Precipitation Intensity Research Articles

Impacts of Fengyun-4A and Ground-Based Observation Data Assimilation on the Forecast of Kaifeng’s Heavy Rainfall (2022) and Mechanism Analysis of the Event

The advancement of Numerical Weather Prediction (NWP) is pivotal for enhancing high-impact weather forecasting and warning systems. However, due to the high spatial and temporal inhomogeneity, the moisture field is difficult to describe by initial conditions in NWP models, which is the essential thermodynamic variable in the simulation of various physical processes. Data Assimilation techniques are central to addressing these challenges, integrating observational data with background fields to refine initial conditions and improve forecasting accuracy. This study evaluates the effectiveness of integrating observations from the Fengyun-4A (FY-4A) Advanced Geosynchronous Radiation Imager (AGRI) and ground-based microwave radiometer (MWR) in forecasts and mechanism analysis of a heavy rainfall event in the Kaifeng region of central China. Our findings reveal that jointly assimilating AGRI radiance and MWR data significantly enhances the model’s humidity profile accuracy across all atmospheric layers, resulting in improved heavy rainfall predictions. Analysis of the moisture sources indicates that the storm’s water vapor predominantly originates from westward air movement ahead of a high-altitude trough, with sustained channeling towards the rainfall zone, ensuring a continuous supply of moisture. The storm’s development is further facilitated by a series of atmospheric processes, including the interplay of high and low-level vorticity and divergence, vertical updrafts, the formation of a low-level jet, and the generation of unstable atmospheric energy. Additionally, this study examines the influence of Tai-hang Mountain’s terrain on precipitation patterns in the Kaifeng area. Our experiments, comparing a control setup (CTL) with varied terrain heights, demonstrate that reducing terrain height by 50–60% significantly decreases precipitation coverage and intensity. In contrast, increasing terrain height enhances precipitation, although this effect plateaus when the elevation increase exceeds 100%, closely mirroring the precipitation changes observed with a 75% terrain height increment.

How frequent and which variables of automatic weather station data should be assimilated into WRF-3DVar model? A case study of a squall line event in Beijing

Accurate precipitation forecasting is one of the most challenging problems in mesoscale Numerical Weather Prediction (NWP) models. The utilization of 3-Dimensional Variational (3DVar) Data Assimilation technique based on automatic weather station (AWS) data can significantly enhance the accuracy of precipitation simulations and forecasts using the Weather Research and Forecasting (WRF) model. However, the impacts of different assimilation frequencies and meteorological variables on the accuracy of precipitation forecasts remain unclear. This study comprehensively evaluated the impact of different assimilation frequencies and meteorological variables on precipitation forecasts, as illustrated by a case study of a squall line event on August 2, 2017, in Beijing. Eight experiments were conducted by assimilating different combinations of meteorological variables (air pressure, temperature, relative humidity, wind speed, and wind direction) at various time intervals (1 h, 3 h, and 6 h). The results indicated that the WRF model roughly simulated the evolution of this event but overestimated the precipitation amount, accompanied by a large deviation in precipitation areas. Assimilating detailed AWS data significantly improves the model performance in precipitation forecasts. The experiment assimilating all variables at a 3 h interval yielded the most accurate forecasts, with the maximum threat score (TS) increasing from 0.02 to 0.56. Higher assimilation frequencies do not guarantee a better performance. In practice, a 3 h assimilation frequency emerges as an optimal choice for AWS data assimilation. The assimilation of various variables enhanced precipitation forecasts to varying degrees, with the optimum results achieved when all variables were assimilated. Wind speed and direction were the most significant factors in dynamically enhancing the simulation of precipitation areas. Relative humidity and temperature influenced the precipitation intensity by affecting the evolution of convective precipitation thermodynamically. The findings of this study can contribute to the development of AWS data assimilation strategies for the WRF-3DVar model, thereby enhancing the precipitation forecast accuracy.

