The tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR) data are used in this study to reveal diurnal variations of precipitation over the Tropics (30◦S − 30◦N) from January, 1998, to December 2002. The TMI data were used for the regions over oceans and islands and the PR data was used over continents. The observations are sorted regionally to examine the difference in diurnal cycle of rainfall over ocean, island, and continental regions. The rain rate is averaged over individual two hour intervals of local time in each region to include more observations in order to reduce the sampling error. F-test is used to determine those regions whose diurnal cycle is detected at the 95% confidence level. In most oceanic regions there is a maximum at 0400 LST - 0700 LST. The amplitude of diurnal variation over ocean regions with small total rain is a little higher than that of the ocean regions with heavy total rain. The diurnal cycle peaks at 0700 LST - 0800 LST over islands with rainfall variation similar to surrounding oceanic regions. A maximum at 1400 LST - 1500 LST was found in areas over continents with heavy total rain, while the maximum occured at 1900 LST - 2100 LST over continents with lesser total rain. The amplitudes of variation over continents with heavy total rain and with small total rain do not show significant differences. The diurnal cycle in in JJA (June, July, August) and DJF (December, January, February) varies with latitude over continents. A seasonal cycle of diurnal cycle can also be found in some oceanic regions. The diurnal cycle annual change is not evident over continents, while the diurnal cycle annual change over oceans exists in some regions. Island regions in this paper exhibit no evident seasonal and annual diurnal change.

The three-spot wrasse (Halichoeres trimaculatus) is distributed in and around the coral reefs and shallow rocky areas in the tropical and subtropical Indo-Pacific regions. This species displays a distinct diurnal behavior, burrowing under the sand at dusk and emerging out of the sand at dawn, which appears to be synchronized to the photoperiod. In this thesis, the hypothesis tested was that this unique life-style subjected the animal to daily hypoxia exposure while under the sand at night. The measurements of oxygen concentration in the sand around the fish at night confirmed a complete lack of oxygen. The study had three specific objectives: i) obtain a tissue-specific temporal profile of the hypoxia-related molecular and biochemical responses in wrasse over a 24 h diurnal cycle, ii) determine the responses that were unique to sand dwelling and iii) determine if the responses seen at night in the sand are similar to an anoxic response in this species. Wrasse were maintained in a flow-through seawater aquaria (29 ±1°C), with sand at the bottom for the fish to hide, and kept under natural photoperiod. The fish were sampled at 10:00, 14:00, 18:00, 21:00, 24:00, 3:00, and 6:00 clock time and plasma and tissue (brain, liver, gill, heart and muscle) were collected to determine the molecular and biochemical responses over a 24 h period. Fish were also sampled from aquaria without sand at night to determine the responses that were specific to hiding in the sand, while fish exposed to nitrogen gas bubbling for 6 and 12 h served as the anoxic group. A partial cDNA sequence of the hypoxia-inducible factor (HIF)-1α and neuroglobin (two genes that are hypoxia-responsive) were cloned and sequenced from the liver and brain, respectively, and their expression was determined using real-time quantitative PCR. HIF-1α mRNA abundance was higher in the brain compared to the liver and the gills, while a clear pattern of diurnal change in tissue HIF-1α and brain neuroglobin gene expressions was not observed at night relative to the fish during the day. However, wrasse brain showed a significant reduction in glycogen content at night under the sand and this corresponded with a higher hexokinase activity and increased glucose level suggesting enhanced glycolytic capacity. The plasma glucose and lactate levels were significantly lower at night, while in sand, relative to the day. The lower plasma glucose at night corresponded with a significant drop in liver gluconeogenic capacity (reduction in phosphoenolpyruvate carboxykinase, a key gluconeogenic enzyme, activity), while the lower lactate levels support a lack of activity along with the absence of glycogen breakdown in the muscle. Overall, there was a reduction in the metabolic capacity in the gills, heart, liver and muscle, but not the brain, supporting a tissue-specific metabolic reorganization as an adaptive strategy to cope with sand-dwelling in the wrasse. The molecular and biochemical responses seen in the wrasse at night in the sand was dissimilar to that seen in fish exposed to anoxia, leading to the conclusion that this species is not experiencing a complete lack of oxygen while under the sand. Also, the lack of muscle movement associated with sand dwelling at night limits anaerobic glycolysis for energy production, thereby eliminating lactate accumulation that was evident in fish exposed to anoxia. Taken together, wrasse showed a tissue-specific difference in metabolic capacity at night while hiding under the sand. While the mechanism involved in this tissue-specific energy repartitioning at night is unclear, one hypothesis involves selective increase in blood flow to the brain, while limiting peripheral circulation, as a means to maintain oxygen and glucose delivery to this critical tissue while the fish is hiding under the sand. The higher metabolic capacity of the brain, but not other tissues, at night under the sand suggests that maintaining the brain function is essential for the diurnal life-style in this animal.

