Frequency Of Heavy Precipitation Research Articles

Multifactor Mathematical Modeling and Analysis of the Impact of Extreme Climate on Geological Disasters

Objective: To investigate the impact of extreme climate on geological disasters in Shanxi and propose effective disaster prevention and mitigation strategies. Methods: Using daily temperature and precipitation data from 27 meteorological stations in Shanxi Province from 1975 to 2020, 32 extreme climate indices were calculated. Combined with geological disaster site data, the distribution characteristics of extreme climates and their relationship with geological disasters were analyzed, and a regression model for geological disaster risk zones was constructed. Results: Sixteen extreme climate indices in Shanxi Province showed significant changes, especially TMAXmean (100% significant). Indices related to negative precipitation effects showed a declining trend, with 77.78% being significant, while 96.3% of positive temperature effect indices showed an increasing trend, with 73.6% being significant. Geological disaster hotspots were concentrated in the mid-altitude (500–1500 m) hilly and low mountain areas along the central north–south axis and on Q and Pz strata. Extreme high-temperature indices were significantly positively correlated with geological disaster hotspots, while extreme low-temperature indices were negatively correlated. Indices related to extreme heavy precipitation (e.g., R99p.Slope, RX5day.Slope) were associated with an increase in geological disaster hotspots, whereas higher total precipitation and frequent heavy precipitation events were associated with a decrease in disaster hotspots. The grey relational degree between the Z-score and TXn.Slope, TXx.Slope, GSL.Slope, and TX90P.Slope was greater than 0.8. The random forest model performed best in evaluation metrics such as MAE, RMSE, and R2. Conclusions: Shanxi is likely to experience more extreme high-temperature and precipitation events in the future. The low-altitude hilly and terraced areas in Zones III and VII are key regions for geological disaster prevention and control. High temperatures and extreme rainfall events generally increase the disaster risk, while higher total precipitation reduces it. The random forest model is the optimal tool for predicting geological disaster risks in Shanxi Province.

Improving Aerosol Radiative Forcing and Climate in E3SM: Impacts of New Cloud Microphysics and Improved Wet Removal Treatments

AbstractNumerous Earth system models exhibit excessive aerosol effective forcing at the top of the atmosphere (TOA), including the Department of Energy's Energy Exascale Earth System Model (E3SM). Here, in the context of the E3SM version 3 effort, the predicted particle property (P3) stratiform cloud microphysics scheme and an enhanced deep convection parameterization suite (ZM_plus) are implemented into E3SM. The ZM_plus includes a convective cloud microphysics scheme, a multi‐scale coherent structure parameterization for mesoscale convective systems, and a revised cloud base mass flux formulation considering impacts of the large‐scale environment. The P3 scheme improved cloud and radiation particularly over the Northern Hemisphere and the frequency of heavy precipitation over the tropics, and the ZM_plus improved clouds in the tropics. P3 decreases aerosol effective forcing by 0.15 W m−2, while the ZM_plus increases it by 0.27 W m−2, resulting from excessive direct (0.31 W m−2) and indirect forcing (−1.79 W m−2). The excessive aerosol forcings are due to aerosol overestimation associated with insufficient aerosol wet removal. By improving the physical treatments in the aerosol wet removal, we effectively mitigate anthropogenic aerosol overestimation and thus attenuate direct (0.09 W m−2) and indirect aerosol forcing (−1.52 W m−2). Adjustment to primary organic matter hygroscopicity reduces direct and indirect forcing to more reasonable values: −0.13 W m−2 and −1.31 W m−2, respectively. On climatology, improved aerosol treatments mitigate overestimation of aerosol optical depth.