Microphysical Characteristics of Precipitation Over Eastern China and Its Coastal Regions

AbstractMany studies have investigated the macro‐ and micro‐physical properties of precipitation, but few classified precipitation into warm‐ and cold‐topped, which affects precipitation phase and precipitation type significantly. Furthermore, the impact of moisture and dynamics on microphysical characteristics of precipitation has been less studied. Using precipitation data from the GPM 2A DPR between May and September from 2015 to 2023, this study conducts a systematic study on microphysical characteristics of precipitation over eastern China and its coastal areas. This study divides precipitation cases into 20 categories, including warm‐/cold‐topped (CTP/WTP) convective/stratiform light/moderate/heavy/extreme/the most extreme precipitation. The findings reveal distinct differences along with similarities in various precipitation categories between eastern China and its coastal regions. The convection ratio for CTP increases with higher precipitation intensity, while WTP is dominated by convective precipitation. The more CTP, the higher the solid water content. The heavier precipitation, the higher liquid water content contributes. The mass‐weighted diameter (Dm) for CTP shows three variations from high to low with little or slight decrease with altitude at upper‐layer, followed by a rapid increase at middle‐layer and finally decreasing slightly at low‐layer. The CTP Dm grows rapidly with temperature from −18.58 (−13.93)°C for convective (stratiform) precipitation and their maximum growth rate are almost located in melting layer. Dm (raindrop density) is larger (lower) over land than ocean and larger (lower) for CTP than WTP. Dm shows positive relation to vertical velocity and specific humidity, especially sensitive to the middle‐ and upper‐layers meteorological conditions.

Can IMERG QPE product capture the heavy rain on urban flood scale?

Urban areas are increasingly vulnerable to sudden flooding disasters caused by intense rainfall and high imperviousness degree, resulting in great economic losses and human casualties. Interactions between rainfall data and urban catchment characteristics highlight the urgent need of accurate and effective precipitation data to apply in reliable hydrological simulations. However, it remains a challenge to obtain accurate rainfall datasets on such small scales in urban areas. As satellite remote sensing is the only method that can achieve global observation, it is important to evaluate satellite precipitation products in their ability to accurately capture intense precipitation on urban flood scales. This study evaluates the performance of the latest version 06B (V06B) Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) in North China Plain, with using the Radar-Gauge merged precipitation estimates as reference data. First, it could be concluded that IMERG fails to accurately estimate precipitation in the whole study area, having the problem of overestimating light precipitation and underestimating heavy precipitation. Second, results show that IMERG has poor ability to capture heavy precipitation on small scales, with the percentage of Hit nearly 0 and the percentage of Miss higher than 40 % for all the precipitation cases. Third, with the expansion of heavy precipitation centers' coverage, the problem of IMERG not to detect heavy precipitation gets mitigated, with the percentage of Miss decreasing by 14 % (19 %). However, the ability to capture both spatial location and precipitation intensity is still not good, the percentage of Hit ranging from 0.05 % to 7 %, without obvious improvement. When IMERG is able to capture the center of strong precipitation, it also tends to overestimate the weak precipitation around the center of strong precipitation. Results of this study provide an improved understanding of how well the V06B IMERG products capture the heavy precipitation center at small scales in urban areas, which will be useful for both developers and users of IMERG.

Changes in Mesoscale Convective System Precipitation Structures in Response to a Warming Climate

AbstractMesoscale convective systems (MCSs) are crucial components of the hydrological cycle and often produce flash floods. Given their impact, it is important to understand how they will change under a warming climate. This study uses a satellite‐ and radar‐based MCS tracking algorithm on convection‐permitting climate model simulations and examines changes in MCS properties and precipitation structures between historical and future simulations. An underestimation in MCS total precipitation is evident in historical simulation compared to observations, due to model's depiction of MCS precipitation area and summertime occurrence frequency. Under pseudo‐global warming, increases in MCS frequency and total warm season precipitation are observed, most notably in the southern U.S. The precipitation intensity and precipitating area generated by future MCSs also rises and results in an increase in precipitation volume. MCS precipitation structures are further classified into convective core and stratiform regions to understand how change in these structures contributes to future rainfall changes. In a warmer climate, the stratiform region demonstrates minimal change in size, but increases in mean precipitation rate and mean maximum precipitation rate by 15% and 29% are noted, respectively. A more robust future response is observed in the convective core region, with its size, mean precipitation rate and mean maximum precipitation rate increasing significantly by 24%, 37% and 42%, respectively. Finally, by examining the environmental properties of MCS initial condition, future intensification of convective rain may be attributed to a combined effect of substantial increases in atmospheric instability and moisture availability.

