Precipitation Frequency Research Articles

Seasonal variations in total deposition velocity and washout ratio of fine aerosols revealed from beryllium-7 (7Be) measurements in Sevastopol, the Black Sea region

Washout ratios and deposition velocities are crucial in fine aerosols as they affect their atmospheric concentration, which in turn impacts human health. The only method to estimate the total (dry and wet) aerosol deposition velocity or washout ratio is by using a tracer such as beryllium-7 (7Be). This study collected field data on the temporal variability of monthly total deposition flux of 7Be and monthly mean 7Be activity in Sevastopol station, the Black Sea region from March 2011 to December 2013. From these data, the washout ratio and deposition velocity of fine aerosol particles were derived. The monthly mean values of the washout ratio and deposition velocity ranged from 388 to 3533 (mean 1112 ± 793) and from 0.1 to 1.5 cm s−1 (mean 0.6 ± 0.4 cm s−1), respectively. The dry deposition velocity in the four precipitation-free months varied between 0.10 and 0.15 cm s−1 with an average of 0.13 ± 0.02 cm s−1. The precipitation amount and frequency strongly influenced the seasonal variability of the deposition velocity, whereas the seasonal variability of the washout ratio was controlled only by the precipitation amount. The reduced washout ratio and the increased deposition velocity were associated with the increased precipitation. Thus, the results obtained allowed for parameterizations to estimate the monthly mean values of the washout ratio and deposition velocity from the data of the monthly precipitation amount.

A Preliminary Assessment of the GSMaP Version 08 Products over Indonesian Maritime Continent against Gauge Data

This study is a preliminary assessment of the latest version of the Global Satellite Measurement of Precipitation (GSMaP version 08) data, which were released in December 2021, for the Indonesian Maritime Continent (IMC), using rain gauge (RG) observations from December 2021 to June 2022. Assessments were carried out with 586 rain gauge (RG) stations using a point-to-pixel approach through continuous statistical and contingency table metrics. It was found that the coefficient correlation (CC) of GSMaP version 08 products against RG observations varied between low (CC = 0.14–0.29), moderate (CC = 0.33–0.45), and good correlation (CC = 0.72–0.75), for the hourly, daily, and monthly scales with a tendency to overestimate, indicated by a positive relative bias (RB). Even though the correlation of hourly data is still low, GSMaP can still capture diurnal patterns in the IMC, as indicated by the compatibility of the estimated peak times for the precipitation amount and frequency. GSMaP data also manage to observe heavy rainfall, as indicated by the good of detection (POD) values for daily data ranging from probability 0.71 to 0.81. Such a good POD value of daily data is followed by a relatively low false alarm ratio (FAR) (FAR < 0.5). However, the GSMaP overestimates light rainfall (R < 1 mm/day); as a consequence, it overestimates the consecutive wet days (CWD) and number of days with rainfall ≥ 1 mm (R1mm) indices, and underestimates the consecutive dry days (CDD) extreme rain index. GSMaP daily data accuracy depends on IMC’s topographic conditions, especially for GSMaP real-time data. Of all GSMaP version 08 products evaluated, outperformed post-real-time non-gauge-calibrated (GSMaP_MVK), and followed by post-real-time gauge-calibrated (GSMaP_Gauge), near-real-time gauge-calibrated (GSMaP_NRT_G), near-real-time non-gauge-calibrated (GSMaP_NRT), real-time gauge-calibrated (GSMaP_Now_G), and real-time non-gauge-calibrated (GSMaP_Now). Thus, GSMaP near-real-time data have the potential for observing rainfall in IMC with faster latency.

