Maximum Daily Precipitation Research Articles

Changes in the temperature and precipitation extremes in China during 1961–2015

Based on daily maximum temperature (Tmax), daily minimum temperature (Tmin) and daily precipitation collected from 1867 meteorological stations in China from 1961 to 2015, the spatiotemporal variations in temperature and precipitation extremes and their associations with large-scale atmospheric and oceanic circulation patterns were analyzed using linear trend analysis, Pearson correlation analysis and Mann-Kendall method. Results indicate that both the maximum Tmin (TNx) and the minimum Tmin (TNn) had increased significantly at rates of 0–0.5 °C and 0.2–1.0 °C per decade respectively in most of China, whereas the trends in the maximum Tmax (TXx) and the minimum Tmax (TXn) were not significant, resulting in a decrease of diurnal temperature range (DTR) at rates of 0–0.7 °C per decade in most of northeastern China, northern China and western China. The percentage changes in TXn and TNn were much higher than those of TXx and TNx. For precipitation indices, simple daily intensity index (SDII) and extremely wet-day precipitation (R99p) had increased at rates of 0.10 mm/day and 2.6 mm per decade respectively, but the trends of maximum 1-day precipitation (Rx1day), maximum 5-day precipitation (Rx5day) and total wet-day precipitation (PRCPTOT) were not significant in China. The spatial trends of five precipitation indices were also not significant in almost the whole of China. Higher percentage changes of precipitation indices were mainly appeared in western China. Most of climatic indices had positive correlation with Atlantic multidecadal oscillation (AMO) and negative correlation with East Atlantic/Western Russia (EA/WR). The variations of TXx and TNx were more related to the variability of AMO and EA/WR in China, and those of TXn and TNn were more associated with the Arctic oscillation (AO) in northeastern China, northern China and northern Xinjiang. The variations of precipitation indices were not significantly related to the circulation patterns in the vast majority of China.

Trends, Variability, and Seasonality of Maximum Annual Daily Precipitation in the Upper Vistula Basin, Poland

The aim of this study was to detect trends in maximum annual daily precipitation in the Upper Vistula Basin. We analyzed data from 51 weather stations between 1971 and 2014. Then we used the Mann–Kendall test to detect monotonical trends of the precipitation for three significance levels: 1, 5, and 10%. Our analysis of weather conditions helped us describe the mechanism behind the formation of maximum annual daily precipitation. To analyze precipitation seasonality, we also used Colwell indices. Our study identified a significant trend of the highest daily precipitation for the assumed significance levels (0.01, 0.05, 0.1) for 22% of the investigated weather stations at different elevations. The significant trends found were positive and an increase in precipitation is expected. From 1971 to 2014, the maximum daily total precipitation most often occurred in the summer half-year, i.e., from May until September. These months included a total of 88% of days with the highest daily precipitation. The predictability index for the highest total precipitation within the area was high and exceeded 5%. It was markedly affected by the coefficient of constancy (C) and to a lesser degree by the seasonality index (M). Our analysis demonstrated a convergence of the Colwell indices and frequency of cyclonic situation and, therefore, confirmed their usability in the analysis of precipitation seasonality.

Assessment of future changes in Southeast Asian precipitation using the NASA Earth Exchange Global Daily Downscaled Projections data set