The three-spot wrasse (Halichoeres trimaculatus) is distributed in and around the coral reefs and shallow rocky areas in the tropical and subtropical Indo-Pacific regions. This species displays a distinct diurnal behavior, burrowing under the sand at dusk and emerging out of the sand at dawn, which appears to be synchronized to the photoperiod. In this thesis, the hypothesis tested was that this unique life-style subjected the animal to daily hypoxia exposure while under the sand at night. The measurements of oxygen concentration in the sand around the fish at night confirmed a complete lack of oxygen. The study had three specific objectives: i) obtain a tissue-specific temporal profile of the hypoxia-related molecular and biochemical responses in wrasse over a 24 h diurnal cycle, ii) determine the responses that were unique to sand dwelling and iii) determine if the responses seen at night in the sand are similar to an anoxic response in this species. Wrasse were maintained in a flow-through seawater aquaria (29 ±1°C), with sand at the bottom for the fish to hide, and kept under natural photoperiod. The fish were sampled at 10:00, 14:00, 18:00, 21:00, 24:00, 3:00, and 6:00 clock time and plasma and tissue (brain, liver, gill, heart and muscle) were collected to determine the molecular and biochemical responses over a 24 h period. Fish were also sampled from aquaria without sand at night to determine the responses that were specific to hiding in the sand, while fish exposed to nitrogen gas bubbling for 6 and 12 h served as the anoxic group. A partial cDNA sequence of the hypoxia-inducible factor (HIF)-1α and neuroglobin (two genes that are hypoxia-responsive) were cloned and sequenced from the liver and brain, respectively, and their expression was determined using real-time quantitative PCR. HIF-1α mRNA abundance was higher in the brain compared to the liver and the gills, while a clear pattern of diurnal change in tissue HIF-1α and brain neuroglobin gene expressions was not observed at night relative to the fish during the day. However, wrasse brain showed a significant reduction in glycogen content at night under the sand and this corresponded with a higher hexokinase activity and increased glucose level suggesting enhanced glycolytic capacity. The plasma glucose and lactate levels were significantly lower at night, while in sand, relative to the day. The lower plasma glucose at night corresponded with a significant drop in liver gluconeogenic capacity (reduction in phosphoenolpyruvate carboxykinase, a key gluconeogenic enzyme, activity), while the lower lactate levels support a lack of activity along with the absence of glycogen breakdown in the muscle. Overall, there was a reduction in the metabolic capacity in the gills, heart, liver and muscle, but not the brain, supporting a tissue-specific metabolic reorganization as an adaptive strategy to cope with sand-dwelling in the wrasse. The molecular and biochemical responses seen in the wrasse at night in the sand was dissimilar to that seen in fish exposed to anoxia, leading to the conclusion that this species is not experiencing a complete lack of oxygen while under the sand. Also, the lack of muscle movement associated with sand dwelling at night limits anaerobic glycolysis for energy production, thereby eliminating lactate accumulation that was evident in fish exposed to anoxia. Taken together, wrasse showed a tissue-specific difference in metabolic capacity at night while hiding under the sand. While the mechanism involved in this tissue-specific energy repartitioning at night is unclear, one hypothesis involves selective increase in blood flow to the brain, while limiting peripheral circulation, as a means to maintain oxygen and glucose delivery to this critical tissue while the fish is hiding under the sand. The higher metabolic capacity of the brain, but not other tissues, at night under the sand suggests that maintaining the brain function is essential for the diurnal life-style in this animal.

