No description available.

In the Asian and other monsoon regions of the world most of the severe weather observed is local or mesoscale in nature. Forecasting convective storms or mesoscale systems in the monsoon regions, especially in the tropics, has always been a challenging task to operational meteorologists. Maldives Islands, being situated in the tropical Indian Ocean, are affected by monsoon depressions and tropical cyclones. Thunderstorms and the passage of squall lines are well known sources of heavy rainfall. However, due to the lack of professional people and necessary equipment the weather systems around these islands are seldom studied. Therefore the aim of this thesis is to investigate whether the small islands can create sufficient perturbations in the mesoscale environment to result in the development of convective systems. In this regard, two numerical models, Weather Research and Forecasting model (WRF version 2.2.1) and Regional Atmospheric Modelling System (RAMS version 6.0) were used in this study. Two experiments were performed using the WRF model. In the first experiment, a case study was investigated where the selected day experienced heavy rainfall and thunderstorms. In the second experiment, the same case study was used but with the topographical and surface properties removed in order to investigate the influence of the island in modifying the mesoscale environment. All the experiments were initialized using the re-analysis data from NECP. WRF was able to predict the large scale synoptic features with reasonable accuracy when compared to the observations. Development of the boundary layer and the downstream advection of the temperature anomaly generated by the island were well represented. However, the magnitude of the effects was shown to be weak, probably due to the influence of large scale synoptic features. Even though the model was able to predict the large scale features and some of the mesoscale features, it did not predict any storm development and underestimated the precipitation. Therefore, it was decided to idealize the storm development using the RAMS model. RAMS model was used in a two-dimensional framework. The model was initialized horizontally homogenous using a single sounding and six simulations were performed. The simulation results clearly depicted that the small island can generate its own circulation and influence the mesoscale environment. The daytime heating of the island and the downstream advection of the temperature anomaly in a moist unstable atmosphere could trigger a thunderstorm later in the day. The storm becomes mature approximately 40-80 km offshore. This also suggests that triggering of a storm on one side of an atoll could influence the islands on the downstream side. Sensitivity of storm development to the thermodynamics showed that even with an unstable atmosphere, enough moisture in the lower and mid-troposphere is needed to trigger the storm. Sensitivity to the change of SST showed that convective development was suppressed with a drop of 1 oC. However, this needs further investigation. Assessment of sensitivity to the size of the island showed that the time of triggering of the storm was later and the scale of influence was smaller with a smaller island.

Mineral dust aerosols, the tiny soil particles in the atmosphere, play a key role in the atmospheric radiation budget through their radiative and cloud condensation nuclei effects. It is therefore important to evaluate the radiative forcing of mineral dust and subsequent changes in atmospheric dynamics. The Weather Research and Forecasting with Chemistry (WRF/Chem) regional model with the integrated dust modules and available observations have been used to investigate the three-dimensional distribution of mineral dust over Australia. Additionally, the WRF/Chem model was used to estimate the direct radiative forcing by mineral dust over Australia. Particular emphasize has been given to direct radiative feedback effect of mineral dust on boundary layer dynamics. Two dust emission schemes embedded within the WRF/Chem model have been utilized in this study: the dust transport (DUSTRAN) and the Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) schemes. The refractive index of mineral dust depends on the mineralogy, size and composition of dust over a given region. The refractive index of mineral dust for shortwave radiation was considered to be wavelength independent and set based on previous mineralogical studies over North Africa and Australia. However, the refractive index of mineral dust for longwave radiation was considered to be wavelength dependent and to vary for 16 longwave spectral bands. Model results were compared with observations to validate the performance of the model, including satellite datasets from the Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging SpectroRadiometer (MISR) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), as well as ground-based measurements obtained from air quality monitoring sites over Australia. The major results can be summarized as follows: (1) Lake Eyre Basin is the most important source of dust in Australia, with a peak activity identified to be during austral spring and summer, and dust emission within the basin is often associated with the passage of dry cold fronts; (2) Mineral dust from Lake Eyre Basin can be transported long distances to southeastern Australia in association with eastward propagating frontal systems, reaching as far as New Zealand and beyond, and to northern tropical Australia by postfrontal southerly winds, and subsequently towards northwestern Australia and the Indian Ocean by southeasterly trade winds; (3) Australian dust plumes are mainly transported in the lower atmosphere, although variation of boundary layer depth during the passage of cold frontal systems, as well as ascending motion at the leading edge of these systems and descending motion where postfrontal anticyclonic circulation is dominant contribute to the vertical extent of mineral dust aerosols; (4) the shortwave direct radiative effect of mineral dust results in cooling of the atmosphere from the surface to near the boundary layer top, but warming of the boundary layer top and lower free atmosphere; (5) changes in the vertical profile of temperature result in an overall decrease of wind speed in the lower boundary layer and an increase within the upper boundary layer and lower free atmosphere; (6) the longwave warming effect of mineral dust partly offsets its shortwave cooling effect at the surface. This compensation is significantly larger over and immediately downwind of dust source regions where coarse particles are more abundant, as they have stronger interaction with longwave radiation emitted from the Earth’s surface; (7) both shortwave and longwave radiative forcing by mineral dust was found to have a diurnal variation in response to changes in solar zenith angle and in the intensity of longwave radiation, respectively; (8) the absorptive nature of dust was shown to be associated with the shortwave heating of the atmosphere; (9) on the other hand, longwave cooling of the atmosphere was identified because absorption of longwave radiation by dust is less than its emission to the surface and top of the atmosphere (TOA).

