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Climate change significantly affects the operating environment of buildings. These changes impact both energy efficiency and occupants' comfort and remain crucial even in building restoration, where design decisions typically rely on historical data, yet performance depends on anticipated future scenarios. The present work evaluates the impact of different climate datasets on dynamic energy simulations for an educational building in Central Italy, focusing on estimating heating demands across historical, current, and future climatic scenarios. The assessment considers both the building's current state and potential energy-efficient retrofits. Initially, various meteorological datasets, including measured and model-generated data, are selected to predict key weather parameters. The analysis reveals the potential and limitations of regional climate models (RCMs) in estimating these variables, with the MM5 dataset emerging as the most reliable. Subsequently, the energy performance of the reference building and its vulnerability to climate change are assessed. Our results show significant differences in energy demand based on construction periods, with the oldest section consuming 29% to 54% more energy monthly than the newer sections. Moreover, using non-representative climatic files can lead to prediction errors of up to 199%. Finally, the building's energy behaviour is analysed under future climate conditions by generating typical meteorological years (TMYs) for 2030, 2050, and 2070. This analysis evaluates the energy requirements for both existing and retrofitted building configurations. The findings confirm that retrofit interventions with high-performance insulation and upgraded windows significantly enhance the building's energy efficiency and resilience to future climate conditions, leading to annual energy savings of 50% to 57%. [ABSTRACT FROM AUTHOR]

Climate change significantly affects the operating environment of buildings. These changes impact both energy efficiency and occupants’ comfort and remain crucial even in building restoration, where design decisions typically rely on historical data, yet performance depends on anticipated future scenarios. The present work evaluates the impact of different climate datasets on dynamic energy simulations for an educational building in Central Italy, focusing on estimating heating demands across historical, current, and future climatic scenarios. The assessment considers both the building’s current state and potential energy-efficient retrofits. Initially, various meteorological datasets, including measured and model-generated data, are selected to predict key weather parameters. The analysis reveals the potential and limitations of regional climate models (RCMs) in estimating these variables, with the MM5 dataset emerging as the most reliable. Subsequently, the energy performance of the reference building and its vulnerability to climate change are assessed. Our results show significant differences in energy demand based on construction periods, with the oldest section consuming 29% to 54% more energy monthly than the newer sections. Moreover, using non-representative climatic files can lead to prediction errors of up to 199%. Finally, the building’s energy behaviour is analysed under future climate conditions by generating typical meteorological years (TMYs) for 2030, 2050, and 2070. This analysis evaluates the energy requirements for both existing and retrofitted building configurations. The findings confirm that retrofit interventions with high-performance insulation and upgraded windows significantly enhance the building’s energy efficiency and resilience to future climate conditions, leading to annual energy savings of 50% to 57%.

Featured Application: Forecast procedures for building energy renovation and design. In recent years, the need to make the built environment more resilient and adaptable to climate change has become essential. In Europe, this aspect concerns most existing buildings with several deficiencies from the energy efficiency point of view, considering they were designed before the introduction of modern codes. Among the various strategies for building energy retrofitting, Double-Skin Façades (DSFs) have gained attention due to their potential to improve the building performance and inhabitants' comfort. This research aims to evaluate the use of adequately designed DSFs for the energy restoration of buildings. In detail, various DSF configurations are applied to a residential building located in Central Italy and investigated under present and future climate conditions, estimated through regional climate models. The installation of multi-layered façades, particularly the Multi-Storey typology, greatly reduces energy consumption and increases the expected comfort rates. When the selected configuration was considered, the results underline a decrease in the annual building energy requirement of about 37–56% up to 42–59%, respectively, for 2030 and 2070. Moreover, using multi-layer façades can increase indoor minimum operative temperatures up to 3.8% during the coldest months and reduce the maximum summer ones by 1.9–3.8%, raising comfort levels. [ABSTRACT FROM AUTHOR]

This essay describes the author's lifetime experiences with predictability theory and weather predictions. [ABSTRACT FROM AUTHOR]