This work is aimed at investigating diurnal cycle variability of the planetary boundary layer characteristics over the Arabian Peninsula and the Red Sea region. To fulfill this goal the downscaling simulations are performed using Weather Research and Forecasting (WRF) model. We analyze planetary boundary layer height, latent and sensible heat fluxes, and surface air temperature. The model results are compared with observations in different areas, for different seasons, and for different model resolutions. The model results are analyzed in order to better quantify the diurnal cycle variability over the Arabian Peninsula and the Red Sea. The specific features of this region are investigated and discussed.

The complex and coupled physical processes taking place in the atmosphere, ocean and land surface are described in Global Circulation Models (GCMs). These models have become the main tools to simulate climate variability and project future climate change. GCMs have the potential to give physically reliable estimates of climate change at global, continental or regional scales, but their projections are currently of too course horizontal resolution to capture the smaller scale features of climate and climate change. This situation stems from the fact that GCM simulations, which are effectively three-dimensional simulations of the coupled atmosphere-ocean-land system, are computationally extremely expensive. Therefore, downscaling techniques are utilised to do perform simulations over preselected areas that are of sufficiently detailed to represent the climate features at the meso-scale. Dynamic regional climate models (RCMs), based on the same laws of physics as GCMs but applied at high resolution over areas of interest, have become the main tools to project regional climate change. The research presented here utilises the Conformal-Cubic Atmospheric Model (CCAM), a variable-resolution global atmospheric model that can be applied in stretched-grid mode to function as a regional climate model. As is the case with RCMs, CCAM has the potential to improve climate simulations along rough topography and coastal areas when applied at high spatial resolution, whilst side-stepping the lateral boundary condition problems experienced by typical limited-area RCMs. CCAM has been developed by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Australia. The objective in the study is to test capability of a regional climate model, CCAM, to realistically simulate cumulus convection at different spatial scales over regions with steep topography, such as the eastern escarpment of South Africa. Since both GCMs and RCMs are known to have large biases and shortcomings in simulating rainfall over the steep eastern escarpment of southern Africa and in particular Lesotho, the paper “Model simulations of rainfall over southern Africa and its eastern escarpment” (Chapter 3) has a focus on verifying model performance over this region. In the paper the CCAM simulations include six 200 km resolution Atmospheric Model Intercomparison Project (AMIP) simulations that are forced with sea surface temperatures and one 50 km resolution National Centre for Environmental Prediction (NCEP) reanalysis simulation that is forced with sea surface temperatures and synoptic scale atmospheric forcings. These simulations are verified against rain gauge data sets and satellite rainfall estimates. The results reveal that at these resolutions the model is capable of simulating the key synoptic-scale features of southern African rainfall patterns. However, rainfall totals are often drastically overestimated. A key aspect of model performance is the representation of the diurnal cycle in convection. For the case of South Africa, the realistic representation of the complex patterns of rainfall over regions of steep topography is also of particular importance. At a larger spatial scale, the model also needs to be capable of representing the west-east rainfall gradient found over South Africa. The ability of CCAM to simulate the diurnal cycle in rainfall as well as the complex spatial patterns of rainfall over eastern South Africa is analysed in “High Resolution Rainfall Modelling over the Eastern Escarpment of South Africa” (Chapter 4). The simulations described in the paper have been performed at 8km resolutions in the horizontal and span a thirty-year long period. These are the highest resolution climate simulations obtained to date for the southern African region, and were obtained through the downscaling reanalysis data of the European Centre for Medium-range Weather Forecasting (ECMWF). The simulations provide a test of the robustness of the CCAM convective rainfall parameterisations when applied at high spatial resolution, in particular in representing the complex rainfall patterns of the eastern escarpment of South Africa. / M (Geography and Environmental Management), North-West University, Potchefstroom Campus, 2015

