Extreme Wet Days Research Articles

The Effect of the El Nino Southern Oscillation on Precipitation Extremes in the Hindu Kush Mountains Range

The El Nino Southern Oscillation (ENSO) phenomenon is devastating as it negatively impacts global climatic conditions, which can cause extreme events, including floods and droughts, which are harmful to the region’s economy. Pakistan is also considered one of the climate change hotspot regions in the world. Therefore, the present study investigates the effect of the ENSO on extreme precipitation events across the Upper Indus Basin. We examined the connections between 11 extreme precipitation indices (EPIs) and two ENSO indicators, the Southern Oscillation Index (SOI) and the Oceanic Niño Index (ONI). This analysis covers both annual and seasonal scales and spans the period from 1971 to 2019. Statistical tests (i.e., Mann–Kendall (MK) and Innovative Trend Analysis (ITA)) were used to observe the variations in the EPIs. The results revealed that the number of Consecutive Dry Days (CDDs) is increasing more than Consecutive Wet Days (CWDs); overall, the EPIs exhibited increasing trends, except for the Rx1 (max. 1-day precipitation) and Rx5 (max. 5-day precipitation) indices. The ENSO indicator ONI is a temperature-related ENSO index. The results further showed that the CDD value has a significant positive correlation with the SOI for most of the UIB (Upper Indus Basin) region, whereas for the CWD value, high elevated stations gave a positive relationship. A significant negative relationship was observed for the lower portion of the UIB. The Rx1 and Rx5 indices were observed to have a negative relationship with the SOI, indicating that El Nino causes heavy rainfall. The R95p (very wet days) and R99p (extreme wet days) indices were observed to have significant negative trends in most of the UIB. In contrast, high elevated stations depicted a significant positive relationship that indicates they are affected by La Nina conditions. The PRCPTOT index exhibited a negative relationship with the SOI, revealing that the El Nino phase causes wet conditions in the UIB. The ONI gave a significant positive relationship for the UIB region, reinforcing the idea that both indices exhibit more precipitation during El Nino. The above observations imply that while policies are being developed to cope with climate change impacts, the effects of the ENSO should also be considered.

Spatiotemporal analysis of consecutive extreme wet days in China from 1980 to 2020

AbstractConsecutive extreme wet days (CEWDs) typically affect the likelihood of flooding and landslides and have negative effects on both natural and artificial ecosystems; however, the spatiotemporal changes in their features are still unclear at the national scale. Investigating changes in the frequency and intensity of such events is essential for climate risk management. Here, this study thoroughly analysed CEWD features in China from 1980 to 2020 using the daily observation dataset. We also evaluated and compared the ability of two widely used precipitation products, the European Centre for Medium‐Range Weather Forecasts Reanalysis 5th Generation (ERA5) and the Multi‐Source Weighted‐Ensemble Precipitation version 2 (MSWEP), to detect CEWD features. According to the observation data, the frequency and intensity of CEWD events are related to local climate and present “high eastern and low western” spatial patterns across China. Since 1980, more than half of China's mainland has experienced increases in both the frequency and intensity of CEWDs. Some stations detected decreasing trends in CEWD frequency and amounts, which are primarily located in the eastern coastal regions and southwest of warm temperate humid/subhumid regions. The ERA5 precipitation product generally outperforms MSWEP data in detecting CEWD events, and the latter significantly underestimates the annual frequency and amounts of CEWDs. These findings provide basic and valuable information regarding CEWD features across China and where such studies can be conducted based on precipitation datasets. Furthermore, these findings will also aid policymakers in managing extreme precipitation‐related natural hazards.