Diurnal cycle of precipitation over the southeastern Tibetan Plateau and surrounding regions: Insights from intensity–frequency structure

AbstractBesides the respective importance of the frequency, intensity and diurnal cycle of precipitation, the diurnal cycle of intensity–frequency structure could reveal more physical details about the evolution process of precipitation systems. Here, an objective method to quantitatively depict the diurnal cycle of intensity–frequency structure of precipitation is proposed, and applied to complex terrains of the southeastern Tibetan Plateau (TP) and its surroundings. Results show the diurnal cycle of precipitation over the high terrain has a unimodal night peak, while low terrain with a frequency‐dominated night peak and an intensity‐dominated afternoon peak. Both weak and intense precipitation are more frequent at night than those in the afternoon over unimodal regions compared to bimodal regions. Further analysis reveals different diurnal evolution process of intensity–frequency structure within unimodal and bimodal regions, respectively, which reflects different spatiotemporal traits and evolution process of precipitation. Among unimodal regions, the elevated southeastern TP is featured by the synchronous decrease in both weak and intense precipitation from the night peak to the afternoon minimum. While the decrease of total precipitation in regions with lower terrain is dominated by the decrease of intense precipitation, but with an increase in weak precipitation simultaneously. Regarding bimodal regions, the intense precipitation over southern Hengduan Mountains has a more prominent role in leading the diurnal cycle of precipitation amount, compared with that over the southeastern Yungui Plateau. The proposed method provides a new perspective with more physical details to investigate precipitation characteristics in complex terrains, which could be further used to reasonably evaluate and improve the performance of numerical models.

High-resolution climate projection over the Tibetan Plateau using WRF forced by bias-corrected CESM

The Tibetan Plateau (TP) has undergone significant climate warming with a stronger amplitude than that experienced elsewhere in the Northern Hemisphere during the past years, but it is still challenging for most regional climate models to realistically simulate the present-day climate and promisingly project the future climate over the TP. In this study, high-resolution simulation using the Weather Research and Forecasting model (WRF) driven by bias-corrected CESM is conducted from 1979 to 2100, with the period from 2006 to 2100 under RCP4.5 and RCP8.5 (Representative Concentration Pathways) scenarios. The simulated present-day climate is evaluated firstly and then the future climate is studied secondly. The results show that compared with station observation, WRF successfully captures the spatial pattern of annual mean surface air temperature (T2m) and precipitation over the TP, with the spatial correlation coefficients larger than 0.95 for T2m and larger than 0.70 for precipitation. However, great underestimation of T2m over the southeastern TP is found in the cold season which is related to the underestimation of snow there, and the snow-temperature positive feedback develops. WRF shows limited ability in reducing the dry bias in summer, which is related to the simulated weaker water vapor transport over the southern and eastern TP. For the future changes, substantial warming, general increase in precipitation and decrease in snow are projected under RCP8.5. The warming magnitude is greater over the western TP where the more significant decrease of snow will occur by the end of 21st century. Projected precipitation tends to consistently decrease over the western TP and along the south flank of TP which is related to the low-level circulation change. The occurring frequency of light precipitation will decrease while that of non-precipitation and extreme precipitation will increase especially in the far future, with the more obvious change occurring under RCP8.5. Overall, WRF shows high ability in simulating the present-day climate and thus reliable performance in future climate projection.

Evaluation of Hourly Precipitation Characteristics from a Global Reanalysis and Variable-Resolution Global Model over the Tibetan Plateau by Using a Satellite-Gauge Merged Rainfall Product