Satellite observations provide information on land surface processes over a large spatial extent with a frequency dependent on the satellite revisit time. These observations are not subject to the spatial limitations of the traditional point measurements and are usually collected in a global scale. With a reasonable spatial resolution and temporal frequency, the Moderate Resolution Imaging Spectroradiometer (MODIS) is one of these satellite sensors which enables the study of land-atmospheric interactions and estimation of climate variables for over a decade from remotely sensed data. This research investigated the potential of remotely sensed land surface temperature (LST) data from MODIS for air temperature (Ta) and soil moisture (SM) estimation in New Zealand and how the satellite derived parameters relate to the numerical model simulations and the in-situ ground measurements. Additionally, passive microwave SM product from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) was applied in this research. As the first step, the MODIS LST product was validated using ground measurements at two test-sites as reference. Quality of the MODIS LST product was compared with the numerical simulations from the Weather Research and Forecasting (WRF) model. Results from the first validation site, which was located in the alpine areas of the South Island, showed that the MODIS LST has less agreement with the in-situ measurements than the WRF model simulations. It turned out that the MODIS LST is subject to sources of error, such as the effects of topography and variability in atmospheric effects over alpine areas and needs a careful pre-processing for cloud effects and outliers. On the other hand, results from the second validation site, which was located on the flat lands of the Canterbury Plains, showed significantly higher agreement with the ground truth data. Therefore, ground measurements at this site were used as the main reference data for the accuracy assessment of Ta and SM estimates. Using the MODIS LST product, Ta was estimated over a period of 10 years at several sites across New Zealand. The main question in this part of the thesis was whether to use LST series from a single MODIS pixel or the series of a spatially averaged value from multiple pixels for Ta estimation. It was found that the LST series from a single pixel can be used to model Ta with an accuracy of about ±1 ºC. The modelled Ta in this way showed r ≈ 0.80 correlation with the in-situ measurements. The Ta estimation accuracy improved to about ±0.5 ºC and the correlation to r ≈ 0.85 when LST series from spatially averaged values over a window of 9x9 to 25x25 pixels were applied. It was discussed that these improvements are due to noise reduction in the spatially averaged LST series. By comparison of LST diurnal trends from MODIS with Ta diurnal trends from hourly measurements in a weather station, it was shown that the MODIS LST has a better agreement with Ta measurements at certain times of the day with changes over day and night. After estimation of Ta, the MODIS LST was applied to derive the near-surface SM using two Apparent Thermal Inertia (ATI) functions. The objective was to find out if more daily LST observations can provide a better SM derivation. It was also aimed to identify the potential of a land-atmospheric coupled model for filling the gaps in derived SM, which were due to cloud cover. The in-situ SM measurements and rainfall data from six stations were used for validation of SM derived from the two ATI functions and simulated by the WRF model. It was shown that the ATI function based on four LST observations has a better ability to derive SM temporal profiles and is better able to detect rainfall effects. Finally, the MODIS LST was applied for spatial and temporal adjustment of the near-surface SM product from AMSR-E passive microwave observations over the South Island of New Zealand. It was shown that the adjustment technique improves AMSR-E seasonal trends and leads to a better matching with rainfall events. Additionally, a clear seasonal variability was observed in the adjusted AMSR-E SM in the spatial domain. Findings of this thesis showed that the satellite observed LST has the potential for the estimation of the land surface variables, such as the near-surface Ta and SM. This potential is greatly important on remote and alpine areas where regular measurements from weather stations are not often available. According to the results from the first validation site, however, the MODIS LST needs a careful pre-processing on those areas. The concluding chapter included a discussion of the limitations of remotely sensed data due to cloud cover, dense vegetation and rugged topography. It was concluded that the satellite observed LST has the potential for SM and Ta estimations in New Zealand. It was also found that a land-atmospheric model (such as the WRF coupled with the Noah and surface model) can be applied for filling the gaps due to cloud cover in remotely sensed variables.

