Mean Precipitation Intensity Research Articles

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.

Analyzing changes in land use practices and livelihoods in the Bhungroo irrigation technology Volta basin piloted sites, West Mamprusi District, Ghana

This study focused on assessing agricultural land use practices and livelihood changes as affected by long-term erratic rainfall patterns characterized by flood and drought cycles in the Bhungroo Irrigation Technology (BIT) piloted sites, West Mamprusi upper and lower catchment area in Ghana. The study defined environmental flow restoration (EFR) factors based on irrigation water demand, natural outflows (e.g. drainage, seepage and percolation), evaporative outflows, rainfall and stored water. Agro-ecological resilience (AER) factors included flooding intensity, crop production under dry season, flood recession, and irrigation, and livestock as well as mixed farming was assessed. The framework of Evaluating Sustainable Land Management (FESLM) was utilized to assess changes in land use and trends analyzed by the Auto Regressive Integrated Moving Average (ARIMA) technique. The main observed land use practices were subsistence cultivation with limited irrigation 72.8%, subsistence cultivation without irrigation 64.5% and livestock keeping with some cultivation 87.4%. Corresponding land use mean weights impact on the EFR and AER were 9, 9, 8, and 9, 8, 7 respectively. The study noted that precipitation was of higher significance than temperature in terms of hydro-climate determinants in both upper and lower catchment areas. Mean monthly precipitation amount and intensity were highest between June–July in the upper catchment while in the lower catchment it was between July–August. These months corresponded with high risk of flooding and waterlogging in both catchments. The opposite was observed in March with access to irrigation water being the most EFR factor influencing the resilience of BIT especially at the upper catchment area. In terms of academic contribution, this paper posits in the hydro-climatic context that excess pressure exerted from a combination of micronized factors such as waterlogging of farmlands, flood recession rate, irrigation capabilities, climate preparedness, adoption and transferability of innovations and scalability of climate innovations are likely be the critical elements which accelerate the climate vulnerability of arid and semi-arid catchment areas. Based on these observations, the study carefully recommends improved BIT infrastructure, including the integration of grundfos pumping systems, solar pay-as-you-go energy, MTN mobile payment systems, participatory decision support systems (PDSS), with improved awareness on determinants of EFR including crop-livestock integration in ecological organic agriculture as resilience building options.

Assessment of total and extreme precipitation over central Asia via statistical downscaling: Added value and multi-model ensemble projection

Central Asia (CA) is highly sensitive and vulnerable to changes in precipitation due to global warming, so the projection of precipitation extremes is essential for local climate risk assessment. However, global and regional climate models often fail to reproduce the observed daily precipitation distribution and hence extremes, especially in areas with complex terrain. In this study, we proposed a statistical downscaling (SD) model based on quantile delta mapping to assess and project eight precipitation indices at 73 meteorological stations across CA driven by ERA5 reanalysis data and simulations of 10 global climate models (GCMs) for present and future (2081–2100) periods under two shared socioeconomic pathways (SSP245 and SSP585). The reanalysis data and raw GCM outputs clearly underestimate mean precipitation intensity (SDII) and maximum 1-day precipitation (RX1DAY) and overestimate the number of wet days (R1MM) and maximum consecutive wet days (CWD) at stations across CA. However, the SD model effectively reduces the biases and RMSEs of the modeled precipitation indices compared to the observations. Also it effectively adjusts the distributional biases in the downscaled daily precipitation and indices at the stations across CA. In addition, it is skilled in capturing the spatial patterns of the observed precipitation indices. Obviously, SDII and RX1DAY are improved by the SD model, especially in the southeastern mountainous area. Under the intermediate scenario (SSP245), our SD multi-model ensemble projections project significant and robust increases in SDII and total extreme precipitation (R95PTOT) of 0.5 mm d−1 and 19.7 mm, respectively, over CA at the end of the 21st century (2081–2100) compared to the present values (1995–2014). More pronounced increases in indices R95PTOT, SDII, number of very wet days (R10MM), and RX1DAY are projected under the higher emission scenario (SSP585), particularly in the mountainous southeastern region. The SD model suggested that SDII and RX1DAY will likely rise more rapidly than those projected by previous model simulations over CA during the period 2081–2100. The SD projection of the possible future changes in precipitation and extremes improves the knowledge base for local risk management and climate change adaptation in CA.