Extreme precipitation and associated flooding cause severe damage to society and the environment. Future climate projections suggest an intensification of precipitation extremes in many regions. However, there is an increasing need for climate change impact assessment at higher spatial resolution, particularly for regions with complex geography such as Southeast Asia (SEA). In this study, we analysed the NASA Earth Exchange 0.25° resolution daily precipitation projections from an ensemble of 20 climate models under two emission scenarios RCP4.5 and RCP8.5. The variability in future precipitation projections is analysed and quantified for six geographical subregions, two climatological regions (wet and dry), and the low‐elevation coastal zones in SEA. Various aspects of precipitation structure are studied using indices that characterize precipitation amount, number of heavy precipitation days, extreme precipitation amount, and maximum daily precipitation at annual and seasonal scales. The results show substantial increases in mean and extreme precipitation in many parts of SEA by the end of the 21st century under both emission scenarios, thus increasing the region's vulnerability to precipitation‐driven hazards. The projected centennial increase in total annual precipitation relative to the baseline period of 1970–1999 when averaged over all land grid cells is about 15% under RCP8.5 scenario, with larger values (∼20%) over mainland SEA and Philippines and smaller values (∼6%) in Java island. The projected changes in extreme precipitation are stronger compared to the total annual precipitation under both emission scenarios. The New Guinea and Java regions show the largest and smallest increases in annual maximum daily precipitation, with ensemble mean values of 30 and 17%, respectively, under RCP8.5 scenario. The results also reveal large inter‐model spread in projected changes, particularly during boreal winter and summer months.

Changing seasonality of moderate and extreme precipitation events in the Alps

Abstract. The intensity of precipitation events is expected to increase in the future. The rate of increase depends on the strength or rarity of the events; very strong and rare events tend to follow the Clausius–Clapeyron relation, whereas weaker events or precipitation averages increase at a smaller rate than expected from the Clausius–Clapeyron relation. An often overlooked aspect is seasonal occurrence of such events, which might change in the future. To address the impact of seasonality, we use a large ensemble of regional and global climate model simulations, comprising tens of thousands of model years of daily temperature and precipitation for the past, present, and future. In order to make the data comparable, they are quantile mapped to observation-based time series representative of the Aare catchment in Switzerland. Model simulations show no increase in annual maximum 1-day precipitation events (Rx1day) over the last 400 years and an increase of 10 %–20 % until the end of the century for a strong (RCP8.5) forcing scenario. This fits with a Clausius–Clapeyron scaling of temperature at the event day, which increases less than annual mean temperature. An important reason for this is a shift in seasonality. Rx1day events become less frequent in late summer and more frequent in early summer and early autumn, when it is cooler. The seasonality shift is shown to be related to summer drying. Models with decreasing annual mean or summer mean precipitation show this behaviour more strongly. The highest Rx1day per decade, in contrast, shows no change in seasonality in the future. This discrepancy implies that decadal-scale extremes are thermodynamically limited; conditions conducive to strong events still occur during the hottest time of the year on a decadal scale. In contrast, Rx1day events are also limited by other factors. Conducive conditions are not reached every summer in the present, and even less so in the future. Results suggest that changes in the seasonal cycle need to be accounted for when preparing for moderately extreme precipitation events and assessing their socio-economic impacts.

Assessing the Robustness of Future Extreme Precipitation Intensification in the CMIP5 Ensemble

AbstractA warming climate is expected to intensify extreme precipitation, and climate models project a general intensification of annual extreme precipitation in most regions of the globe throughout the twenty-first century. We investigate the robustness of this future intensification over land across different models, regions, and seasons and evaluate the role of model interdependencies in the CMIP5 ensemble. Strong similarities in extreme precipitation changes are found between models that share atmospheric physics, turning an ensemble of 27 models into around 14 projections. We find that future annual extreme precipitation intensity increases in the majority of models and in the majority of land grid cells, from the driest to the wettest regions, as defined by each model’s precipitation climatology. The intermodel spread is generally larger over wet than over dry regions, smaller in the dry season compared to the wet season and at the annual scale, and largely reduced in extratropical compared to tropical regions and at the global scale. For each model, the future increase in annual and seasonal maximum daily precipitation amounts exceeds the range of simulated internal variability in the majority of land grid cells. At both annual and seasonal scales, however, there are a few regions where the change is still within the background climate noise, but their size and location differ between models. In extratropical regions, the signal-to-noise ratio of projected changes in extreme precipitation is particularly robust across models because of a similar change and background climate noise, whereas projected changes are less robust in the tropics.

