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This paper investigates the possible relationship between solar activity and monthly rainfall in Pokhara and Kathmandu cities in Nepal from the year 1968 to 2023. The study uses Cross Correlation Analysis (CCA) and wavelet analysis, the Cross-Wavelet Transform (XWT) and Wavelet Transform Coherence (WTC), to analyze the time series data. The CCA shows a strong positive correlation between the solar cycle and rainfall trend, with correlation coefficients of 0.77 and 0.76 and time lags of 18 months and 14 months at Pokhara and Kathmandu, respectively. The p-values, calculated to be < 0.0001 through the t-test, indicate that the observed correlations are statistically significant. The XWT results show a long-term ∼ 11-year common periodicity in solar cycle and rainfall. The WTC analysis confirms the local correlation between these two time series in time–frequency domain at a common periodicity. The results indicate that the monthly rainfall pattern in Nepal is closely related to the solar cycle pattern. Thus, solar activity likely plays a role in influencing rainfall trends in Nepal. This study shows that solar-climate interaction on a regional scale is complex and emphasizes the importance of understanding these relationships for predicting and managing climate change. [ABSTRACT FROM AUTHOR]

A declining trend in Indian summer monsoon precipitation (ISMP) in the latter half of the 20th century is a scientifically challenging and societally relevant research issue. Heavy aerosol loading over India is one of the key factors in modulating the ISMP. Using the state-of-the-state-of-the-art chemistry-climate model, ECHAM6-HAMMOZ, the impacts of South Asian anthropogenic sulfate aerosols on the Indian summer monsoon precipitation were investigated against: (1) 2010 La Niña (excess monsoon), (2) 2015 El Niño (deficit monsoon) in comparison to (3) normal monsoon 2016. Sensitivity simulations were designed with 48% enhancement in South Asian SO 2 emissions based on a trend estimated from Ozone Monitoring Instrument (OMI) satellite observations during 2006–2017. The model simulations showed that sulfate aerosols reduce ISMP by 27.5%–43.3 %, while simulations without sulfate loading enhanced ISMP by 23% in 2010 La Niña and reduction by 35% in 2015 El Niño. This paper reports that sulfate aerosols loading over India reduce precipitation by aerosol-induced direct and indirect effects by inducing atmospheric cooling, weakening in the convection, and reduction in moisture transport to Indian landmass. This paper emphasizes the necessity of alternate use of energy to reduce sulfate aerosol emissions to solve water issues in South Asia. [Display omitted] • Sulfate emission reduces Indian summer monsoon precipitation through aerosol-radiation and aerosol-cloud interactions. • Over 27% of the summer monsoon rainfall deficit in a normal year are linked to Asian anthropogenic sulfate emissions. • Sulfate-induced rainfall reduction is the maximum for La Niña year. • SO 2 loading increases atmospheric stability and weakens moisture transport to India. [ABSTRACT FROM AUTHOR]

• An LRFD framework for embankments considering climate change effects is established. • Additional partial factors are introduced to account for the climate change effects. • Non-stationary maximum flood depth is developed using a peak-over-threshold method. • Embankment reliability is evaluated against overtopping and slope failure. • The proposed framework can serve as a reference for future code design. Riverine floods have become increasingly prevalent on a global scale, posing significant risks to infrastructure systems and communities. The escalating impacts of climate change associated with the increase in rainfall intensities and frequencies necessitate the improvement of the existing design methodologies to account for the non-stationary climate change effects to ensure that the reliability is above the target level and mitigate future flood disasters. This paper presents a novel LRFD approach for river embankments subjected to extreme rainfall under non-stationary climate change effects. This approach introduces an additional partial factor to account for the effects of climate change. Precipitation and temperature projections are collected from various climate models considering several cases of emission scenarios. An integrated hydrological and hydraulic modeling of the analyzed river is carried out to estimate the associated time-variant river discharge and water surface elevation. The non-stationary extreme value associated with the maximum flood level is leveraged using the peak-over-threshold approach. The embankment reliability and the corresponding most probable points are evaluated using limit states associated with overtopping and slope failures. Based on the estimated and target reliability indexes, the design point for each random variable is assessed considering the cases with and without climate change effects. Finally, the partial factors associated with climate change effects are determined. As an illustrative example, the proposed framework is applied to the Ashida River in Fukuyama city of Japan. [ABSTRACT FROM AUTHOR]