In recent years, the need to make the built environment more resilient and adaptable to climate change has become essential. In Europe, this aspect concerns most existing buildings with several deficiencies from the energy efficiency point of view, considering they were designed before the introduction of modern codes. Among the various strategies for building energy retrofitting, Double-Skin Façades (DSFs) have gained attention due to their potential to improve the building performance and inhabitants’ comfort. This research aims to evaluate the use of adequately designed DSFs for the energy restoration of buildings. In detail, various DSF configurations are applied to a residential building located in Central Italy and investigated under present and future climate conditions, estimated through regional climate models. The installation of multi-layered façades, particularly the Multi-Storey typology, greatly reduces energy consumption and increases the expected comfort rates. When the selected configuration was considered, the results underline a decrease in the annual building energy requirement of about 37–56% up to 42–59%, respectively, for 2030 and 2070. Moreover, using multi-layer façades can increase indoor minimum operative temperatures up to 3.8% during the coldest months and reduce the maximum summer ones by 1.9–3.8%, raising comfort levels.

روش‌های اندکی به امکان‌سنجی استفاده از برونداد مدل‌های پیش‌بینی عددی در تخمین مقادیر از دست‌رفته تصاویر سنجش‌ازدور پرداخته‌اند. بدین منظور در تحقیق حاضر علاوه بر ارزیابی الگوریتم SPA در بازسازی تصاویر، امکان‌ استفاده از برونداد مدل پیش‌بینی عددی MM5 در تخمین مقادیر مفقود تصاویر سنجش‌ازدور بررسی شد. این مطالعه با استفاده از سری زمانی تولیدات LST مودیس در سال‌های 2000 تا 2010 میلادی و برای منطقه شمال شرق ایران انجام شده است. نتایج شبیه‌سازی‌ها بر اساس شاخص‌های اعتبارسنجی RMSE، AD و R2 با یکدیگر مقایسه شدند. ارزیابی‌های کمی نشان دادند که روش SPA با مقدار میانگین خطای 48/1 درجه سلسیوس، 95/1= RMSE و 79/0=R2 دقت مناسب و عملکرد خوبی در تخمین مقادیر مفقود دارد. اعتبار‌سنجی و مقایسه الگوریتم‌ها در حالت پایه (آزمون 1) و حالت استفاده از برو‌نداد مدل MM5 (آزمون 2) نشان دادند که در صورت نبود تصاویر کمکی مناسب سنجش‌ازدور می‌توان از خروجی مدل‌ MM5 در الگوریتم‌های هیبرید و بازسازی تصاویر استفاده نمود. ارزیابی بصری تصاویر بازسازی شده نشان داد که اجرای الگوریتم SPA برای هر دو آزمون، در بافت تصاویر مورد مطالعه الگوی مکانی مصنوعی ایجاد نکرد و روند تغییرات مکانی LST حفظ شد. روش‌های اندکی به امکان‌سنجی استفاده از برونداد مدل‌های پیش‌بینی عددی در تخمین مقادیر از دست‌رفته تصاویر سنجش‌ازدور پرداخته‌اند. بدین منظور در تحقیق حاضر علاوه بر ارزیابی الگوریتم SPA در بازسازی تصاویر، امکان‌ استفاده از برونداد مدل پیش‌بینی عددی MM5 در تخمین مقادیر مفقود تصاویر سنجش‌ازدور بررسی شد. این مطالعه با استفاده از سری زمانی تولیدات LST مودیس در سال‌های 2000 تا 2010 میلادی و برای منطقه شمال شرق ایران انجام شده است. نتایج شبیه‌سازی‌ها بر اساس شاخص‌های اعتبارسنجی RMSE، AD و R2 با یکدیگر مقایسه شدند. ارزیابی‌های کمی نشان دادند که روش SPA با مقدار میانگین خطای 48/1 درجه سلسیوس، 95/1= RMSE و 79/0=R2 دقت مناسب و عملکرد خوبی در تخمین مقادیر مفقود دارد. اعتبار‌سنجی و مقایسه الگوریتم‌ها در حالت پایه (آزمون 1) و حالت استفاده از برو‌نداد مدل MM5 (آزمون 2) نشان دادند که در صورت نبود تصاویر کمکی مناسب سنجش‌ازدور می‌توان از خروجی مدل‌ MM5 در الگوریتم‌های هیبرید و بازسازی تصاویر استفاده نمود. ارزیابی بصری تصاویر بازسازی شده نشان داد که اجرای الگوریتم SPA برای هر دو آزمون، در بافت تصاویر مورد مطالعه الگوی مکانی مصنوعی ایجاد نکرد و روند تغییرات مکانی LST حفظ شد.

