Development of high resolution simulations of the atmospheric environment using the MASS model

Numerical simulations were performed with a very high resolution (7.25 km) version of the MASS model (Version 4.0) in an effort to diagnose the vertical wind shear and static stability structure during the Shuttle Challenger disaster which occurred on 28 January 1986. These meso-beta scale simulations reveal that the strongest vertical wind shears were concentrated in the 200 to 150 mb layer at 1630 GMT, i.e., at about the time of the disaster. These simulated vertical shears were the result of two primary dynamical processes. The juxtaposition of both of these processes produced a shallow (30 mb deep) region of strong vertical wind shear, and hence, low Richardson number values during the launch time period. Comparisons with the Cape Canaveral (XMR) rawinsonde indicates that the high resolution MASS 4.0 simulation more closely emulated nature than did previous simulations of the same event with the GMASS model

Mesoscale acid deposition modeling studies

The work performed in support of the EPA/DOE MADS (Mesoscale Acid Deposition) Project included the development of meteorological data bases for the initialization of chemistry models, the testing and implementation of new planetary boundary layer parameterization schemes in the MASS model, the simulation of transport and precipitation for MADS case studies employing the MASS model, and the use of the TASS model in the simulation of cloud statistics and the complex transport of conservative tracers within simulated cumuloform clouds. The work performed in support of the NASA/FAA Wind Shear Program included the use of the TASS model in the simulation of the dynamical processes within convective cloud systems, the analyses of the sensitivity of microburst intensity and general characteristics as a function of the atmospheric environment within which they are formed, comparisons of TASS model microburst simulation results to observed data sets, and the generation of simulated wind shear data bases for use by the aviation meteorological community in the evaluation of flight hazards caused by microbursts

Photoreceptor Outer Segment-like Structures in Long-Term 3D Retinas from Human Pluripotent Stem Cells.

The retinal degenerative diseases, which together constitute a leading cause of hereditary blindness worldwide, are largely untreatable. Development of reliable methods to culture complex retinal tissues from human pluripotent stem cells (hPSCs) could offer a means to study human retinal development, provide a platform to investigate the mechanisms of retinal degeneration and screen for neuroprotective compounds, and provide the basis for cell-based therapeutic strategies. In this study, we describe an in vitro method by which hPSCs can be differentiated into 3D retinas with at least some important features reminiscent of a mature retina, including exuberant outgrowth of outer segment-like structures and synaptic ribbons, photoreceptor neurotransmitter expression, and membrane conductances and synaptic vesicle release properties consistent with possible photoreceptor synaptic function. The advanced outer segment-like structures reported here support the notion that 3D retina cups could serve as a model for studying mature photoreceptor development and allow for more robust modeling of retinal degenerative disease in vitro

Model studies on the role of moist convection as a mechanism for interaction between the mesoscales

A three year research effort is described which had as its goal the development of techniques to improve the numerical prediction of cumulus convection on the meso-beta and meso-gamma scales. Two MESO models are used, the MASS (mesoscale) and TASS (cloud scale) models. The primary meteorological situation studied is the 28-29 Jun. 1986 Cooperative Huntsville Meteorological Experiment (COHMEX) study area on a day with relatively weak large scale forcing. The problem of determining where and when convection should be initiated is considered to be a major problem of current approaches. Assimilation of moisture data from satellite, radar, and surface data is shown to significantly improve mesoscale simulations. The TASS model is shown to reproduce some observed mesoscale features when initialized with 3-D observational data. Convection evolution studies center on comparison of the Kuo and Fritsch-Chappell cumulus parameterization schemes to each other, and to cloud model results. The Fritsch-Chappell scheme is found to be superior at about 30 km resolution, while the Kuo scheme does surprisingly well in simulating convection down to 10 km in cases where convergence features are well-resolved by the model grid. Results from MASS-TASS interaction experiments are presented and discussed. A discussion of the future of convective simulation is given, with the conclusion that significant progress is possible on several fronts in the next few years