Air quality modeling is a recent development in atmospheric science dedicated to simulating the characteristics of surface emissions within the context of a variety of meteorological conditions. In western Kentucky, there are several concentrated animal feeding operations (CAFOs) that emit a variety of gases, including sulfur dioxide (SO2). The hypothesis was that the concentration and spread of SO2 emissions from these sources would differ between wet and dry periods over the CAFO locations. In this thesis, point emissions from locations representing CAFOs in western Kentucky and the transit of SO2throughout the southeastern U.S. were simulated in multiple sensitivity experiments using the Weather Research and Forecasting model with Chemistry (WRFChem). Simulations were performed for the convective precipitation events that occurred over western Kentucky between July 7 and July 13, 2012. The spatial coverage of SO2 emissions originating from the locations was reduced during precipitation events and expanded during dry periods. The average concentration of SO2 over the study area was also higher during the breaks between precipitation events than during times when precipitation was occurring. The highest concentrations of SO2 exceeding 1,000 pptv remained within close range of the emission locations for the majority of the simulations, except for when local surface winds were blowing at higher speeds. Most emissions from the locations remained limited to the surface and 850 mb levels.

Wind farm assessment is a costly and time consuming process when it is planned by traditional methods such as a met mast. Therefore, new models have been established and used for the wind farm assessment to ease the process of wind farm planning. These models are Global-regional models which add to cost efficiency and time saving. There are several types of these models in the market that have different accuracy. This thesis discusses and uses in simulations Global – regional model data outputs from European Centre for Medium-Range Weather Forecasts (ECMWF), Weather Research Forecast WRF and ECMWF, which is currently producing ERA-Interim, global reanalysis of the data-rich period since 1989 .The goal of the master's thesis is to see whether it is useful and efficient to use Global – regional weather model data such as the Era Interim Global Reanalysis Model data for wind assessment by comparing it with the real data series (met mast) located in Maglarp, in the south of Sweden.The comparison shows that in that specific area (hindcast) at Maglarp, in the south of Sweden, very promising results for planning a wind farm for a 100m, 120m and 38m heights.

Vertical mixing is an important process that relates surface fluxes to concentrations of pollutants and other chemical species in the atmosphere. Errors in vertical mixing have been identified as a major source of uncertainties in various atmospheric modeling efforts including tracer transport, weather forecasting, and regional climate simulation. This thesis aims to quantify uncertainties in model-derived mixed layer heights (zi) over North America through direct comparisons between radiosonde observations and four models at different months of the year 2004 through the bulk Richardson number method. Results of this study suggest that considerable errors in zi exist throughout the region with the spatial and temporal variations of the errors differ significantly among the selected models. Over all, errors in zi were larger in global models than in the limited area mesoscale models, and the magnitude of the random error was two times larger than the bias. Notably, spatial regions of with extremely large positive biases correspond to those with especially large random errors. The biases and random errors, however, were not correlated linearly nor can be easily used to predict each other. Uncertainties in model-derived zi were attributed, through errors in the bulk Richardson number, to temperature and horizontal winds. Errors in both horizontal winds and temperatures were found contributing more or less the same to uncertainties in zi, with relative errors in both variables being the greatest in the lowest part of the troposphere. Lastly, independent observations from the cooperative profiler network suggest that data assimilation did not add qualitative advantages for the comparisons presented in this study. The mixed layer height uncertainties demonstrated in this study may provide a guide for selecting a model to simulate regional scale atmospheric transport and for interpreting flux estimation and inversions studies.

To this date, estimates of the climate response to mineral dust remain largely uncertain because of our limited capability to quantify dust distribution in the atmosphere. Focusing on the Central and East Asian dust source regions, this thesis aims to develop a coupled regional dust modeling system to provide an improved modeling capability of atmospheric dust as well as to aid the integration of ground-based and satellite observations. The objectives of this study are as follows: 1) evaluate the capabilities of the available data to detect and quantify mineral dust in the atmosphere; 2) develop and test a coupled regional dust modeling system able to simulate size resolved dust concentrations accounting for the regional specifics of Central and East Asia; and 3) outline a methodology for data and modeling integration. The capabilities of ground-based and satellite data to characterize dust in the atmosphere are examined in great details. Based on analysis of MODIS data reflectance and radiances, we found evidence for regional signature of dust in near-IR and proposed a new probabilistic dust-cloud mask that explicitly takes into account the spatial variability characteristics of dust aerosols. We developed a coupled regional dust modeling system (WRF-DuMo) by incorporating a dust emission module (DuMo) into the NCAR WRF model. The WRF-DuMo unique capabilities include explicit treatment of land surface properties in Central and East Asia, a suite of dust emission schemes with different levels of complexity, multiple options for dust injection in the atmosphere and flexible parameters of the initial size distribution of emitted dust. Two representative dust events that originated in East Asia in the springs of 2001 and 2007 have been modeled with WRF-DuMo. Simulations with different initial size distribution of dust, injection and emission parameterizations have been performed to investigate their relative role on the modeled dust fields. We performed an integrated analysis of modeled dust fields and satellite observations by introducing an ensemble model dust index, which used in conjunction with satellite dust retrievals improves the capability to characterize dust fields. Finally, we provide recommendations for the development of an integrated observational and modeling dust framework.

