Climatic trends in most parts of the world show a significant increase in rainfall amount, intensity and its frequency. Similarly, these trends are likely to continue in future as well. The major catastrophe caused by these rainfall trends comes as flooding, which is getting harder to predict, and mainly over the mountainous regions. Modelling these extreme rainfall events is crucial, which needs better forecasting skills and more understanding of existing Numerical Weather Prediction (NWP) modelling setup. Although, recent developments in NWP models increase the capabilities to simulate rainfall more precisely but the strengths and weaknesses of model need to be evaluated based on climatic conditions, terrain characteristics -- which include landuse, topography, new physical schemes and static datasets. Therefore, we have conducted comprehensive sensitivity and qualitative analysis with a numerous model setup, physical schemes and terrain datasets. / We contemplate various physical parameterizations and updated terrain datasets to simulate the rainfall over the complex topography using WRFV3-ARW modelling system. Additionally, the impact of topography and landuse on rainfall are discussed in detail along with a several combinations of newly available land surface, planetary boundary layer (PBL), cumulus, and cloud microphysics (MP) schemes. As a case study, we select the north region of Pakistan, which includes Khyber-Pakhtunkhwa (KPK) province and part of Hindukush-Karakoram-Himalaya (HKH), and this region have diversified the landscape and complex topographic features. For the sake of better understanding and comparative discussions, we study three extreme rainfall events; two of them occurred during monsoon period (i.e., July), while one in post monsoon period (i.e., September). / WRF-ARW 3.5.1 model is tuned and tested with GFS0.5 and CFSR/CFSv2 as forcing and lateral boundary conditions with a number of parameterization schemes. Similarly, to minimize the errors induced by terrain features, we apply wind correction and drag parameterizations. Furthermore, 3-arc-second hydrologically corrected SRTM digital elevation model (DEM), modified MODIS IGBP 30-arc-second, MODIS 15-arc-second and GLCNMO2008 landuse datasets were also integrated to WRF along with default datasets in WRF modelling system. / We verify the simulated rainfall by using observed, the Tropical Rainfall Measuring Mission (TRMM) and the Climate Prediction Centre morphing method (CMORPH) rainfall datasets. The GIS-based verification technique, called fisher-net is also introduced which is more compatible and flexible with other tools as well. / 隨著全球氣候變化的加劇，強暴雨極端天氣事件呈現突發、多發、併發的特點，其頻次、強度、持續時間、籠罩範圍近年來均呈現急速上升的趨勢。如何構建高時效性、高精度和高可用的極端天氣事件模擬工具，已經成為災害應急管理與回應等領域迫切需要解決的關鍵科學問題。作為極端天氣事件類比的核心，數值氣象模型對極端暴雨事件的模擬能力日益完善；然而，到目前為止，氣象模型的可靠性和有效性評價仍是其推廣應用的關鍵，特別是如何顧及土地利用類型、地形、新型物理機制和多源靜態資料庫前提下的模型可靠性評價仍面臨很多挑戰。因此，本文提出了顧及不同物理機制、地形特徵的模型構建、模型敏感性評價和定量分析方法。 / 首先，本文在顧及不同的物理參數和地形特徵的基礎上，利用WRFV3-ARW 建模系統實現了對複雜地形特徵下降雨過程的類比與分析。在此基礎上，本文充分考慮和利用新的土地下墊面、行星邊界層、積雲以及雲微物理機制，以詳細分析了地形和土地利用類型對降雨影響。實驗選用具有複雜地形結構和特徵的巴基斯坦北部的Khyber-Pakhtunkhwa (KPK)省和部分Hindukush-Karakoram-Himalaya (HKH) 區域；為了獲取更充分的分析結果，本位對該實驗區域內三次極端降雨事件進行了模擬和分析，包括季風期（例如七月）的兩次降雨事件和季風期過後（例如九月）的一次降雨事件。 / 其次，本文利用GFS0.5 和 CFSR/CFSv2 作為強迫和側邊界條件，設置多參數方案對WRF-ARW 3.5.1 模型進行了優化和測試。與此同時，為了降低由地形特徵導致的類比誤差，本文引入了風向糾正參數和風阻參數。除此之外，本文充分利用了水文糾正過後的3 弧秒精度的SRTM DEM 資料、30 弧秒精度的MODIS IGBP 資料、15 弧秒精度的MODIS 資料、GLCNMO2008 格式的土地利用資料、以及WRF 建模系統的預設資料，支撐WRF 的建模過程。 / 最後，為了驗證本文實驗結果的可靠性，本文利用TRMM 獲取的實測降雨量資料以及TRMM 提供的降雨資料庫驗證，基於GIS 的漁網驗證法，對上述模擬結果進行了詳細的分析 / Sultan, Shahzad. / Thesis Ph.D. Chinese University of Hong Kong 2015. / Includes bibliographical references (leaves 111-125). / Abstracts also in Chinese. / Title from PDF title page (viewed on 09, September, 2016). / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.