High-resolution meteorological datasets are urgently needed for understanding the hydrological cycle of the Tibetan Plateau (TP), where ground-based meteorological stations are sparse. Rapid advances in remote sensing create possibilities to represent spatiotemporal properties of precipitation at a high resolution. In this study, the hourly precipitation characteristics over the TP from two gridded precipitation products, one from global reanalysis (the fifth generation of the European Center for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate; ERA5) and the other is simulated by Global-to-Regional Integrated forecast SysTem (GRIST) global nonhydrostatic model, are compared against satellite-gauge merged precipitation analysis (China Merged Precipitation Analysis; CMPA) from 27 July to 31 August 2014, and a satellite-retrieved precipitation estimate from the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) is also evolved. Two aspects are mainly focused on: the spatial distribution and the elevation dependence of hourly precipitation characteristics (including precipitation amount, frequency, intensity, diurnal variations, and frequency–intensity structure). Results indicate that: (1) The precipitation amount, frequency, and intensity of CMPA and IMERG decrease with altitude in the Yarlung Tsangpo river valley (YTRV), but increase at first and then decrease with altitude (except for intensity) in the eastern periphery of TP (EPTP). ERA5 performed well on the variation of precipitation amount with altitude (especially in EPTP), but poorly on the frequency and intensity. GRIST is the antithesis of ERA5, but they all overestimate (underestimate) the frequency (intensity) at all heights; (2) With increasing altitude, the diurnal phase of precipitation of CMPA and IMERG shifted from night to evening in the two sub-regions. IMERG’s diurnal phase is 1 to 3 h earlier than CMPA’s, and the discrepancy decreases (increases) as the altitude increases in YTRV (EPTP). The diurnal phase of precipitation amount and frequency in ERA5 and GRIST is significantly earlier than CMPA, and the frequency peaks around midday except in the basin. GRIST’s simulation of the diurnal variation in intensity at various altitudes is consistent with CMPA; (3) ERA5 and GRIST overestimate (underestimate) the frequency of weak (intense) precipitation, with ERA5’s deviance being the most severe. The deviations increased with altitude. These findings provide intensive metrics to evaluate precipitation in complex terrain and are helpful for deepening the understanding of simulated biases for further improving performance in high-resolution simulation.

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.

Evaluation of the GPM IMERG product at the hourly timescale over China

More-accurate satellite-based precipitation data are required for the study of hydrological and meteorological phenomena in the face of the rapidly changing climate. In this study, we evaluated IMERG V06 Final Precipitation product (IMERG-F) of the Global Precipitation Measurement (GPM) mission based on China Merged Precipitation Analysis (CMPA) data at the hourly timescale for the period from 2008 to 2017. Results indicated the following: (1) The spatial distribution of precipitation is highly consistent between the CMPA and IMERG product. However, precipitation and precipitation frequency ratios in the IMERG data are both overestimated, by 0.1–0.3 mm/h and 5%–15%, respectively. IMERG product has better ability to estimate precipitation in the east and south of China than in the west of China. The precipitation error is larger during nighttime than daytime, while the frequency ratio error is smaller during nighttime than daytime. (2) The time of maximum precipitation is more consistent between the two products than the time of maximum frequency ratio. The time of maximum precipitation is later in the IMERG product than in the CMPA product in most regions except northwestern China, and the time of maximum frequency ratio is later in most regions. (3) Gauge density has a stronger influence on the mean error in precipitation than the mean error in frequency ratio. The findings of this study could help improve the accuracy of satellite precipitation at the hourly scale and help it become a more important tool in the field of hydrometeorology.

Precipitation and Adolescent Respiratory Health in the Northeast United States.