Extreme temperature and precipitation response to solar dimming and stratospheric aerosol geoengineering

Abstract. We examine extreme temperature and precipitation under two potential geoengineering methods forming part of the Geoengineering Model Intercomparison Project (GeoMIP). The solar dimming experiment G1 is designed to completely offset the global mean radiative forcing due to a CO2-quadrupling experiment (abrupt4 × CO2), while in GeoMIP experiment G4, the radiative forcing due to the representative concentration pathway 4.5 (RCP4.5) scenario is partly offset by a simulated layer of aerosols in the stratosphere. Both G1 and G4 geoengineering simulations lead to lower minimum temperatures (TNn) at higher latitudes and on land, primarily through feedback effects involving high-latitude processes such as snow cover, sea ice and soil moisture. There is larger cooling of TNn and maximum temperatures (TXx) over land compared with oceans, and the land–sea cooling contrast is larger for TXx than TNn. Maximum 5-day precipitation (Rx5day) increases over subtropical oceans, whereas warm spells (WSDI) decrease markedly in the tropics, and the number of consecutive dry days (CDDs) decreases in most deserts. The precipitation during the tropical cyclone (hurricane) seasons becomes less intense, whilst the remainder of the year becomes wetter. Stratospheric aerosol injection is more effective than solar dimming in moderating extreme precipitation (and flooding). Despite the magnitude of the radiative forcing applied in G1 being ∼ 7.7 times larger than in G4 and despite differences in the aerosol chemistry and transport schemes amongst the models, the two types of geoengineering show similar spatial patterns in normalized differences in extreme temperatures changes. Large differences mainly occur at northern high latitudes, where stratospheric aerosol injection more effectively reduces TNn and TXx. While the pattern of normalized differences in extreme precipitation is more complex than that of extreme temperatures, generally stratospheric aerosol injection is more effective in reducing tropical Rx5day, while solar dimming is more effective over extra-tropical regions.

The responses of precipitation and streamflow to recent climate variations in the frigid and subtropical zones

Abstract Extreme hydrological events have occurred in many climate zones in recent decades. Most importantly, the water distribution in hydrological components has changed with apparent variations in climate. The associated impact on water resources is of concern because an understanding of the hydrological response mechanism is necessary for human survival. In this study, we compare precipitation and streamflow responses to climate variations in two different climate zones. Continental-scale frigid zone (CSFZ) data were collected from Russia, while island-scale subtropical zone (ISSZ) data were collected from Taiwan. The results show that the teleconnection of the precipitation between the ISSZ and CSFZ is subtle and is linked to global atmospheric conditions. The daily maximum precipitation and the duration without precipitation increased in both the CSFZ and the ISSZ. The streamflow response became more extreme in the ISSZ and was associated with pronounced dry and wet seasons. In contrast, a rise in winter temperatures has led to more uniform streamflow and extreme hydrological situations have become less frequent. The responses of streamflow to recent climate variations in the CSFZ and ISSZ are different. Precipitation and temperature are driving forces for the change in streamflow in the CSFZ while precipitation is for the ISSZ.

Rearing, bird type and pre-slaughter transport conditions I. Effect on dead on arrival

The transport of broilers to slaughter normally results in a small percentage of dead on arrival (DoA) but little is known about the effects of flock thinning or bird weight. A multivariable linear model was used to analyse the incidence of DoA over one year in 1,856 flocks of Ross broilers (9,188 shipments). Each flock was categorized according to broiler type (yellow-skinned females and males, white-skinned females and males and roaster females) and thinning (birds transported after thinning, remaining birds after thinning and non-thinned flocks), in addition to transport distance, waiting time, maximum and minimum daily temperatures, precipitation and maximum wind speed. The overall percentage of DoA was 0.187%. The effect of the daily maximum outside temperature on DoA was quadratic with minimum DoA at 21.5ºC. Arrival time to the slaughterhouse and waiting time increased DoA by 0.0044% and 0.0021% for every 60 min increase, respectively. DoA were higher in males (which were heavier than females), and in the flocks that were previously thinned. An interaction between thinning and bird type was found, so that DoA were higher in previously thinned flocks of male broilers and roaster females. Despite the high incidence of thinning and larger bird weight, the percentage of DoA was comparable to previous studies. This research provides one of the largest detailed analyses of DoA in commercial broiler production in the Iberian Peninsula. The models described allow to quantify how increases in temperature, transport distance, waiting time, bird weight and the practise of thinning can all increase broiler mortality.

