Maximum Monthly Precipitation Research Articles

Assessment of climate simulation over the Tibetan Plateau based on high-resolution multi-RCM within CORDEX-EA-II

The climate simulation over the Tibetan Plateau (TP) remains a challenge for climate models, limiting the reliability of future climate projections over there. This study focuses on the performance of five regional climate models (RCMs) under the Coordinated Regional Climate Downscaling Experiment-East Asia (CORDEX-EA-II) in reproducing the climate over the TP for the period 1981–2015. All simulations are driven by ERA-Interim reanalysis at a resolution of 25 km (0.22°), and are evaluated against the two observation datasets (CN05 and ERA5) as well as inter-compared to identify their weaknesses and differences among them. The results show that all RCMs can capture the observed spatial distribution and annual cycle of temperature and precipitation over the TP, with overall cold and wet biases. The cold biases exhibit a clear altitude dependence, while there is no obvious relationship between precipitation biases and altitude, and most of the RCMs advance the time with the maximum monthly precipitation by 1 month over the northwestern TP. The distribution of temperature trends and the signal of elevation-dependent warming in the observation are well reproduced by most of the RCMs. Inconsistent precipitation trends are found between the two observational datasets during summer and autumn, and the simulated precipitation trends are more consistent with that in ERA5 than in CN05. Further analysis suggests that the downward shortwave radiation is the main contributor to the diverse temperature simulations among the RCMs for all seasons, and the inability of RCMs to reproduce the precipitation trends may be related to the misrepresentation of convection processes. Moreover, some of the RCMs perform better than ERA5 over the TP, demonstrating the importance of dynamical downscaling over the TP.

Long-Term Nitrogen and Phosphorus Outflow from an Instream Constructed Wetland under Precipitation Variability

In many agricultural watersheds, surface runoff often causes unwanted nitrogen (N) and phosphorus (P) losses from croplands into stream networks. When this phenomenon is pronounced, it significantly changes N and P concentrations in streams affecting aquatic ecosystems. To protect stream water quality, the installation of instream-constructed wetlands (ICWs) for treating runoff water is often reported as a low-cost alternative to conventional water treatment systems. Indeed, ICWs have the capacity to collect and temporarily retain nutrients transported from agricultural landscapes and then slowly release them into downstream networks. However, the long-term hydrologic behavior of ICWs relative to N and P outflow control is still insufficiently reported. Especially in the context of climate change, it is relevant to investigate the effect of precipitation variability on ICWs N and P outflow. This study uses the soil and water assessment tool (SWAT) model to approximate the long-term hydrologic behavior of an experimental ICW installed in a small agricultural watershed. The model was set assuming a continuous corn and soybean rotation on croplands, then a multidecadal (period 2001–2020) simulation was used to evaluate the implication of precipitation variability on total nitrogen (TN), nitrate-N (NO3-N), total P (TP), and dissolved P (DP) outflows. Results show meaningful changes in the precipitation pattern with contrasting effects on N and P outflows. While analyses show significant trends in the maximum monthly precipitation, nutrient outflows during two consecutive decades, 2001–2010 and 2011–2020, show increases of 46% for TN, and 82% for TP. At the watershed scale, month-to- month TN and TP outflows range from 24 to 810 kg N and 26 to 1358 kg P during 2011–2020, compared with 42 to 398 kg N and 40 to 566 kg P during 2001–2010. The increase in nutrient outflow is particularly pronounced for TP and DP which show significant trends and high correlations (r > 0.70) with maximum monthly precipitation. An exception is nitrate-N outflow, which counts on average for less than 5% of TN outflow but appears more affected by the timing of N fertilization in the watershed.