Rationale: With more frequent and intense precipitation events across the globe due to a changing climate, there is a need to understand the relationship between precipitation and respiratory health. Precipitation may trigger asthma exacerbations, but little is known about how precipitation affects lung function and airway inflammation in early adolescents. Objectives: To determine if short-term precipitation exposure is associated with lung function and airway inflammation in early adolescents and if ever having a diagnosis of asthma modifies associations of precipitation with lung function and airway inflammation. Methods: In a prospective prebirth cohort, Project Viva, that included 1,019 early adolescents born in the northeastern United States, we evaluated associations of 1-, 2-, 3-, and 7-day moving averages of precipitation in the preceding week and forced expiratory volume in 1 second, forced vital capacity, and fractional exhaled nitric oxide (FeNO) using linear regression. We used log-transformed FeNO with effect estimates presented as percentage change. We adjusted for maternal education and household income at enrollment; any smoking in the home in early adolescence; child sex, race/ethnicity, and ever asthma diagnosis; and age, height, weight, date, and season (as sine and cosine functions of visit date) at the early adolescent visit and moving averages for mean daily temperature (same time window as exposure). Results: In fully adjusted linear models, 3- and 7-day moving averages for precipitation were positively associated with FeNO but not lung function. Every 2-mm increase in the 7-day moving average for precipitation was associated with a 4.0% (95% confidence interval, 1.1, 6.9) higher FeNO. There was evidence of effect modification by asthma status: Precipitation was associated with lower forced vital capacity and higher FeNO among adolescents with asthma. We also found that outdoor aeroallergen sensitization (immunoglobulin E against common ragweed, oak, ryegrass, or silver birch) modified associations of precipitation with FeNO, with higher FeNO in sensitized adolescents compared with nonsensitized adolescents. The associations of precipitation with FeNO were not explained by relative humidity or air pollution exposure. Conclusions: We found that greater short-term precipitation may trigger airway inflammation in adolescents, particularly among those with asthma.

Extreme hourly precipitation characteristics of Mainland China from 1980 to 2019

AbstractInstantaneous precipitation can often cause devastating disasters on the Earth's surface. Continuous increases in extreme precipitation around the world have caused widespread concern, and it is necessary to study the extreme hourly precipitation over a large scale and long time series. Using specific numbers of unique hourly precipitation point data from 1980 to 2019, our research found that there are different spatial patterns regarding the frequency and intensity of extreme hourly precipitation in Mainland China, but the clear spatial pattern of being weak in the west and strong in the east of China. Most extreme hourly precipitation events occurred from June to August in the north of China and from April to October in the south of China. Afternoon and midnight are the peak periods of extreme precipitation events in southern China. The frequency of extreme hourly precipitation in the whole of China had increased by 0.7 hr/10a and increased significantly in the northwest and southeast of China. The average intensity of extreme hourly precipitation has decreased by 0.1 mm·hr−1/10a in the whole of China. While the maximum intensity has increased in local areas, the trend of changes is not significant in the whole of China. We have discovered that rapid urbanization is likely to be responsible for the frequency of extreme hourly precipitation in China. It is urgent to enact flood protection measures because this change is expected to worsen in the future with intensified urbanization in China.

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.

Longer dry and wet spells alter the stochasticity of microbial community assembly in grassland soils

Climate change is increasing the duration of alternating wet and dry spells. These fluctuations affect soil water availability and other soil properties which are crucial drivers of soil microbial communities. While soil microbial communities have a moderate capacity to recover once a drought ceases, the expected alternation of strongly opposing regimes can challenge their capacity to adapt. Here, we set up experimental grassland mesocosms where precipitation frequency was adjusted along a gradient while holding total precipitation constant. The gradient varied the duration of wet and dry spells from 1 to 60 days during a total of 120 days, where we hypothesized that especially intermediate durations would increase the importance of stochastic community assembly due to frequent alternation of opposing environmental regimes. We examined bacterial and fungal community composition, diversity, co-occurrence patterns and assembly mechanisms across these different precipitation treatments. Our results show that 1) intermediate regimes of wet and dry spells increased the stochasticity of microbial community assembly whereas microbial communities at low and high regimes were subjected to more deterministic assembly, and 2) more persistent precipitation regimes (>6 days duration) reduced the fungal diversity and network connectivity but had little effect on bacterial communities. Collectively, these findings indicate that longer alternating wet and dry events lead to a less predictable and connected soil microbial community. This study provides new insight into the likely mechanisms through which precipitation persistence alters soil microbial communities and their predictability.

Impact of climate change on public health in Brazil

AbstractBrazil is South America's largest country and economy, represented mainly by agricultural commodities. Its vast rainforest and biodiversity are at constant risk from human actions that are seen by scientists contributing to climate change. This article dissects how Brazil influences and is directly and indirectly affected by climate change and possible strategies to control the current situation. Climate change impacts Brazilian public health in multi‐scenarios and is influenced by socioeconomical and geopolitical aspects, such as urbanization, access to sanitation and sewage, precipitation intensity and frequency, and public health policies. Therefore, surveillance and control measures, alongside socioeconomic policies, must be orchestrated to minimize human actions that impact climate change.