Regional approach for the analysis of annual maximum daily precipitation in northern Morocco

Abstract Information on extreme rainfall frequencies is required for Urban Drainage (UD) networks design. In this paper, the Regional Frequency Analysis (RFA), based on the L-moments, is used to: (i) analyze the trend of Annual Maximum Precipitation (AMP) over two analysis periods (1970–1989 and 1990–2015), (ii) estimate the regional Intensity-Duration-Frequency (IDF) curves of northern Morocco and (iii) assess the impact of the changes in rainfall intensities on the UD networks design during analysis periods. In reference to Hosking & Wallis (1997) and Alila, (1999), the Generalized Extreme Value (GEV) distribution has been used as a regional distribution to estimate regional quantiles for the analysis periods (1970–1999 and 1990–2015). The results show an increase up to 9% for quantiles used in UD networks design.

How have daily climate extremes changed in the recent past over northeastern Argentina?

Abstract Changes in climate extremes affect socioeconomics and natural systems in northeastern Argentina (NEA) and may increase its vulnerability leading to unprecedented disasters. This study investigates the long-term changes and interannual variability of daily temperature and precipitation climate extremes and assesses to what extent global reanalyses reproduce the observed variability in the recent past. Datasets include quality-controlled observations (1963–2013) and ERA-Interim and NCEP2 reanalyses (1979–2011). Climate extremes are characterized spatially and temporally by 15 indices proposed by the Expert Team on Climate Change Detection and Indices. The leading modes of the area-averaged index time series were obtained by means of a Singular Spectrum Analysis, while the spatial distribution of mean changes was estimated by fitting nonparametric linear trends to each index time series. The results show that temperature extremes are changing towards warmer conditions. The number of warm days has been increasing since 1990 while the number of cold days has been decreasing. Warm and cold nights show a significant signal of warming that seems to be stabilizing in recent decades. Heat waves almost double the frequency and duration of cold waves, and the duration of heat waves increased while cold spells decreased in last decades. Longer heat waves are related to longer dry spells. On the other hand, the number of frost days remained stable although they exhibit high interannual and decadal variability. As well, intense precipitation events in most of the region increased steadily since 1970. The annual maximum amount of 1-day and 5-day precipitation events increased from the 1970s to the 2000s, stabilizing in recent years. The ERA-Interim and NCEP2 reanalyses represent climate extremes with different success. ERA-Interim can recognize temperature extremes in time and space, while the older NCEP2 presents systematic positive errors and has some difficult to replicate the interannual variability of the number of summer days. Both reanalyses reproduce dry spells and the annual maximum 5-day precipitation with large biases, which are particularly noticeable at each observation station. Although reanalyses would be expected to add information for climate extremes in areas of scarce observations like northeastern Argentina, they still need to be used with great caution and only as a complement to observations, especially in studies focusing on precipitation extremes.