The observed evolution of sub‐daily to multi‐day heavy precipitation in Switzerland

AbstractHeavy precipitation is a major natural hazard in the Alps. Understanding the possible changes due to climate change is a prerequisite for effective climate adaptation and protection. In this study, we revisit the long‐term (1901–2023) evolution of daily and multi‐day heavy precipitation intensity and frequency, discuss trends for sub‐daily to multi‐day events in the recent period 1981–2023 and investigate elevation dependencies in the complex topography of Switzerland. We analyze station measurements from MeteoSwiss' dense operational network covering the whole country and a wide range of elevation levels. We find that daily maximum precipitation and the frequency of precipitation events exceeding the 99th all‐day percentile have increased since 1901 with a peak in the 1980s and decreases thereafter. For the recent period 1981–2023, positive trends in summer heavy precipitation intensity are detected for short (10‐min to 3‐h) events, but no changes are found for the frequency of these moderate extreme events. For longer (1‐ to 5‐day) events on the other hand, decreases in intensity and frequency are found, especially for the winter half‐year. We hypothesize that the opposing trends on the centennial (1901–2023) vs. decadal (1981–2023) time scales are caused by the interaction between thermodynamics, reflecting the primary influence of human‐induced climate change, and the internal variability of atmospheric dynamics. Moreover, we observe a small negative elevation dependency of the daily long‐term trends up to 2300 m above sea level. For the 1981–2023 trends, no strong elevation dependencies are found for sub‐daily events. For daily events, we find small opposing negative summer and positive winter elevation dependencies for both intensities and frequencies. The reason for these tendencies remains unclear. Our results underscore the need to further investigate the interplay between climate change, internal variability of large‐scale dynamics and elevation to better understand heavy precipitation variability in the complex Alpine terrain.

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.

Projection of climate change effects on flood inundation in the Gin River basin, Sri Lanka

Abstract. Human-induced climate change has altered the frequency and severity of heavy precipitation, droughts, and floods worldwide. Sri Lanka, a developing country in the Indian Ocean, has suffered frequent floods, affecting over 64 % of the population in the past decade. The Gin River, the primary drinking water source of the densely populated Galle district with over 1 million residents, faces recurrent flood disasters. Therefore, this study employed a multi-model ensemble to simultaneously simulate the impact of climate change on both river flow and inundation extent in the frequently flooded Gin River basin located in humid tropical monsoon region. Bias-corrected climate projections of an ensemble of five General Circulation Models (GCMs) from the Coupled Model Inter-comparison Project Phase 5 (CMIP5) under Representative Concentration Pathway (RCP) 4.5 emission scenario were used to project future river flow and flood inundation in the Gin River basin, Sri Lanka. The validated Rainfall–Runoff–Inundation (RRI) model projected a 5 % increase in high flows (flows exceeding a 5 % probability of exceedance (<Q5)) at the downstream (Baddegama) gauging station and a 16 % increase at the upstream (Thawalma) gauging station in the future (2040–2060) in comparison to the past (1980–2000), which can be attributed to the elevated rainfall projected during the two monsoon seasons (southwest monsoon (May–September) and northeast monsoon (December–February)) by the GCM ensemble. In addition to the projected changes in high flows revealed by the RRI simulations, the model also yielded critical information about the expansion of annual maximum inundated extent in the basin by 3.5 % that will aid flood risk projection and sustainable management in the basin.

Improving simulations of extreme precipitation events in China by the CMIP6 global climate models through statistical downscaling

The recently released NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is a high-resolution daily downscaled dataset derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6) model simulations. We comprehensively evaluated the performance of the NEX-GDDP dataset in simulating the characteristics of the climatological precipitation and extreme precipitation events across China from 1960 to 2014. We present here the projected changes in precipitation at the end of the 21st century (2070–2099) with respect to a reference period (1985–2014). We compared the NEX-GDDP dataset with both a state-of-the-art gauge data analysis system and the CMIP6 global climate models. The NEX-GDDP dataset significantly outperformed the CMIP6 simulations in replicating the climatological patterns of precipitation. It showed a closer alignment with the observed data, as evidenced by notably increased correlation coefficients and reduced model-relative errors. The NEX-GDDP dataset exceled in accurately reproducing the spatial distribution of indices of extreme precipitation, surpassing the performance of the CMIP6 simulations. The projections show an increased frequency of heavy precipitation under higher emission scenarios in both datasets, with the CMIP6 simulations consistently estimating a higher probability of heavy rain than the NEX-GDDP dataset.