Temporal and spatial evolutionary trends of regional extreme precipitation under different emission scenarios: Case study of the Jialing River Basin, China

Exploration of the temporal and spatial evolutionary trends of future extreme precipitation under different emission scenarios is of considerable importance for promoting active response to climate change. Based on the output of CMIP6 global climate models (GCMs) with four Shared Socioeconomic Pathways (SSPs), precipitation data for the Jialing River Basin (China) were obtained through CMhyd downscaling and correction. A relative threshold of 95 percentile of each year was used to extract extreme precipitation in the basin, and historical observational data were used to verify the capability of the GCMs to simulate extreme precipitation. Based on Extreme-point Symmetric Mode Decomposition, the trends and periodic characteristics of future extreme precipitation in the Jialing River Basin under four different emission scenarios (SSP2.6, SSP4.5, SSP7.0, and SSP8.5) were simulated and analyzed. The future temporal and spatial distributions of extreme precipitation frequency and intensity in different periods were described. The results revealed the following. (1) Future extreme precipitation in the Jialing River Basin is likely to increase with rates of 21.8 mm/10a, 11.4 mm/10a, 8.7 mm/10a, and 8.3 mm/10a for SSP8.5, SSP 7.0, SSP4.5, and SSP2.6, respectively. (2) The frequency of extreme precipitation decreased in the whole basin with a 1-day decrease of 3.88 % (SSP8.5), 7.11 % (SSP7.0), 5.66 % (SSP4.5), and 2.40 % (SSP2.6) from historical levels. (3) The intensity of extreme precipitation increased with a 1-day increase of 11.18 % (SSP8.5), 6.80 % (SSP7.0), 5.04 % (SSP4.5), and 4.57 % (SSP2.6) from historical levels. Over time, the change of extreme precipitation showed strong periodic characteristics with three periodic components of 2–3, 4–6, and 9–12 years. In terms of spatial distribution, the frequency (intensity) center of extreme precipitation in the next 80 years will be distributed in the south (southeast) of the basin. Compared with historical observations, the area of extreme precipitation intensity in the future accounted for a larger proportion, while the area of extreme precipitation frequency accounted for a smaller proportion. In terms of increased emission levels, the extreme precipitation frequency would decrease and the intensity would increase. The conclusions of this study could provide a reference for disaster prevention and mitigation of the effects of extreme precipitation under future climate change.

Projected changes in precipitation characteristics over the Drakensberg Mountain Range

AbstractThis study examines the potential impacts of climate change on the characteristics of precipitation over the Drakensberg Mountain Range (DMR) at different global warming levels (GWLs: 1.5, 2.0, 2.5 and 3.0°C) under the Representative Concentration Pathway 8.5 (RCP8.5) scenario, using dynamical and statistical downscaled datasets. The dynamical datasets consist of 19 multi‐model simulations datasets from the Coordinated Regional Climate Downscaling Experiment (CORDEX), whereas the statistical downscaled datasets comprise 19 multi‐model simulations from the National Aeronautics and Space Administration (NASA) Earth Exchange (NEX) Global Daily Downscaled Projections (NEX‐GDDP, hereafter NEX). The capacity of the CORDEX and NEX datasets to represent past characteristics of extreme precipitation over the DMR was evaluated against eight observation datasets. The precipitation characteristics were represented by eight precipitation indices. Both CORDEX and NEX realistically capture the characteristics of extreme precipitation over the Drakensberg and, in most cases, their biases lie within the observation uncertainty. However, NEX performs better than CORDEX in reproducing most of the precipitation characteristics, except in simulating the threshold of extreme rainfall. The ensemble means of CORDEX and NEX agree on a future increase in the intensity of normal precipitation, in the frequency and intensity of extreme precipitation, as well as an increase in widespread extreme events, with a decrease in the number of precipitation days and continuous wet days. However, they disagree on the projected changes of annual precipitation, for which CORDEX projects an increase over most parts of the DMR, whereas NEX indicates a decrease. The self‐organizing‐map analysis, which reveals diversity in the projection patterns hidden in the ensemble means, shows the most probable combinations of projected changes in the annual precipitation and extreme precipitation events (in terms of intensity and frequency): (a) increase in both annual precipitation and extreme precipitation events; (b) decrease in both annual precipitation and extreme precipitation events; (c) decrease in annual precipitation but increase in extreme precipitation events. The results of this study can thus provide a basis for developing climate change adaptation and mitigating strategies over the DMR.