The complex and coupled physical processes taking place in the atmosphere, ocean and land surface are described in Global Circulation Models (GCMs). These models have become the main tools to simulate climate variability and project future climate change. GCMs have the potential to give physically reliable estimates of climate change at global, continental or regional scales, but their projections are currently of too course horizontal resolution to capture the smaller scale features of climate and climate change. This situation stems from the fact that GCM simulations, which are effectively three-dimensional simulations of the coupled atmosphere-ocean-land system, are computationally extremely expensive. Therefore, downscaling techniques are utilised to do perform simulations over preselected areas that are of sufficiently detailed to represent the climate features at the meso-scale. Dynamic regional climate models (RCMs), based on the same laws of physics as GCMs but applied at high resolution over areas of interest, have become the main tools to project regional climate change. The research presented here utilises the Conformal-Cubic Atmospheric Model (CCAM), a variable-resolution global atmospheric model that can be applied in stretched-grid mode to function as a regional climate model. As is the case with RCMs, CCAM has the potential to improve climate simulations along rough topography and coastal areas when applied at high spatial resolution, whilst side-stepping the lateral boundary condition problems experienced by typical limited-area RCMs. CCAM has been developed by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Australia. The objective in the study is to test capability of a regional climate model, CCAM, to realistically simulate cumulus convection at different spatial scales over regions with steep topography, such as the eastern escarpment of South Africa. Since both GCMs and RCMs are known to have large biases and shortcomings in simulating rainfall over the steep eastern escarpment of southern Africa and in particular Lesotho, the paper “Model simulations of rainfall over southern Africa and its eastern escarpment” (Chapter 3) has a focus on verifying model performance over this region. In the paper the CCAM simulations include six 200 km resolution Atmospheric Model Intercomparison Project (AMIP) simulations that are forced with sea surface temperatures and one 50 km resolution National Centre for Environmental Prediction (NCEP) reanalysis simulation that is forced with sea surface temperatures and synoptic scale atmospheric forcings. These simulations are verified against rain gauge data sets and satellite rainfall estimates. The results reveal that at these resolutions the model is capable of simulating the key synoptic-scale features of southern African rainfall patterns. However, rainfall totals are often drastically overestimated. A key aspect of model performance is the representation of the diurnal cycle in convection. For the case of South Africa, the realistic representation of the complex patterns of rainfall over regions of steep topography is also of particular importance. At a larger spatial scale, the model also needs to be capable of representing the west-east rainfall gradient found over South Africa. The ability of CCAM to simulate the diurnal cycle in rainfall as well as the complex spatial patterns of rainfall over eastern South Africa is analysed in “High Resolution Rainfall Modelling over the Eastern Escarpment of South Africa” (Chapter 4). The simulations described in the paper have been performed at 8km resolutions in the horizontal and span a thirty-year long period. These are the highest resolution climate simulations obtained to date for the southern African region, and were obtained through the downscaling reanalysis data of the European Centre for Medium-range Weather Forecasting (ECMWF). The simulations provide a test of the robustness of the CCAM convective rainfall parameterisations when applied at high spatial resolution, in particular in representing the complex rainfall patterns of the eastern escarpment of South Africa. / M (Geography and Environmental Management), North-West University, Potchefstroom Campus, 2015

Sperm whales (Physeter macrocephalus) are nomadic species typically studied across broad (>100km) spatial scales. In this study, I model fine-scale (or submesocale) habitat preferences, determine how organization into distinctive units of associating female and juveniles influences habitat use, and describe how movements change across the 24-hour cycle. This study concerns a well-studied population of sperm whales off Dominica in the Eastern Caribbean. Statistical models suggest that overall habitat use is rather homogenous, and social behaviour is best predicted by the presence of mature males. Variation among social units in the amount of time spent, and space occupied, within the study area indicates habitat preferences at the level of the social unit. Finally, movements are influenced by the diurnal cycle, as whales tend to move from inshore to offshore at dusk. This study betters our understanding of sperm whale habitat decisions over fine-scales, and has implication for conservation and management strategies.