Evaluation and comparison of 11 sets of gridded precipitation products over the Qinghai-Tibet Plateau

The Qinghai Tibet Plateau (QTP) poses challenges in developing high-quality gridded precipitation data with high spatial and temporal resolution due to its complex terrain, harsh weather conditions, and sparse gauge observations. Previous research showed that gridded precipitation products from remote sensing satellites, reanalysis, and merged data are useful over the QTP. However, the precipitation products were usually calibrated against ground meteorological stations, so the evaluation based on these stations might be misleading. This study collected 11 sets of gridded precipitation products on the QTP, and evaluated them by using 53 independent rain gauges obtained from the hydrological yearbook (HY). The results showed that the CMFD precipitation product performed better than other products at meteorological sites from the National Meteorological Information Center (NMIC), with average daily and monthly correlation coefficients (CCs) of 0.55 and 0.94 and root mean square errors (RMSEs) of 3.78 and 0.44 mm/d, respectively. Following closely is CLDAS. In contrast, MSP performed best at HY sites, with average CCs of 0.70 and 0.91 and RMSEs of 2.47 and 0.65 mm/d, respectively. The following are TPHiPr, GSMAP, and CLDAS. Some global products, such as CHIPRS and CMORPH, performed poorly over the QTP. Most products overestimated the frequency of light precipitation (0.1– 0.5 mm/d) and underestimated the frequency of heavy precipitation. The fluctuation amplitudes of relative deviations for all precipitation products are markedly greater at hydrological sites compared to that at meteorological sites. Therefore, it is essential to consider correcting magnitude deviations before using these products. Based on independent assessment, this study suggests that further improvements are still needed for precipitation products on the QTP.

Changes in Classified Precipitation in Iran

Changes in classified precipitation in Iran and its relationship with global mean surface temperature (GMST) have not been comprehensively investigated. Therefore, this study analyzed changes in precipitation of different intensities over Iran for the 1987–2017 period. Results show that the total annual precipitation (PRCPTOT) and the number of wet days (RR) have significantly decreased over Iran. Also, the mean precipitation intensity (SDII) has increased somewhat. There is a non-uniform change for three intensity categories of precipitation. The amounts (frequency) of light, moderate, and heavy precipitation have significantly decreased at 47% (57.9%), 18.7% (15.8%), and 3.94% (7.9%) of stations respectively. Therefore, the decrease in the amount and frequency of light and moderate precipitation is more severe than heavy precipitation and the proportion of heavy precipitation to the total annual precipitation has increased somewhat during 1987-2017. Overall, the result shows that the intensity of decreasing trends of amount and frequency of precipitation has increased from the south (east) to the north (west) of Iran. Also, SDII has increased from the south (east) to the north (west) of Iran. The sensitivity value was obtained by calculating the ratio of linear trends of precipitation indices and GMST. The regional median sensitivity and percentage change in PRCPTOT, RR, and SDII per 1-kelvin increase in GMST are -6.1%, -11.2%, and 12.9% respectively. Considering that Iran is located in the arid subtropical region, a significant decrease in the amount and frequency of precipitation may have destructive effects on water resources.

What Influences the Demand for a Potential Flood Insurance Product in an Area with Low Previous Exposure to Insurance? – A Case Study in the West African Lower Mono River Basin (LMRB)

