Number Of Consecutive Dry Days Research Articles

Analysis of extreme precipitation variation characteristics in mountain grasslands of arid and semi-arid regions in China

Introduction: With global warming, the disaster losses caused by extreme precipitation events are increasing. The poor natural conditions and climate change make the arid and semi-arid mountainous grassland area a sensitive region of climate change. The study on the spatio-temporal variation characteristics of extreme precipitation events in this region is helpful to improve the ability of climate prediction and disaster prevention and reduction in grassland.Methods: Based on the daily precipitation data of four meteorological monitoring stations in the Yinshanbeilu from 1970 to 2020, the trend analysis, M-K test and wavelet analysis were used to select seven typical extreme precipitation indicators to analyze the temporal and spatial characteristics of extreme precipitation.Results and Discussion: The results showed that the precipitation in the Yinshanbeilu increased in the past 51a, and the number of heavy rain days increased significantly. The significance test of CDD and CWD showed that the number of continuous dry days and continuous wet days decreased abruptly. The spatial analysis showed that the high value areas of R95p, R95d and PRCRTOT were all located in Siziwang Banner, and it could be concluded that the extreme precipitation risk was the highest in Siziwang Banner, while the low value areas of SDII, Rx1day, R95p and PRCRTOT were all located in Sonid Right Banner, which could be inferred that the Sonid Right Banner was relatively dry. The first main cycle of the seven indexes of extreme precipitation almost runs through the whole time series, and the starting point of the minimum main cycle changes inconsistent. In addition to the number of consecutive dry days, the other indices have a good correlation with annual precipitation, flood season and monthly precipitation from June to September, and July is the peak period of extreme precipitation events.

The increases in extreme climatic events over the northeastern Tibetan Plateau and their association with atmospheric circulation changes

In the context of global warming, increasing frequency of climate extremes poses a great challenge to natural systems and humankind. However, the spatial and temporal characteristics, as well as the mechanisms of extreme climate change, remain insufficiently understood, particularly in arid and semi-arid mountainous regions with high climate sensitivity and ecological fragility. In this study, we analyzed the spatial and temporal characteristics of 27 extreme climate indices (including intensity, duration, and frequency) in the Qilian Mountains, northeastern Tibetan Plateau, from 1961 to 2016 using the CN05.1 meteorological grid dataset, explored the relationship between the extreme climate indices and internal variability of the climate system (e.g., the North Atlantic Multi-decadal Oscillation (AMO), the Pacific Decadal Oscillation (PDO), and the Arctic Oscillation (AO)), and further probed into the mechanisms affecting climate extremes using ERA5 reanalysis dataset. The results showed that extreme temperatures in the Qilian Mountains were significantly enhanced in terms of intensity, frequency, and duration during 1961–2016. The decrease rates of frost days (FD0) and ice days (ID0) were − 4.4 d per decade and − 4.7 d per decade, respectively, and the increase rate of growing season length (GSL) was 2.9 d per decade. Extreme precipitation intensity increased significantly, with the intensity indices R95P and PRCPTOT showing the most significant change trends of 4 mm per decade and 14.9 mm per decade, respectively (p < 0.05). The number of consecutive dry days (CDD) displayed a significant downward trend, with a rate of −6 d per decade, the number of moderate precipitation days (R10) showed an increasing trend of 0.12 d per decade. Correlation analyses revealed significant associations between the increases in extreme climates and the AMO and PDO. Additionally, the enhancement of the AO contributed to the increased extreme precipitation. Enhanced anticyclonic circulation in Eurasia and geopotential height, as well as increased cloud cover in winter, were the main reasons for the increase in extreme temperatures in the Qilian Mountains, whereas the significant increase in water vapor transport entering the east boundary of the Qilian Mountains in summer mainly contributed to the increase in extreme precipitation. This study highlights internal oscillations in the climate system that regulate the extreme climate variability in the Qilian Mountains at various spatial-temporal scales.

Quantifying causal teleconnections to drought and fire risks in Indonesian Borneo

AbstractFires occurring over the peatlands in Indonesian Borneo accompanied by droughts have posed devastating impacts on human health, livelihoods, economy and the natural environment, and their prevention requires comprehensive understanding of climate‐associated risk. Although it is widely known that the droughts are associated with El Niño events, the onset process of El Niño and thus the drought precursors and their possible changes under the future climate are not clearly understood. Here, we use a causal network approach to quantify the strength of teleconnections to droughts at a seasonal timescale shown in observations and climate models. We portray two drivers of June‐July‐August (JJA) droughts identified through literature review and causal analysis, namely Niño 3.4 sea surface temperature (SST) in JJA (El Niño Southern Oscillation [abbreviated as ENSO]) and SST anomaly over the eastern North Pacific to the east of the Hawaiian Islands (abbreviated as Pacific SST) in March‐April‐May (MAM) period. We argue that the droughts are strongly linked to ENSO variability, with drier years corresponding to El Niño conditions. The droughts can be predicted with a lead time of 3 months based on their associations with Pacific SST, with higher SST preceding drier conditions. We find that under the SSP585 scenario, the Coupled Model Intercomparison Phase 6 (CMIP6) multi‐model ensembles show significant increase in both the maximum number of consecutive dry days in the Indonesian Borneo region in JJA (p = 0.006) and its linear association with Pacific SST in MAM (p = 0.001) from year 2061 to 2100 compared with the historical baseline. Some models are showing unrealistic amounts of JJA rainfall and underestimate drought risks in Indonesian Borneo and their teleconnections, owing to the underestimation of ENSO amplitude and overestimation of local convections. Our study strengthens the possibility of early warning triggers of fires and stresses the need for taking enhanced climate risk into consideration when formulating long‐term policies to eliminate fires.