Enhancement of Groundwater Recharge from Wadi Al Bih Dam, UAE

Groundwater and harvested rainwater represent the only conventional freshwater resources in the United Arab Emirates (UAE). Groundwater resources in Wadi Al Bih, UAE, are sustainable due to the low exploitation rate for domestic and agricultural purposes. Thus, the groundwater depletion in this area is far less than in other parts of the country. The Wadi Al Bih area is very important for achieving water security in UAE. Therefore, the possible measures of increasing groundwater recharge (e.g., managed aquifer recharge (MAR) methods) are investigated in this paper. The available water resource data were collected, reviewed, validated, and stored in a GIS database. Then, a GIS-based water budget model (WBM) was developed to evaluate the available groundwater resources in Wadi Al Bih and recharge sources. The analyses showed that only 49% of the accumulated rainwater behind the dam is recharging the underlying aquifer. Due to the absence of any direct recharge techniques, the remaining 51% is lost by direct evaporation (15%), and as soil moisture increases in the unsaturated zone (36%), it will subsequently evaporate or percolate depending on the precipitation pattern and air temperature. The results of the WBM indicated that the freshwater resources were decreasing at an alarming rate of approximately thirty-five million cubic meters (MCM) per year until 2019. The groundwater storage and salinity were governed by the rates and patterns of precipitation. For example, the recharge resulting from the two consecutive maximum monthly precipitation events in December 2019 and January 2020 has significantly increased the fresh groundwater reserve and slightly retreated the saline/brackish water toward the shoreline. Moreover, a Mann–Kendall trend analysis was conducted to assess the influence of precipitation, temperature, and evaporation on groundwater recharge. The outcomes suggested that climate variables had a significant effect on groundwater supplies. The mitigation measures include revising groundwater withdrawal rates based on the annual recharge and enhancing recharge using different MAR techniques and dam operation plans.

Appropriated protection time and region for Qinghai–Tibet Plateau grassland

Abstract Grassland accounts for 67% of the land area in Qinghai–Tibet Plateau (QTP) to sensitive to climate. This article carried out extensive temporal–spatial variations of grassland water deficit/surplus (GWDS) and net primary productivity (NPP) of QTP grassland using meteorological data of 1981–2018. The results indicate that precipitation’s temporal variations are not related to potential evapotranspiration (PET). The maximum monthly precipitation occurs in July, while the maximum monthly PET appears in June. Precipitation is the second highest in spring when PET is the highest. The water deficit (PET-precipitation) from March to June takes up 51.4% of the total year. Therefore, droughts are more likely to happen in spring and June. This is the most important period for grassland protection. Water deficit is higher in the central and west and the highest in the northwest of QTP grasslands. This indicates the place where the droughts are more likely to occur. The grassland’s annual NPP is high in the southeastern part of QTP and low in the west. This shows the central and western parts of QTP grassland should receive more attention. The specific time and region obtained in this study are important for environmental protection policy-making and reducing grassland degradation in QTP.