Floods portray a severe problem in the riverine areas of West Africa while more frequent and intense heavy precipitation events are projected under climatic change scenarios. Already, floods cause manifold impacts, leaving the population to cope with the financial impacts of floods through their own means. As formal risk transfer mechanisms (e.g., insurance) are not yet widely available to the population, efforts to increase their accessibility are being intensified. However, studies assessing flood insurance demand currently mostly focus on regions with more established markets. Also, they are majorly applying conventional statistical modeling approaches that consider only a small number of parameters. Contrarily, this study aims to provide an approach for assessing flood insurance in a context of low previous exposure to such products, to allow for a better consideration of the research context. Therefore, a parameter selection framework is provided and machine learning and deep learning models are applied to selected parameters from an existing household survey data set. In addition, the deep learning sequential neural networks outperformed all machine learning models achieving an accuracy between 93.5—100% depending on the loss function and optimizer used. The risk to be covered, insurance perception, no access to any source, access to support from community solidarity funds, access to governmental support, or drawing upon own resources for financial coping, financial recovery time, lack of means and prioritizing more essential needs emerged as important model parameters in researching insurance demand. Future roll-out campaigns could consider the parameters pointed out by this study.

Seasonal Differences of Precipitation and Microphysical Characteristics over the Asian Monsoon Region Using Spaceborne Dual-Frequency Precipitation Radar

Abstract This study aimed to reveal the seasonal climatic variations in the microphysical properties of precipitation over the Asian monsoon region. We used the Dual-Frequency Precipitation Radar satellite product aboard the Global Precipitation Measurement Mission Core Observatory for 8 years from 2014 to 2021 to statistically analyze the mass-weighted mean diameter (Dm) and frequency of heavy ice precipitation (graupel and hail). The results showed statistically significant seasonal changes. The microphysical characteristics of large Dm and frequent heavy ice precipitation were observed over the Indian subcontinent and Indochina Peninsula in the premonsoon season and over the western Himalayan region in the mature-monsoon season, which can be related to the intense and deeply developed precipitation systems. The relationship between precipitation rate and Dm was also examined. The results indicated that changes in Dm were not caused only by changes in precipitation rate but were probably induced by changes in precipitation characteristics. In terms of the relationship between the microphysical properties, heavy ice precipitation particles in the upper atmosphere above the melting layer were observed more frequently as Dm near the surface increased. We also studied lower-atmospheric instability by investigating the vertical gradients of the dry and moist static energies. The results indicated that instability properties were different; dry and wet instabilities were dominant in the premonsoon and monsoon seasons, respectively, consistent with the results of the precipitation characteristics. Significance Statement The purpose of this study was to reveal seasonal variations in precipitation microphysical characteristics, such as precipitation particle size and the existence of graupel and hail in the upper atmosphere, by climatological analysis over the Asian monsoon region. In previous studies, microphysical characteristics have mainly been addressed using ground-based observations. However, more sampling is needed to expand our understanding of climatological perspectives; therefore, we used recently available satellite observations. As a result, we found that precipitation particles at the surface were larger, and more graupel and hail existed in clouds in the premonsoon season when less precipitation was observed, compared to the mature-monsoon season when precipitation amount and frequency were abundant.

Observed and projected changes in wet and dry spells for the major river basins in East Asia

AbstractSpatiotemporal changes in wet and dry spells had significantly contributed to climate‐related natural hazards in East Asia, especially in river basins undergoing warming. However, few studies have systematically analysed these changes for river basins at different latitudes. Herein, we investigated the observed and projected variations in wet and dry spells for East Asian river basins at different latitudes. We found that river basins at low latitudes (Yangtze and Pearl rivers) had obvious wet characteristics, whereas those at high latitudes (Amur and Yellow rivers) had obvious dry characteristics. In general, the river basins presented a ‘wet south but dry north’ spatial pattern. Long‐duration wet spells have been shown to be the primary contributor to total wet spells in low‐latitude river basins, while long‐duration dry spells have been found to be the primary contributor to total dry spells in high‐latitude river basins. Importantly, climate is changing from prolonged wet spells to short, intense wet spells in low‐latitude river basins, whereas the climate is changing from single, short dry spells to moderate, prolonged dry spells at high latitudes. These changes indicate a high probability of flash floods in river basins at low latitudes and a high probability of droughts at high latitudes. In the future, more temporally clustered heavy precipitation events and prolonged dry spells may lead to increasingly uneven precipitation in high‐latitude river basins and the Pearl River basin, especially under the higher shared socioeconomic pathway scenarios. In contrast, more frequent consecutive heavy precipitation events may aggravate the risk of flooding in the Yangtze River basin. These findings are expected to serve as a guide for flood and drought risk mitigation in East Asia under a warming climate.