Spatiotemporal analysis of temperature and precipitation extremes over Bangladesh using a novel gridded observational dataset

This study explores spatial changes in trends of 29 climate extremes indices between 1981 and 2020 in Bangladesh, a country that frequently experiences the impacts of extreme events. This is the first study to examine trends in extreme climate over Bangladesh using a high resolution (0.05° × 0.05°) gridded daily temperature and precipitation data rather than individual stations. Trends in mean daily maximum and minimum temperatures were +0.38 °C and +0.25 °C per decade, respectively, for the last 40 years. The maximum increases in both warm days and nights were 12.75 days per decade with the fastest rate of warming in the eastern part of the country, whereas the maximum decreases in both cold days and nights were 7 days per decade with the western part experiencing the greatest increase in extreme cold. Significant reductions in total precipitation (225 mm per decade) were observed in the major parts of the country. However, the number of very heavy precipitation days (R20mm) showed a statistically significant increase (2.25 days per decade) in the southern coastal areas, with the tendency of more extreme wet days (R30 mm). The maximum decrease in annual total precipitation was 225 mm per decade while the consecutive dry days increased by 12.5 days per decade. While previous studies reported a faster rise in minimum temperature than maximum temperature, this study shows a faster increase in maximum temperature instead of minimum temperature in the study area. Extreme temperature changes were statistically more significant than changes in extreme precipitation. This study also shows statistically significant and consistent spatial trends of extreme temperature and precipitation when using high-resolution gridded observational datasets instead of station data.

The effects of weather on beef carcass and growth traits

To predict the impact of climate change on our beef animals and systems, we need a better understanding of how beef cattle traits are affected by varying weather and frequency of extreme events. We analysed the effect of minimum and maximum temperatures and average daily precipitation on a range of important carcass traits, including age at slaughter, cold carcass weight, carcass growth rate and conformation and fat score (N = >1.6 million), as well as calf 200-day live weight and growth rate (N = >270 000), using data from abattoirs across Britain (carcass traits) and calves in Scottish suckler beef herds (live weights and growth). Animals which experienced higher daily maximum and minimum temperatures had slower carcass and calf growth rates. Increased precipitation also led to poorer cold carcass weights, conformation scores, calf 200-day weights and calf growth. We also analysed the effect of frequency of extreme weather events, including heatwaves, cold waves, and dry and wet days. The frequency of heatwaves, dry and wet days were shown to have significant negative effects on almost all traits considered, for example, predicting that an increase in the frequency of heatwaves by 1 day per 100 days of life would reduce cold carcass weights by about 200 g and increase age at slaughter by about 3 days. Results show that varying weather and frequency of extreme weather, across the lifetime of a beef animal, influences traits which affect the potential profit for a beef farmer. These effects may be due to several factors, including direct effects on the animal, as well as feed availability and management decisions made by the farmer. However, there is potential to mitigate negative effects through a range of animal management strategies.

Temporally compounding heatwave–heavy rainfall events in Australia

AbstractNatural hazards often occur in combination with other natural hazards rather than as isolated events. While some combinations of hazards are well studied and their physical connection is increasingly understood, other combinations have received considerably less attention. High temperatures are known to be an important component for conditions that lead to heavy rainfall; however, sequences of heatwaves followed by heavy rainfall are not well understood, especially in a compound event context. Here, we analyse heatwave–heavy rainfall events across Australia using rainfall observations at hourly resolution. Our results show that heavy rainfall is more likely to occur if preceded by a heatwave, demonstrating that heatwave–heavy rainfall sequences should be seen as temporally compounding events. In particular, many regions in Australia experience both more frequent and more extreme wet days immediately following a heatwave. This behaviour is strongest in coastal regions, especially on the Australian east coast. These findings highlight the need for heatwave–heavy rainfall sequences to be studied as compounding events, as future changes in either hazard is likely to have impacts on related risks such as flash flooding.