El cambio de uso de suelo es uno de los problemas más complejos que se observa como parte del proceso de expansión urbana, lo cual trae como consecuencia la formación de la Isla de Calor Urbano (ICU). Con el objetivo de identificar la presencia de la ICU en la ciudad de Tuxtla Gutiérrez, Chiapas, se implementó el modelo meteorológico MM5 para simular las condiciones meteo- rológicas durante el período del 30 de abril al 6 de mayo de 2017. Con base en las condiciones atmosféricas, se seleccionó el día 3 de mayo para ilustrar la ICU sobre la zona de estudio. Los resultados muestran la existencia del fenómeno sobre la ciudad a diferentes horas del día con intensidades que varían de 0.5 a 2.5 ◦C, sin embargo, éstas podrían ser mayores a los 5 ◦C y afectar principalmente la zona centro de la ciudad debido a factores como las propiedades del suelo, los flujos de calor, así como las características geomorfológicas del lugar. Por otro lado, se simuló un cambio de uso de suelo a partir de las tendencias de crecimiento actual de la ciudad, observándose en algunos casos un incremento en la extensión e intensidad de la ICU. Por tanto, se señala la presencia de la ICU en la ciudad donde se indica la importancia de la protección y conservación de las áreas verdes, por lo que los estudios relacionados a la ICU deberían ser considerados como parte de la planeación territorial para el desarrollo urbano.

The present paper aims to expose the Mesoscale-Microscale numerical approach adopted for studying the air fluxes inside an urban area located in the city of Pescara (Italy). The data, recorded by a real anemometer, are compared with three Mesoscale models (Pleim-Xiu, Blackadar and MRF-LSM), each of them presents five nested domains. On the bases of the monthly values of Root Mean Square Error, BIAS and Standard Deviation, the most accurate mesoscale model is identified and evaluated. On the Microscale side, instead, two cylindrical domains are studied. The first model considers only the topography of the terrain, whereas the other also adds the buildings present inside the investigated area. The domains, with a diameter of 6 [km] and a height equal to 0.5 [km], are studied by assuming the incoming wind from four different directions. Comparisons are then made among wind speeds and directional inflows obtained from the two models. Mesoscale analyses are carried out with the weather forecast software MM5, and Microscale simulations are performed with the commercial software STAR-CCM+. [ABSTRACT FROM AUTHOR]

Surface water and energy fluxes are tightly coupled with CO2 exchanges between the ecosystem and atmosphere. Other surface-to-atmosphere trace-gas exchanges of interest in climate change research (e.g., N2O, CH4, C18OO, and H218O) are also strongly impacted by surface energy exchanges. Further, land-use change has large effects on the surface energy balance and therefore the exchanges of these trace gases. To investigate these issues at the regional scale we have coupled MM5 (Grell et al. 1995) with ISOLSM (Riley et al. 2002, Riley et al. 2003), a land-surface model based on LSM1 (Bonan 1995).

O objetivo desse estudo é a analise dos efeitos dos parâmetros de configuração do modelo CALMET sobre a simulação da circulação atmosférica em superfície nas Bacias Aéreas I e III da Região Metropolitana do Rio de Janeiro (RMRJ). O estudo foi realizado para um período em que a RMRJ estava sob a atuação de um sistema de alta pressão, que não influenciou significativamente as circulações locais na região. A análise conjunta dos resultados indica que a melhor configuração para simulações do campo de vento na RMRJ com o sistema combinado de modelagem MM5/CALMET é obtida utilizando o valor de 10 km para o parâmetro TERRAD e Raio de Influência entre 7 e 10 km.