Land–Atmosphere Interactions Partially Offset the Accelerated Tibetan Plateau Water Cycle through Dynamical Processes

Abstract The Tibetan Plateau (TP) has become wetter and warmer during the past four decades, which leads to an adjustment in the surface energy budget, characterized by enhanced surface latent heat and weakened surface sensible heat. However, the impacts of these surface energy changes on climate are unclear. In this study, we investigate the atmospheric response to the altered surface energy budget in the monsoon season over the TP using regional climate simulations. The inhibited surface sensible heating weakens the thermal effect of the TP, which further suppresses low-level convergence and upper-level divergence, thereby weakening the water vapor flux convergence over the plateau. The weakening of low-level air humidity by this dynamical response exceeds the supply from the enhanced surface evaporation, causing decreased precipitation (decreasing more in the wet eastern plateau and less in the dry west). Further analyses show that the precipitation frequency increases mainly for light precipitation while decreasing for heavy precipitation. It is thus demonstrated that on the TP, land surface energy–atmosphere interactions can mitigate the rate of precipitation increase, suppress the increase in frequency of heavy precipitation, and weaken the east–west contrast in precipitation amount, through a dynamical mechanism. Overall, land–atmosphere interactions on the TP exert negative feedback to partially offset the accelerated plateau water cycle under a changing climate.

Are carbon-storing soils more sensitive to climate change? A laboratory evaluation for agricultural temperate soils

A range of agroecological practices allow to increase soil organic carbon (SOC) stocks, which makes a positive impact on climate change mitigation and soil health, but the permanence of this additional SOC storage can be questioned, in particular in a climate change context. Increased temperatures, accentuated evaporation of terrestrial water and increased atmosphere moisture content are anticipated, resulting in more frequent droughts and heavy precipitation events. Understanding the SOC dynamics and assessing the sensitivity of carbon mineralization to these climatic events is necessary to anticipate future carbon losses in terrestrial ecosystems. To this respect, it seems relevant to investigate carbon-storing soils as increased carbon mineralization induced by climate change may limit the carbon storing potential in agricultural soils. Thus, we evaluated the sensitivity of SOC mineralization to increased temperature, decreased soil moisture and drying-rewetting cycles using soils from long-term field experiments. We performed an incubation experiment on topsoil (0–30 cm) samples from temperate luvisols that had been under 20 years under conservation agriculture (CA), organic agriculture (ORG) and conventional agriculture (CON-LC) at the La Cage experiment, and under organic waste products (OWPs) applications in QualiAgro experiment, including biowaste composts (BIOW), residual municipal solid waste composts (MSW), farmyard manure (FYM) and conventional agriculture without organic inputs (CON-QA). Soil samples were incubated in the lab for 3 months under different temperature conditions (20, 28 and 35 °C) or under different moisture conditions (matric potential: pF1.5; pF 2.5 and pF 4.2) or under several dry (pF 4.2)-wet (pF 1.5) cycles (DWC). The results shown that, whatever the agricultural practices, soil moisture regime and temperature significantly affect the SOC mineralization. Overall, the DWC did not stimulate soil carbon mineralization relative to wet controls (pF1.5 and pF2.5). Whatever the soil moisture regime and temperature, specific carbon mineralization was similar between agricultural practices at La Cage, while at QualiAgro, specific carbon mineralization was lower in soils receiving organic waste products (OWPs) compared to the baseline soil. These results suggest a strong carbon stabilization by OWPs in soils as assessed by laboratory incubation experiments. Within each long-term experiment, we observed no significant difference between the carbon-storing soils (CA, ORG, MSW, FYM and BIOW) and their respective baseline soils (CON-LC and CON-QA) in the delta SOC mineralized whatever the soil moisture regime. The Q10 also indicated no significant difference between carbon-storing soils and their respective baseline soils. These results indicate that the SOC mineralization in carbon-storing soils had a similar sensitivity to the soil moisture regime and temperature as the baseline ones. Hence, the implementation of these agroecological practices appears beneficial for climate change mitigation, even in the context of extreme climatic events.