Spatiotemporal Changes in Mean and Extreme Climate: Farmers’ Perception and Its Agricultural Implications in Awash River Basin, Ethiopia

The increase in the intensity and frequency of climate extremes threatens socioeconomic development. This study examines variability of mean and extreme climate, farmers’ perception of the changes, and impacts in the Awash River Basin. Daily rainfall and temperature data were used to analyze 23 extreme climate indices. The Mann–Kendall test was used to assess the magnitude and significance of the changes. Results show an increase in minimum (0.019–0.055 °C/year) and maximum temperatures (0.049–0.09 °C/year), while total rainfall is on a downward trend (from −3.84 mm/year to −10.26 mm/year). Warm extreme temperature indicators, including warmest day (TXx), warmest night (TNx), warm day (TX90p), warm night (TN90p), and warm spell duration indicator (WSDI), show a significant increasing trend (p < 0.05). Nevertheless, except the tepid–cool humid agroecology zone, cold extreme temperature indicators in cool days (TN10p), cool nights (TX10p), and cold spell duration (CSDI) are declining. Extreme precipitation indices, including maximum 1-day precipitation amount (RX1day), count of days when precipitation ≥10 mm (R10 mm), maximum 5-day precipitation amount (RX5day), count of days when precipitation ≥20 mm (R20mm), very wet days (R95p), extreme wet days (R99p), and total precipitation (PRCPTOT), show a decreasing trend. The perception of most farmers’ on climate change and climate extremes agreed with climate records. The major impacts perceived and asserted over all agroecologies are food price inflation, crop productivity decline, crop pests and diseases spread, livestock disease increase, and the emergence of pests and weeds. The increasing trend in extreme warm temperatures, decreasing trend in the cold extreme, and declining trend in precipitation indicators affected agricultural productivity and farmers whose livelihood depends on rainfed agriculture. This agroecology-specific study provides critical information to policymakers, decision makers, and farmers about the potential impacts of climate change and extreme events, leading to the development of agroecology-based adaptation measures.

Spatiotemporal Variability in Precipitation Extremes in the Jianghuai Region of China and the Analysis of Its Circulation Features

In the context of global warming, changes in extreme-precipitation events are becoming increasingly complex, and investigating the spatial and temporal variation characteristics of extreme precipitation is extremely important for scientific water-resource planning, preventing new climate risks and maintaining ecosystem balances. Based on the daily precipitation from 1960–2017 at 15 meteorological stations in the Jianghuai region, the extreme-precipitation indices were calculated. The variations in 12 extreme-precipitation indices were detected by using the Mann–Kendall test in the Jianghuai region. The periodicity of indices was examined by wavelet analysis detecting significant time sections. Through the cross wavelet transform and wavelet coherence analyses, the nonlinear connections between extreme precipitation and atmospheric circulation were explored. The results indicate significant increasing trends in the max one-day precipitation amount (Rx1day), extreme wet days (R99p), and simple precipitation intensity index (SDII). The intensity of extreme precipitation increased significantly. The variation in extreme precipitation showed different trends in different regions, with a greater likelihood of increasing extreme-precipitation intensity and frequency in the southern region compared to the central and northern regions. The period of most oscillations of the indices tend toward be on a time scale of 2–4 years and are in the 1990s. The number of heavy precipitation days (R10 mm) and number of very heavy precipitation days (R20 mm) had, mainly, periods of 5.84 years. Additionally, there were significant resonance periods between the extreme-precipitation indices and the atmospheric circulation index; however, there were obvious differences in time domains. The North Atlantic Oscillation (NAO) and East Asian summer monsoon (EASM) had the most significant effect on the duration of extreme precipitation; Atlantic Oscillation (AO) and EASM had the most significant influence on the extreme-precipitation intensity. The results of the study can provide a scientific basis for water-resource management and disaster prevention and control in the Jianghuai region.