An investigation of the effects of commercial mechanised selective logging on rain forest vegetation and mammals, was undertaken in the Lope Reserve, central Gabon, between January 1989 to July 1991. Vegetation in Lope is mostly semi-evergreen lowland tropical rain forest, but there are some localised patches of savanna., which are thought to be natural in origin, but which are maintained today by regular fires started by humans. Study sites were established in areas of forest logged 20-25, 10-15, and 3-5 years previously, a fourth was logged during the study, and a fifth remained unexploited. None of the study sites had been subject to hunting in the recent past. A line-transect five kilometres in length was cut across the drainage in each site. Forest composition and structure was assessed along each transect, by identifying and measuring trees and lianes in botanical plots, counting stem density of herbaceous vegetation in the families Marantaceae and Zingiberaceae, and by measuring canopy cover at three heights. At total of 4885 trees and lianes of 327 species occurred in five 2.5 ha samples of plants greater than 10 cm dbh, whilst 1832 individuals of 137 species were found in five 25ha samples of trees greater than 70cm dbh. There were marked differences in structure and species composition both between and within sites. A model was developed to attempt to explain this variation, based upon the theory that much of Lope had been covered by savanna vegetation during a previous cool, dry climatic phase, and that forest structure and composition reflected recolonisation of the savanna by forest. Physical features such as swamps, rocky outcrops and altitude were also considered. Two types of multivariate analysis were applied to botanical data and supported the model. The effects of logging on forest vegetation were assessed by returning after logging to botanical plots established before exploitation. Damage levels were low, compared to other parts of the World, resulting in about a 10% reduction in canopy cover. Patterns of fruit production were studied by counting fallen ripe and unripe fruit on transects. Fruits encountered were classified on the basis of their morphology and dispersal mechanism. There was a period of low fruit production during the major dry season, when frugivores are likely to suffer dietary stress. A number of plant species which did produce fruit at this time were identified as species which might represent 'keystone' resources. Over 70% of fruit species were animal-dispersed, demonstrating the the important role animals play in the ecology of tropical rain forests. Forest elephant (Loxodonta africana cyclotis) diet, ecological role and group structure were analysed. The bulk of the diet consisted of the bark and leaves of trees, and some monocotyledons in the families Marantaceae and Zingiberaceae, but fruit was also important. Large-scale seasonal movements in response to fruit availability were detected. Elephants were important seed dispersers f o r many plant species, and were responsible for less than 1% of natural tree mortality. The social structure of these forest elephants differed from that of populations that have been studied i n east and southern Africa. Average group size was 2.8, and no groups of more than 10 individuals were encountered. Densi ties of primates, ungulates and squirrels were assessed using standard line-transect censuses. Resolution was poor, but statistical differences were detected between sites for some species. Chimpanzee, (Pan t. troglodytes) densities declined in logged forest, but no other species could be shown to decline after logging. Some other differences between sites were related to vegetation composition. Biomass was high, estimated a t up to 4692.6 kg km-2, but was dominated by elephants, which made up 25-82%. Conservation implications of this study are discussed, and recommendations made.