In the current study, we have presented a systematic analysis of the diurnal cycle of rainfall over the Indian region using satellite observations, and evaluated the ability of the Weather Research and Forecasting Model (WRF) to simulate some of the salient features of the observed diurnal characteristics of rainfall. Using high resolution simulations, we also investigate the underlying mechanisms of some of the observed diurnal signatures of rainfall. Using the Tropical Rain-fall Measuring Mission (TRMM) 3-hourly, 0.25 ×0.25 degree 3B42 rainfall product for nine years (1999-2007), we extract the finer spatial structure of the diurnal scale signature of Indian summer monsoon rainfall. Using harmonic analysis, we construct a signal corresponding to diurnal and sub-diurnal variability. Subsequently, the 3-hourly time-period or the octet of rain-fall peak for this filtered signal, referred to as the “peak octet,” is estimated with care taken to eliminate spurious peaks arising out of Gibbs oscillations. Our analysis suggests that over the Bay of Bengal, there are three distinct modes of the peak octet of diurnal rainfall corresponding to 1130, 1430 and 1730 IST, from north central to south Bay. This finding could be seen to be consistent with southward propagation of the diurnal rainfall pattern reported by earlier studies. Over the Arabian sea, there is a spatially coherent pattern in the mode of the peak octet (1430 IST), in a region where it rains for more than 30% of the time. In the equatorial Indian Ocean, while most of the western part shows a late night/early morning peak, the eastern part does not show a spatially coherent pattern in the mode of the peak octet, owing to the occurrence of a dual maxima (early morning and early/late afternoon). The Himalayan foothills were found to have a mode of peak octet corresponding to 0230 IST, whereas over the Burmese mountains and the Western Ghats (west coast of India) the rainfall peaks during late afternoon/early evening (1430-1730 IST). This implies that the phase of the diurnal cycle over inland orography (e.g., Himalayas) is significantly different from coastal orography (e.g., Western Ghats). We also find that over the Gangetic plains, the peak octet is around 1430 IST, a few hours earlier compared to the typical early evening maxima over land. The second part of our study involves evaluating the ability of the Weather Research and Fore-casting Model (WRF) to simulate the observed diurnal rainfall characteristics. It also includes conducting high resolution simulations to explore the underlying physical mechanisms of the observed diurnal signatures of rainfall. The model (at 54km resolution) is integrated for the month of July 2006 since this period was particularly favourable for the study of diurnal cycle. We first evaluate the sensitivity of the model to the prescribed sea surface temperature (SST) by using two different SST datasets, namely Final Analyses (FNL) and Real-time Global (RTG). The overall performance of RTG SST was found to be better than FNL, and hence it was used for further model simulations. Next, we investigated the impact of different parameterisations (convective, microphysical, boundary layer, radiation and land surface) on the simulation of diurnal cycle of rainfall. Following this sensitivity study, we identified the suite of physical parameterisations in the model that “best” reproduces the observed diurnal characteristics of Indian monsoon rainfall. The “best” model configuration was used to conduct two nested simulations with one-way, three-level nesting (54-18-6km) over central India and Bay of Bengal. While the 54km and 18km simulations were conducted for July 2006, the 6km simulation was carried out for the period 18-24 July 2006. This period was chosen for our study since it is composed of an active period (19-21 July 2006), followed by a break period (22-24 July 2006). At 6km grid-spacing the model is able to realistically simulate the active and break phases in rainfall. During the chosen active phase, we find that the observed rainfall over central India tends to reach a maximum in the late night/early morning hours. This is in contrast to the observed climatological diurnal maxima of late evening hours. Interestingly, the 6km simulation for the active phase is able to reproduce this late night/early morning maxima. Upon further analysis, we find that this is because of the strong moisture convergence at the mid-troposphere during 2030-2330 IST, leading to the rainfall peak seen during 2330-0230 IST. Based on our analysis, we conclude that during both active and break phases of summer monsoon, mid-level moisture convergence seems to be one of the primary factors governing the phase of the diurnal cycle of rainfall. Over the Bay of Bengal, the 6km model simulation is in very good agreement with observations, particularly during the active phase. The southward propagation observed during 19-20 July 2006, which was not captured by the coarse resolution simulation (54km), is exceedingly well captured by the 6km simulation. The positive anomalies in specific humidity attain a maxima during 2030-0230 IST in the north and during 0830-1430 IST in the south. This confirms the role of moisture convergence in the southward propagation of rainfall. Equally importantly we find that while low level moisture convergence is dominant in the north Bay, it is the mid-level moisture convergence that is predominant in the south Bay.