Adaptation of Mesoscale Weather Models to Local Forecasting

Methodologies have been developed for (1) configuring mesoscale numerical weather-prediction models for execution on high-performance computer workstations to make short-range weather forecasts for the vicinity of the Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) and (2) evaluating the performances of the models as configured. These methodologies have been implemented as part of a continuing effort to improve weather forecasting in support of operations of the U.S. space program. The models, methodologies, and results of the evaluations also have potential value for commercial users who could benefit from tailoring their operations and/or marketing strategies based on accurate predictions of local weather. More specifically, the purpose of developing the methodologies for configuring the models to run on computers at KSC and CCAFS is to provide accurate forecasts of winds, temperature, and such specific thunderstorm-related phenomena as lightning and precipitation. The purpose of developing the evaluation methodologies is to maximize the utility of the models by providing users with assessments of the capabilities and limitations of the models. The models used in this effort thus far include the Mesoscale Atmospheric Simulation System (MASS), the Regional Atmospheric Modeling System (RAMS), and the National Centers for Environmental Prediction Eta Model ( Eta for short). The configuration of the MASS and RAMS is designed to run the models at very high spatial resolution and incorporate local data to resolve fine-scale weather features. Model preprocessors were modified to incorporate surface, ship, buoy, and rawinsonde data as well as data from local wind towers, wind profilers, and conventional or Doppler radars. The overall evaluation of the MASS, Eta, and RAMS was designed to assess the utility of these mesoscale models for satisfying the weather-forecasting needs of the U.S. space program. The evaluation methodology includes objective and subjective verification methodologies. Objective (e.g., statistical) verification of point forecasts is a stringent measure of model performance, but when used alone, it is not usually sufficient for quantifying the value of the overall contribution of the model to the weather-forecasting process. This is especially true for mesoscale models with enhanced spatial and temporal resolution that may be capable of predicting meteorologically consistent, though not necessarily accurate, fine-scale weather phenomena. Therefore, subjective (phenomenological) evaluation, focusing on selected case studies and specific weather features, such as sea breezes and precipitation, has been performed to help quantify the added value that cannot be inferred solely from objective evaluation

IEA wind recommended practices for selecting renewable power forecasting solutions : part 3 : evaluation of forecasts and forecast solutions

[Abstract unavailable

Spatial Heterogeneity Can Lead to Substantial Local Variations in COVID-19 Timing and Severity

Standard epidemiological models for COVID-19 employ variants of compartment (SIR) models at local scales, implicitly assuming spatially uniform local mixing. Here, we examine the effect of employing more geographically detailed diffusion models based on known spatial features of interpersonal networks, most particularly the presence of a long-tailed but monotone decline in the probability of interaction with distance, on disease diffusion. Based on simulations of unrestricted COVID-19 diffusion in 19 U.S cities, we conclude that heterogeneity in population distribution can have large impacts on local pandemic timing and severity, even when aggregate behavior at larger scales mirrors a classic SIR-like pattern. Impacts observed include severe local outbreaks with long lag time relative to the aggregate infection curve, and the presence of numerous areas whose disease trajectories correlate poorly with those of neighboring areas. A simple catchment model for hospital demand illustrates potential implications for health care utilization, with substantial disparities in the timing and extremity of impacts even without distancing interventions. Likewise, analysis of social exposure to others who are morbid or deceased shows considerable variation in how the epidemic can appear to individuals on the ground, potentially affecting risk assessment and compliance with mitigation measures. These results demonstrate the potential for spatial network structure to generate highly non-uniform diffusion behavior even at the scale of cities, and suggest the importance of incorporating such structure when designing models to inform healthcare planning, predict community outcomes, or identify potential disparities

IEA wind recommended practices for the implementation of wind power forecasting solutions part 2 and 3 : designing and executing forecasting benchmarks and evaluation of forecast solutions

In this paper, we summarize the second and third part of a series of three IEA Recommended Practice documents for the power industry that deal with how to setup and run a trial or benchmark as well as verifying the goodness of forecast solutions. The Recommended Practice is intended to serve as a set of standards that provide guidance for private industry, academics and government for the process of obtaining an optimal forecast solution for specific applications as well as the ongoing evaluation of the performance of the solution to increase the probability that it continues to be an optimal solution as forecast technology evolves. The work is part of the IEA Wind Task 36 on Wind Power Forecasting