Asia, one of the most densely populated regions in the world, receives 50%-80% of annual rainfall during the summer monsoon season. While agricultural yield and water resource over this region benefit greatly from the summer rainfall, human lives and infrastructures are, at the same time, threatened by the frequently occurring heavy downpour. Although large efforts have been devoted to delineate the characteristics and variations of Asian monsoon extreme rainfall, its dynamical triggers and the physical mechanisms underlying the past and future changes remain poorly understood. To address the knowledge gap, this thesis aims to provide a process-oriented perspective on monsoon rainfall extremes with special attention given to the heavy-rain producing weather systems, namely the monsoon low-pressure systems (LPSs). In Chapter 1, an objective feature-tracking algorithm is adopted to compile the observed trajectories of monsoon LPSs over the East Asia monsoon region during the post-1979 satellite era. Two types of LPS are identified. One forms near the downwind side of the Tibetan Plateau (i.e., southwestern China) and travels northeastward toward north-central China. The other forms over the western North Pacific Ocean and migrates along the southern and western peripheries of the subtropical high. The two types of LPS together account for approximately half of the rainfall extremes. The terrestrial LPSs are responsible for a great majority of extreme rainfall over inland areas, whereas the influences of marine LPSs are primarily confined to the coastal regions where they frequently make landfall. The observed long-term change in extreme rainfall, featured by a “south flood-north drought” pattern, aligns well with the change in LPS activity. The decreasing number of northeastward-moving terrestrial LPSs leads to an extreme rainfall dipole with negative trends in north-central China and positive trends in southern China, while the increasing number of northward-recurving marine LPSs enhances the extreme rainfall along the southeastern China coast. These trends are driven by the weakening of the monsoonal southwesterlies and the eastward retreat of the subtropical high. Despite the great importance of terrestrial LPSs in modulating extreme rainfall over East Asia, these storms have so far received limited attention in research community because of the lack of a track archive. Chapter 2 further investigates the dynamical processes fueling the different evolution regimes of individual terrestrial LPSs and explores the environmental factors controlling their evolution. Chapters 3 and 4 concentrate on the South Asian monsoon region, where the long-term trend of LPS activity remains debatable owing to the potential errors arising from the manual and subjective identification of LPSs from weather charts. Using two different tracking algorithms, in Chapter 3 we find that the trends of extreme rainfall and LPS activity indeed exhibit a strong coherence. Over time, the LPSs propagate preferentially through south-central India rather than north-central India, imparting a corresponding dipole footprint in rainfall extremes. In agreement with previous studies that the LPS propagation is a combined effect of the northwestward-propagating component due to horizontal nonlinear adiabatic advection and the southwestward-propagating component due to diabatic heating, the LPSs traveling through south-central India have stronger updrafts on their west-southwestern flank than those passing through north-central India. The increased frequency of LPSs propagating through south-central India is likely due to a strengthened cross-equatorial moisture transport over the Arabian Sea, which favors more vigorous storm convection through the conditional instability of second kind mechanism. Chapter 4 then focuses specifically on the role of LPS in triggering the record-breaking Pakistan flood during summer 2022, when most of the South Asian LPSs were able to propagate into Pakistan with intensity and longevity far exceeding historical records. The abnormal LPS activity was fueled by a historically-high cross-equatorial moisture transport, which is in agreement with the fingerprint of anthropogenic warming in the Coupled Model Intercomparison Project - Phase 6 (CMIP6) models. The last chapter of this thesis proceeds to evaluate the performance of CMIP6 models in simulating the monsoon rainfall extremes and to explore whether the performance is affected by the degree to which the models could realistically capture the LPS activity. The modelled precipitation often occurs more frequently and the extreme events are commonly less intense than in observations. A robust improvement of model performance in simulating monsoon rainfall extremes as resolution increases is seen across most models, both in terms of spatial distribution and intensity. The dry biases get improved in the regions with high exposure to monsoon LPSs, such as central India, southern China, and western North Pacific. The improvement is associated with a better representation of LPSs, which become more frequent and stronger at finer resolution.