The West African Monsoon (WAM) is a significant component of the global monsoon system and plays a key role in the annual cycle of precipitation in the Sahel region of Africa (10°N to 20°N) during the summer months (July to September). Rainfall in the Sahel varies on timescales ranging from seasons to millennia as a result of changes in the WAM. In the last century, the Sahel experienced a relatively wet period (prior to the 1960s) followed by a period of severe drought (1970s-1980s) with higher-frequency variability superimposed on this low-frequency background signal. Understanding precipitation variability like that which occurred over the 20th Century and its impact on Sahel precipitation is critically important for skillful hydroclimate predictions and disaster preparedness in the region. Previous work has shown that the WAM responds to both internal atmospheric variability and external oceanic forcing. A large fraction of 20th Century Sahel rainfall variability has been linked to nearby and remote oceanic forcing from the Atlantic, Pacific, and Indian Oceans, suggesting that the ocean is the primary driver of variability. However, the mechanisms underlying the influence of sea surface temperature (SST) forcing to land based precipitation and the relative importance of the roles of different basins are not as well understood. To this end, the work completed in this thesis examines the physical mechanisms linking oceanic forcing to recent precipitation variability in the Sahel and identifies them alongside large-scale environmental conditions. A series of moisture budget decomposition studies are performed for the Sahel in order to understand the processes that govern regional hydroclimate variability on decadal and interannual time scales. The results show that the oceanic forcing of atmospheric mass convergence and divergence explains the moisture balance patterns in the region to first order on the timescales considered. On decadal timescales, forcing by the Indian and Atlantic Oceans correlate strongly with precipitation variability. The combination of a warm Indian Ocean and negative gradient across the Atlantic forces anomalous circulation patterns that result in net moisture divergence by the mean and transient flow. Together with negative moisture advection, these processes result in a strong drying of the Sahel during the later part of the 20th Century. Diagnosis of moisture budget and circulation components within the main rainbelt and along the monsoon margins show that changes to the mass convergence are related to the magnitude of precipitation that falls in the region, while the advection of dry air is associated with the maximum latitudinal extent of precipitation. On interannual timescales, results show that warm conditions in the Eastern Tropical Pacific remotely force anomalously dry conditions primarily through affecting the low-troposphere mass divergence field. This behavior is related to increased subsidence over the tropical Atlantic and into the Sahel and an anomalous westward flow of moisture from the continent, both resulting in a coherent drying pattern. The interannual signal is then further explored, particularly in light of the expected link between the El Niño Southern Oscillation and dry conditions in the Sahel, notably unseen during the historic El Niño event of 2015. Motivated by this, recent El Niño years and their precipitation signature in the Sahel along with the associated large-scale environmental conditions are examined. Two different outcomes for Sahel summer season are defined; an anomalously wet or an anomalously dry season coincident with El Niño conditions. The different precipitation patterns are distinguished by increased moisture supply for the wet years, which can be driven by both regional oceanic conditions that favor increased moisture convergence over the continent as well as weaker El Niño forcing. Finally, a series of new idealized SST-forced experiments that explore the causal link between oceanic forcing and the response of convection in the region on daily time resolution are discussed and preliminary results shown. These experiments aim to understand how convection in the Sahel responds to SST forcing using transient model simulations that track the evolving response of the WAM through time, day-by-day, under different oceanic conditions. Preliminary results show the stark differences in seasonal precipitation that occur when anomalies of opposite sign are applied in parts of the Atlantic and Pacific basin. There is also a suggestion of a difference in the timing of the rainy season when the model is run with different SST configurations.

The tropical rainforest has interested ecologists for hundreds of years because of its vast species diversity. The distribution and establishment of trees is related to soil properties and rootassociated microorganisms. The coexistence of hyper-diverse plant communities in tropical rainforests has resulted in associations being formed with belowground communities, mycorrhizas (particularly arbuscular mycorrhizal (AM), ectomycorrhizas (ECM)) and root associated bacterial communities. The rapid deforestation in Southeast Asia is causing the loss of the dominant and important tree species belonging to the family Dipterocarpaceae. It is important to understand whether different host species in the same environment maintain mycorrhizal and bacterial diversity, especially mycorrhizas with a restricted host range. In this study, I examine the ecology of mycorrhizas and bacteria associated with Dipterocarpaceae and also the plant community as a whole. The aim of this project is to understand the effect of host properties (e.g. species, size), soil factors (e.g. nutrient concentrations) and spatial factors on mycorrhizal fungi and bacterial diversity and community structure. The research took place in two Centre for Tropical Forest Science (CTFS) plots in Malaysia: Pasoh Forest Reserve (in Negeri Sembilan) and Danum Valley Conservation Area (in Sabah). Molecular protocols and a modern technique, Next Generation Sequencing (NGS), were adopted to quantify mycorrhizal and bacterial loads in tropical plants. ITS1 and ITS2 regions were used for ECM, 18S rRNA were used for AM, and 16S rRNA were used for bacteria. Mycorrhizas and bacteria present in the roots of Dipterocarpaceae from 60 individual plants belonged to 25 species within 6 genera were traced and sampled in 2015. To my knowledge, this study is the first attempt to study root-associated bacteria across multiple species within a single family, Dipterocarpaceae. Dipterocarpaceae's species was found to significantly influence root bacteria. Analyses showed that mycorrhizal communities are similar on the host, unlike the null model. Dipterocarpaceae was previously believed to solely host ECM, but this study disproves this. This study shows that Dipterocarpaceae can have dual colonization, as it iv can also associate with AM fungi. One soil core of 10 cm × 10 cm × 7.5 cm were collect randomly in three subplot and further divided at 2.5 cm each slice into 75 individual 'microcubes' of 2 cm × 2 cm × 2.5 cm depths enumerates a total of 192 fine root samples. Multivariate analysis revealed that AM fungi tend to associate with non-dipterocarp (as well as unidentified families) while ECM fungi tend to associate with dipterocarps. Data was also collected on host attributes, plant size, and root density. Dipterocarpaceae size does not influence the distribution of mycorrhizal or bacterial communities. The root density reduces as depth increases. Therefore, root density does have a significant influence on mycorrhizal community structure. The diversity of ECM and AM fungal communities within cubes decreased significantly with depth (p < 0.001), whereas the mycorrhizal communities did not change across horizontal distances within cubes. To investigate whether there is a relationship between belowground communities and soil properties, soil macro and micro nutrients were examined and a multivariate analysis was performed. The results showed that communities of belowground (mycorrhizal and bacterial) species correlate with soil parameters. Spatial scale also had an effect on community assembly, independent of environmental variation. These results demonstrate that mycorrhizal fungal communities can vary substantially over very fine spatial scales, and that the distribution of roots from different species do not reflect their proximity aboveground. This study clearly demonstrates the widespread presence of mycorrhizal fungi and root associated bacteria in tropical rainforest plants.