• Nationwide streamflow projections for Australia informed by CMIP5 and CMIP6. • Vast majority of CMIP5 and CMIP6 GCMs project less winter rainfall across Australia. • Lower winter rainfall translates to a significant reduction in annual runoff. • Modelled median projection of runoff shows a 50% reduction in far southwest Australia. • Modelled median projection of runoff shows a 20% reduction in far southeast Australia. Projections of streamflow under future climate are essential for developing adaptation strategies in the water and related sectors. This paper presents nationwide streamflow projections for Australia informed by climate change signals in CMIP6 GCMs and compares the projections with those from CMIP5 GCMs. The modelled future runoff projections driven by CMIP5 and CMIP6 GCMs are relatively similar for far southern Australia. The median projection is a 50% reduction in mean annual runoff in far southwest Australia and 20% reduction in far southeast Australia by 2046–2075 relative to 1976–2015 under the high SSP5-8.5/RCP8.5 global warming scenario. The vast majority of CMIP5 and CMIP6 GCMs project less winter rainfall across Australia. As most of the runoff in far southern Australia occurs in winter and spring, the lower winter rainfall translates to a significant reduction in annual runoff. It is therefore prudent to plan and manage for a reduction in future water resources, particularly in the densely populated and important agricultural regions in southeast Australia. There is less agreement between GCMs in the summer rainfall projection, with the CMIP6 GCMs generally projecting a wetter future (or smaller decrease in rainfall) than the CMIP5 GCMs. The modelled median projection for mean annual runoff is a 10% reduction in the south-east coast, 5% reduction in the north-east coast and little change in northern Australia. More GCMs project an increase rather than a decrease in the interannual variability of rainfall, and this would further amplify multi-year hydrological droughts. [ABSTRACT FROM AUTHOR]

The collapse of glacial, permafrost, and ice-rich moraine slopes in high-altitude mountainous areas not only threatens downstream residents and infrastructure but also displaces ice mass to lower and warmer elevations, accelerating glacial ablation to some extent. Despite being considered rare, ice-rich slopes collapse more frequently than commonly thought due to climate change. For example, two adjacent mountain glaciers in the Aru Range of the Tibetan Plateau, characterized by large volumes (68 × 106 m3 and 83 × 106 m3, respectively) and low surface slope angles (12.3° and 12.9°, respectively), collapsed surprisingly in 2016. While the mechanisms behind these collapses have garnered broad attention, the ability to quantitatively assess the instability of ice-rich slopes remains limited due to the complex interplay of multi-physical processes. Taking the Aru glacier collapses as reference cases, this paper presents a conceptual model, implemented through coupled thermo-hydro-mechanical simulation, to evaluate the stability of high-altitude ice-rich slopes due to climate change, rainfall and ice ablation. Results indicate that the methodology captures the effects of temperature change, rainfall and meltwater on the instability events well, demonstrating promising potential in evaluating potential collapse zones of ice-rich slopes similar to the Aru glaciers. Furthermore, the role of climate change in the well-known Aru events is demonstrated using a state-of-the-art global climate reanalysis dataset. Findings reveal that the increase in liquid water infiltrating the Aru glaciers since 2010 was a critical factor leading to the instability events. • A conceptual model is proposed to analyse the stability and collapse zones of ice-rich slopes. • The modelling elucidates the causes of twin collapses of the Aru glaciers. • Results contribute to ice-rich slope instability prediction and associated disaster risk management. [ABSTRACT FROM AUTHOR]