Effects of Land Cover Changes on Compound Extremes over West Africa Using the Regional Climate Model RegCM4

This study aims to characterize the impacts of the Sahel–Sahara interface reforestation on compound extremes in the Sahel region during the West African monsoon season (June–July–August–September, JJAS). For this purpose, we performed a simulation with the standard version of the RegCM4 model, and another simulation with the altered version of the same model, taking into account the incorporated forest. Results show that reforestation may strongly influence the frequency of individual extreme events (dry and warm days) by decreasing them over and off the reforested zone. The reduction in these extreme dry and warm days may be due partly to the strengthening of the atmospheric moisture content over most parts of the West African domain and the weakening of the sensible heat flux south of 16° N. The analysis also shows an increase in extreme wet days over and off the reforested zone, which could be associated partly with the strengthening of evapotranspiration over most parts of the West African domain, including the reforested area. The analysis of compound extremes shows a strong occurrence of the compound dry/warm mode over the northern Sahel for both runs, probably due to the weak precipitation recorded in this zone. Both experiments also simulated a strong compound wet/warm mode occurrence over the Sahel due to a high rainfall occurrence over this region. When comparing both runs, the impact of the reforestation was to decrease (increase) the compound extreme dry/warm (wet/warm) mode over the reforested zone. The dry/warm mode decrease is consistent with that of individual extreme dry and warm days, while the compound wet/warm mode increase may be driven by that of the extreme wet days. Finally, when considering the seasonal cycle, the dry/warm mode exhibits a more substantial decrease in the beginning (June–July, JJ) than during the peak of the West African summer monsoon season (August–September, AS). Moreover, reforestation similarly affects the compound wet/warm mode in JJ and AS by increasing it in the reforested region and decreasing it over the Southern Sahel (south of 15° N). This work suggests that reforestation may be a good solution for West African policymakers to mitigate climate change over the region and to develop better strategies for water resource management.

Spatiotemporal changes of precipitation extremes in Bangladesh during 1987–2017 and their connections with climate changes, climate oscillations, and monsoon dynamics

This study provides a comprehensive framework to explore the spatiotemporal changes in precipitation extremes in Bangladesh, an important South Asian country, over the 1987–2017 period and their links with climate changes, large-scale climate oscillations ( i.e. , El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD)), and the East Asian Summer Monsoon (EASM) dynamics. Precipitation extremes are measured by ten extreme precipitation indices (EPIs) recommended by the Expert Team on Climate Change Detection and Indices. The comprehensive framework consists of an iterative-based Mann–Kendall trend analysis to explore the trends in the EPIs across the country and a joint analysis based on a Pearson product-moment correlation analysis and a multivariate linear regression to investigate the links of the EPIs with local to global climate changes, ENSO, IOD, and EASM dynamics. This study finds that precipitation extremes show clearly regional and seasonal differential changes across Bangladesh. All of the 28 stations across Bangladesh show positive trends for consecutive dry days, while 21 out of 28 stations show negative trends in annual total wet-day precipitation. Maximum 1-day precipitation amount and 5-day precipitation amount are increasing over the coastal areas during the monsoon season and decreasing in winter for most parts of Bangladesh. The trends of precipitation extremes show a clear spatial dependency on topography and distance from the coastline. Precipitation extremes in Bangladesh appear to respond more actively to IOD, local to global climate changes, and EASM than ENSO, especially for annual total wet-day precipitation, very and extreme wet days, and wet spells. In addition, precipitation extremes in coastal regions are more responsive to global warming than in inland regions. Most of the EPIs show negative associations with local temperature anomalies and the EASM strength. This study provides a new comprehensive look at the important links of extreme precipitations variations with climate changes, large-scale climate oscillations, and EASM dynamics across Bangladesh. • Provided a comprehensive framework to explore the spatiotemporal changes in precipitation extremes in Bangladesh. • Investigated trends in precipitation extremes during 1987–2017. • Identified spatial patterns of extreme precipitation trends and the associated geography effects. • Precipitation extremes show regional and seasonal differential changes.

