The Application of a Genetic Algorithm to the Optimization of a Mesoscale Model for Emergency Response

Besides solving the equations of momentum, heat, and moisture transport on the model grid, mesoscale weather models must account for subgrid-scale processes that affect the resolved model variables. These are simulated with model parameterizations, which often rely on values preset by the user. Such ‘free’ model parameters, along with others set to initialize the model, are often poorly constrained, requiring that a user select each from a range of plausible values. Finding the values to optimize any forecasting tool can be accomplished with a search algorithm, and one such process – the genetic algorithm (GA) – has become especially popular. As applied to modeling, GAs represent a Darwinian process – an ensemble of simulations is run with a different set of parameter values for each member, and the members subsequently judged to be most accurate are selected as ‘parents’ who pass their parameters onto a new generation. At the Department of Energy’s Savannah River Site in South Carolina, we are applying a GA to the Regional Atmospheric Modeling System (RAMS) mesoscale weather model, which supplies input to a model to simulate the dispersion of an airborne contaminant as part of the site’s emergency response preparations. An ensemble of forecasts is run each day, weather data are used to ‘score’ the individual members of the ensemble, and the parameters from the best members are used for the next day’s forecasts. As meteorological conditions change, the parameters change as well, maintaining a model configuration that is best adapted to atmospheric conditions.

Effects of change in orientation and surface roughness of terrain oil thermally induced up slope flows in western Ghats: A numerical study

ABSTRACT. The effect of change in orientation and surface roughness of terrain on the daytime up slope flow is investigated using a 2-dimensional mesoscale model. A realistic orography profile of western ghat is chosen for the purpose. Twelve hour of integrations are performed starting from sunrise. The numerical simulation have shown that the intensity of up slope flows remained practically unaffected by change of orientation of terrain. However, increase in roughness length decreases the intensity of developed flows. For comparison purposes, the results of previous investigators are verified with a change in slope angles.

Non-Hydrostatic RegCM4 (RegCM4-NH): model description and case studies over multiple domains

We describe the development of a non-hydrostatic version of the regional climate model RegCM4, called RegCM4-NH, for use at convection-permitting resolutions. The non-hydrostatic dynamical core of the Mesoscale Model MM5 is introduced in the RegCM4, with some modifications to increase stability and applicability of the model to long-term climate simulations. Newly available explicit microphysics schemes are also described, and three case studies of intense convection events are carried out in order to illustrate the performance of the model. They are all run at a convection-permitting grid spacing of 3 km over domains in northern California, Texas and the Lake Victoria region, without the use of parameterized cumulus convection. A substantial improvement is found in several aspects of the simulations compared to corresponding coarser-resolution (12 km) runs completed with the hydrostatic version of the model employing parameterized convection. RegCM4-NH is currently being used in different projects for regional climate simulations at convection-permitting resolutions and is intended to be a resource for users of the RegCM modeling system.

Verifying urban canopy parameterization effects in a mesoscale model with wind tunnel data

<p>Airflow within and above urban canopy layers are modelled by different approaches in a wind tunnel and in a numerical mesoscale model. For the experimental approaches in the wind tunnel, the combination of spires, roughness elements and a physical model generates a scaled boundary layer flow with velocity and turbulence characteristics that are consistent with microscale urban canopy flows in reality. A wind tunnel is comparable in resolution with an obstacle resolving microscale model, therefore data comparisons are frequently done for this scale. However, for many applications numerical models of 1 km resolution are used, resolving mesoscale atmospheric phenomena but not microscale ones. Parameterizations are then used to represent physical processes and obstacle influences on the atmospheres. Due to the coarse resolution, a direct comparison of mesoscale model results and wind tunnel is difficult.</p> <p>In this study, we use wind tunnel data as validation datasets to evaluate the urban canopy parameterization effects on airflow in a mesoscale model. We have developed a multi-layer urban canopy parameterization using nudging, implemented in the atmospheric model METRAS. The extended model is tested in an idealized case, in which the model domain is designed using realistic topographical data for the Hamburg city center but not resolving buildings. To simplify the city structure, two important canopy morphological parameters are used: building surface fraction and building height. Experiments with a similar model configuration were carried out in parallel in the Blasius wind tunnel facility of the Environmental Wind-Tunnel Laboratory of the University of Hamburg at a model scale of 1:500. Based on the realistic building surface fraction and building height, a pyramid-like model for the urban canopy is placed in the wind tunnel. The set-ups of the numerical model runs and the wind tunnel experiments are designed following two principles: first, keeping the set-up in both approaches as equivalent as possible, in terms of meteorological conditions, roughness lengths, simulation durations, etc.; secondly, taking into account the limitations of the microscale wind tunnel datasets and keeping as many characteristics of atmospheric processes as possible.</p> <p>The METRAS results show a good agreement with the wind tunnel datasets, in terms of representing building effects such as the reduction of mean wind speeds in the building wake, enhanced turbulence intensities and turbulent fluctuation characteristics for a sufficiently fine scale. However, for coarser resolution, the result comparability reduces and the agreement is less. Thus, we conclude that sub-grid scale canopy effects can be parameterized sufficiently well for their impacts on the average flow, but any detailed changes can only be simulated with a sufficiently high resolution.</p>