Our ability to predict precipitation on climate time-scales (months–decades) is limited by our ability to separate signals in the climate system (cyclical and secular) from noise — that is, variability due to processes that are inherently unpredictable on climate time-scales. This dissertation describes methods for characterizing “weather” noise — variability that arises from daily-scale processes — as well as the potential predictability of precipitation on climate time-scales. In each method, we make use of a climate-stationary null model for precipitation and determine which characteristics of the true, non-stationary system cannot be captured by a stationary assumption. This un-captured climate variability is potentially predictable, meaning that it is due to climate time-scale processes, although those processes themselves may not be entirely predictable, either practically or theoretically. The three primary methods proposed in this dissertation are 1. A stochastic framework for modeling precipitation occurrence with proper daily-scale memory representation, using variable order Markov chains and information criteria for order selection. 2. A corresponding method for representing precipitation intensity, allowing for memory in intensity processes. 3. A semi-parametric stochastic framework for precipitation which represents intensity and occurrence without separating the processes, designed to handle the issues that arise from estimating likelihoods for zero-inflated processes. Using each of these methods, potential predictability is determined across the contiguous 48 United States. Additionally, the methods of Chapter 4 are used to determine the magnitude of weather and climate variability for the “historical runs” of five global climate models for comparison against observational data. It is found that while some areas of the contiguous 48 United States are potentially very predictable (up to ∼ 70% of interannual variability), many regions are so dominated by weather noise that climate signals are effectively masked. Broadly, perhaps 20–30% of interannual variability may be potentially predictable, but this ranges considerably with geography and the annual seasonal cycle, yielding “hot spots” and “cold spots” of potential predictability. The analyzed global climate models demonstrate a fairly robust representation of weather-scale processes, and properly represent the ratio of weather-to- climate induced variability, despite some regional errors in mean precipitation totals and corresponding variability.

Previous works have validated the concept of a microwave rain gauge that operates as follows. With a microwave Doppler motion sensor, the Doppler shift created by falling rain drops is measured. One can then relate the corresponding fall velocity to rain rate. However, the available Doppler motion sensors are lacking in several aspects. Here we address the important electronic design and signal processing considerations related to a microwave-based rain gauge.

An extreme precipitation categorization scheme, developed to temporally and spatially visualize and track the multi-scale variability of extreme precipitation climatology, is introduced over the continental United States and used as the basis for an observational dataset intercomparison. The categorization scheme groups three-day precipitation totals exceeding 100 mm into five precipitation categories, or "P-Cats". To assess observational uncertainty across a range of precipitation measurement approaches, we compare in situ station data from the Global Historical Climatology Network-Daily (GHCN-D), satellite derived data from the Tropical Rainfall Measuring Mission (TRMM), gridded station data from the Parameter-elevation Regression on Independent Slopes Model (PRISM), global reanalysis from the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA 2), and regional reanalysis from the North American Regional Reanalysis (NARR). While all datasets capture the principal spatial patterns of extreme precipitation climatology, results show considerable variability across the five-platform suite in P-Cat frequency, spatial extent, and magnitude. Higher resolution datasets, PRISM and TRMM, most closely resemble GHCN-D and capture a greater frequency of high-end totals relative to lower resolution products, NARR and MERRA-2. When all datasets are regridded to a common coarser grid, differences persist with datasets originally constructed at a high resolution maintaining the highest frequency and magnitude of P-Cats. Potential future applications of this scheme include tracking change in P-Cats over space and time, climate model evaluation, and assessment of model projected change.