A dinâmica de urbanização nas metrópoles produz um ambiente urbano altamente degradado, com muitos efeitos graves sobre a qualidade de vida da população. Na Região Metropolitana do Rio de Janeiro (RMRJ) o uso intensivo das atividades antrópicas causam problemas ambientais, observando-se dentre outros a modificação do solo proporcionando o surgimento do fenômeno de Ilha de Calor Urbana (ICU). O presente trabalho objetiva avaliar o desempenho dos modelos meteorológicos MM5 e WRF em simular a variável temperatura do ar próximo à superfície na RMRJ. Os modelos são comparados baseados em índices estatísticos e dados observacionais em um período em que houve a ocorrência do fenômeno de ICU. Nas avaliações é analisado o ciclo diário de temperatura do ar e índices estatísticos a partir dos dados simulados e dados observados. Os resultados apontam um desempenho satisfatório de ambos os modelos em reproduzir o ciclo diário de temperatura do ar próximo à superfície para todo o período de estudo, com uma ligeira tendência dos dados simulados em subestimar as temperaturas máximas observadas e superestimar as mínimas temperaturas observadas. Os índices estatísticos revelam desempenho semelhante entre o MM5 e WRF, e uma adequada aderência aos dados observados de temperatura nas estações SBGL, SBAF, SBJR e SBSC. Os maiores desvios entre os dados simulados e observados ocorreram na estação SBRJ. A análise conjunta da variação temporal e dos índices estatísticos mostrou a habilidade dos modelos meteorológicos em representar a temperatura do ar próximo à superfície tanto na distribuição espacial bem como na variação temporal, e desta forma, existe uma confiabilidade em estudar o fenômeno de ICU através dos modelos MM5 e WRF na RMRJ.

The objective of the present research was to assess the surface energy balance particularly in terms of the computed surface energy and radiation balance and the development of boundary layer over Jakarta and Neighboring Regions (JNR) by means of numerical model of fifth generation of Mesoscale Model (MM5). The MM5 with four domains of 9 kilometers in spatial resolution presenting the outermost and the innermost of JNR is utilized. The research focuses on the third and fourth domains covering the entire JNR. The description between radiation and energy balance at the surface is obtained from the model. The result showed that energy balance is higher in the city area during daytime. Meanwhile, energy components, e.g., surface sensible and latent heat flux showed that at the sea and in the city areas were higher than other areas. Moreover, ground flux showed eastern region was higher than others. In general, radiation and energy balance was higher in the daytime and lower in the nighttime for all regions. The calculation of Bowen Ratio, the ratio of surface sensible and latent heat fluxes, was also higher in the city area, reflecting the dominations of urban and built-up land in the region. Meanwhile, Bowen Ratio in the rural area dominated by irrigated cropland was lower. It is consistent with changes of land cover properties, e.g. albedo, soil moisture, and thermal characteristics. In addition, the boundary layer is also higher in the city. Meanwhile western region dominated by suburban showed higher boundary layer instead of eastern region.

La gran disponibilidad de vapor de agua en los niveles inferiores de la atmósfera, advectada sobre la costa de la provincia de Santa Catarina por el anticiclón semiestacionario del Océano Atlántico, favoreció períodos frecuentes de lluvia durante el mes de noviembre de 2008. La exploración del evento extremo ocurrido en Santa Catarina, que se caracterizó por un intenso bloqueo en niveles altos, se realizó con pronósticos de los modelos del mesoescala MM5 y WRF. Estos modelos fueron procesados con muy alta resolución espacial, abarcando toda la región afectada por el evento severo. La temperatura de la superficie del mar presentaba anomalías positivas de temperatura a lo largo de la costa de Santa Catarina, favoreciendo la transferencia de calor latente hacia la atmósfera, con su posterior advección hacia la zona continental. Los resultados obtenidos con los modelos son consistentes con las observaciones, aunque fuertemente dependientes de la resolución horizontal de los mismos.The large availability of water vapor at low levels of the atmosphere, advected into the coastal region of Santa Catharina State by the Atlantic Ocean semi-stationary anticyclone, provided the frequent and copious rainfall during the November, 2008. One of the most extreme event occurred in Santa Catharina coastal zone, when a quite strong blocking formed at high levels of the atmosphere is explored processing both, the MM5 and WRF mesoscale models. These models were processed with very high spatial resolution domains, covering the entire region affected by the severe event. The sea surface temperature field revealed that there was a large core on Atlantic waters with quite high temperatures along the coast of Santa Catharina, which enhanced the vertical integrated latent heat supply into the continental region by the winds. The models forecasting results showed consistent results with the observations, as well as an indication that coherences are directly related to the horizontal resolution of the models configurations.