Potential Effects of Urbanization on Precipitation Extremes in the Pearl River Delta Region, China

Rapid urbanization plays an indelible role in modifying local climate, with more extreme precipitation in urban areas. Understanding the mechanism of urban-induced precipitation changes and quantifying the potential effects of urbanization on the changes in precipitation extremes have become hotspot issues in hydrometeorology. We examine the spatiotemporal changes of precipitation extremes over the Pearl River Delta region in China using the homogenized daily precipitation dataset from the period 1961–2017, and quantify the urbanization effects on these changes. Most of the extreme precipitation indices show increasing trends, but only the mean precipitation intensity has a significant increase. Urbanization could induce the intensification of extreme precipitation, with a higher amount, intensity, and frequency of precipitation extremes and a larger magnitude of their trends in urban areas by comparison with those rural areas. Moreover, high-level urbanization tends to make a greater contribution to the temporal changes in precipitation extremes, indicating that urbanization effects on precipitation extremes may be related to urbanization levels. However, urbanization level shows little effect on the changes in the spatial patterns of precipitation extremes, with similar spatial distribution in different urbanization stages. Our findings highlight the important role of urbanization in precipitation extremes and offer insights into the feedback of anthropogenic changes into variations in precipitation extremes.

Global hydro-climatological indicators and changes in the global hydrological cycle and rainfall patterns

There are few commonly used indicators that describe the state of Earth’s global hydrological cycle and here we propose three indicators to capture how an increased greenhouse effect influences the global hydrological cycle and the associated rainfall patterns. They are: i) the 24-hr global total rainfall, ii) the global surface area with daily precipitation, and iii) the global mean precipitation intensity. With a recent progress in both global satellite observations and reanalyses, we can now estimate the global rainfall surface area to provide new insights into how rainfall intensity changes over time. Based on the ERA5 reanalysis, we find that the global area of daily precipitation decreased from 43 to 41% of the global area between 1950 and 2020, whereas the total daily global rainfall increased from 1440 Gt to 1510 Gt per day. However, the estimated 24-hr global precipitation surface area varies when estimated from different reanalyses and the estimates are still uncertain. To further investigate historical variations in the precipitation surface area, we carried out a wavelet analysis of 24-hr precipitation from the ERA5 reanalysis that indicated how the rainfall patterns have changed over time. Our results suggest that individual precipitation systems over the globe have shrunk in terms of their spatial extent while becoming more intense throughout the period 1950–2020. Hence, the wavelet results are in line with an acceleration of the rate of the global hydrological cycle, combined with a diminishing global area of rainfall.

A Study of AR-, TS-, and MCS-Associated Precipitation and Extreme Precipitation in Present and Warmer Climates

Abstract Atmospheric rivers (ARs), tropical storms (TSs), and mesoscale convective systems (MCSs) are important weather phenomena that often threaten society through heavy precipitation and strong winds. Despite their potentially vital role in global and regional hydrological cycles, their contributions to long-term mean and extreme precipitation have not been systematically explored at the global scale. Using observational and reanalysis data, and NOAA’s Geophysical Fluid Dynamics Laboratory’s new high-resolution global climate model, we quantify that despite their occasional (13%) occurrence globally, AR, TS, and MCS days together account for ∼55% of global mean precipitation and ∼75% of extreme precipitation with daily rates exceeding its local 99th percentile. The model reproduces well the observed percentage of mean and extreme precipitation associated with AR, TS, and MCS days. In an idealized global warming simulation with a homogeneous SST increase of 4 K, the modeled changes in global mean and regional distribution of precipitation correspond well with changes in AR/TS/MCS precipitation. Globally, the frequency of AR days increases and migrates toward higher latitudes while the frequency of TS days increases over the central Pacific and part of the south Indian Ocean with a decrease elsewhere. The frequency of MCS days tends to increase over parts of the equatorial western and eastern Pacific warm pools and high latitudes and decreases over most part of the tropics and subtropics. The AR/TS/MCS mean precipitation intensity increases by ∼5% K−1 due primarily to precipitation increases in the top 25% of AR/TS/MCS days with the heaviest precipitation, which are dominated by the thermodynamic component with the dynamic and microphysical components playing a secondary role.