Water Vapor Budget Features and Its Precipitation Effects over the Key Area of Sichuan-Tibet Railway in Summer

In this study, we investigate the variation of characteristics of summer precipitation with different magnitudes and the water vapor budget in different key areas of the Sichuan-Tibet Railway by using the daily precipitation data from meteorological stations and the monthly mean ERA-Interim reanalysis data from 1979 to 2018. The results show that the summer heavy precipitation anomaly in the Brahmaputra valley and mountain (BVM) area is generated by the multi-scale interactions between the unique topography and different water vapor transports at low latitudes. When an intense anticyclonic circulation occurs over the western Pacific and the South China Sea, there is also an anomalous anticyclonic circulation extending from the northern Indian Peninsula to the Bay of Bengal. This circulation pattern is conductive to the increase of the water vapor inflow from the southern boundary and the net water vapor budget in the BVM area. The strong southwesterly wind and water vapor convergence over this area thus leading to heavy precipitation in the summer. The summer heavy precipitation amount, frequency and intensity in the western parts of the steep terrain (ST) area on the east slope of the plateau are positively correlated with the water vapor inflow from its western boundary. However, the correlations of the water vapor budget to the summer heavy precipitation amount and frequency are opposite in the eastern parts of the ST area. The unique terrain and circulation patterns lead to the localization and diversity of heavy precipitation in the ST area.

A 440-Year Reconstruction of Heavy Precipitation in California from Blue Oak Tree Rings

Abstract The variability of water year precipitation and selected blue oak tree-ring chronologies in California are both dominated by heavy precipitation delivered during just a few days each year. These heavy precipitation events can spell the difference between surplus or deficit water supply and elevated flood risk. Some blue oak chronologies are highly correlated with water year precipitation (r = 0.84) but are equally well correlated (r = 0.82) with heavy precipitation totals ≥25.4 mm (1 in., ≈95th percentile of daily totals, 1949–2004). The blue oak correlation with nonheavy daily totals is much weaker (<25.4 mm; r = 0.55). Consequently, some blue oak chronologies represent selective proxies for the temporal and spatial variability of heavy precipitation totals and are used to reconstruct the amount and number of days with heavy precipitation in northern California from 1582 to 2021. Instrumental and reconstructed heavy precipitation totals are strongly correlated with gridded atmospheric river–related precipitation over the western United States, especially in central California. Spectral analysis indicates that instrumental heavy precipitation totals may be dominated by high-frequency variability and the nonheavy totals by low-frequency variance. The reconstruction of heavy precipitation is coherent with instrumental heavy totals across the frequency domain and include concentrations of variance at ENSO and biennial frequencies. Return period analyses calculated using instrumental heavy precipitation totals are representative of the return periods in the blue oak reconstruction despite the large differences in series length. Decadal surges in the amount, frequency, and interannual volatility of heavy precipitation totals are reconstructed, likely reflecting episodes of elevated atmospheric river activity in the past. Significance Statement Tree-ring chronologies of blue oak are highly correlated with precipitation delivered to northern California during just the heaviest days of precipitation each year. The reconstruction of heavy precipitation indicates decadal episodes with a high frequency of extreme precipitation. These episodes of frequent heavy precipitation likely arose because of elevated atmospheric river activity and are relevant to the analysis of water supply and flood hazard in California.

