence interval, while the majority of the precipitation changes were not.     

Simulations of Cyclone Sidr in the Bay of Bengal with a high-resolution model: sensitivity to large-scale boundary forcing

The predictability of Cyclone Sidr in the Bay of Bengal was explored in terms of track and intensity using the Advanced Research Hurricane Weather Research Forecast (AHW) model. This constitutes the first application of the AHW over an area that lies outside the region of the North Atlantic for which this model was developed and tested. Several experiments were conducted to understand the possible contributing factors that affected Sidr??s intensity and track simulation by varying the initial start time and domain size. Results show that Sidr??s track was strongly controlled by the synoptic flow at the 500-hPa level, seen especially due to the strong mid-latitude westerly over north-central India. A 96-h forecast produced westerly winds over north-central India at the 500-hPa level that were notably weaker; this likely caused the modeled cyclone track to drift from the observed actual track. Reducing the model domain size reduced model error in the synoptic-scale winds at 500?hPa and produced an improved cyclone track. Specifically, the cyclone track appeared to be sensitive to the upstream synoptic flow, and was, therefore, sensitive to the location of the western boundary of the domain. However, cyclone intensity remained largely unaffected by this synoptic wind error at the 500-hPa level. Comparison of the high resolution, moving nested domain with a single coarser resolution domain showed little difference in tracks, but resulted in significantly different intensities. Experiments on the domain size with regard to the total precipitation simulated by the model showed that precipitation patterns and 10-m surface winds were also different. This was mainly due to the mid-latitude westerly flow across the west side of the model domain. The analysis also suggested that the total precipitation pattern and track was unchanged when the domain was extended toward the east, north, and south. Furthermore, this highlights our conclusion that Sidr was influenced from the west side of the domain. The displacement error was significantly reduced after the domain size from the western model boundary was decreased. Study results demonstrate the capability and need of a high-resolution mesoscale modeling framework for simulating the complex interactions that contribute to the formation of tropical cyclones over the Bay of Bengal region.     

A history of mesoscale model development

The development of atmospheric mesoscale models from their early origins in the 1970’s until the present day is described. Evolution has occurred in dynamical and physics representations in these models. The dynamics has had to change from hydrostatic to fully nonhydrostatic equations to handle the finer scales that have become possible in the last few decades with advancing computer power, which has enabled real-time forecasting to go to finer grid sizes. Meanwhile the physics has also become more sophisticated than the initial representations of the major processes associated with the surface, boundary layer, radiation, clouds and convection. As resolutions have become finer, mesoscale models have had to change paradigms associated with assumptions related to what is considered sub-grid scale needing parameterization, and what is resolved well enough to be explicitly handled by the dynamics. This first occurred with cumulus parameterization as real-time forecast models became able to represent individual updrafts, and is now starting to occur in the boundary layer as future forecast models may be able resolve individual thermals. Beyond that, scientific research has provided a greater understanding of detailed microphysical and land-surface processes that are important to aspects of weather prediction, and these parameterizations have been developing complexity at a steady rate. This paper can just give a perspective of these developments in the broad field of research associated with mesoscale atmospheric model development.     

Nonhydrostatic,mesobeta-scale,real-data simulations with the Penn State University/National Center for Atmospheric Research mesoscale model

Summary The Penn State University/National Center for Atmospheric Research (PSU/NCAR) mesoscale model is a widely used research tool that has been applied in a wide variety of real-data, mesoalpha-scale applications. Recently a nonhydrostatic version of this model has been developed by Dudhia (1993). It is the purpose of this paper to illustrate the capabilities of this modeling system by describing four examples of mesobeta-scale simulations: two of the cases involve maritime processes and two deal with continental weather events. All utilize fully three-dimensional sets of initial conditions that are based on real data, both standard data and from special measurements programs. One case employs the model in a data-assimilation configuration, wherein Newtonian relaxation terms are used in the equations to assimilate data from a variety of platforms. This example of nonhydrostatic four-dimensional data assimilation (FDDA) is performed for the purpose of generating a dynamically consistent four-dimensional data-set, however the same procedure can be used for model initialization. The first case, described in section 2, involves the simulation of a coastal front that forms offshore near the western edge of the Gulf Stream. In the second case, described in section 3, the model is used in the FDDA mode to define the mesobeta-scale windfield over the complex terrain of the region around Grand Canyon, Arizona. In sections 4 and 5 will be described the mesobeta-scale structure of cold fronts, one within a marine cyclone, and another near the Rocky Mountains.With 21 FiguresNCAR is sponsored by the National Science Foundation.     

A new technique for evaluating mesospheric momentum balance utilizing radars and satellite data

A new method for evaluating momentum balance in the mesosphere using radar and satellite data is presented. This method is applied to radar wind data from two medium frequency installations (near Adelaide, Australia and Christchurch, New Zealand) and satellite temperature data from the Improved Stratospheric and Mesospheric Sounder (ISAMS). Because of limitations in data availability and vertical extent, the technique can only be applied to evaluate the momentum balance at 80 km above the radar sites for May 1992. The technique allows the calculation of the residual terms in the momentum balance which are usually attributed to the effects of breaking gravity waves. Although the results are inconclusive above Adelaide, this method produces values of zonal and meridional residual accelerations above Christchurch which are consistent with expectation. In both locations it is apparent that geostrophic balance is a poor approximation of reality. (This result is not dependent on a mismatch between the radar and satellite derived winds, but rather is inherent in the satellite data alone.) Despite significant caveats about data quality the technique appears robust and could be of use with data from future instruments.     

公里级CMA_MESO模式FSS评分技术研究

本文研究计算CMA_MESO模式预报降水FSS（Fractions Skill Score）评分时,当其水平分辨率与观测降水不一致时,采取两种匹配方式统一分辨率,分析这两种方式得到的FSS评分结果是否有差异。针对3 km分辨率CMA_MESO模式6 h累积降水,选取5 km分辨率的观测降水,分别采取预报降水匹配观测降水分辨率,以及观测降水匹配预报降水分辨率两种方式,选择4种邻域尺度：5、25、51和105 km;4种降水阈值：0.1、4、13和25 mm,得到两组不同预报时效的FSS评分。通过分析发现：两组FSS评分结果没有显著差异。研究结果表明,当CMA_MESO模式预报降水水平分辨率与观测降水不一致时,可以将预报降水匹配到观测降水格点场,也可以将观测降水匹配到预报降水格点场,两种匹配方式对FSS评分结果没有影响。