新疆三种独尾草的适宜分布及其对未来气候变化的响应

PDF HTML阅读 XML下载 导出引用 引用提醒 新疆三种独尾草的适宜分布及其对未来气候变化的响应 DOI: 10.5846/stxb202110152910 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41561007，41261011）；新疆维吾尔自治区草原总站草原生态修复治理补助项目（XJCYZZ202007） Suitable distributions of three species of Eremurus in Xinjiang and their responses to future climatic changes Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:研究国内仅分布于新疆的3种短命植物阿尔泰独尾草（Eremurus altaicus）、粗柄独尾草（Eremurus inderiensis）和异翅独尾草（Eremurus anisopterus）的适宜分布及其对未来气候的可能响应，对新疆短命植物资源的分布、利用与科学保护具有重要意义。共收集了64个自然分布点，筛选了6个气候因子和2个地形因子数据，利用MaxEnt模型和地理信息系统ArcGIS软件模拟了当前气候情景下3种独尾草的生态适宜性，探讨影响3种植物分布的主导因子及其数值范围，预测3种独尾草的适宜分布对未来气候变化（2001-2040年、2041-2080年，基于温室气体中等排放情景：SSP2-4.5共享社会经济路径）的可能响应。结果表明：（1）基准气候下，3种独尾草在新疆的适宜分布存在较大差异：阿尔泰独尾草主要分布于伊犁河谷、天山北麓、阿尔泰山中段和准噶尔西部山地；两种沙生独尾草均分布于天山中段的绿洲-荒漠区过渡带，古尔班通古特沙漠西南部沙地；（2）最干月降水量（1-25mm）主要限制了阿尔泰独尾草的适宜分布；温度季节性变动指数（1150-1672）主要限制了两种沙生独尾草的适宜分布；（3）2001-2040年和2041-2080年，3种独尾草的适宜分布整体均呈缩减趋势：阿尔泰独尾草向天山北麓和准噶尔西部山地略微缩减；粗柄独尾草和异翅独尾草向古尔班通古特沙漠南缘略微缩减。 Abstract:In China,Eremurus altaicus,Eremurus inderiensis and Eremurus anisopterus are only distributed in Xinjiang.It is of great significance to the distribution, utilization and scientific protection of ephemeral plant resources in Xinjiang to study the suitable distributions of Eremurus altaicus, Eremurus inderiensis and Eremurus anisopterus and their possible responses to future climatic changes. A total of 64 natural distribution sites, 6 climate factors and 2 topographic factors were collected in this study. MaxEnt model and ArcGIS software were used to simulate the ecological suitability of the three species of Eremurus under current climate scenario. To investigate the dominant factors influencing the distribution of the three species and their numerical ranges, and to predict the possible responses of the suitable distribution of the three species to future climatic changes (2001-2040、2041-2080,the society is a medium greenhouse gas emission scenario:based on SSP2-4.5 shard socio-economic path).The research results show that:(1) Under the basic climate, there is great differences in the suitable distribution of the three species in Xinjiang:Eremurus altaicus is mainly distributed in Ili River Valley, northern foot of the Tianshan Mountain, middle of the Altai Mountain and the Western Junggar Mountains. Both of psammophytes are distributed in the oasis-desert transition zone in the central Tianshan Mountains and the sandy land in the southwest of Gurbantunggut Desert; (2) The maximum monthly precipitation (1-25mm) mainly limited the suitable distribution of Eremurus altaicus, the temperature seasonal variation index (1150-1672) mainly limited the suitable distribution of Eremurus inderiensis and Eremurus anisopterus; (3) During 2001-2040 and 2041-2080, the suitable distribution of the three species of Eremurus show a decreasing trend as a whole:the Eremurus altaicus is reduced slightly towards the northern foot of the Tianshan Mountain and the Western Junggar Mountains; Eremurus inderiensis and Eremurus anisopterus shrink slightly towards the southern edge of the Gurbantunggut Desert. 参考文献 相似文献 引证文献

Trend Analysis of Precipitation Datas Observed for Many Years (1970-2019) in Niğde Center and Ulukisla District of Turkey

This research situated in Turkey's Anatolia region, Nigde center and Ulukışla district were conducted. Long annual precipitation data were subjected to statistical analysis on a monthly basis. Within the scope of the research, 50 years and 600 months long total monthly precipitation and maximum monthly precipitation values between 1970-2019 were examined. Spearman Rho test, Mann-Kendall Correlation test and Sen's slope methods were used in trend analysis. According to the total precipitation values; The highest total precipitation was observed in 2009 as 460,8 mm. The lowest total precipitation was calculated as 192,9 mm in 1973. Total rainfall average was calculated as 120,5 mm in spring and 98,4 mm in winter. The total rainfall average in the summer months was determined as 38,2 mm. In general, the average total precipitation for many years in the center of Niğde was found to be 325,9 mm. The highest total precipitation in Ulukışla district was determined as 428,2 mm in 1997. The lowest total precipitation for many years was 182,1 mm in 1989. The average total precipitation for long years was determined to be 318,5 mm. Total rainfall average was determined as 132,8 mm in spring and 80,7 mm in winter. Total rainfall average in the summer months was calculated as 42,4 mm. According to the trend analysis results; It is concluded that there is no significant trend in total precipitation values for many years in the center of Niğde and Ulukışla district. The maximum annual precipitation in the center of Niğde is calculated as 10,5 mm and in the Ulukışla district as 10,3 mm. The average maximum precipitation in spring was found to be 13,2 mm in the center of Niğde and 14 mm in the town of Ulukışla. The highest maximum precipitation was observed in 1978 in Niğde city center as 27 mm in winter. The highest maximum precipitation in Ulukışla district was found as 33,8 mm in 2003. According to the long annual maximum precipitation values; It has been determined that there is an increasing trend in Niğde center in the general average of winter, summer and all months. It is observed that there is an increasing trend in the Ulukışla district in the winter months and in general average