Atmospheric Rivers Carry Nonmonsoon Extreme Precipitation Into Nepal

AbstractAtmospheric rivers (ARs) are concentrated bands of water vapor that can cause extreme precipitation and severe flooding. Fortunately, due to their 1,500+ km spatial extent, they may also be forecasted days in advance. The goals of this study were to investigate the seasonal climatology of ARs in the Himalayan region of Nepal and to determine the role of ARs in extreme precipitation events. Using the ERA‐Interim atmospheric reanalysis, we applied a standard integrated vapor transport AR detection approach for the 35‐year period from 1979 to 2013. We detected 433 ARs, or approximately 12 ARs yearly. Along our six (0.75°) grid detection transect, ARs explain 35% of grid annual maximum daily precipitation events and 70% of grid nonmonsoon (October–May) maximum daily precipitation events. In 89% and 71% of years, at least one of the six detection grids experienced an AR‐related nonmonsoon maximum or annual maximum event, respectively. Overall, ARs explain 78% of daily precipitation totals exceeding 33 mm in the nonmonsoon season in comparison to 18% if the entire year is considered. As we show, ARs constitute a valuable new lens through which extreme precipitation in the region may be understood and forecasted. However, follow‐on integrated vapor transport analyses that more closely investigate the interaction between ARs and their synoptic‐scale environment are needed to better differentiate January and February ARs from Western Disturbances and June–September ARs from the Indian monsoon.

Spatial and Temporal Variations of Precipitation Extremes and Seasonality over China from 1961~2013

Using the 0.5° × 0.5° gridded Chinese ground precipitation dataset from 1961~2013, spatial and temporal variations in precipitation extremes, total precipitation, the seasonality of precipitation and their linkages in the context of climate change are investigated using the Mann-Kendall trend test, Pettitt change-point test and correlation analysis. The investigation focuses on four extreme indices, i.e., the annual maximum number of consecutive dry days (CDD), the annual maximum number of consecutive wet days (CWD), the annual total precipitation when daily precipitation is greater than 95th percentile (R95pTOT), and the maximum 1-day precipitation (RX1day). The results show that precipitation extremes increased in northwestern China, especially Xinjiang, Tibet and Qinghai (CWD, R95pTOT and RX1day), and scattered parts of southeastern China (R95pTOT and RX1day), but decreased over considerable parts of southwestern China (CWD) and some small parts of northern China (CWD, R95pTOT and RX1day); the spatial patterns of the trends in precipitation extremes and that of total precipitation exhibit considerable similarity over China, which indicates the close relationship between changes in precipitation extremes and total precipitation; change points are detected in different periods ranging from early 1970s to early 2000s for different regions and extreme precipitation indices, and the spatial patterns of the abrupt changes of extreme indices are similar to those of the trends in extreme indices; the concentration index (CI) is strongly positively correlated with R95pTOT and RX1day in most areas in northern China (from the northeast to the northwest) and southwestern China (including Sichuan, Chongqing Guizhou and Guangxi), which means for these regions, the temporal heterogeneity of daily precipitation over a year is dominated by heavy rainfall amounts. The seasonality index of precipitation (SI) is positively related to R95pTOT and RX1day over most areas above 30° N, indicating that heavy precipitation events have a better chance to occur in places with a strong seasonal variation in annual precipitation in these areas, but for most areas below 30° N, the positive relationship is not significant.

Spatiotemporal extremes of temperature and precipitation during 1960–2015 in the Yangtze River Basin (China) and impacts on vegetation dynamics