Study on the Impact of Future Climate Change on Extreme Meteorological and Hydrological Elements in the Upper Reaches of the Minjiang River

Global warming increases global average precipitation and evaporation, causing extreme climate and hydrological events to occur frequently. Future changes in temperature, precipitation, and runoff from 2021 to 2050 in the upper reaches of the Minjiang River were analyzed using a distributed hydrological model, the SWAT (Soil and Water Assessment Tool), under a future climate scenario. Simultaneously, future variation characteristics of extreme climate hydrological elements in the upper reaches of the Minjiang River were analyzed using extreme climate and runoff indicators. The research shows that the frequency and intensity of the extreme temperature warming index will increase, while those of the extreme temperature cooling index will increase and then weaken in the upper reaches of the Minjiang River under a future climate scenario. The duration of precipitation, the intensity of continuous heavy precipitation, and the frequency of heavy precipitation will increase, whereas the intensity of short-term heavy precipitation and the frequency of heavy precipitation will decrease. However, spatial distribution of flood in the upper reaches is different, and thus flood risk in the upstream source area will still tend to increase. Particular attention should be given to the increase in autumn flood risk in the upper reaches of the Minjiang River.

Fluvial Flood Losses in the Contiguous United States Under Climate Change

AbstractFlooding is one of the most devastating natural disasters causing significant economic losses. One of the dominant drivers of flood losses is heavy precipitation, with other contributing factors such as built environments and socio‐economic conditions superimposed to it. To better understand the risk profile associated with this hazard, we develop probabilistic models to quantify the future likelihood of fluvial flood‐related property damage exceeding a critical threshold (i.e., high property damage) at the state level across the conterminous United States. The model is conditioned on indicators representing heavy precipitation amount and frequency derived from observed and downscaled precipitation. The likelihood of high property damage is estimated from the conditional probability distribution of annual total property damage, which is derived from the joint probability of the property damage and heavy precipitation indicators. Our results indicate an increase in the probability of high property damage (i.e., exceedance of 70th percentile of observed annual property damage for each state) in the future. Higher probability of high property damage is projected to be clustered in the states across the western and south‐western United States, and parts of the U.S. Northwest and the northern Rockies and Plains. Depending on the state, the mean annual probability of high property damage in these regions could range from 38% to 80% and from 46% to 95% at the end of the century (2090s) under RCP4.5 and RCP8.5 scenarios, respectively. This is equivalent to 20%–40% increase in the probability compared to the historical period 1996–2005. Results show that uncertainty in the projected probability of high property damage ranges from 14% to 35% across the states. The spatio‐temporal variability of the uncertainty across the states and three future decades (i.e., 2050s, 2070s, and 2090s) exhibits nonstationarity, which is driven by the uncertainty associated with the probabilistic prediction models and climate change scenarios.

The direct and legacy effects of drying‐rewetting cycles on active and relatively resistant soil carbon decomposition

AbstractGlobal climate change is expected to increase the frequency of drought and heavy precipitation, which could create more frequent drying‐rewetting cycles (DWC) in the soils. Although the DWC effects on soil organic carbon (SOC) decomposition have been widely studied, the effect of DWC and the subsequent legacy effect on the decomposition of different SOC pools is still unclear. We conducted a 128‐d laboratory incubation to investigate the DWC effects by using soils from old‐field for 15 years (OF, representing active SOC), bare‐fallow (BF)for 15 years, and BF for 23 years plus an extra 815‐d incubation (BF+, representing relatively resistant SOC). The experiment included nine 10‐d DWC of three treatments: (1) one mean constant‐moisture at 60% water‐holding capacity (WHC), (2) a mild DWC with 10‐d drying to 40% WHC and immediately rewetting to 80% WHC, and (3) a strong DWC with 10‐d drying to 20% WHC and immediately rewetting to 100% WHC. Following the DWC period (0–90 d), there was a 10‐d stabilization period (adjusting all treatments to 60% WHC), and then a 28‐d extended incubation under the constant moisture of 60% WHC. During the DWC period, the strong DWC had a strong effect on CO2 release compared with the constant‐moisture control, reducing the SOC decomposition of OF by 8% and BF by 10%, while increasing the SOC decomposition of BF+ by 16%. In addition, during the extended period, both mild and strong DWC significantly increased SOC mineralization of OF, but decreased that of BF and BF+. This legacy effect induced by DWC compensated for the changes in CO2 release during the DWC period, resulting in the minor response of SOC decomposition of OF and BF+ to the DWC during the entire incubation. Together, DWC could create both direct and legacy effects, and these effects vary with DWC intensity and SOC pools.