Turbulence-induced droplet grouping and augmented rain formation in cumulus clouds

This paper provides the first observational analysis of how droplet separation is impacted by the flinging action of microscale vortices in turbulent clouds over a select radii range and how they vary over cloud cores and along the peripheral edges. It is premised that this mechanism initiates droplet separation within a cloud volume soon after condensational growth, largely in the cloud core, and operates until the cloud droplet radii exceed 20–30 µm when this effect fades rapidly. New observations are presented showing how microscale vortices also impact the settling rates of droplets over a critical size range (6–18 µm) causing them to sediment faster than in still air affecting swept volumes and thereby impacting the rain initiation and formation. Large-scale atmospheric models ignore these microscale effects linked to rapid droplet growth during the early stages of cloud conversion. Previous studies on droplet spatial organization along the cloud edges and inside the deep core have shown that homogeneous Poisson statistics, indicative of the presence of a vigorous in-cloud mixing process at small scales obtained, in contrast to an inhomogeneous distribution along the edges. In this paper, it is established that this marked core region, homogeneity can be linked to microscale vortical activity which flings cloud droplets in the range of 6–18 µm outward. The typical radius of the droplet trajectories or the droplet flung radii around the vortices correlates with the interparticle distance strongly. The correlation starts to diminish as one proceeds from the central core to the cloud fringes because of the added entrainment of cloud-free air. These first results imply that droplet growth in the core is first augmented with this small-scale interaction prior to other more large-scale processes involving entrainment mixing. This first study, combining these amplified velocities are included in a Weather Research and Forecasting- LES case study. Not only are significant differences observed in the cloud morphology when compared to a baseline case, but the ‘enhanced’ case also shows early commencement of rainfall along with intense precipitation activity compared to the ‘standard’ baseline case. It is also shown that the modelled equilibrium raindrop spectrum agrees better with observations when the enhanced droplet sedimentation rates mediated by microscale vortices are included in the calculations compared to the case where only still-air terminal velocities are used.

High resolution Tibetan Plateau regional reanalysis 1961-present

With the rapid global warming in recent decades, the Tibetan Plateau (TP) has suffered severe impacts, such as glacier retreat, glacial lake expansion, and permafrost degradation, which threaten the lives and properties of the local and downstream populations. Regional Reanalysis (RR) is vital for TP due to the limitations of observations. In this work, a 62-year (1961–2022) long atmospheric regional reanalysis with spatial resolution of 9 km (convective gray-zone scale) and temporal resolution of 1 hour over the TP (TPRR) was developed using the Weather Research and Forecasting (WRF) model, combined with re-initialization method, spectral nudging (SN), and several optimizations. TPRR is forced by ERA5 at hourly intervals. TPRR outperforms ERA5, realistically capturing climatological characteristics and seasonal variations of precipitation and T2m (air temperature at 2m above ground level). Moreover, TPRR better reproduces the frequency and intensity of precipitation, as well as the diurnal cycle of precipitation. This study also quantifies the wetting trend of 0.0071 mm/year over the TP amid global warming using TPRR.

Slower-decaying tropical cyclones produce heavier precipitation over China

The post-landfall decay of tropical cyclones (TC) is often closely linked to the magnitude of damage to the environment, properties, and the loss of human lives. Despite growing interest in how climate change affects TC decay, data uncertainties still prevent a consensus on changes in TC decay rates and related precipitation. Here, after strict data-quality control, we show that the rate of decay of TCs after making landfall in China has significantly slowed down by 45% from 1967 to 2018. We find that, except the warmer sea surface temperature, the eastward shift of TC landfall locations also contributes to the slowdown of TC decay over China. That is TCs making landfall in eastern mainland China (EC) decay slower than that in southern mainland China (SC), and the eastward shift of TCs landfall locations causes more TCs landfalling in EC with slower decay rate. TCs making landfall in EC last longer at sea, carry more moisture upon landfall, and have more favorable dynamic and thermodynamic conditions sustaining them after landfall. Observational evidence shows that the decay of TC-induced precipitation amount and intensity within 48 h of landfall is positively related to the decay rate of landfalling TCs. The significant increase in TC-induced precipitation over the long term, due to the slower decay of landfalling TCs, increases flood risks in China’s coastal areas. Our results highlight evidence of a slowdown in TC decay rates at the regional scale. These findings provide scientific support for the need for better flood management and adaptation strategies in coastal areas under the threat of greater TC-induced precipitation.