Recently, extreme climate variation has been studied in different parts of the world, and the present study aims to study the impacts of climate extremes on vegetation. In this study, we analyzed the spatiotemporal variations of temperature and precipitation extremes during 1960–2015 in the Yangtze River Basin (YRB) using the Mann-Kendall (MK) test with Sen’s slope estimator and kriging interpolation method based on daily precipitation (P), maximum temperature (Tmax), and minimum temperature (Tmin). We also analyzed the vegetation dynamics in the YRB during 1982–2015 using Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) datasets and investigated the relationship between temperature and precipitation extremes and NDVI using Pearson correlation coefficients. The results showed a pronounced increase in the annual mean maximum temperature (Tnav) and mean minimum temperature (Txav) at the rate of 0.23 °C/10 years and 0.15 °C/10 years, respectively, during 1960–2015. In addition, the occurrence of warm days and warm nights shows increasing trends at the rate of 1.36 days/10 years and 1.70 days/10 years, respectively, while cold days and cold nights decreased at the rate of 1.09 days/10 years and 2.69 days/10 years, respectively, during 1960–2015. The precipitation extremes, such as very wet days (R95, the 95th percentile of daily precipitation events), very wet day precipitation (R95p, the number of days with rainfall above R95), rainstorm (R50, the number of days with rainfall above 50 mm), and maximum 1-day precipitation (RX1day), all show pronounced increasing trends during 1960–2015. In general, annual mean NDVI over the whole YRB increased at the rate of 0.01/10 years during 1982–2015, with an increasing transition around 1994. Spatially, annual mean NDVI increased in the northern, eastern, and parts of southwestern YRB, while it decreased in the YRD and parts of southern YRB during 1982–2015. The correlation coefficients showed that annual mean NDVI was closely correlated with temperature extremes during 1982–2015 and 1995–2015, but no significant correlation with precipitation extremes was observed. However, the decrease in NDVI was correlated with increasing R95p and R95 during 1982–1994.

Applying Independent Component Analysis on Sentinel-2 Imagery to Characterize Geomorphological Responses to an Extreme Flood Event near the Non-Vegetated Río Colorado Terminus, Salar de Uyuni, Bolivia

In some internally-draining dryland basins, ephemeral river systems terminate at the margins of playas. Extreme floods can exert significant geomorphological impacts on the lower reaches of these river systems and the playas, including causing changes to flood extent, channel-floodplain morphology, and sediment dispersal. However, the characterization of these impacts using remote sensing approaches has been challenging owing to variable vegetation and cloud cover, as well as the commonly limited spatial and temporal resolution of data. Here, we use Sentinel-2 Multispectral Instrument (MSI) data to investigate the flood extent, flood patterns and channel-floodplain morphodynamics resulting from an extreme flood near the non-vegetated terminus of the Río Colorado, located at the margins of the world’s largest playa (Salar de Uyuni, Bolivia). Daily maximum precipitation frequency analysis based on a 42-year record of daily precipitation data (1976 through 2017) indicates that an approximately 40-year precipitation event (40.7 mm) occurred on 6 January 2017, and this was associated with an extreme flood. Sentinel-2 data acquired after this extreme flood were used to separate water bodies and land, first by using modified normalized difference water index (MNDWI), and then by subsequently applying independent component analysis (ICA) on the land section of the combined pre- and post-flood images to extract flooding areas. The area around the Río Colorado terminus system was classified into three categories: water bodies, wet land, and dry land. The results are in agreement with visual assessment, with an overall accuracy of 96% and Kappa of 0.9 for water-land classification and an overall accuracy of 83% and Kappa of 0.65 for dry land-wet land classification. The flood extent mapping revealed preferential overbank flow paths on the floodplain, which were closely related to geomorphological changes. Changes included the formation and enlargement of crevasse splays, channel avulsion, and the development of erosion cells (floodplain scour-transport-fill features). These changes were visualized by Sentinel-2 images along with WorldView satellite images. In particular, flooding enlarged existing crevasse splays and formed new ones, while channel avulsion occurred near the river’s terminus. Greater overbank flow on the floodplain led to rapid erosion cell development, with changes to channelized sections occurring as a result of adjustments in flow sources and intensity combined with the lack of vegetation on the fine-grained (predominantly silt, clay) sediments. This study has demonstrated how ICA can be implemented on Sentinel-2 imagery to characterize the impact of extreme floods on the lower Río Colorado, and the method has potential application in similar contexts in many other drylands.