Estimate Probability Distribution of Monthly Maximum Daily Rainfall of Iraq

Precipitation is very important to humankind, as it represents a pure source of water beside the earth. Therefore, many researchers are interested in rain. In this study, the monthly data for the amount of rainfall for fourteen stations (Baghdad, Basra, Diwania, Kirkuk, Smaw, Tikirit, Rutb, Mousl, Alialgarbi, talafer, Kut, samara, Hali, and Nasiriya) in Iraq was collected from the General Authority for Meteorology and Seismic Monitoring, the maximum understanding of precipitation behavior, was tested the data according to tests Kolmogorov-Smirnov. Anderson, Chi-Squared, The 20 probability distributions were applied to find the appropriate distribution of this data. Was found that the Mosul station has the largest amount of rain from other stations and that this data follows the distribution Log-Gamma Which is considered the best distribution according to the tests, while Basra station takes to distribute Burr (4p), while, Rutba Station takes logistical distribution while Baghdad Log-Pearson 3 Station, despite the maximum monthly precipitation, Baghdad has more statistics than Rutba.

Characteristics of Extreme Value Statistics of Annual Maximum Monthly Precipitation in East Asia Calculated Using an Earth System Model of Intermediate Complexity

Extreme precipitation is no longer stationary under a changing climate due to the increase in greenhouse gas emissions. Nonstationarity must be considered when realistically estimating the amount of extreme precipitation for future prevention and mitigation. Extreme precipitation with a certain return level is usually estimated using extreme value analysis under a stationary climate assumption without evidence. In this study, the characteristics of extreme value statistics of annual maximum monthly precipitation in East Asia were evaluated using a nonstationary historical climate simulation with an Earth system model of intermediate complexity, capable of long-term integration over 12,000 years (i.e., the Holocene). The climatological means of the annual maximum monthly precipitation for each 100-year interval had nonstationary time series, and the ratios of the largest annual maximum monthly precipitation to the climatological mean had nonstationary time series with large spike variations. The extreme value analysis revealed that the annual maximum monthly precipitation with a return level of 100 years estimated for each 100-year interval also presented a nonstationary time series which was normally distributed and not autocorrelated, even with the preceding and following 100-year interval (lag 1). Wavelet analysis of this time series showed that significant periodicity was only detected in confined areas of the time–frequency space.

Mapping the risk zoning of storm flood disaster based on heterogeneous data and a machine learning algorithm in Xinjiang, China

AbstractMapping flood risk zone is an essential task in the arid region for sustainable water resources management. Due to the lack of hydrological and meteorological information and disaster event inventory in Xinjiang, China, storm flood disaster (SFD) risk zoning is an effective technique in investigating the potential impact of SFD. In this study, the statistics about natural, social, and risk related to SFD are collated. With the help of the compiled inventory data, a disaster risk assessment model for storm flood is proposed for the Xinjiang region based on the random forest (RF) algorithm. Randomly selected negative and positive samples from the historical SFD locations are composed of five different total samples. The overall prediction accuracy of the five sample groups attained 83.48%, indicating that the proposed RF model can well capture the spatial distribution of SFD in Xinjiang. It should also be noted that the spatial heterogeneity and complexity of SFD had a significant effect on its spatial distribution in Xinjiang. There are spatial distribution characteristics of lowland plains and high plateaus; the main mountainous regions, plains in the middle‐lower reaches of major rivers, and areas surrounding major lakes are prone to flooding. The variable importance RF indicates that the disaster risk is mainly affected by the following factors, including hazard factors, catastrophic intensity, population density, as well as economic development in the affected area. Besides, latitude, longitude, agricultural acreage, road density, distance from rivers, and the maximum monthly precipitation account for most of the increase in storm flooding disasters, and they are the main triggering point for SFD in Xinjiang. The proposed model provides some insight into the disaster in the mountainous region, and gives useful guidance for the national macro‐control of flood prevention and disaster reduction.