• We propose a new method to quantify Climate Change Effects at hydrological scales. • The method allows to assimilate climatic projections in CDFs at rain gauge scale. • The initial (i.e., before any change scenario begins) skewness plays a crucial role. • A strong increase of outliers frequency is expected for series EV1 alike skewed. Quantifying the potential effects of Climate Change (CC) on hydrological scales is a topic with a more and more increasing interest for the scientific community, given the CC impact on agriculture, industry, economy, human health, ecosystems, among the others. In this context, the paper focuses on the sub-daily Annual Maxima (AM) of rainfall height time series, and specifically on the crucial role played by initial skewness, i.e. the skewness of the observed rainfall series used to evaluate potential parametric trends. Here a quick and user-friendly methodology is proposed, that is aimed at quantifying plausible future changes in terms of probability distributions assumed at rain gauge scale, from projections of any climatic model. In detail, the Generalized Extreme Value (GEV) and the Two-Component Extreme Value (TCEV) distributions are adopted as probability functions suitable for modelling observed rainfall AM series, which could increase their frequency and magnitude into future horizons under CC. EURO-CORDEX projections for Europe are considered, under the hypothesis that the values of the change factor, i.e. the ratio between the values of a specific quantile at two specific time horizons, are invariant when moving from an areally-averaged scale (typical for any climate model) to a point rain gauge scale, which induces that future changes are provided (in terms of frequency and magnitude of extreme events) without the need of any spatial downscaling from the assumed projections. The proposed methodology can contribute to hazard quantification associated to potential climate changes, and thus it can play a crucial role in the assessment of hydraulic structures resilience; the obtained results, specific for the study area of Italy, but easily extendable on a global scale, showed that larger increases in frequency of future heavy events are expected for time series with "EV1 alike" values of initial skewness. [ABSTRACT FROM AUTHOR]

• Exploring the urban inundation response law based on designed rainstorms by coupled hydrodynamic and rainfall-tracking model. • Source tracking analysis method is novelty proposed to excavate the response law of the connectivity among source areas to characteristics of rainstorms. • The analysis of source areas contribution further illustrates the reason why the study area would undergo inundation damage when the precipitation exceeds 100 mm. • The study is helpful to further understand the response law of inundation and relationship among source areas to characteristics of rainstorms, provide novel insights for constructing integrated flooding intervention practices. Extreme stormwater and high-impervious area, caused by climate change and high-urbanization, are widely considered as the essential factors for causing urban flood. Understanding the response law of urban inundation to characteristics of rainstorms is helpful to implement integrated flood mitigation measures. Therefore, this paper is focused on exploring the urban inundation response law based on designed rainstorms by coupled hydrodynamic and rainfall-tracking model. Pilot area of Guyuan sponge city, which is divided into 5 source areas, is adopted to conduct 36 types of rainfall scenario simulations with the combination of different rainfall amounts and durations as well as peak coefficients. Inundation analysis methods is used to obtain the relationship between maximum inundation maps and characteristics of rainstorms, and source tracking analysis method is novelty proposed to excavate the response law of the connectivity among source areas to characteristics of rainstorms. First, Results of inundation analysis reveal that rainfall amount, duration and peak value are the first, second and third critical rainstorm characteristics that determine the severity of disasters, the variation of inundation volume are 140 %, 30 % and 4.2 % when precipitation and duration as well as peak value double. Second, the inundation area that water depth more than 0.5 m increases quickly is the major reason that inundation volume varies with 2 times as the increasing of precipitation; the transferring runoff volume between source areas and land use reaches 0–6 % and 0–10 % of inundation volume. Third, SA 1 and 2 are the critical sub-areas to manage the runoff, when precipitation equals to 200 mm, SA 1 contributes 19.5–33.7 % of inundation volume in SA 2, and SA 2 contributes 28–30 % of inundation volume in SA 3. The study is helpful to further understand the response law of inundation and relationship among source areas to characteristics of rainstorms, provide novel insights for constructing integrated flooding intervention practices. [ABSTRACT FROM AUTHOR]