A mesoscale meteorological model of modified land cover to the effect of urban heat island (UHI) in Jakarta was done. Although higher temperature in the city has been generally known, factors and issues that result in the increase of temperature particularly nighttime temperature over the city, however, are not well-understood. Jakarta, the capital of Indonesia, is encountering urbanization problems foremost. The increasing demand of housing as well as rapid development of sky crapper building, market places and highway diminishes the vegetation which in turn trap heat in the troposphere throughout the year, particularly during dry season on June-August. The fifth-generation mesoscale meteorological model (MM5) was employed in the study. The model involves medium range forecast planetary boundary layer (MRF PBL) scheme and land surface with two following parameters: i.e. roughness length over land and thermal inertia of land. These two parameters are chosen to enhance the characteristics of land surface. The simulation was carried out for 3 days on August 5-7, 2004 during dry season. The results showed that the simulation of surface temperature done by MM5 modified land cover described a good comparison to that of weather observation data. As a result, the effect of UHI was also well-observed during day-time. In addition, MM5 modified land cover simulation also illustrated a well-development of sea-breeze and country-breeze during mid-day and nighttime, respectively. However, long-term simulation is still required. Thus, daily diurnal cycles of air temperature and their differences can be well-observed in detail.

This article reports on the inland re-intensification of tropical storm (TS) Erin (2007). In this research, the physical processes that resulted in the re-intensification of TS Erin over Oklahoma, USA, on 19 August 2007 was determined and a sensitivity study on microphysics, planetary boundary layer and convective parameterisation schemes was performed in the mesoscale modelling system, MM5. Also, we diagnosed and explained the remarkable difference between model behaviour of the original Kain–Fritsch 1 (KF1) scheme and its revised counterpart (KF2). The numerical results showed only modest sensitivity to the selected microphysics schemes – the relatively simple ‘Simple Ice’ and the advanced Reisner-Graupel. We found a relatively high sensitivity to the selected boundary layer parameterisation. Enhanced mixing in the medium range forecast (MRF) scheme leads to a relatively small convective available potential energy (CAPE), a deeper boundary layer and a lower dew point temperature, thus to a relatively stable environment. Therefore, MRF forecasts less precipitation (up to 150 mm) than the local mixing scheme, ETA. Model results appeared most sensitive to the selected convection schemes, that is, Grell, KF1 and KF2. With Grell and KF1, Erin intensifies and produces intense precipitation, but its structure remains close to a mesoscale convective system (MCS) or squall line rather than of the observed tropical cyclone. Both schemes also simulate the most intense precipitation too far south (100 km) compared to observations. On the contrary, KF2 underestimates precipitation, but the track of the convection, the precipitation and the pressure distribution are relatively close to radar and field observations. A sensitivity study reveals that the downdraft formulation is critical to modelling TS Erin's dynamics. Within tropical cyclogenesis, the mid-level relative humidity (RH) is generally very high, resulting in very small downdrafts. KF2 generates hardly any downdrafts due to its dependence on mid-level RH. However, KF1 and Grell generate much stronger downdrafts because they both relate the downdraft mass flux (DMF) to vertical wind shear. This larger DMF then completely alters TS Erin's dynamics. A modified version of the Grell scheme with KF2 RH-dependent downdraft formulation improved the simulation considerably, with better resemblance to observations on trajectory, radar reflectivity and system structure.