An assessment of tropical cyclones in North American CORDEX WRF simulations

This work presents an assessment of tropical cyclones (TCs) in the 25 km and 50 km resolution reanalysis-forced and baseline and future (RCP8.5) global climate model (GCM) forced simulations produced for the North American branch of the international Coordinated Regional climate Downscaling Experiment (NA-CORDEX) using the Weather Research and Forecasting (WRF) model. A set of complementary 12 km resolution simulations produced as a part of a different project is also included in this assessment.Before examining the projections from the GCM-driven simulations, the ability of the simulations to minimally produce a realistic spatial distribution of historical TC occurrence was assessed in simulations forced by reanalysis and the three different GCMs used herein. Then, projections for occurrence, TC related mean precipitation and precipitation intensity, storm duration, the intensity measured by minimum pressure and maximum wind speed, storm size, and translation speed were examined. Several of these characteristics show little to no change in the future in trend or in distribution across the ensemble. However, many simulations suggest a westward shift or increase in TC occurrence over the East Pacific basin and a decrease in occurrence over the Caribbean and Gulf of Mexico. Increases (decreases) in total storm-related precipitation are projected where TC occurrence increases (decreases). TC precipitation intensity is found to increase in all simulations over the East Pacific, but projections are mixed over the North Atlantic. Finally, the ensemble projects a distribution shift towards more intense TC over the East Pacific, and a shift toward faster translation speeds over the North Atlantic.

Projected future daily characteristics of African precipitation based on global (CMIP5, CMIP6) and regional (CORDEX, CORDEX-CORE) climate models

We provide an assessment of future daily characteristics of African precipitation by explicitly comparing the results of large ensembles of global (CMIP5, CMIP6) and regional (CORDEX, CORE) climate models, specifically highlighting the similarities and inconsistencies between them. Results for seasonal mean precipitation are not always consistent amongst ensembles: in particular, global models tend to project a wetter future compared to regional models, especially over the Eastern Sahel, Central and East Africa. However, results for other precipitation characteristics are more consistent. In general, all ensembles project an increase in maximum precipitation intensity during the wet season over all regions and emission scenarios (except the West Sahel for CORE) and a decrease in precipitation frequency (under the Representative Concentration Pathways RCP8.5) especially over the West Sahel, the Atlas region, southern central Africa, East Africa and southern Africa. Depending on the season, the length of dry spells is projected to increase consistently by all ensembles and for most (if not all) models over southern Africa, the Ethiopian highlands and the Atlas region. Discrepancies exist between global and regional models on the projected change in precipitation characteristics over specific regions and seasons. For instance, over the Eastern Sahel in July–August most global models show an increase in precipitation frequency but regional models project a robust decrease. Global and regional models also project an opposite sign in the change of the length of dry spells. CORE results show a marked drying over the regions affected by the West Africa monsoon throughout the year, accompanied by a decrease in mean precipitation intensity between May and July that is not present in the other ensembles. This enhanced drying may be related to specific physical mechanisms that are better resolved by the higher resolution models and highlights the importance of a process-based evaluation of the mechanisms controlling precipitation over the region.

The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, part I: evaluation of precipitation

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of sim 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (sim 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from sim , −40% at 12 km to sim , −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales.

The use of media filters in treatment of runoff pollution

The study will examine the ability of recycled aggregates and sand to classify wastewater in a manner that decreases the level of environmental pollution. The sample was taken from Kg Wang Ulu, Perlis agricultural district, Jejawi, Perlis industrial area and Taman Desa Katong, Perlis residential area. Water quality research has been investigated to find the characteristics of effluent such as suspended solids, BOD, COD and TSS. Three rainfall intensity values, of 5 LPM as low rainfall, 12.5 LPM as mean precipitation intensity, and 22.5 LPM as high-cut rainfall consisted of recycled aggregate and high-absorptive sand as drainage beds, were included in this operating system. Experimental findings indicate that the recycling of aggregates and sand filters has a positive effect on water in industrial and residential areas. It shows that the use of recycled aggregates as a drainage bed can increase the permeability of the region by reducing erosion, preventing flooding and promoting natural infiltration.