A Quantitative Precipitation Estimation Method Based on 3D Radar Reflectivity Inputs

Quantitative precipitation estimation (QPE) by radar observation data is a crucial aspect of meteorological forecasting operations. Accurate QPE plays a significant role in mitigating the impact of severe convective weather. Traditional QPE methods mainly employ an exponential Z–R relationship to map the radar reflectivity to precipitation intensity on a point-to-point basis. However, this isolated point-to-point transformation lacks an effective representation of convective systems. Deep learning-based methods can learn the evolution patterns of convective systems from rich historical data. However, current models often rely on 2 km-height CAPPI images, which struggle to capture the complex vertical motions within convective systems. To address this, we propose a novel QPE model: combining the classic extrapolation model ConvLSTM with Unet for an encoder-decoder module assembly. Meanwhile, we utilize three-dimensional radar echo images as inputs and introduce the convolutional block attention module (CBAM) to guide the model to focus on individual cells most likely to trigger intense precipitation, which is symmetrically built on both channel and spatial attention modules. We also employ asymmetry in training using weighted mean squared error to make the model concentrate more on heavy precipitation events which are prone to severe disasters. We conduct experiments using radar data from North China and Eastern China. For precipitation above 1 mm, the proposed model achieves 0.6769 and 0.7910 for CSI and HSS, respectively. The results indicate that compared to other methods, our model significantly enhances precipitation prediction accuracy, with a more pronounced improvement in forecasting accuracy for heavy precipitation events.

Spatial and Temporal Patterns in Observed Extreme Precipitation Change Over Northern Part of the Korean Peninsula

AbstractThe present study aims to detect the variation of precipitation extreme events in the northern part of the Korean Peninsula during 1961–2020, as well as to investigate its possible causes, based on daily precipitation data from 37 representative stations. Nonparametric tests such as Mann‐Kendall and Kendall‐tau were used to detect statistical characteristics of changes in precipitation indices and climate variables. Findings are as follows: (a) the annual total precipitation manifested a clear shifting point in 1968, with a decreasing rate of about −37.7 mm/decade, conversely, daily precipitation intensity had a clear upward trend, and extreme precipitation events above 100 mm/day became more frequent. (b) There occurred significant upward trends of 8.9 mm/decade for intense rainfall (>95th percentile) and 6.3 mm/decade for extreme intense rainfall (>99th percentile). (c) The continuous wet (dry) days showed a decreasing (increasing) trend of about −0.2 days/decade (1.0 days/decade). The decrease rate of 5‐day max precipitation is five times as large as 1‐day max precipitation. (d) For June‐September, the strengthened West Pacific Subtropical High intensity and the variation of its ridge‐axis position, the southerly shift of the upper subtropical Jetstream and the weakening of lower moisture supplement may have suppressed the northerly move of the summer rain band and delayed the development of rainy season over the study area. (e) In view of the urbanization effect, the possible causes of the precipitation externalization were investigated, and it was found that the upward trends in daily precipitation intensity and 95th percentile intense precipitation in big cities are generally higher than rural regions.

Global Precipitation Experiment - A New World Climate Research Programme Lighthouse Activity

Abstract The future state of the global water cycle and prediction of freshwater availability for humans around the world remain among the challenges of climate research and are relevant to several United Nations Sustainable Development Goals. The Global Precipitation EXperiment (GPEX) takes on the challenge of improving the prediction of precipitation quantity, phase, timing and intensity, characteristics that are products of a complex integrated system. It will achieve this by leveraging existing World Climate Research Programme (WCRP) activities and community capabilities in satellite, surface-based, and airborne observations, modeling and experimental research, and by conducting new and focused activities. It was launched in October 2023 as a WCRP Lighthouse Activity. Here we present an overview of the GPEX Science Plan that articulates the primary science questions related to precipitation measurements, process understanding, model performance and improvements, and plans for capacity development. The central phase of GPEX is the WCRP Years of Precipitation for 2-3 years with coordinated global field campaigns focusing on different storm types (atmospheric rivers, mesoscale convective systems, monsoons, and tropical cyclones, among others) over different regions and seasons. Activities are planned over the three phases (before, during, and after the Years of Precipitation) spanning a decade. These include gridded data evaluation and development, advanced modeling, enhanced understanding of processes critical to precipitation, multi-scale prediction of precipitation events across scales, and capacity development. These activities will be further developed as part of the GPEX Implementation Plan.