• The extent of flooding in China is greater than in any other country. • Nearly 66% of China's landmass is submerged by flooding. • Financial toll of flooding accounts for approximately 1.42% of the annual GDP. • Various forms of climatic change contribute to flooding. The extent of flooding in China is more significant than in any other country. Our research reveals that approximately 66 % of China's landmass is submerged by flooding, affecting about 50 % of the population. Furthermore, the financial toll of flooding now accounts for approximately 1.42 % of the annual gross domestic product (GDP), which is almost 40 times higher than the corresponding figure for the United States. We have observed that Zhengzhou city in Henan province, which faced a devastating flood in 2021, received a significant amount of rainfall, specifically a total of 552.5 mm within a 24-hour period. The floods in Henan province in 2021 caused considerable damage, including impacting nearly 15 million people, resulting in almost 400 deaths, damaging over 10,000 square kilometers of agricultural land, causing almost $19 billion in economic losses, and leading to the collapse of over 35,000 households and damage to various properties. In a similar manner, the significant flooding that occurred in southern China in 2020 impacted approximately 7.1 million individuals across eight provinces and resulted in 54 fatalities, the collapse of 6,700 houses, and incurred a direct economic loss of US$3.33 billion. We found that rainstorms have significantly increased to 10 % in the last 60 years in China. In this paper, we delved into exploring the existing published articles, reports, and government and authoritative legal texts to analyze the causes and impacts of flooding in China's flood-prone regions and potential mitigation strategies to reduce the repercussions of distressing flood events. We believe this study will help policymakers by providing new insights while formulating policy to reduce the loss caused by high-level flooding. [ABSTRACT FROM AUTHOR]

This paper studies the influence of temperature and of rainfall intensity and the effect of such variations on the treatment efficiencies and on the electrical consumptions in seven medium-large size Wastewater Treatment Plants (WWTPs) in Apulia in South Italy (Bari, Barletta, Brindisi, Lecce, Foggia, Andria and Taranto). It has been observed, in the considered WWTPs, a slight but clear increase of the incoming flow due to the increase in rainfall intensity, which results to an increase of the energy consumption per incoming volume. The impact of the climate change to the incoming flow, during the last five years (2016–2020), has been assessed indicating that an increase in rainfall intensity results to an increase of the WWTPs energy consumptions per wastewater treated volume. More specifically, for a specific WWTP (Lecce) it was found that the electrical consumption increases from 0.36 kw/m3 to 0.51 kw/m3 when the rainfall intensity was increased from 0.8 mm/min to 2.9 mm/min. Some adaption measures have been considered to upgrade the existing WWTP so to mitigate the energy increase and to limit the global effects of climate change. [Display omitted] • As Rain intensity rises, wastewater influx into WWTPs increases. • Rainfall intensity influences negatively electrical consumptions. • BOD removal is lower with increasing annual precipitations. • Temperature influences BOD, COD and SST removal efficiency. [ABSTRACT FROM AUTHOR]

This paper matched the data for all non-financial listed firms in China from 1990 to 2017 with weather data and used temperature and precipitation to represent climate change. Using daily temperature and daily precipitation data, we constructed temperature bins and precipitation bins. This study presents a potential first empirical analysis that applies the risk perception theory to comprehensively examine the impacts of daily temperature and daily precipitation on firms' debt financing costs. Compared to a day with a suitable temperature, a day with temperatures above 30 °C increases firms' debt financing costs by 0.2411%. Compared to a sunny day, a day with torrential rain increases firms' financing costs by 0.2697%. Approximately $122.13 million and $20.49 million in extra costs were incurred across all firms in 2017. We conducted a series of heterogeneity tests. We found that the negative impacts of climate change on debt financing costs are greater for firms that investor considers more vulnerable. Finally, we found two possible mechanisms. First, from the firm's subjective initiative perspective, firms that respond proactively during seasons of high temperatures and heavy rains can reduce the negative impacts. Second, adverse weather caused by climate change may also increase firms' debt financing costs by blocking travel. These results enrich the literature on firms' debt financing costs and contribute to the understanding of climate change's impact on firms. [Display omitted] • An extra high-temperature day increases firms' debt financing cost by 0.2411%. • An extra heavy-rain day increases firms' debt financing costs by 0.2697%. • The negative impacts will be greater for those firms that investor considers more vulnerable. • Firms' response proactively can reduce the negative impacts. • Climate change also may increase firms' debt financing costs by blocking travel. [ABSTRACT FROM AUTHOR]