Shallow landslide susceptibility assessment under future climate and land cover changes: A case study from southwest China

There is no doubt that land cover and climate changes have consequences on landslide activity, but it is still an open issue to assess and quantify their impacts. Wanzhou County in southwest China was selected as the test area to study rainfall-induced shallow landslide susceptibility under the future changes of land use and land cover (LULC) and climate. We used a high-resolution meteorological precipitation dataset and frequency distribution model to analyse the present extreme and antecedent rainfall conditions related to landslide activity. The future climate change factors were obtained from a 4-member multi-model ensemble that was derived from statistically downscaled regional climate simulations. The future LULC maps were simulated by the land change modeller (LCM) integrated into IDRISI Selva software. A total of six scenarios were defined by considering the rainfall (antecedent conditions and extreme events) and LULC changes towards two time periods (mid and late XXI century). A physically-based model was used to assess landslide susceptibility under these different scenarios. The results showed that the magnitude of both antecedent effective recharge and event rainfall in the region will evidently increase in the future. Under the scenario with a return period of 100 years, the antecedent rainfall in summer will increase by up to 63% whereas the event rainfall will increase by up to 54% for the late 21st century. The most considerable changes of LULC will be the increase of forest cover and the decrease of farming land. The magnitude of this change can reach + 22.1% (forest) and –9.2% (farmland) from 2010 until 2100, respectively. We found that the negative impact of climate change on landslide susceptibility is greater than the stabilizing effect of LULC change, leading to an over decrease in stability over the study area. This is one of the first studies across Asia to assess and quantify changes of regional landslide susceptibility under scenarios driven by LULC and climate change. Our results aim to guide land use planning and climate change mitigation considerations to reduce landslide risk.

Land‒atmosphere coupling effects of soil temperature and moisture on extreme precipitation in the arid regions of Northwest China

With global warming and more frequent extreme precipitation events in recent years, the phenomenon of warming and humidification in the arid regions of Northwest China (ANWC) has attracted increasing attention. We assessed the coupling effects of soil temperature and moisture on extreme precipitation in the ANWC by using daily precipitation data from CN05.1 and monthly data on soil temperature, soil moisture, and energy from ERA5-land, 1961–2018. After logical partitioning by K-means clustering, the primary influencing routes in each partition were investigated using two indices of extreme precipitation, indicated by precipitation on very wet days (R95P) and the number of extreme precipitation days (R10day). We found that 1) Local extreme precipitation has had a steadily growing impact on overall precipitation. In summer, this impact is primarily driven by an increase in the quantity of extreme precipitation, but in winter, it is primarily driven by an increase in the intensity of single precipitation. 2) The Tianshan Mountains (TM) and Qilian Mountains (QM) are the key locations for the coupling of soil temperature and moisture with the extreme precipitation index. Both locations exhibit a positive coupling state for soil temperature with extreme precipitation with positive coupling in the TM but negative coupling in the QM for soil moisture with extreme precipitation. 3) In the coupling of soil temperature and moisture with energy, the relevant significant regions are almost all over the ANWC throughout the year and all seasons, and the coupling high-value areas are concentrated around the basin. 4) In the TM–Hami Basin (HB)–QM, the coupling between energy and the extreme precipitation index is also stronger. The specific coupling paths have been changing with seasonal and regional changes.