Impact of precipitation disparity on groundwater fluctuation in a semi-arid region (Vellore district) of southern India using geospatial techniques.

In the present study, impact of precipitation disparity on groundwater level fluctuation was carried out in Vellore district, Tamil Nadu, India, using geospatial techniques. There are five rain gauge stations in the study area in which three rain gauge stations, namely Alangayam, Jolarpettai and Pernampet, receive more precipitation when compared with the average annual precipitation of Tamil Nadu state (920 mm). The other two stations, namely Madanur and Natrampalli, receive less than 920 mm of precipitation annually. The overall average annual precipitation of the study area is 913.6 mm. More than 100 mm precipitation is received in all the five rain gauge stations during southwest (SW) and northeast (NE) monsoon seasons. The maximum monthly precipitation is usually recorded during the month of November and the minimum precipitation is recorded during June. The post-monsoon precipitation is around 10.8 mm, which is almost negligible in the study area. The contribution of precipitation by various seasons is in the following sequence: Southwest monsoon > Northeast monsoon > Pre-monsoon > Post-monsoon. The spatial disparity study indicates that the intensity of average annual, pre-monsoon and post-monsoon precipitations increase towards west in the study area. The intensity of precipitation is more in the northern part during SW monsoon season, whereas the intensity is more in the southern part during NE monsoon season. The spatial disparity analysis of groundwater fluctuation shows that the depth of groundwater (below ground level) increases towards west during all the monsoon seasons. The minimum, mean and maximum depths of occurrence of groundwater in this region are, respectively, 1.6, 9.6 and 21.15 m. Declining trend in the regional groundwater level is observed from December to June because of less precipitation during non-monsoon season. However, the monsoon (both SW and NE monsoon) precipitation recharges the groundwater from June to December to reach the maximum in the month of December.

ClimCKmap, a spatially, temporally and climatically explicit distribution database for the Italian fauna

Understanding and counteracting biodiversity losses requires quantitative knowledge on species distribution and abundance across space and time, as well as integrated and interoperable information on climate conditions and climatic changes. In this paper we developed a new biodiversity-climate database for Italy, ClimCKmap, based on the critical analysis, quality estimation and subsequent integration of the CKmap database with several high-resolution climate datasets. The original database was quality-checked for errors in toponym, species name and dating; the retained records were georeferenced and their distribution polygonised via Voronoi tessellation. We then integrated the species distribution information with several high-resolution climatic datasets: average monthly minimum and maximum temperature and total monthly precipitation were reconstructed for each Voronoi cell and year. The resulting database contains 268,977 occurrence records from 8,445 binomials and 16,332 localities, dating between 1680 and 2006 CE. This dataset, fully available at https://doi.org/10.6084/m9.figshare.7906739.v4 and http://hdl.handle.net/21.11125/a91f85cb-befd-4e14-8e83-24f17c4a0491, represents the largest, fully quality-checked, spatially, temporally and climatically explicit distribution database ever assembled for the Italian fauna, now ready for scientific exploitation.