The fine-scale structure of global (30N-30S) tropical rainfall is characterised using 13 years (1998-2010) of 3-hourly and daily, 0.25-degree Tropical Rainfall Measuring Mission (TRMM) 3B42 rainfall product. At the outset, the dominant timescales present in rainfall are identified. Specifically, the Fourier spectrum (in time) is estimated in two ways (a) spectrum of spatially averaged (SoSA) rainfall; and (b) spatial average of the spectrum (SAoS) of rainfall at each grid point. This procedure is applied on rainfall at the 3-hourly and daily temporal resolutions. Both estimates of the spectrum show the presence of a very strong seasonal cycle. But, at subseasonal timescales, the two methods of estimating spectrum show a marked difference in daily rainfall. Specifically, with SoSA the variability peaks at a subseasonal timescale of around 5 days, with a possible secondary peak around 30-40 days (mostly in the southern tropics). With SAoS, the variability is distributed across a range of timescales, from 2 days to 90 days. However, with finer resolution (3-hourly) observations, it is seen that (besides the seasonal cycle) both methods agree and yield a dominant diurnal scale. Along with other subseasonal scales, the contribution and geographical distribution of diurnal scale variability is estimated and shown to be highly significant. Given its large contribution to the variability of tropical rainfall, the diurnal cycle is extracted by means of a Fourier-based filtering and analysed. The diurnal rainfall anomaly is constructed by eliminating all timescales larger than 1 day. Following this, taking care to avoid spurious peaks associated with Gibbs oscillations, the time of day (called the peak octet) when the diurnal anomaly is largest is identified. The peak octet is estimated for each location in the global tropics. This is repeated for 13 years, and the resulting mode of the time of maximum rainfall is established. It is seen that (i) most land regions receive rainfall during the late afternoon/early evening hours; (ii) rainfall over open oceans lack a dominant diurnal signature with a possible combination of early morning and afternoon showers; (iii) coastal regions show a clear south/southwest propagation in the mode of the peak octet of rainfall. In addition to being a comprehensive documentation of the diurnal cycle at very fine scales, the results serve as a critical test for the validation of theoretical and numerical models of global tropical rainfall.