Formation conditions of an ice storm in Vladivostok in November 2020

Synoptic conditions for the formation of an unprecedented ice storm with the generation of long-lived high-intensity glaze ice on the vast territory in Primorsky Krai are investigated. The leading role of the strong extension of the layer with positive temperature towards the cold air mass and the existence of two-way temperature advection in the lower troposphere are shown. It is shown that the long-term preservation of glaze ice on the territory of the region was associated with the movement of the southern cyclone to the east and the arrival of cold air masses from the continent. Experiments were implemented to simulate freezing precipitation using the WRF-ARW mesoscale model. The simulation results made it possible to obtain more detailed data on the vertical structure of the atmosphere during the formation of freezing precipitation and to fill in the missing data for analysis. Keywords: severe weather events, ice accretion, glaze ice, freezing rain, ice pellets, numerical weather prediction, WRF-ARW

Verification of real-time WRF-ARW forecast in IMD during monsoon 2010

Performance of the mesoscale model WRF-ARW has been evaluated for whole monsoon season of 2011. The real-time model forecasts are generated day to day in India meteorological Department for short-range weather prediction over the Indian region. Verification of rainfall forecasts has been carried out against observed rainfall analysis whereas for all other meteorological parameters verification analysis which was generated using WRFDA assimilation system. Traditional continuous scores and categorical skill scores are computed over seven different zones in India in the verification of rainfall. For other parameters (upper-air as well as surface), continuous scores are evaluated with temporal and spatial features during whole season. The forecast errors of meteorological parameters other than rainfall are analyzed to portray the model efficiency in maintaining monsoon features in large scale along with localized pattern. In the study, time series of errors throughout the season also has been maneuvered to evaluate model forecasts during diverse phases of monsoon. Categorical scores suggest the model forecasts are reliable up to moderate rainfall category for all seven zones. But, rainfall areas with rainfall above 35.5 mm per day associated with migrated weather system from Indian seas could not be predicted as the model displaces them in the forecast. The verification for a whole monsoon season has shown that the model has capability to predict orographic rainfall for the interactive areas with low level monsoon flow over Western Ghats. The model efficiency are in general brought out for a single monsoon season and errors characteristics are discussed for further improvement which could not perceived during real-time use of the model.

Ensemble Forecasting Experiments Using the Breeding of Growing Modes with Perturbed Land Variables

Although land surface influences atmospheric processes significantly, insufficient studies have been conducted on the ensemble forecasts using the breeding of growing modes (BGM) with perturbed land surface variables. To investigate the practicability of perturbed land variables for ensemble forecasting, we used the ARWv3 mesoscale model to generate ensembles for an event of 24 h heavy rainfall with perturbed atmospheric and land variables by the BGM method. Results show that both atmospheric and land variables can generate initial perturbations with BGM, except that they differ in time and saturation characteristics, e.g., saturation is generally achieved in approximately 30 h with a growth rate of ~1.30 for atmospheric variables versus 102 h and growth rate of 1.02 for land variables. With the increase in precipitation, the importance of the perturbations of land variables also increases as compared to those of atmospheric variables. Moreover, the influence of the perturbations of land variables on simulated precipitation is still relatively large, although smaller than that of atmospheric variables, e.g., the spreads of perturbed atmospheric and land subsets were 7.3 and 3.8 mm, respectively. The benefits of perturbed initialisation can also be observed in terms of probability forecast. All findings indicate that the BGM method with perturbed land variables has the potential to ensemble forecasts for precipitation.

Employment of MM5 in simulating MCSs developed in and around Bangladesh

The Mesoscale Convective Systems (MCSs) produce numerous weather hazards with their variety of forms. The formation mechanism of MCSs is thus important to know for Bangladesh and its surroundings, because this region is one of the heaviest rainfall areas in the tropical zone. The meteorologists are studying and analyzing the formation mechanism of different types of MCSs using radar and satellite observations data. Observations are limited to real time, but for planning purposes projected parameters over a certain period obtained from a mesoscale model is the requirement. Consequently, the motivation of this paper is to obtain the evolution and life cycle of MCSs developed in and around Bangladesh during pre-monsoon period through the simulation by a mesoscale model named MM5. In this work the calibration of MM5 model for different cumulus parameterization has been performed during the pre-monsoon period of this region. In the present study two domains with mesh resolutions 45 km × 45 km and 15 km × 15 km are prepared. MM5 runs using different cumulus parameterizations are carried out for sensitivity test. The precipitation simulated by the model are compared structurally and numerically with that of Tropical Rainfall Measuring Mission (TRMM) data products, available data from radar scan and observed rain-gauges rainfall in Bangladesh. Important features like lifetime, maintenance mechanism, traversed path, propagation speed and direction of MCSs developed during pre-monsoon period of 2002 in and around Bangladesh have been pointed out.