Life Cycle of Precipitating Cloud Systems from Synergistic Satellite Observations: Evolution of Macrophysical Properties and Precipitation Statistics from Geostationary Cloud Tracking and GPM Active and Passive Microwave Measurements

Abstract Observations of clouds and precipitation in the microwave domain from the active dual-frequency precipitation radar (DPR) and the passive Global Precipitation Measurement (GPM) Microwave Imager (GMI) onboard the GPM Core Observatory satellite are used in synergy with cloud tracking information derived from infrared imagery from the GOES-13 and Meteosat-7 geostationary satellites for analysis of the life cycle of precipitating cloud systems, in terms of temporal evolution of their macrophysical characteristics, in several oceanic and continental regions of the tropics. The life cycle of each one of the several hundred thousand cloud systems tracked during the 2-yr (2015–16) analysis period is divided into five equal-duration stages between initiation and dissipation. The average cloud size, precipitation intensity, precipitation top height, and convective and stratiform precipitating fractions are documented at each stage of the life cycle for different cloud categories (based upon lifetime duration). The average life cycle dynamics is found remarkably homogeneous across the different regions and is consistent with previous studies: systems peak in size around midlife; precipitation intensity and convective fraction tend to decrease continuously from the initiation stage to the dissipation. Over the three continental regions, Amazonia (AMZ), central Africa (CAF), and Sahel (SAH), at the early stages of clouds’ life cycle, precipitation estimates from the passive GMI instrument are systematically found to be 15%–40% lower than active radar estimates. By highlighting stage-dependent biases in state-of-the-art passive microwave precipitation estimates over land, we demonstrate the potential usefulness of cloud tracking information for improving retrievals and suggest new directions for the synergistic use of geostationary and low-Earth-orbiting satellite observations.

Multi-scale analysis of satellite, reanalysis and muti-source precipitation estimates over the Tibetan Plateau

Due to the important hydrological and meteorological significance, the performance of different kinds of precipitation products for the Tibetan Plateau (TP) has been evaluated in previous studies. However, the performance of the products on a high spatial-temporal scale has not been clearly shown. Based on the Chinese Meteorological Administration (CMA) ground rain gauge observations during 2017–2018 over the TP, this paper analyzes the multi-scale performance of four satellite-based datasets (IMERG_Uncal, IMERG_Cal, GSMaP_MVK, and GSMaP_Gauge), two reanalysis datasets (ERA5 and ERA5-L), and one multi-source merged dataset (CMFD) for different precipitation intensities with a special attention to the characterization of spatiotemporal variability of heavy precipitation. Firstly, this study examines how the quality of precipitation products varies with time scale and precipitation intensity. CMFD generally shows the best quality and has the most stable quality at all temporal scales. Satellite products perform better in summer while reanalysis products show better results in cold seasons. Another significant issue is the impact of gauge-based calibration. GSMaP_Gauge with daily-scale gauge calibration is often considered to outperform other products. However, our study finds that GSMaP_Gauge is problematic at smaller spatiotemporal scales, especially in capturing heavy precipitation. The long-term performance of multi spatiotemporal scale comparison of different precipitation products is the focus of this study, which can help with their application and improvement.

That's not what my app says: Perceptions of accuracy, consistency, and trust in weather apps

AbstractThe usage of weather apps for forecast information has increased dramatically over the last 10–15 years. Ensuring that consumers value and trust weather apps is important to the integrity of weather forecasting. Public perception of weather app forecast accuracy and consistency undergirds the apps' value and trustworthiness. With app forecasts being interpreted solely by the app user, misunderstanding and consequent false expectations could jeopardize the public's perception of accuracy and consistency. Furthermore, weather apps often offer excessively—and potentially unrealistically—detailed forecasts on time and spatial scales, extending far into the future without sufficient disclaimers regarding the confidence level associated with such detailed forecasts. A survey of the public found perceived app accuracy and consistency to be positively correlated with the trust in an app. Participants indicated that they take at least modest consideration of uncertainty and spatial variability when assessing specific and longer range forecasts. On average, participants had low to moderate confidence in forecasts beyond 10 days, and a significant majority did not perceive a precipitation forecast as inaccurate, even when no rain occurred at their location, as long as it rained nearby. We tested for misinterpretation using a common expression of uncertainty in weather apps, namely probability of precipitation (PoP). A majority of participants made a correct interpretation of the two PoP values given, although, depending on the percentage, some misinterpreted the values as indicating precipitation intensity, totals, or duration. Overall, these findings offer encouragement for a society heavily reliant on weather apps while also encouraging more research on weather information interpretation.