Influence of Okhotsk Sea blocking on summer precipitation over South Korea

AbstractThis study examined the influence of atmospheric blocking on the variability of precipitation over South Korea during summer (June–July–August) by defining the blocking frequency over the Okhotsk Sea (Okhotsk Sea blocking frequency; OK_BF). According to composite analysis for the years of high precipitation over South Korea, blocking occurs more frequently over the Okhotsk Sea (140°E–160°E). Partial correlation and regression analyses were conducted to separate the contribution of OK_BF to precipitation variability from that of the low‐level meridional wind (LLMW) because LLMW over the region is another important aspect of summer precipitation in South Korea. The barotropic structures of positive geopotential height anomalies over the Okhotsk Sea associated with increasing OK_BF can induce negative temperature anomalies over South Korea due mainly to the equatorward advection of cold air masses from higher latitudes. The enhanced meridional temperature gradient can cause increases in baroclinic instability and zonal wind vertical shear according to the thermal wind balance. This instability can induce anomalous cyclonic circulations over South Korea, resulting in positive precipitation anomalies. The partial correlation coefficients (R2 = 0.35–0.40) between the OK_BF and precipitation indices, including mean precipitation, extreme precipitation intensity, wet days, and consecutive wet days, were all statistically significant at the 95% confidence level. Overall, the effects of the increasing OK_BF on both precipitation and potential evapotranspiration can intensify the surface water budget in South Korea.

Revealing alarming changes in spatial coverage of joint hot and wet extremes across India

Compared to any single hydroclimatic variable, joint extremes of multiple variables impact more heavily on the society and ecosystem. In this study, we developed new joint extreme indices (JEIs) using temperature and precipitation, and investigated its spatio-temporal variation with observed records across Indian mainland. Analysis shows an alarming rate of change in the spatial extent of some of the joint extreme phenomena, tending to remain above normal. For example, above normal hot nights and wet days events expands at a rate of 0.61% per year considering entire Indian mainland. If the historical trend continues at the same rate, consecutive cold and wet day events will drop below the threshold of mean value observed in the base line period (1981–2010) everywhere in the country by the end of the twenty-first century. In contrast, the entire country will be covered by hot nights and wet days events only (frequency of occurrence will cross the threshold of mean value observed in the base line period). This observation is also supported by the CMIP6 climate model outputs. It is further revealed that extremes of any single variable, i.e. either precipitation or temperature (e.g., Extreme Wet Days, Consecutive Wet Days, Hot Nights, and Cold Spell Duration Index), do not manifest such an alarming spatial expansion/contraction. This indicates that the consideration of the joint indices of hydroclimatic variables is more informative for the climate change impact analysis.

Analysis of Climate Change and Extreme Climatic Events in the Lake Victoria Region of Tanzania

The understanding of climate change impacts and the associated climate extreme events at regional and local scales is of critical importance for planning and development of feasible adaptation strategies. In this paper, we present an analysis of climate change and extreme climate events in the Lake Victoria region of Tanzania, focusing on the Kagera and Geita regions. We use daily simulated climate variables (rainfall and minimum and maximum temperatures) from the Coordinated Regional Climate Downscaling Experiment Program Regional Climate Models (CORDEX_RCMs) for the analysis. Extreme climate event, rainfall, and minimum and maximum temperatures time series during historical (1971–2000) climate condition are compared to future climate projection (2011–2100) under two Representative Concentration Pathway (RCP): RCP 4.5 and RCP 8.5 emission scenarios. The existence, magnitude, and statistical significance of potential trends in climate data time series are estimated using the Mann–Kendall (MK) non-parametric test and Theil-SEN slope estimator methods. Results show that during historical (1971–2000) climate, the Lake Victoria region of Tanzania experienced a statistically significant increasing trend in temperature. The annual minimum and maximum temperatures in the Kagera and Geita regions have increased by 0.54–0.69°C, and 0.51–0.69°C, respectively. The numbers of warm days (TX90p) and warm nights (TN90p) during the historical climate have increased, while the numbers of cold days (TX10p) and cold nights (TN10p) have decreased significantly. However, in future climate condition (2011–2100) under both RCP 4.5 and RCP 8.5 emission scenarios, the Lake Victoria region is likely to experience increased temperatures and rainfall. The frequency of cold events (cold days and cold nights) is likely to decrease, while the frequency of warm events (warm days and warm nights) is likely to increase significantly. The number of consecutive wet days, the intensity of very wet days, and the number of extreme wet days are likely to increase. These results indicate that in future climate condition, socioeconomic livelihoods of people in the Kagera and Geita regions are likely to experience significant challenges from climate-related stresses. It is, therefore, recommended that appropriate planning and effective adaptation policies are in place for disaster risk prevention.