Bayesian temporal density estimation with autoregressive species sampling models

We propose a novel Bayesian nonparametric (BNP) model, which is built on a class of species sampling models, for estimating density functions of temporal data. In particular, we introduce species sampling mixture models with temporal dependence. To accommodate temporal dependence, we define dependent species sampling models by modeling random support points and weights through an autoregressive model, and then we construct the mixture models based on the collection of these dependent species sampling models. We propose an algorithm to generate posterior samples and present simulation studies to compare the performance of the proposed models with competitors that are based on Dirichlet process mixture models. We apply our method to the estimation of densities for the price of apartment in Seoul, the closing price in Korea Composite Stock Price Index (KOSPI), and climate variables (daily maximum temperature and precipitation) of around the Korean peninsula.

GCM 및 상세화 기법 선정을 고려한 충주댐 유입량 기후변화 영향 평가

In this study, we evaluated the uncertainty in the process of selecting GCM and downscaling method for assessing the impact of climate change, and influence of user-centered climate change information on reproducibility of Chungju Dam inflow was analyzed. First, we selected the top 16 GCMs through the evaluation of spatio-temporal reproducibility of 29 raw GCMs using 30-year average of 10-day precipitation without any bias-correction. The climate extreme indices including annual total precipitation and annual maximum 1-day precipitation were selected as the relevant indices to the dam inflow. The Simple Quantile Mapping (SQM) downscaling method was selected through the evaluation of reproducibility of selected indices and spatial correlation among weather stations. SWAT simulation results for the past 30 years period by considering limitations in weather input showed the satisfactory results with monthly model efficiency of 0.92. The error in average dam inflow according to selection of GCMs and downscaling method showed the bests result when 16 GCMs selected raw GCM analysi were used. It was found that selection of downscaling method rather than selection of GCM is more is important in overall uncertainties. The average inflow for the future period increased in all RCP scenarios as time goes on from near-future to far-future periods. Also, it was predicted that the inflow volume will be higher in the RCP 8.5 scenario than in the RCP 4.5 scenario in all future periods. Maximum daily inflow, which is important for flood control, showed a high changing rate more than twice as much as the average inflow amount. It is also important to understand the seasonal fluctuation of the inflow for the dam management purpose. Both average inflow and maximum inflow showed a tendency to increase mainly in July and August during near-future period while average and maximum inflows increased through the whole period of months in both mid-future and far-future periods.

Relationship between vegetation change and extreme climate indices on the Inner Mongolia Plateau, China, from 1982 to 2013

Climate extremes have resulted in substantial vegetation changes during the last several decades, especially in high latitude regions of the Northern Hemisphere. As a climatically-sensitive region, the Inner Mongolia Plateau (IMP) is currently experiencing prominent climate extremes. To identify how climate extremes affect vegetation in the IMP, we calculated 11 indices of climatic extremes for 6 sub-regions of the IMP based on daily maximum and minimum temperature and precipitation. Long intervals of Normalized Difference Vegetation Index (NDVI) derived from the Global Inventory Modeling and Mapping Study (GIMMS), as well as their correlations with climate indices, were investigated at different temporal scales (annual, seasonal and monthly). The results show that on an annual scale, NDVI has the same trend as precipitation extremes and extreme low temperatures, while it has the opposite trend with extreme high temperatures. In contrast, on monthly and seasonal scales, most of the extreme climate indices are significantly positively related with NDVI. In addition, a spatial heterogeneity analysis indicates that the vegetation in desert steppe and steppe desert was relatively less sensitive to the extreme temperature indices in summer, while in general the vegetation in forest and sand desert was insensitive to the extreme precipitation indices in summer. NDVI has a significant relationship with the extreme temperature indices with a time lag of least three months, and with the extreme precipitation indices with a time lag of two months. Finally, our results suggest that extreme climatic events have become more frequent and intense under ongoing global warming.