Fast adjustment versus slow SST-mediated response of daily precipitation statistics to abrupt 4xCO2

Projected changes in global to regional precipitation remain highly model-dependent and are driven by both fast atmospheric adjustments and slower ocean-mediated responses to increasing concentrations of greenhouse gases. Understanding the relative influence of these multiple drivers is one of the main objectives of the Cloud Feedback Model Intercomparison Project. Here the focus is on the daily precipitation response to an abrupt quadrupling of atmospheric CO2, as simulated by the CNRM-CM6-1 global climate model. Extended atmosphere-only experiments with prescribed sea surface temperature (SST) are used to decompose the precipitation changes into separate responses to uniform SST warming, the pattern of SST anomalies, as well as fast radiative and physiological CO2 effects. The uniform SST warming dominates the global and regional changes in annual mean and annual maximum daily precipitation intensity. In contrast, the annual mean number of wet days and the annual maximum of consecutive dry days show a strong fast adjustment. They are also sensitive to the SST warming pattern that strongly influences changes in large-scale circulation. The increase in daily precipitation intensity drives the global-mean magnitude of the annual precipitation change. In contrast, the response of wet day frequency shapes the geographical distribution and interannual variability of the annual mean precipitation, especially in the subtropics, and is more sensitive to changes in near-surface relative humidity than in the total water column over land. Although the annual precipitation response does not seem highly sensitive to the base state, these results deserve further investigation and model intercomparison within CFMIP.

Performance of multisite stochastic precipitation models for a tropical monsoon region

Stochastic weather generator (SWG) produces synthetic time series of weather data based on the statistical characteristics of observed weather for a given location. Although SWG models are extensively evaluated and applied in different hydro-climate related studies, they often ignore the spatial correlation between weather patterns observed at multiple locations. This can limit the value of some spatial impact assessments such as flood modeling, agricultural crop modeling, water resources management and urban infrastructure design. To address such limitations, multisite SWG models are implemented to preserve the spatial characteristics of weather variables. In this study, we compared the performance of three multisite stochastic precipitation models, which includes modified Wilks model (modWilks), RainSim V3 (RSIM) and perturbed K-Nearest Neighbor (pKNN) models. The performances of these models are investigated for a study area located in the tropical monsoon climate region over Central Highland, Vietnam. The models are evaluated based on their performance for simulating precipitation occurrence and amount statistics on a wet day, extreme cumulative wet/dry days, transition and joint probability of wet/dry state, cross-correlation across all sites as well as the behavior of precipitation amount in relation to neighboring station state. The performance of model depends on the type of the precipitation characteristics, for example, the RSIM model performed well in term of the mean precipitation intensity. Overall, the pKNN model outperformed other models in term of temporal statistics, spatial characteristics, as well as extreme events measured based on Intensity–Duration–Frequency (IDF) curves.

Global distribution of the intensity and frequency of hourly precipitation and their responses to ENSO

We investigate the global distribution of hourly precipitation and its connections with the El Niño–Southern Oscillation (ENSO) using both satellite precipitation estimates and the global sub-daily rainfall gauge dataset. Despite limited moisture availability over continental surfaces, we find that the highest mean and extreme hourly precipitation intensity (HPI) values are mainly located over continents rather than over oceans, a feature that is not evident in daily or coarser resolution data. After decomposing the total precipitation into the product of the number of wet hours (NWH) and HPI, we find that ENSO modulates total precipitation mainly through the NWH, while its effects on HPI are more limited. The contrasting responses to ENSO in NWH and HPI is particularly apparent at the rising branches of the Pacific and Atlantic Walker Circulations, and is also notable over land-based gauges in Australia, Malaysia, the USA, Japan and Europe across the whole distribution of hourly precipitation (i.e. extreme, moderate and light precipitation). These results provide new insights into the global precipitation distribution and its response to ENSO forcing.

High-Resolution, In Situ Monitoring of Stable Isotopes of Water Revealed Insight into Hydrological Response Behavior

High temporal resolution (20-min intervals) measurements of stable isotopes from groundwater, stream water and precipitation were investigated to understand the hydrological response behavior and control of precipitation and antecedent wetness conditions on runoff generation. Data of 20 precipitation events were collected by a self-sufficient mobile system for in situ measurements over four months in the Schwingbach Environmental Observatory (SEO, temperate climate), Germany. Isotopic hydrograph separation indicated that more than 79% of the runoff consisted of pre-event water. Short response times of maximum event water fractions in stream water and groundwater revealed that shallow subsurface flow pathways rapidly delivered water to the stream. Macropore and soil pipe networks along relatively flat areas in stream banks were likely relevant pathways for the rapid transmission of water. Event water contribution increased with increasing precipitation amount. Pre-event water contribution was moderately affected by precipitation, whereas, the antecedent wetness conditions were not strong enough to influence pre-event water contribution. The response time was controlled by mean precipitation intensity. A two-phase system was identified, at which the response times of stream water and groundwater decreased after reaching a threshold of mean precipitation intensity of 0.5 mm h−1. Our results suggest that high temporal resolution measurements of stable isotopes of multiple water sources combined with hydrometrics improve the understanding of the hydrological response behavior and runoff generation mechanisms.