Projected increasing temperatures and reduced summer precipitation in the UK raises questions about the sustainability of aspects of the agriculture industry and food security. This study investigates the potential impact of precipitation changes on sugar beet yield in Eastern England. Observations of precipitation was examined for the period 1971-2000 and the expected changes in precipitation were investigated using seven CMIP5 climate models for the historical phase (1971-2000) and RCP45 and RCP85 future scenarios (2021-2050). Three out of the seven models were found to show good agreement with observations but the MOHC ensemble mean was the closest to the observed means and was used for further precipitation analyses. Statistical analysis of the future precipitation changes were performed using the Met Office Hadley Centre (MOHC) model focused on changes between the historical phase and RCP45 and RCP85. Results showed a consistent and significant reduction in annual May-October precipitation under future scenarios. The study then investigated the impact of reduced future precipitation changes on sugar beet yield by applying controlled watering regimes informed by the CMIP5 projections to sugar beet plants in a greenhouse experiment over two seasons - the use of CMIP5 projections in this way is a first. In the first experiment carried out in 2014, a climatological watering regime (i.e. where the total seasonal rainfall for the different scenarios was applied in equal and regular watering events) was applied to the plants, which meant a 16% reduction in precipitation in the "future" category relative to a "control" category. Analysis of the yields indicated a statistically significant reduction in mean tuber wet mass: mean of 360g for the control and 319g for the future (p-value 0.03). This implies a potential yield reduction of 11% by 2050. In the second experiment carried out in 2015, a "realistic distribution" watering regime (i.e. where the total seasonal rainfall is applied in a series of watering events that reflect the analysed sizes and distribution of rainfall events in the different categories), this meant a reduction in precipitation in the months of June (-15.6%), July (-7.7%) and August (-3.7%). This resulted in statistically significant reduction in mean tuber wet mass between control (153g) and RCP85 (113g) with a p-value of 0.01. This implies a reduction of 26% in future yields under RCP85 by 2050. Results in this thesis further show how changes and variation in precipitation are intertwined with changes in soil moisture and yield of sugar beet plants. The findings will enable UK sugar beet farmers to identify potential areas of challenges in order to adapt their management practices to ensure maximum crop yield in future growing seasons. Moreover, from a global perspective, the findings here are also broadly applicable to a variety of agricultural crops in different parts of the world, where changes in yield may have important consequences to food security and food prices.

The dissertation focuses on the application of entropy theory in hydrologic analysis and simulation, namely, rainfall analysis, streamflow simulation and drought analysis. The extreme value distribution has been employed for modeling extreme rainfall values. Based on the analysis of changes in the frequency distribution of annual rainfall maxima in Texas with the changes in duration, climate zone and distance from the sea, an entropy-based distribution is proposed as an alternative distribution for modeling extreme rainfall values. The performance of the entropy based distribution is validated by comparing with the commonly used generalized extreme value (GEV) distribution based on synthetic and observed data and is shown to be preferable for extreme rainfall values with high skewness. An entropy based method is proposed for single-site monthly streamflow simulation. An entropy-copula method is also proposed to simplify the entropy based method and preserve the inter-annual dependence of monthly streamflow. Both methods are shown to preserve statistics, such as mean, standard deviation, skenwess and lag-one correlation, well for monthly streamflow in the Colorado River basin. The entropy and entropy-copula methods are also extended for multi-site annual streamflow simulation at four stations in the Colorado River basin. Simulation results show that both methods preserve the mean, standard deviation and skewness equally well but differ in preserving the dependence structure (e.g., Pearson linear correlation). An entropy based method is proposed for constructing the joint distribution of drought variables with different marginal distributions and is applied for drought analysis based on monthly streamflow of Brazos River at Waco, Texas. Coupling the entropy theory and copula theory, an entropy-copula method is also proposed for constructing the joint distribution for drought analysis, which is illustrated with a case study based on the Parmer drought severity index (PDSI) data in Climate Division 5 in Texas.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第25250号 / 工博第5209号 / 新制||工||1994(附属図書館) / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 立川 康人, 教授 角 哲也, 教授 森 信人 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

京都大学 / 新制・課程博士 / 博士(工学) / 甲第25262号 / 工博第5221号 / 新制||工||1996(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 岸田 潔, 教授 安原 英明, 准教授 橋本 涼太 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

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.

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Hydrogeological hazards are quite diffuse rainfall-induced phenomena that affect mountain regions and can severely impact these territories, producing damages and sometimes casualties. For this reason, hydrogeological risk reduction is crucial. Mitigation strategies aim to reduce hydrogeological risk to an acceptable level and can be classified into structural and non-structural measures. This work focuses on enhancing some non-structural risk mitigation measures for mountain areas: debris-flow rainfall thresholds, as a part of an Early Warning System (EWS), multivariate rainfall scenarios with multi-hazard mapping purpose and public awareness. Regarding debris-flow rainfall thresholds, an innovative calibration method, a suitable uncertainty analysis and a proper validation process are developed. The Backward Dynamical Approach (BDA), a physical-based calibration method, is introduced and a threshold is obtained for a study area. The BDA robustness is then tested by assessing the uncertainty in the threshold estimate. Finally, the calibrated threshold's reliability and its possible forecast use are assessed using a proper validation process. The findings set the stage for using the BDA approach to calibrate debris-flow rainfall thresholds usable in operational EWS. Regarding hazard mapping, a multivariate statistical model is developed to construct multivariate rainfall scenarios with a multi-hazards mapping purpose. A confluence between a debris-flow-prone creek and a flood-prone river is considered. The multivariate statistical model is built by combining the Simplified Metastatistical Extreme Value approach and a copula approach. The obtained rainfall scenarios are promising to be used to build multi-hazard maps. Finally, the public awareness within the LIFE FRANCA (Flood Risk ANticipation and Communication in the Alps) European project is briefly considered. The project action considered in this work focuses on training and communication activities aimed at providing a multidisciplinary view of hydrogeological risk through the holding of courses and seminars.