Exploring the predictability of within-season rainfall statistics of the Bangladesh monsoon using North American Multimodel Ensemble outputs

Improvement of rainfall forecasts on seasonal to within-season timescales is crucial for many vulnerable regions and nations, including Bangladesh. For South Asia, seasonal predictability of rainfall can be quite challenging, and Bangladesh has limited predictive skill with respect to total seasonal rainfall due to its weak relationship with ENSO variability. The relationship between total seasonal monsoon rainfall from June through September (JJAS), as simulated by the North American Multimodel Ensemble (NMME), and within-season observed rainfall statistics for Bangladesh were explored, employing 25-year cross-validations at lead times up to 3 months. The model hindcasts of total JJAS rainfall demonstrate only low-to-modest skill at predicting total observed seasonal rainfall, but a more robust predictive relationship is found for the number of observed dry and wet spells within the season, more so than with the number of extreme dry or wet days. A small ensemble of NMME models could be used to provide more valuable information to aid decision-makers than previously thought, with important implications for agricultural decision-making and climate services.

Projected Changes to Extreme Runoff and Precipitation Events From a Downscaled Simulation Over the Western United States

Extreme precipitation and runoff events, which often impact natural and social systems more than mean changes, generally occur over regional scales. Future climate projections can be used to estimate how the hydrologic cycle may change, but the coarse resolution of global climate models (>1°) makes it difficult to evaluate regional changes, such as over a single watershed. To estimate changes in hydroclimatic variables at finer spatial resolutions, we dynamically downscale the Community Earth System Model (CESM) with the Weather Research and Forecasting (WRF) regional climate model over the western United States at 9 km spatial resolution. By running WRF at a higher spatial resolution, we estimate future climate conditions, including 99% and 99.9% event magnitude, over seventeen watersheds: the Columbia, Lower Colorado, Upper Colorado, the Upper Missouri/Yellowstone, and twelve basins draining the western slope of the Sierra Nevada in California. Over each basin, we compare a historical period (1996-2005) with mid-century (2041-2050) and end-century (2091-2100). From the WRF/CESM simulations, most basins are projected to have earlier peaks in springtime streamflow. The Columbia and the Lower Colorado watersheds are both expected to experience more extreme wet days, with the 99th percentile of daily precipitation estimated to increase by over 10%. For the Upper Colorado, however, the 99th percentile of daily runoff is projected to decrease by over 30%. Basins in the northern and central Sierra Nevada are projected to have substantial increases in extreme runoff, with doubling of high flow event magnitude possible for some basins. By end-century, the contribution of high-magnitude runoff (>90th percentile) to total runoff is projected to increase from 46% to 56%, when averaged across all twelve Sierra Nevada basins. Though only one realization from a single global climate model, the downscaled simulation presented here shows interesting results regarding how extreme events may change; these results can be tested by downscaling other global models with WRF to create an ensemble of dynamically downscaled future projections.

Characterization of future climate extremes over Tamil Nadu, India, using high-resolution regional climate model simulation