The hourly precipitation intensity and frequency in the Yarlung Zangbo river basin in China during last decade

The analysis of precipitation intensity and frequency should be conducted on data with high temporal resolution, such as hourly precipitation data. This study focuses on the spatial distribution and temporal variation of precipitation intensity and frequency in the Yarlung Zangbo River basin during 2008–2017, based on a merged hourly precipitation dataset with 0.1° of latitude/longitude spatial resolution. The hourly precipitation intensity is represented as the mean accumulated amount in each observation hour and the precipitation frequency is the proportion of precipitation hours in this study. The multi-year mean values and temporal changes of precipitation intensity and frequency are compared at annual time scale, during the warm season (from May to October) and cold season (from November to the next April), as well as among the upper, middle and lower basins. For the whole stream region, the mean hourly precipitation intensity is 0.92 mm/h during the warm season, larger than 0.69 mm/h during the cold season. The mean precipitation frequency is about 7.79% during the warm season, larger than 4.40% during the cold season. For the sub-region, the mean hourly precipitation intensity and frequency are largest for the lower basin during the warm season (1.10 mm/h and 10.62%), whereas largest for the upper basin during the cold season (0.86 mm/h and 4.26%). The hourly precipitation intensity increases during the warm season but decreases during the cold season. The precipitation frequency continuously decreases with larger tendency during the warm season than that during the cold season.

Convective Shower Characteristics Simulated with the Convection-Permitting Climate Model COSMO-CLM

This paper evaluates convective precipitation as simulated by the convection-permitting climate model (CPM) Consortium for Small-Scale Modeling in climate mode (COSMO-CLM) (with 2.8 km grid-spacing) over Germany in the period 2001–2015. Characteristics of simulated convective precipitation objects like lifetime, area, mean intensity, and total precipitation are compared to characteristics observed by weather radar. For this purpose, a tracking algorithm was applied to simulated and observed precipitation with 5-min temporal resolution. The total amount of convective precipitation is well simulated, with a small overestimation of 2%. However, the simulation underestimates convective activity, represented by the number of convective objects, by 33%. This underestimation is especially pronounced in the lowlands of Northern Germany, whereas the simulation matches observations well in the mountainous areas of Southern Germany. The underestimation of activity is compensated by an overestimation of the simulated lifetime of convective objects. The observed mean intensity, maximum intensity, and area of precipitation objects increase with their lifetime showing the spectrum of convective storms ranging from short-living single-cell storms to long-living organized convection like supercells or squall lines. The CPM is capable of reproducing the lifetime dependence of these characteristics but shows a weaker increase in mean intensity with lifetime resulting in an especially pronounced underestimation (up to 25%) of mean precipitation intensity of long-living, extreme events. This limitation of the CPM is not identifiable by classical evaluation techniques using rain gauges. The simulation can reproduce the general increase of the highest percentiles of cell area, total precipitation, and mean intensity with temperature but fails to reproduce the increase of lifetime. The scaling rates of mean intensity and total precipitation resemble observed rates only in parts of the temperature range. The results suggest that the evaluation of coarse-grained (e.g., hourly) precipitation fields is insufficient for revealing challenges in convection-permitting simulations.

A synthesis of hourly and daily precipitation extremes in different climatic regions