As part of the group of research institutions and universities participating in the UNIDATA program, the Federal University of Pelotas (RS-Brazil) has implemented an automatic data acquisition with forecasting and synoptic analysis system. It is based on the data distribution system (IDD) of the UNIDATA (University Data Project) and uses the Local Data Management module (LDM). This is an integrated system which has been primarily implemented to use the GFS/NCEP global forecasting model data for the processing of the regional MM5 mesoscale model, providing the necessary initial and lateral boundary conditions data. The MM5 has been configured to provide the forecast of the mesoscale systems over the State of Rio Grande do Sul (RS). The use of the data and model integrated system contributes to improve the skill analysis of the model output, aiming to investigate the benefits of its association in the evaluation of the performance of the integrated system.

To identify the domains that have the greatest impacts on air quality at the surface, both the upwind and downwind areas of Seoul were determined by season using refined wind fields. Four consecutive days were selected as the study period typical of each season. The mesoscale meteorology of the study period was reproduced by using the MM5 prognostic meteorological model (PSU/NCAR Mesoscale Model) with horizontally nested grids. The gridded meteorological field, which was used on the study area of 242 km×226 km with grid spacing of 2 km, was generated by using the CALMET diagnostic meteorological model. Upwind and downwind areas of Seoul were determined by calculating 24-hour backward and forward air parcel trajectories, respectively, with u, v, and w velocity vectors. The results showed that the upwind and downwind areas were extended far to the northwest and the southeast as a result of high wind speeds in the spring and winter, while they were restricted on the fringe of Seoul in the summer and fall.

It has been widely known that changes of the land surface from vegetation area to urban area can substantially affect the surrounding meteorological condition. Meteorological model was used to assess meteorological condition for air quality modeling and forecasting. Inputs used in this study for the meteorological and air quality model were land use and land cover of the terrain. This study tends to examine the sensitivity of land use and land cover on the predicted meteorological conditions. A meteorological simulation using fifth generation mesoscale model (MM5) by Penn State/NCAR was used to compare the effects of land use from two different years on meteorological condition. The predicted meteorological conditions were then compared with the respective monitoring station onsite. Results showed there is an improved of surface wind speed and temperature simulated using improved land use map. Findings suggest land use map should be taking into consideration in historical meteorological fields to access future air quality if the area of study expects large changes in land use pattern.

A numerical weather simulation of the depression 23W moving over the Gulf of Thailand during October 19-26, 2003 expressed in terms of meteorological variables including pressure, humidity, geopotential height, wind velocity, divergence, vertical velocity, vorticity and rain was performed by the fifth generation of PSN/NCAR mesoscale model, MM5 version 3.7. Favorable conditions for the storm development and storm center during its passage were indicated from the model simulation. The favorable weather conditions of the storm evolution were found to be high relative humidity of 90-100% and less than 1003 mb mean sea-level pressure. The central pressure of the storm decreased at the rate of at least 6 mb/24 hrs with the lowest value of 987 mb and the corresponding lowest geopotential height of 1326 m on October 22, 2003. Cyclonic flows were detected around the areas of negative horizontal divergence of -19.81 x 10-4 s-1 with gusts over 26 ms-1 and the positive vorticities of 128.4-234.1 x 10-4 s-1 along with moist air updrafts of 10-130 m/s. Continuous updrafts in an unstable atmosphere with adequate moisture supply enhanced the condensation process, and the cloud and rain formation, resulting in heavy rainfall in southern Thailand. Simulated rains are comparable with reported rains of 197-200 mm/24 hr at Prachuab Khiri Khan Province during October 24-25, 2003.

The sensitivity of the planetary boundary layer (PBL) parameterizations is investigated using the hybrid Fifth Generation Penn State University/National Center for Atmospheric Research (NCAR) Mesoscale Model (MM5) and its results were compared with observations from two field campaigns held during the dry and wet seasons at the Centro de Lançamento de Alcântara CLA). The comparisons were made using the integrated zonal and meridional components of observed and forecasted winds. Initially, three boundary layer parameterizations, in addition to the current parameterization, were selected for evaluation: Blackadar (BLK), Medium Range Forecast (MRF), Janjic (ETA) and Burk-Thompson (BT). The MRF and BLK schemes produced better results than the ETA and BT schemes. Nevertheless, MRF and BLK underestimate the zonal and meridional wind components by around 16% in the rainy season and overestimate them by on average 18% in the dry season.