This thesis presents an approach for generating long synthetic sequences of single-site daily rainfall which can incorporate low-frequency features such as drought, while still accurately representing the day-to-day variations in rainfall. The approach is implemented in a two-stage process. The first stage is to generate the entire sequence of rainfall occurrence (i.e. whether each day is dry or wet). The second stage is to generate the rainfall amount on all wet days in the sequence. The models used in both stages are nonparametric (they make minimal general assumptions rather than specific assumptions about the distributional and dependence characteristics of the variables involved), and ensure an appropriate representation of the seasonal variations in rainfall. A key aspect in formulation of the models is selection of the predictor variables used to represent the historical features of the rainfall record. Methods for selection of the predictors are presented here. The approach is applied to daily rainfall from Sydney and Melbourne. The models that are developed use daily-level, seasonal-level, annual-level, and multi-year predictors for rainfall occurrence, and daily-level and annual-level predictors for rainfall amount. The resulting generated sequences provide a better representation of the variability associated with droughts and sustained wet periods than was previously possible. These sequences will be useful in catchment water management studies as a tool for exploring the potential response of catchments to possible future rainfall.

<p>Human activities have caused acidification of freshwater systems on a large scale resulting in reduced species diversity and ecological functioning in many lakes and streams. However, many naturally acidic freshwater systems have also been found, for instance in northern Sweden. In regions where such naturally acidic aquatic ecosystems have prevailed over evolutionary periods, species diversity and ecological functioning are not automatically impaired due to possible adaptation to the putatively adverse environmental conditions. I studied species diversity patterns and ecological functioning in anthropogenically acidified, naturally acidic, circumneutral, and limed streams to test the adaptation hypothesis and examine the ecological effects of variation in naturally acidic water chemistry. Species diversity was studied using benthic macroinvertebrates, while functioning was modelled using the decomposition rates of leaf litter. In accordance with the evolutionary species pool hypothesis, species richness was reduced more strongly in regions with anthropogenic than natural acidity when compared to circumneutral streams, supporting the adaptation hypothesis. In contrast, the patterns in ecological functioning along the pH-gradients did not differ between regions with anthropogenic and natural acidity, likely resulting from compensation: the biomass of tolerant taxa probably increased which thus rescued the loss in functioning otherwise mediated by the more sensitive taxa. Furthermore, the naturally variable acidic water chemistry clearly supported distinct macroinvertebrate assemblages, as was reflected in differing patterns of species diversity and ecological functioning. Such naturally acidic waters that were rich in dissolved organic carbon supported higher ecosystem process rates and lower species diversity than waters that contained little dissolved organic carbon. Upon liming naturally acidic streams microbial leaf decomposition increased, whereas shredding decreased along with changes in shredder abundances. The abundance of large caddisflies decreased, while the abundance of small stoneflies increased. The results suggest that various types of benthic macroinvertebrates with varying levels of adaptation and tolerance inhabited the hydrochemically variable naturally acidic streams. The distributions of macroinvertebrates in response to different pH levels and differences in acid quality and how these distributions translate into varying patterns of species diversity and ecological functioning are worthy of further investigation. This will likely improve our understanding of how such naturally acidic streams and their biota can be successfully managed.</p>

An acid rain simulation was created under laboratory conditions to study the effects of mortality rates and developmental time of Aedes triseriatus (Say) mosquito larvae. Two hundred-forty instar 1 mosquitoes were placed into separate 120 ml glass jars containing rain water adjusted to pH 2, 3, 4, 5, 6, and 7 with a nitric acid solution. A second part of the experiment was set up like the first except a 70 percent to 30 percent sulfuric-nitric acid solution was used to adjust pH levels. Mortality and developmental time was observed until the insects reached maturity or died.No significant differences at the .05 level in mortality rates were observed between larvae raised in nitric acid solution as compared to sulfuric acid solution. However, exposures to 70 to 30% sulfuric-nitric solution resulted in a significantly (0.05) higher mortality at pH levels 4, 5, and 6 than the sulfuric acid or nitric acid exposures.Developmental time did not vary more the 0.5 days between the sulfuric acid exposure group and the nitric acid group except at pH 4.Ball State UniversityMuncie, IN 47306