Tamil Nadu, an agriculturally important state in India, is recurrently exposed to floods, cyclones, and droughts that have devastating effects on human, agriculture, and economy. This persuades the study to focus on future climate extremities of the state. The future climate extremes are examined using daily temperature and rainfall simulations developed by Hadley Center’s Regional Climate Model termed PRECIS (Providing REgional Climates for Impacts Studies) at a horizontal resolution of 25 km. The study uses the simulations that are driven by the lateral boundary condition of HadCM3Q0 (Hadley Centre Coupled Model-Q0) generated by a Perturbed Physical Ensemble of 17 ensembles under A1B scenario for the period of 2005 to 2095. Extreme indices have been acquired from the simulations using RClimDex. The trends of extreme indices are computed and verified for statistical significance using Mann–Kendall and Sen’s slope test. The changes in extreme indices with respect to baseline (1970–2000) reveal that almost all temperature indices denote a highly significant trend. The minimum temperature indices have shown prominent increase compared with maximum temperature indices, which is also upheld by the significant decrease in the diurnal temperature range trend. The summer days above 40 °C have indicated a substantial increase with a stronger slope of 0.77. However, the rainfall indices depict the insignificant trend. The changes in extreme wet days (R99p) and very wet days (R95p) exhibit a positive shift, and the increase of maximum 1-day rainfall is projected to be higher than maximum 5-day rainfall. Furthermore, the probability of rainfall indices exemplifies the increase of intense rainfall by the end of the century. The overall results of indices intimate that Tamil Nadu will be shifted to the extreme warmer and wetter condition by 2080s (2065–2095). Such information will act as a baseline to study the future impact assessment on different sectors thereby supporting policymakers and stakeholders to formulate suitable adaptation and mitigation strategies.

Rainfall distribution and trends of the daily precipitation concentration index in northern Morocco: a need for an adaptive environmental policy

A national priority at the Moroccan level is to understand the spatiotemporal rainfall irregularity to anticipate suitable strategies for water and agriculture management. The most northern mountainous region shows intense sensitivity to extreme hydroclimatic hazards which may compromise the future of socioeconomic acceleration and further weaken environmental balances. However, planning and decision making require accurate data, on a detailed scale and with good spatial distribution which is not the case in several south-Mediterranean countries where rainfall data and/or well-established hydro-meteorological network is lacking. In this paper, abundant rain gauge measurements combined with time-series open data (1958–2015) were used to study the rainfall variability. Results show an annual rainfall increase trend since 1996 with frequent, intense and abundant rains causing violent torrents and floods. This humid trend alternates with short but severe dry periods. Spatial distribution shows a rainfall increase from eastern to western area and from the coastal plains to high mountains. Based on a continuous daily rainfall dataset (from 1988 to 2012) from six scattered stations, it appears that the pattern of heavy and extreme wet days takes the form of an irregular interannual cycle. Trends of the annual precipitation daily concentration indicate a significant positive trend in the center than in the East of the study area. Considering these observations, a review of water needs/obligations priorities seems crucial so that a new conscious and adaptative environmental policy would approve new procedures for a sustainable management.

Observed Trends and Changes in Temperature and Precipitation Extreme Indices over Myanmar

Projected increase in frequency and severity of extreme events are important threat brought by climate change. Thus, there is a need to understand the dynamics and magnitude of climate extreme at local and regional level. This study examines the patterns of annual trends and changes of extreme daily temperature and precipitation in Myanmar for the period of 1981 to 2015 using the RClimDex 1.1 software. The trends of maximum and minimum temperature show significant warming trends (p < 0.001) across Myanmar. From 2009 to 2015, the maximum temperature anomaly has continuously increased by 0.5 °C for all years except 2011. The larger rise in both maximum and minimum temperature observed after 2000 suggests that, overall, days and nights are becoming hotter for the entirety of Myanmar over this recent period. Furthermore, our works also show that the temperature extreme indices of warm days and warm nights have increased, whereas the frequency of cool days and cool nights have decreased. Our analysis also reveals that increasing trends in precipitation anomaly were not significant during 1981–2015. On the contrary, slight increasing trends towards wetter conditions were observed with a rate of 76.52 mm/decade during the study period. The other precipitation extreme indicators—namely, annual total precipitation (PRCPTOT), heavy precipitation days (R20mm), extreme wet days precipitation (R99p), and consecutive wet days (CWD)—are consistent with warming trends. Additionally, the relationship between inter-annual variability in the climate extremes indices and Oceanic Niño Index (ONI) patterns was also examined with a focus on the influence of the El Niño-Southern Oscillation (ENSO) phenomenon.