Climatological features of observed annual maximum hourly precipitation have not been documented systematically compared to those on daily timescales due to observational limitations. Drawing from a quality-controlled database of hourly records sampling different climatic regions including the United States, Australia, the British Isles, Japan, India and peninsular Malaysia over the 1950–2016 period, we examined climatological features of annual maximum precipitation (AMP) across timescales ranging from 1-hr (AMP1−hr) to 24-hr (AMP24−hr). Our analysis reveals strong relations between the magnitude of AMP and the climatological average annual precipitation (AAP), with geographic variations in the magnitude of AMP24−hr across topographic gradients not evident in AMP1−hr. Most AMP1−hr are found to be embedded within short-duration storms (>70% of AMP1−hr are embedded within 1–5 h storms), especially in regions with low AAP and in the tropical zone. Likewise, most AMP24−hr are found to be the accumulation of a very limited number of wet hours in the 24-h period (>80% of AMP24−hr are due to storms lasting <15 h) across many parts of the sampled regions, highlighting the added-value of hourly data in estimating the actual precipitation intensities. The seasonal distribution of AMP may change across different timescales at a specific location, reflecting the prevalence of different seasonal triggering mechanisms. We also find that most AMP1−hr occur preferentially in late afternoon to late evening, slightly later than the usual mid-to-late afternoon peak in the mean precipitation intensity. Finally, analysis of atmospheric instability, realized through the convection available potential energy (CAPE), reveals that CAPE is higher before AMP1−hr with respect to AMP24−hr, although the response of precipitation intensity seems to saturate at higher CAPE levels, a feature evident both in the tropical and extratropical zones. This study provides insights on climatological features of hourly precipitation extremes and how they contrast with the daily extremes examined in most studies.

Selamento superficial e formação de crosta em solos representativos do Estado da Paraíba

The formation of seal and surface crust in the soil has direct consequences for the development of the crops and environmental quality, altering the soil structure, reducing the availability of water to the plants and favoring the erosion. The objective of this study was to evaluate the changes caused by successive rainfall events on the soil surface. Four soils were evaluated: Ferralsol; Acrisol; Leptsol; Luvisol. The selection criterion was based on pedogenetic development. The experiment was conducted under simulated rainfall, in experimental plots with a useful area of 0,3481 m², uncovered soil and slope of 0.10 mm-1. The tests were performed with mean precipitation intensity of 85 mm h-1 for 75 min, applied in three consecutive events at 7 day intervals, to determine the effects of surface sealing during rainfall and crust formation after the soil drying period. The hydraulic flow variables, the soil losses (PSi), soil disaggregation rate in interrill (Di) and the interrill erodibility factor (Ki) were evaluated. The formation of sealing and surface crusts were observed with increase of the flow velocity and liquid discharge, and the decrease of water sheet height, as well as in the changes in PSi, Di and Ki, being in the first event of simulated rainfall the greater contribution to formation of superficial crusting. TX showed the most stable after the successive events of simulated rainfall, even though the surface roughness was modified, did not present significant changes in the soil losses, disaggregation rate and soil interill erodibility. Keywords: Interill erosion, semiarid, sediment concentration, surface roughness, hydraulic flow variables.

The tri-pole relation among daily mean temperature, atmospheric moisture and precipitation intensity over China

Abstract Governed by the Clausius-Clapeyron (CC) equation, daily mean temperature (Tm) and precipitation extremes would be theoretically linked by atmospheric moisture. However, precipitation extremes cannot systematically follow the CC rate of 7% per warming degree, due to moisture limitations. In this study, the observational tri-pole relation among Tm, atmospheric moisture and precipitation intensity over China have been investigated. The results indicate that atmospheric moisture (specific humidity and dew-point temperature) is positively correlated with Tm (precipitation) across four seasons at the interannual timescale. Particularly, the increase in precipitation extremes is accompanied by high atmospheric moisture, but is different in four seasons. In comparison, the year-to-year relation between Tm and atmospheric moisture is stronger than that between atmospheric moisture and precipitation. The atmospheric moisture has acted as a bridge linking Tm and precipitation extremes. Tm is highly correlated with precipitation extremes, while the relation also shows seasonal difference. The difference may be attributed to the negative scaling of daily precipitation extremes and precipitation efficiency (defined as the percentage of moisture in the air converting into precipitation) with Tm, when Tm exceeds ~25 °C.

Simulation of Climate and Weather Extreme Indices with the INM-CM5 Climate Model

The simulation of extreme weather indices with the INM-CM5 and INMCM4 climate models for modern climate which were developed in the Institute of Numerical Mathematics of Russian Academy of Sciences is considered. It is shown that the INM-CM5 model improved the simulation of almost all indices concerning temperature (especially to its minimum values) and precipitation (mean total precipitation, mean precipitation intensity) extremes and concerning consecutive dry days and consecutive wet days. At the same time, the simulation of indices connected with extreme heavy precipitation became worse. It was found that this shortcoming can be minimized by introducing the vertical mixing of horizontal wind for the large-scale condensation and deep convection.