Extreme precipitation over northern China in autumn 2021 and joint contributions of tropical and mid-latitude factors

Frequent heavy precipitation and severe flood disasters struck northern China in early autumn 2021, with seven provinces/municipalities surpassing their precipitation records since 1961. Causes for such extreme events from the climate perspective are unclear because the variability of autumn precipitation in northern China is poorly understood. This study revealed that the event was directly caused by the extremely north-westward location of the western Pacific subtropical high (WPSH), which was jointly induced by several tropical and mid-latitude factors. The developing La Niña and warmer than normal tropical Atlantic sea surface temperature altered the Pacific Walker Circulation and enhanced the convection over the tropical western Pacific. Meanwhile, the Madden–Julian Oscillation stagnated for a long time in its phases 3–5 in early autumn and contributed constructively to the active convection over the tropical eastern Indian Ocean and western Pacific. These effects altogether excited a lower-tropospheric cyclone anomaly to the west of the Philippines and shifted the WPSH northwestwards in early autumn. A mid-latitude cyclonic centre was also observed upstream of East Asia. It dispersed Rossby wave energy southeastwards in the form of cold air invasions. The resultant convergence of cold and dry air from the north with warm and moist air from the south together caused extreme precipitation over northern China in autumn 2021. Relevant conclusions can enhance our current understanding of the causes of autumn extreme precipitation events in northern China and improve our ability to predict such events and prevent resultant disasters.

Projected Changes in Future Extreme Precipitation over the Northeast United States in the NA-CORDEX Ensemble

Abstract The northeastern United States (NEUS) is a densely populated region with a number of major cities along the climatological storm track. Despite its economic and social importance, as well as the area’s vulnerability to flooding, there is significant uncertainty around future trends in extreme precipitation over the region. Here, we undertake a regional study of the projected changes in extreme precipitation over the NEUS through the end of the twenty-first century using an ensemble of high-resolution, dynamically downscaled simulations from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) project. We find that extreme precipitation increases throughout the region, with the largest changes in coastal regions and smaller changes inland. These increases are seen throughout the year, although the smallest changes in extreme precipitation are seen in the summer, in contrast to earlier studies. The frequency of heavy precipitation also increases such that there are relatively fewer days with moderate precipitation and relatively more days with either no or strong precipitation. Averaged over the region, extreme precipitation increases by +3%–5% °C−1 of local warming, with the largest fractional increases in southern and inland regions and occurring during the winter and spring seasons. This is lower than the +7% °C−1 rate expected from thermodynamic considerations alone and suggests that dynamical changes damp the increases in extreme precipitation. These changes are qualitatively robust across ensemble members, although there is notable intermodel spread associated with models’ climate sensitivity and with changes in mean precipitation. Together, the NA-CORDEX simulations suggest that this densely populated region may require significant adaptation strategies to cope with the increase in extreme precipitation expected at the end of the next century. Significance Statement Observations show that the northeastern United States has already experienced increases in extreme precipitation, and prior modeling studies suggest that this trend is expected to continue through the end of the century. Using high-resolution climate model simulations, we find that coastal regions will experience large increases in extreme precipitation (+6.0–7.5 mm day−1), although there is significant intermodel spread in the trends’ spatial distribution and in their seasonality. Regionally averaged, extreme precipitation will increase at a rate of ∼2% decade−1. Our results also suggest that the frequency of extreme precipitation will increase, with the strongest storms doubling in frequency per degree of warming. These results, taken with earlier studies, provide guidance to aid in resiliency preparation and planning by regional stakeholders.