Over the 1951-2009 time period, 47% of all tropical systems in the Atlantic Basin transitioned to post-tropical storms. These storms are capable of producing hurricaneforce winds, torrential, flooding rains and storm surge that floods coastal areas. This study adds to previous climatological work by completing a case-study of Hurricane Ike (2008) and examining how teleconnections such as the El Niño Southern Oscillation (ENSO), the Madden-Julian Oscillation (MJO), the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO) contribute to the strength of a transitioning post-tropical storm. T-tests performed show strong statistical relationships between an increase (decrease) in post-tropical storm frequency and warm PDO – La Niña (cold PDO – La Niña), cold PDO – ENSO neutral (warm PDO – ENSO neutral), and warm (cold) AMO conditions. Moreover, nearly significant results were found for the same increase (decrease) and La Niña seasons since (pre) 1980 and for cold (warm) PDO conditions. Modeling the MJO suggests that increased (decreased) relative humidity associated with the wet (dry) phase could increase (decrease) precipitation output from the storm and decrease (increase) forward speed of the storm, decreasing (increasing) wind speeds observed at the surface.

The tropical cyclone is a majestic, yet violent atmospheric weather system occurring over tropical waters. Their majesty evolves from the significant range of spatial scales they operate over: from the mesoscale, to the larger synoptic-scale. Their associated violent winds and seas, however, are often the cause of damage and destruction for settlements in their path. Between 10/11/07 and 16/11/07, tropical cyclone Sidr formed and intensified into a category 5 hurricane over the southeast tropical waters of the northern Indian Ocean. Sidr tracked west, then north, during the course of its life, and eventually made landfall on 15/11/07, as a category 4 cyclone near the settlement of Barguna, Bangladesh. The storm affected approximately 2.7 million people in Bangladesh, and of that number 4234 were killed. In this study, the dynamics of tropical cyclone Sidr are simulated using version 2.2.1 of Advanced Weather Research and Forecasting — a non-hydrostatic, two-way interactive, triply-nested-grid mesoscale model. Three experiments were developed examining model sensitivity to ocean-atmosphere interaction; initialisation time; and choice of convective parameterisation scheme. All experiments were verified against analysed synoptic data. The ocean-atmosphere experiment involved one simulation of a cold sea surface temperature, fixed at 10 °C; and simulated using a 15 km grid resolution. The initialisation experiment involved three simulations of different model start time: 108-, 72-, and 48-hours before landfall respectively. These were simulated using a 15 km grid resolution. The convective experiment consisted of four simulations, with three of these using a different implicit convective scheme. The three schemes used were, the Kain-Fritsch, Betts-Miller-Janjic, and Grell-Devenyi ensemble. The fourth case simulated convection explicitly. A nested domain of 5km grid spacing was used in the convective experiment, for high resolution modelling. In all experiments, the Eta-Ferrier microphysics scheme, and the Mellor-Yamada-Janjic planetary boundary layer scheme were used. As verified against available observations, the model showed considerable sensitivity in each of the experiments. The model was found to be well suited for combining ocean-atmosphere interactions: a cool sea surface caused cyclone Sidr to dissipate within 24 hours. The initialisation simulations indicated moderate model sensitivity to initialisation time: variations were found for both cyclone track and intensity. Of the three simulations, an initialisation time 108 hours prior to landfall, was found to most accurately represent cyclone Sidr’s track and intensity. Finally, the convective simulations showed that considerable differences were found in cyclone track, intensity, and structure, when using different convective schemes. The Kain-Fritsch scheme produced the most accurate cyclone track and structure, but the rainfall rate was spurious on the sub-grid-scale. The Betts-Miller-Janjic scheme resolved realistic rainfall on both domains, but cyclone intensity was poor. Of particular significance, was that explicit convection produced a similar result to the Grell-Devenyi ensemble for both model domain resolutions. Overall, the results suggest that the modelled cyclone is highly sensitive to changes in initial conditions. In particular, in the context of other studies, it appears that the combination of convective scheme, microphysics scheme, and boundary layer scheme, are most significant for accurate track and intensity prediction.