How is climate change altering the precipitation pattern over Northwestern India?

AbstractClimate change in India is causing devastating downpour events and shifts in spatial characterization, with apparent regional differences. The Northwest India (NWI), which is in the Aravalli rain shadow zone and was formerly drier, has attracted great attention in recent years due to its changing rainfall patterns. This study throws light on the astonishing behaviour of ISMR over NWI with the advent of intensified rainfall over the region in the recent time frame. The Pettitt test of change point (CP) detection is utilized in this analysis to measure the change in rainfall patterns over a period of 70 years, from 1950 to 2019. This analysis suggests significant variation in the CP's time frame for different months of ISMR. The earliest change was noticed in July, while the latest was for September for the mean as well as for the intense precipitation. Moreover, we found a maximum change in the precipitation during the peak monsoon month (i.e., July and August). The difference in the precipitation of different percentile values before and after CP indicates a decrease (increase) in low (high) intensity precipitation for all the months and seasons as a whole with varying magnitude. The highest reduction of low‐intensity precipitation is noticed for the months of July and August, while the highest increase of high‐intensity precipitation (>95th percentile) is noticed for June and September. The heavier precipitation contributes largely to the mean increase of precipitation, expecting to receive more mean and precipitation extremes in the future. Unlike the increasing precipitation trend, potential evapotranspiration (source of local moisture) shows a declining trend, revealing the negative association among them and the possibility of enhanced advection of remote moisture responsible for enhanced precipitation over NWI. The enhanced vertically integrated moisture transport of the Arabian Sea and Bay of Bengal and its strengthening relationship with precipitation further confirm the contribution of remote moisture to intensified precipitation over NWI, though the in‐depth dynamical cause remains unclear. The increased Convective Available Potential Energy for entire monsoon seasons as a whole and individual months facilitates a favourable condition for enhanced convective activity over the region, resulting in strengthening the precipitation.

EUROPEAN CLIMATE PROTECTION STRATEGY UNDER CONSIDERATION OF BUILT HERITAGE PRESERVATION

Climate change affects all areas of life. The European Union strives for climate-neutrality of their members until 2050 with the project European Green Deal. By this, the emissions of greenhouse gases should be reduced to zero by 2050 with simultaneous economic development decoupled from resource use. 600 Billion Euros the European Union will spend to lower net greenhouse gas emissions until 2030 by at least 55%, compared to 1990 levels. Climate change affects historical structures, thus by variations in groundwater levels, hydrological cycle, or intense precipitation. However, also climate protection activities such as renewable energy installations may result in negative effects. Solar panels or wind turbines do not emit carbon dioxide and other greenhouse gases but, installed nearby historical buildings, affect the historical appearance of structures. That may result in conflicts between ecological and heritage conservation interests. The authors inform about the European Green Deal and analyze effects of the planned measures on built heritage with a focus on solar and wind energy installations. They also discuss requirements from heritage preservation regulations. The manuscript analyzes how renewable energy installations may affect built heritage in its historical appearance. For that, the authors use available information about the European Green Deal, discuss current research literature and relevant German court cases. It is concluded that renewable energy installations may negatively affect the appearance of built heritage. Interests of climate protection and built preservation need to be balanced to ensure that future generations even can experience and enjoy the cultural heritage.

A Quantitative Provenance Analysis (QPA) Approach to Quantify Controls on Sediment Generation and Sediment Flux in the Upper Reaches of the Magdalena River (Colombia): 2. Lithological Control on Contribution to Silt‐ to Clay‐Sized Fractions

AbstractThe composition of 27 fluvial silt and clay sediments was used in this study to identify and quantify the processes in the upper valley of the Magdalena river in South Colombia. The combination of seismic activity, intense precipitation, and landsliding resulted in limited chemical weathering and a very efficient transfer of weathered products to the transfer zone of both tributary rivers and the main trunk. Inputs from plutonic, high‐grade metamorphic, volcanic, and low‐ to medium‐grade metamorphic lithologies vary in coarse silt‐sized versus fine silt‐ and clay‐sized sediments, reflecting inherited textural parameters and mineralogy. Plutonic and high‐grade metamorphic rocks mostly produce sand‐sized sediments, up to two times more than coase silt and up to 10 times more than fine silt to clay. The prevalence of siltstone in the area enhances the contribution of sedimentary rocks to fine silt and clay (up to 50% higher than to sand). Volcanic rocks mainly produce coarse silt (up to 2.5 times more than sand). Low‐grade metamorphic detritus is enriched in silt and clay (up to 5–7 times). These findings highlight the critical role of lithology in regulating sediment generation. The study's approach can establish or modify factors modeling lithological control on suspended sediment flux, such as in the BQART equation.