Trends in daily precipitation in highlands region of Santa Catarina, southern Brazil

This study evaluates the occurrence of trends in time series of precipitation in the highlands region of Santa Catarina, Southern Brazil. Daily precipitation data of three weather stations at Lages, São Joaquim and Campos Novos were used to evaluate rainfall trends. The trends were analyzed through the Seasonal Mann Kendall test, to include occurrence of maximum annual 1-day precipitation (RX1), maximum annual consecutive 2-day precipitation (RX2) and maximum annual consecutive 3-day precipitation (RX3) and evaluation of Rainfall Anomaly Index (RAI). Trends were identified in two of three weather stations investigated. Positive precipitation trends were found in the spring and winter for Lages, and in the spring and summer for São Joaquim. Also, there is a trend of increase in the RX1, RX2 and RX3 frequencies and an increase in positive anomalies in the last decade for these stations. There are no statistically significant trends in the precipitation of Campos Novos, which may be associated with the short series of available data for the analysis. The occurrence of El Niño phenomenon with moderate to strong intensity was usually associated with the occurrence of positive precipitation anomalies and the La Niña phenomenon was related to the occurrence of negative anomalies. However, the influence of La Niña in the periods of negative anomaly has been reduced since the beginning of the 21st century.

Contributions of natural climate changes and human activities to the trend of extreme precipitation

This study focuses on the analysis of the nonstationarity characteristics of extreme precipitation and their attributions in the southeastern coastal region of China. The maximum daily precipitation (MDP) series is extracted from observations at 79 meteorological stations in the study area during the first flood season (April–June) from 1960 to 2012. The trends of the mean (Mn) and variance (Var) of MDP are detected using the Generalized Additive Models for Location, Scale, and Shape parameters (GAMLSS) and Mann-Kendall test. The contributions of natural climate change and human activities to the Mn and Var changes of MDP are investigated using six large-scale circulation variables and emissions of four greenhouse gases based on GAMLSS and a contribution analysis method. The results demonstrate that the nonstationarity of extreme precipitation on local scales is significant. The Mn and Var of extreme precipitation increase in the north of Zhejiang, the middle of Fujian, and the south of Guangdong. In general, natural climate change contributes more to Mn from 1960 to 2012 than to Var. However, human activities cause a greater Var in the rapid socioeconomic development period (1986–2012) than in the slow socioeconomic development period (1960–1985), especially in Zhejiang and Guangdong. The community should pay more attention to the possibility of extreme precipitation events and associated disasters triggered by human activities.

Multi-objective optimization integrated with life cycle assessment for rainwater harvesting systems

The major limitation of optimization models applied previously for rainwater harvesting (RWH) systems is the systematic evaluation of environmental and human health impacts across all the lifecycle stages. This study integrated life cycle assessment (LCA) into a multi-objective optimization model to optimize the construction areas of green rooftops, porous pavements and green lands in Beijing of China, considering the trade-offs among 24 h-interval RWH volume (QR), stormwater runoff volume control ratio (R), economic cost (EC), and environmental impacts (EI). Eleven life cycle impact indicators were assessed with a functional unit of 10,000 m2 of RWH construction areas. The LCA results showed that green lands performed the smallest lifecycle impacts of all assessment indicators, in contrast, porous pavements showed the largest impact values except Abiotic Depletion Potential (ADP) elements. Based on the standardization results, ADP fossil was chosen as the representative indicator for the calculation of EI objective in multi-objective optimization model due to its largest value in all RWH systems lifecycle. The optimization results for QR, R, EC and EI were 238.80 million m3, 78.5%, 66.68 billion RMB Yuan, and 1.05E + 16 MJ, respectively. After the construction of optimal RWH system, 14.7% of annual domestic water consumption and 78.5% of maximum daily rainfall would be supplied and controlled in Beijing, respectively, which would make a great contribution to reduce the stress of water scarcity and water logging problems. Green lands have been the first choice for RWH in Beijing according to the capacity of rainwater harvesting and less environmental and human impacts. Porous pavements played a good role in water logging alleviation (R for 67.5%), however, did not show a large construction result in this study due to the huge ADP fossil across the lifecycle. Sensitivity analysis revealed the daily maximum precipitation to be key factor for the robustness of the results for three RWH systems construction in this study.