Water-table response to extreme precipitation events

Extreme precipitation events (EPEs) will play a significant role in influencing soil–water and groundwater storage worldwide. We examined water-table depth (WTD) response to EPEs for 17 cases representative of soils and climate settings across the United States. Precipitation data from NOAA’s Precipitation Frequency Data Server were used for each case to characterize 1-day extreme precipitation events (EPEs) with annual exceedance probabilities of 0.1 % over an average baseline date range of 1981–2011. The inverse solution in the HYDRUS-1D modeling software was used to obtain the soil–water retention curve for each case. Non-EPE and EPE scenarios were modeled and compared to examine water-table displacement (ΔWTD) and recession time (trec). The ΔWTD ranged from 0.6 to 2.4 m across cases and were not directly controlled by EPE amount; instead, ΔWTD was inversely related to available porosity. Soils with low available porosity experienced large ΔWTD compared to soils with higher available porosity. In cases with larger diffusivity values, the modeled water table receded faster than in cases with smaller diffusivity values. This was because water-table recession times, trec, were inversely related to hydraulic diffusivity. For all cases, recession back to pre-EPE levels ranged from months to years suggesting an increased role by the unsaturated zone in buffering EPEs that should be considered in future EPE-groundwater modeling studies.

New Prospects to Systematically Improve the Particulate Matter Removal Efficiency of Urban Green Spaces at Multi-Scales

Previous studies on the removal of airborne particulate matter (PM) by plants have mostly focused on the individual scale, hence there is a lack of systematic understanding of how to improve the PM removal effect of green spaces (GS) at multi-scales. We provide new insights into an integrated model, which integrates the utilization efficiency of vertical space and time into the multi-cycle PM removal model developed in our previous study. By analyzing the variabilities of the influencing factors at different scales, directions to improve this function at multiple scales can be proposed. According to the planning of urban GS, five scales were divided. At the species scale, plants should not only have the characteristics to match the local climate, but also a high utilization efficiency of time and space. At the community scale, increasing the hierarchy and structural complexity can help improve the utilization of vertical space. At the patch and landscape scales, the factor affecting the PM removal efficiency of GS lie in precipitation frequency, and large/small green patches with low/high landscape fragmentation in climates with low/high precipitation frequency are recommended. At the urban scale, it is necessary to increase the degree of temporal and spatial distribution matching between PM and GS. These findings can improve urban GS planning to contribute to the removal of airborne PM.

Methane dynamics from a mixed plantation of north China: Observation using closed-path eddy covariance method.

Although an important greenhouse gas, methane flux in hilly forest ecosystems remains unclear. By using closed-path eddy covariance systems, methane flux was measured continuously from 2017 to 2019 in a mixed plantation in the Xiaolangdi area of the Yellow River in North China. The methane flux footprint and its diurnal and monthly variations were analysed, and its characteristics on rainy days are discussed. The results showed that: (a) the observation data were reliable with good spatial representation (b) The methane flux in the mixed plantation ecosystem had obvious diurnal and seasonal variations: the monthly average diurnal variation of the methane flux had a single-peak; the methane flux value was source in the daytime and sink at night. The daily mean maximum value of methane flux in growing season was lower than that in non-growing season with the maximum value appearing in March, and the minimum value in October. (c) The forest is an atmospheric CH4 source with the annual emission in 2017 of (3.31g C·m-2·year -1) >2019 (2.94g C·m-2·year-1) >2018 (2.81g C·m-2·year -1), and the main influencing factor was precipitation. Rainfall affected CH4 flux with a lag period of approximately three days. Rainfall also changed the balance of CH4 flux between sink or source according to precipitation intensity and frequency.

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.