Selection of urban flood shelter locations based on risk assessment

Within the framework of global climate change, there is a recurring occurrence of floods and waterlogging disasters, which pose significant risks to human lives and overall safety. The phenomenon of urbanization has led to an increased vulnerability of cities to flood disasters. Evacuation serves as a viable strategy for adapting to climate change, managing intense precipitation events, and mitigating the impact of flood disasters. Hence, the meticulous choice of shelters has emerged as a crucial element in enhancing the effectiveness of evacuations. Nevertheless, the process of choosing shelters sometimes neglects to consider the potential for flooding and has not undergone thorough testing. Hence, the objective of this research is to systematically choose shelters within the central metropolitan region, incorporate flood risk considerations into the shelter site model, and assist cities in mitigating the consequences of floods resulting from climate change. To begin with, employ a two-dimensional shallow water model in order to replicate instances of intense precipitation and produce data on flood inundation. Subsequently, the simulation results are utilized to assess the flood risk using the entropy weight approach. This risk is then incorporated into the multi-objective optimization model to determine the optimal shelter placement. Ultimately, the ABM model was employed to create a simulation of crowd evacuation in urban areas, confirming the efficacy of shelter selection and thoroughly examining the influence of various shelters on the efficiency of community emergency evacuation. The study's findings indicate that a total of 26 shelters were chosen within the study area using a multi-objective methodology, ensuring the inclusion of all affected populations. The utilization of multi-objective models in the selection of shelter places has been shown to enhance evacuation efficiency, as confirmed by the ABM model. The simulation findings indicate a decline in the population's death rate from 1.94% to 0.98%, an increase in the evacuation rate from 97.4% to 98.4%, and a reduction in the number of casualties by 133 individuals.

EUROPEAN CLIMATE PROTECTION STRATEGY UNDER CONSIDERATION OF BUILT HERITAGE PRESERVATION

Climate change affects all areas of life. The European Union strives for climate-neutrality of their members until 2050 with the project European Green Deal. By this, the emissions of greenhouse gases should be reduced to zero by 2050 with simultaneous economic development decoupled from resource use. 600 Billion Euros the European Union will spend to lower net greenhouse gas emissions until 2030 by at least 55%, compared to 1990 levels. Climate change affects historical structures, thus by variations in groundwater levels, hydrological cycle, or intense precipitation. However, also climate protection activities such as renewable energy installations may result in negative effects. Solar panels or wind turbines do not emit carbon dioxide and other greenhouse gases but, installed nearby historical buildings, affect the historical appearance of structures. That may result in conflicts between ecological and heritage conservation interests. The authors inform about the European Green Deal and analyze effects of the planned measures on built heritage with a focus on solar and wind energy installations. They also discuss requirements from heritage preservation regulations. The manuscript analyzes how renewable energy installations may affect built heritage in its historical appearance. For that, the authors use available information about the European Green Deal, discuss current research literature and relevant German court cases. It is concluded that renewable energy installations may negatively affect the appearance of built heritage. Interests of climate protection and built preservation need to be balanced to ensure that future generations even can experience and enjoy the cultural heritage.

Analysis of heavy precipitation-induced rill erosion

Erosion is an ongoing environmental problem that leads to soil loss and damages ecosystems downstream of agriculture. Increasingly frequent heavy precipitation causes single erosion events with potentially high erosion rates owing to gully erosion. In this study, analyses of croplands affected by heavy precipitation and linear erosion indicate that erosion occurs only on sparsely vegetated fields with land cover ≤ 25% and that slope gradient and length are significant factors for the occurrence of linear erosion tracks. Existing erosion models are not calibrated to the conditions of heavy precipitation and linear erosion, namely high precipitation intensities and long and steep croplands. In this study, natural linear erosion was analyzed using an unmanned aerial vehicle and erosion volumes were determined for 32 rills and gullies of different sizes. Comparisons with the RUSLE2 and EROSION-3D model values showed an underestimation of linear erosion in both models. Therefore, calibration data for erosion models used for heavy precipitation conditions must be adapted. The data obtained in this study meet the required criteria.