Observed changes in extreme precipitation in Poland: 1991\u20132015 versus 1961\u20131990

Several episodes of extreme precipitation excess and extreme precipitation deficit, with considerable economic and social impacts, have occurred in Europe and in Poland in the last decades. However, the changes of related indices exhibit complex variability. This paper analyses changes in indices related to observed abundance and deficit of precipitated water in Poland. Among studied indices are maximum seasonal 24-h precipitation for the winter half-year (Oct.–March) and the summer half-year (Apr.–Sept.), maximum 5-day precipitation, maximum monthly precipitation and number of days with intense or very intense precipitation (respectively, in excess of 10 mm or 20 mm per day). Also, the warm-seasonal maximum number of consecutive dry days (longest period with daily precipitation below 1 mm) was examined. Analysis of precipitation extremes showed that daily maximum precipitation for the summer half-year increased for many stations, and increases during the summer half-year are more numerous than those in the winter half-year. Also, analysis of 5-day and monthly precipitation sums show increases for many stations. Number of days with intense precipitation increases especially in the north-western part of Poland. The number of consecutive dry days is getting higher for many stations in the summer half-year. Comparison of these two periods: colder 1961–1990 and warmer 1991–2015, revealed that during last 25 years most of statistical indices, such as 25th and 75th percentiles, median, mean and maximum are higher. However, many changes discussed in this paper are weak and statistically insignificant. The findings reported in this paper challenge results based on earlier data that do not include 2007–2015.

Uncertainties in observations and climate projections for the North East India

The Northeast-India has undergone many changes in climatic-vegetation related issues in the last few decades due to increased human activities. However, lack of observations makes it difficult to ascertain the climate change. The study involves the mean, seasonal cycle, trend and extreme-month analysis for summer-monsoon and winter seasons of observed climate data from Indian Meteorological Department (1°×1°) and Aphrodite & CRU-reanalysis (both 0.5°×0.5°), and five regional-climate-model simulations (LMDZ, MPI, GFDL, CNRM and ACCESS) data from AR5/CORDEX-South-Asia (0.5°×0.5°). Long-term (1970–2005) observed, minimum and maximum monthly temperature and precipitation, and the corresponding CORDEX-South-Asia data for historical (1970–2005) and future-projections of RCP4.5 (2011–2060) have been analyzed for long-term trends. A large spread is found across the models in spatial distributions of various mean maximum/minimum climate statistics, though models capture a similar trend in the corresponding area-averaged seasonal cycles qualitatively. Our observational analysis broadly suggests that there is no significant trend in rainfall. Significant trends are observed in the area-averaged minimum temperature during winter. All the CORDEX-South-Asia simulations for the future project either a decreasing insignificant trend in seasonal precipitation, but increasing trend for both seasonal maximum and minimum temperature over the northeast India. The frequency of extreme monthly maximum and minimum temperature are projected to increase. It is not clear from future projections how the extreme rainfall months during JJAS may change. The results show the uncertainty exists in the CORDEX-South-Asia model projections over the region in spite of the relatively high resolution.

Estacionalidad Reproductiva de la Hembra Bufalina (Bubalus bubalis)

El objetivo de este estudio fue describir la estacionalidad reproductiva en la búfala en condiciones del trópico bajo en el Magdalena Medio colombiano y su relación con parámetros climáticos. Se evaluaron registros de nacimientos de 30 571 animales desde 1970 a 2013 del Fondo Bufalero del Centro y los datos hidrometeorológicos de la estación Puerto Berrio-Antioquia, Colombia. Para el análisis, se utilizó una regresión de Poisson y una correlación de Spearman para determinar la relación entre la época de la concepción y nacimientos, expresados en porcentajes, con las siguientes variables hidrometeorológicas: valores mínimos, medios y máximos mensuales de caudales de ríos (m3/seg), valores medios, máximo mensuales de niveles de los ríos (cm), valores totales mensuales de brillo solar (oC), valores mínimos, medios y máximos mensuales de temperatura (oC), valores medios mensuales de humedad relativa (%), valores máximos mensuales de precipitación (mm en 24 h), valores totales mensuales de precipitación (mm) y el índice de temperatura y humedad (ITH). El porcentaje de concepción fue mayor durante el primer trimestre del año y la mayor probabilidad de partos se presentó durante el segundo semestre. Se encontró una correlación negativa (p<0.05) entre la concepción y los valores máximos mensuales de caudales de río, valores media mínimos mensuales y mínimos mensuales de temperatura, así como una correlación positiva con los valores medios mensuales de humedad relativa y los valores máximos mensuales de precipitación. Se encontró una relación negativa entre el ITH y los nacimientos y la concepción. Los resultados demuestran que el búfalo en Colombia presenta ciclos estrales durante todo el año, con una estacionalidad relacionada con la temperatura ambiente, el régimen de lluvias y la humedad relativa.