In this thesis, we have presented a systematic analysis of the change of cloud properties due to variation in aerosol concentration over Indian region using satellite observations, and Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) simulations. The Tropical Rainfall Measurement Mission (TRMM) based Microwave Imager (TMI) estimates (2A12) have been used to compare and contrast the characteristics of cloud liquid water and ice over the Indian land region and the surrounding oceans, during the pre-monsoon (May) and monsoon (June–September) seasons. Based on the spatial homogeneity of rainfall, we have selected five regions for our study (three over ocean, two over land). In general, we find that the mean cloud liquid water and cloud ice content of land and oceanic regions are different, with the ocean regions showing higher amount of CLW. A comparison across the ocean regions suggests that the cloud liquid water over the or graphically influenced Arabian Sea (close to the Indian west coast) behaves differently from the cloud liquid water over a trapped ocean (Bay of Bengal) or an open ocean (Equatorial Indian Ocean). Specifically, the Arabian Sea region shows higher liquid water for a lower range of rainfall, whereas the Bay of Bengal and the Equatorial Indian Ocean show higher liquid water for a higher range of rainfall. Apart from geographic differences, we also documented seasonal differences by comparing cloud liquid water profiles between monsoon and pre-monsoon periods, as well as between early and peak phases of the monsoon. We find that the cloud liquid water during the lean periods of rainfall (May or June) is higher than during the peak and late monsoon season (July-September) for raining clouds over central India. However, this is not true over the ocean. As active and break phases are important signatures of the monsoon progression, we also analyzed the differences in cloud liquid water during various phases of the monsoon, namely, active, break, active-to-break (a2b) and break-to-active (b2a) transition phases. We find that the cloud liquid water content during the b2a transition phase is significantly higher than that during the a2b transition phase over central India. We speculate that this could be attributed to higher amount of aerosol loading over this region during the break phase. We lend credence to this aerosol-liquid water/rain association by comparing the central Indian cloud liquid water with Southeast Asia (where the aerosol loading is significantly smaller) and find that in the latter region, there are no significant differences in cloud liquid water during the different phases of their monsoon. The second part of our study involves evaluating the ability of the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) to simulate the observed variation of cloud liquid water and rain efficiency. We have used no chemistry option, and the model was run with constant aerosol concentration. The model simulations (at 4.5 km resolution) are done for the month of June–July 2004 since this period was particularly favorable for the study of an active–break cycle of the monsoon. We first evaluate the sensitivity of the model to different parameterizations (microphysical, boundary layer, land surface) on the simulation of rain over central India and Bay of Bengal. This is done to identify an “optimal” combination of parameterizations which reproduces the best correlation with observed rain over these regions. In this default configuration (control run), where the aerosol concentration is kept constant throughout the simulation period, the model is not able to reproduce the observed variations of cloud liquid water during the different phases of an active-break cycle. To this end, we proceeded to modify the model by developing an aerosol-rain relation, using Aerosol Robotic Network (AERONET) and TRMM 3B42 data that realistically captures the variation of aerosol with rain. It is worth highlighting here that our goal was to primarily isolate the indirect effect of aerosols in determining the observed changes in cloud liquid water (CLW) during the active-break phases of the Indian monsoon, without getting into the complexity of a full chemistry model such as that incorporated in WRF-Chem. Moreover, the proposed modification (modified run) is necessitated by the lack of realistic emission estimates over the Indian region as well as the presence of inherent biases in monsoon simulation in WRF. The main differences we find between the modified and control simulations is in the mean as well as spatial variability of CLW. We find that the proposed modification (i.e., rate of change of aerosol concentration as a function of rain rate) leads to a realistic variation in the CLW during the active-break cycle of Indian monsoon. Specifically, the peak value of CLW in the b2a (a2b) phase is larger (smaller) in the modified as compared to the control run. These results indicate a stronger change in CLW amount in the upper levels between the two transition phases in the modified scheme as compared to the control simulation. More significantly, we also observe a change in sign at the lower levels of the atmosphere, i.e., from a strong positive difference in the control run to a negative difference in the modified simulation, similar to that observed. Additionally, we investigated the impact of the proposed modification, via CLW changes, on cloud coverage, size of clouds and their spatial variability. We find that the transformation of optically thin clouds to thick clouds during the break phase was associated with larger cloud size in modified compared to the control simulation. Moreover, the higher rate of decay of the spatial variability of CLW with grid resolution, using the modified scheme, suggests that clusters of larger clouds are more in the modified compared to control simulation. Taken together, the interactive aerosol loading proposed in this thesis yields model simulations that better mimic the observed CLW variability between the transition phases.