Features of Extreme Precipitation at Progress Station, Antarctica

AbstractObserved daily precipitation data were used to investigate the characteristics of precipitation at Antarctic Progress Station and synoptic patterns associated with extreme precipitation events during the period 2003–16. The annual precipitation, annual number of extreme precipitation events, and amount of precipitation during the extreme events have positive trends. The distribution of precipitation at Progress Station is heavily skewed with a long tail of extreme dry days and a high peak of extreme wet days. The synoptic pattern associated with extreme precipitation events is a dipole structure of negative and positive height anomalies to the west and east of Progress Station, respectively, resulting in water vapor advection to the station. For the first time, we apply self-organizing maps (SOMs) to examine thermodynamic and dynamic perspectives of trends in the frequency of occurrence of Antarctic extreme precipitation events. The changes in thermodynamic (noncirculation) processes explain 80% of the trend, followed by the changes in the interaction between thermodynamic and dynamic processes, which account for nearly 25% of the trend. The changes in dynamic processes make a negative (less than 5%) contribution to the trend. The positive trend in total column water vapor over the Southern Ocean explains the change of thermodynamic term.

Evaluating Stochastic Precipitation Generators for Climate Change Impact Studies of New York City’s Primary Water Supply

AbstractWatersheds located in the Catskill Mountains of southeastern New York State contribute about 90% of the water to the New York City water supply system. Recent studies show that this region is experiencing increasing trends in total precipitation and extreme precipitation events. To assess the impact of this and other possible climatic changes on the water supply, there is a need to develop future climate scenarios that can be used as input to hydrological and reservoir models. Recently, stochastic weather generators (SWGs) have been used in climate change adaptation studies because of their ability to produce synthetic weather time series. This study examines the performance of a set of SWGs with varying levels of complexity to simulate daily precipitation characteristics, with a focus on extreme events. To generate precipitation occurrence, three Markov chain models (first, second, and third orders) were evaluated in terms of simulating average and extreme wet days and dry/wet spell lengths. For precipitation magnitude, seven models were investigated, including five parametric distributions, one resampling technique, and a polynomial-based curve fitting technique. The methodology applied here to evaluate SWGs combines several different types of metrics that are not typically combined in a single analysis. It is found that the first-order Markov chain performs as well as higher orders for simulating precipitation occurrence, and two parametric distribution models (skewed normal and mixed exponential) are deemed best for simulating precipitation magnitudes. The specific models that were found to be most applicable to the region may be valuable in bottom-up vulnerability studies for the watershed, as well as for other nearby basins.

Changes in mean and extreme temperature and precipitation over the arid region of northwestern China: Observation and projection

This paper reports a comprehensive study on the observed and projected spatiotemporal changes in mean and extreme climate over the arid region of northwestern China, based on gridded observation data and CMIP5 simulations under the RCP4.5 and RCP8.5 scenarios. The observational results reveal an increase in annual mean temperature since 1961, largely attributable to the increase in minimum temperature. The annual mean precipitation also exhibits a significant increasing tendency. The precipitation amount in the most recent decade was greater than in any preceding decade since 1961. Seasonally, the greatest increase in temperature and precipitation appears in winter and in summer, respectively. Widespread significant changes in temperature-related extremes are consistent with warming, with decreases in cold extremes and increases in warm extremes. The warming of the coldest night is greater than that of the warmest day, and changes in cold and warm nights are more evident than for cold and warm days. Extreme precipitation and wet days exhibit an increasing trend, and the maximum number of consecutive dry days shows a tendency toward shorter duration. Multi-model ensemble mean projections indicate an overall continual increase in temperature and precipitation during the 21st century. Decreases in cold extremes, increases in warm extremes, intensification of extreme precipitation, increases in wet days, and decreases in consecutive dry days, are expected under both emissions scenarios, with larger changes corresponding to stronger radiative forcing.