Research on the Detail Time of Grassland Water Deficit for the Qinghai-Tibetan Plateau

The detail variations of precipitation, potential evapotranspiration (PET) impacts the terrestrial ecosystem.The grassland water deficit or surplus status (GWDS) from 1961 to 2010 were systemically studied for the Qinghai-Tibetan Plateau (QTP) using daily data of all meteorological stations. The results indicated that the temporal variations of precipitation were not corresponding to those of PET in a year. The maximum monthly precipitation occurred in July, while the maximum monthly PET appeared in June, the spring precipitation was ranked the second, but its PET was ranked the first in a year. The total water deficit (PET-precipitation) from March to June was more, 51.4 % of the total annual value. Therefore, the drought more frequently occurred in Spring and June in the QTP. The grassland can be protected in a year, especially in Spring and June.

Analysis of Precipitation Projections over the Climate Gradient of the Arkansas Red River Basin

AbstractIncreases in the frequency and intensity of extreme precipitation are projected for most U.S. regions under climate change. There is a high degree of uncertainty, however, in precipitation regime changes across the large precipitation gradient of the Arkansas Red River basin (ARRB). The authors analyzed future precipitation regimes using two statistical downscaling datasets based on the scenarios from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Seasonal precipitation in low-to-high quantiles was calculated and compared for the southern ARRB where the downscaled data were available. The results showed a generally comparable shift in precipitation patterns and amounts between the two datasets. However, some spatial variation of precipitation amount change exists, and the direction of change could be opposite for the summer. Both datasets showed that the top 10% of monthly precipitation amounts could increase for the southern ARRB, mostly ranging from 5–10 mm month−1 for the early part of the century (2010–39) to 15–30 mm month−1 for the midcentury (2040–69) as compared with the historical period (1968–97). The maximum monthly precipitation could increase by up to 150 mm in both datasets by the midcentury. Precipitation was projected to increase regardless of quantile during both winter and spring but tended to decrease during summer and autumn. More-frequent and higher-intensity rainfall events were expected for the eastern part of the basin, and longer and drier dry periods were expected for the western basin. Conservation strategies and sustainable water management should consider the regional differences in the projected changes in precipitation regimes for the basin under climate change.

Threshold-Based Hybrid Data Mining Method for Long-Term Maximum Precipitation Forecasting

In this paper, the application of two data mining techniques (decision tree and association rules) was offered to discover affiliation between several thresholds of monthly precipitation (MP) values of Tabriz and Kermanshah synoptic stations (located in Iran) and de-trend sea surface temperature (SST) of the Black, Mediterranean and Red Seas. Two major steps of the modeling in this study were the classification of de-trend SST data and selecting the most effective groups and extracting hidden predictive information involved in the data. The decision tree techniques which can identify the good traits from a data set for the classification purpose were used for classification and selecting the most effective groups and association rules were employed to extract the hidden predictive information from the large observed data. To examine the accuracy of the rules, confidence and lift measures were calculated and compared for different thresholds of precipitation at different lag times. The computed measures confirm reliable performance of the proposed hybrid data mining method to forecast extreme precipitation events considering higher threshold values and the results show a relative correlation between the Mediterranean, Black and Red Sea de-trend SSTs and maximum MP of Tabriz and Kermanshah synoptic stations so that the confidence between the threshold of 35% of MP values and the de-trend SST of seas is higher than 70 for Tabriz and 60% for Kermanshah. It was also shown that the geographical location of stations and the distribution of precipitation data affect the measures of the rules and forecasting outcomes.