The main objective of this study is to analyze the MM5 MesoscaleModel results comparing with observational datasets in surface and altitude from meteorological station of Galeão International Airport- RIO DE JANEIRO. These datasets are used to evaluate wind direction and intensity,temperature and relative humidity in surface and altitude. Simulations for two periods of July 2003 were carried through days 10-12 when a frontal system cross Rio de Janeiro, and days 13-15, characterized by presence of high-pressure system over continent. The 10m wind direction are well simulated, but resultshad demonstrated a trend of model to underestimate wind intensity. The best model results are in 1-3 m/s intensity band. The simulations got better results in reproducing wind and temperature vertical profiles than dewpoint temperature profiles and relative humidity for the analyzed period.

The city of Rio de Janeiro is often affected by meteorological systems that cause intense rainfalls. These events bring about economic and social disruptions of significant magnitude. This paper analyses the meteorological event occurred between the 05th and 06th of April 2010 in the city of Rio de Janeiro, using numerical modelling by MM5 model (PSU/NCAR Mesoscale Model). From 20h of the 5th until 8h of the 6th there was on average 178 mm of rainfall in the this city, almost twice the expected for April, bringing about floods, landslides, and many deaths. In this study, eight parameterization groups were used, with different configurations of cloud microphysics, cumulus and atmospheric boundary layer. Two simulation rounds were performed, starting at different times and the simulation results were compared with the observed precipitation data, obtained from pluviometric stations from the "Alerta-Rio" system. Thus, it was possible to analyse the effectiveness of the MM5 model for prognosticate extreme rainfall events as some of the model configurations have captured the position and/or intensity of the cores with intense rainfall with a three-hour time gap in some cases. Therefore, this prognostic model had proven that it can be a useful tool to forecast and reduce the consequences of extreme rainfall events in Rio de Janeiro city. [ABSTRACT FROM AUTHOR]

This study compares MM5 and WRF modeled upper air and surface wind speed and direction with observations from two standard meteorological stations locat;ed in areas characterized by either flat or complex terrain. Additionally, we evaluate the boundary layer height calculated by AERMET VIEW Upper Estimator. The upper air wind speed predictions of MM5 (but not of WRF) met all the acceptance criteria. In contrast, WRF surface wind predictions were mostly in better agreement with the observations than those of MM5, with a clear advantage for the 12 km grid resolution over the 3 km grid resolution. Modeled wind fields over complex terrain were less accurate than over flat terrain. Based on these results we conclude that in the absence of measured on-site meteorological data, WRF surface wind field predictions are expected to provide more reliable pollutant dispersion estimations and to propagate the estimation uncertainties to a lesser extent than MM5 surface wind field predictions, in particular for flat terrain scenarios. [ABSTRACT FROM AUTHOR]

Irrigation is the only method to sustain oasis agriculture in northwest China. In this study, the effects of soil moisture perturbations on the oasis self-maintenance mechanism were investigated using the mesoscale model MM5 with satellite observations of land-surface parameters from MODIS data. Twelve simulations were performed, among which CTL (default simulation) and MOD (with parameters replaced with MODIS data) were used to evaluate the model results. Another 10 simulations with soil moisture perturbations (DRY and WET) assessed the influence of soil moisture on the oasis self-maintenance mechanism. Independent of the initial soil moisture content, all simulations showed dramatic reductions of soil moisture in the initial several days of the simulation, due to the strong evapotranspiration in this arid environment. Both the DRY and WET perturbations led to substantial changes in surface heat flux partitioning and the oasis 'cold-wet' effect, which were also verified by an analysis of the secondary circulation and moisture-inversion level. Drying tends to have more influence than wetting, which indicates that irrigation should be performed more frequently than intensively to protect the oasis self-maintenance mechanism. [ABSTRACT FROM AUTHOR]