Analysis of precipitation for the past 20th century and its multi-decadal oscillation: a case study of Bankura Town, Bankura, West Bengal

The present investigation is based on maximum monthly precipitation for the past 20th century of Bankura Town, of West Bengal. The analysis was based on 100 years time series of maximum monthly rainfall data of Bankura Town. First of all, data sets were analysed as a whole and in a separated part of it using Linear Regression model. We have found that there were no such good relationships or trends do exist at all. But using 30 years of moving average, we have found oscillatory trends within this data, which seems to be very much effective in understanding and dealing with precipitation trends. This study concluded that precipitation trends oscillatory must be used for analyse of the past.

Dynamical downscaling with COSMO and COSMO-CLM in the Sino-Mongolian Altai region

For the first time, regional atmospheric simulations with spatial resolution down to 6 km have been performed in the Sino-Mongolian Altai region using the COSMO weather forecast and regional climate model. Two 5-year periods (1979–1982 and 2008–2012) have been simulated for a first evaluation of the model in this special region. The added value of a dynamical downscaling with the COSMO regional climate model CCLM towards the driving ERA-Interim reanalysis is investigated by comparison with weather station observations. In the mountainous region, the CCLM simulation much better relates to the observed monthly mean 2 m temperature and maximum monthly precipitation sums in summer than ERA-Interim. In addition, the intensity distribution of sub-daily precipitation amounts becomes more realistic with increasing altitude. CCLM does, however, overestimate convection in the mountains and accordingly simulates too much precipitation. Moreover, wintertime near-surface temperature inversions are underrated in the southern near-Gobi area, which leads to too high 2 m temperatures in that region. To examine the ability of the COSMO model to reproduce the vertical thermodynamic structure of the troposphere, additional simulations with the weather forecast version of COSMO were performed for July 2013 and compared to radiosonde measurements of the WATERCOPE field experiment in this region. The results indicate that the COSMO model is quite capable of qualitatively simulating a range of features of the local tropospheric stratification. Mean differences between observed and simulated dew point and temperature profiles were in the range of only to 1–2 °C in the lower troposphere.

Disturbance in Georgia salt marshes: variation across space and time

AbstractWe documented the frequency and effect on live biomass of five different types of disturbance over 14 years in creekbank and mid‐marsh zones of eight salt marshes dominated by Spartina alterniflora in Georgia, USA. Wrack (floating debris) and creekbank slumping were the most common disturbances at the creekbank, and snails were the most common disturbance agent in the mid‐marsh. Disturbance frequency varied among sites due to differences in plot elevation and landscape position. Wrack disturbance at the creekbank was positively correlated with plot elevation, and both initial slumping and terminal slumping of creekbank plots were negatively correlated with plot elevation. Wrack disturbance at the creekbank and snail disturbance in the mid‐marsh were also most common at barrier island vs. interior marshes. Disturbance varied up to 14‐fold among years. Wrack disturbance at the creekbank was negatively correlated with river discharge and sea level, and initial slumping of creekbank plots was also negatively correlated with sea level. The different disturbance types varied in their effects on end‐of‐year standing plant biomass. At the creekbank, wrack disturbance reduced biomass in affected plots by ~46%, but slumping did not affect biomass until the plot was totally lost. In the mid‐marsh, slumping and wrack were not important disturbances, but snail disturbance reduced biomass in affected plots by ~70%. In addition, abiotic conditions (river discharge, maximum monthly temperature, sea level, and precipitation) strongly affected year‐to‐year variation in biomass. Across the entire landscape, fewer than a quarter of the plots on average were disturbed, and disturbance reduced overall standing biomass by ~18% in the creekbank zone and ~3% in the mid‐marsh zone. Our results indicate that wrack has fairly strong effects on end‐of‐year biomass at the creekbank. Overall, however, variation in abiotic conditions among years had stronger effects on end‐of‐year standing biomass in both marsh zones than did disturbance.