Exposure of African ape sites to climate change impacts

Large gaps remain in our understanding of the vulnerability of specific animal taxa and regions to climate change, especially regarding extreme climate impact events. Here, we assess African apes, flagship and highly important umbrella species for sympatric biodiversity. We estimated past (1981–2010) and future exposure to climate change impacts across 363 sites in Africa for RCP2.6 and RCP6.0 for near term (2021–2050) and long term (2071–2099). We used fully harmonized climate data and data on extreme climate impact events from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Historic data show that 171 sites had positive temperature anomalies for at least nine of the past ten years with the strongest anomalies (up to 0.56°C) estimated for eastern chimpanzees. Climate projections suggest that temperatures will increase across all sites, while precipitation changes are more heterogeneous. We estimated a future increase in heavy precipitation events for 288 sites, and an increase in the number of consecutive dry days by up to 20 days per year (maximum increase estimated for eastern gorillas). All sites will be frequently exposed to wildfires and crop failures in the future, and the latter could impact apes indirectly through increased deforestation. 84% of sites are projected to be exposed to heatwaves and 78% of sites to river floods. Tropical cyclones and droughts were only projected for individual sites in western and central Africa. We further compiled available evidence on how climate change impacts could affect apes, for example, through heat stress and dehydration, a reduction in water sources and fruit trees, and reduced physiological performance, body condition, fertility, and survival. To support necessary research on the sensitivity and adaptability of African apes to climate change impacts, and the planning and implementation of conservation measures, we provide detailed results for each ape site on the open-access platform A.P.E.S. Wiki.

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.

Climate Change and Extreme Events in Northeast Atlantic and Azores Islands Region

In small island regions, the influence of climate change assumes particular relevance. In the Azores archipelago, made up of nine islands, the geographical circumstances, oceanic condition, territorial dispersion, land use model and other physiographic constraints reinforce and enhance the vulnerability of the islands to changes in current weather patterns. Coupled Model Intercomparison Phase 6 (CMIP6) projections are used for the northeast Atlantic region to evaluate daily extreme climate events in large scale for the Azores region. Results shows changes in the annual maximum number of consecutive dry days, the annual number of wet days, and especially in the annual number of tropical nights. Despite limitations due to the lack of spatial detail, the large-scale framework suggests changes that may be enhanced by topography, particularly with respect to precipitation. The conclusions point to the need to establish standard rules in the processes of design, reviewing and/or amending territorial management instruments at the municipal scale in the Autonomous Region of the Azores, with the goal of adapting to a different climate from the recent past.

Analysis of river drying in Slovenia

Intermittent watercourses lack water during some periods of the year, which especially applies to karst sinking streams. Droughts also occur in dry periods with no rainfall over a longer period of time. The drying up of Slovenian rivers was analysed using the data from the state hydrological monitoring of the Slovenian Environment Agency. By analysing the periodic statistics of minimum low discharges (nQnp), 18 gauging stations were extracted where the watercourses dried up during the measurement period. For these stations, sets of mean daily discharges were analysed, and dry days where the flow was equal to zero were listed. The number of dry days and the number of consecutive dry days were analysed by month and year, and the longest dry periods were determined. The results are presented graphically. At most of the gauging stations considered, the number of dry days was the highest in the years characterized by extreme hydrological droughts, namely 2003, 2012, and 1993. In some watercourses, drying up is a constant phenomenon that occurs almost every year, while others only dry up in years characterized by extreme droughts. Exceptions to this are the karst rivers, which sink and are therefore dry for part of the year. The Pivka and Branica Rivers regularly dry up. Watercourses in Pomurje and Velunja, Kožbanjšček, and Dragonja also dry up very often. Analysis results demonstrated that river drying has become more frequent in the past two decades. The driest month is August, followed by July and September.

Climatological trends of mean and extreme daily precipitation in Arizona (USA)

Precipitation in Arizona, USA, represents a fundamental resource for the needs of agriculture, people, and the environment. However, due to the risk associated with flash flooding, extreme precipitation also constitutes a natural hazard. Available research on precipitation in Arizona has been limited in scope and focus and there currently exists no comprehensive assessment of statewide, historical, mean, and extreme precipitation. We use daily precipitation records from 43 Global Historical Climate Network daily (GHCNd) weather stations to examine trends in mean and extreme precipitation across Arizona from 1950 to 2020. We use a suite of standardized precipitation indices and explore the statistical significance of historical changes at the annual, monthly, and seasonal scales. Our analysis returns a motley collection of results displaying a great degree of spatial variability and sensitivity to the temporal scale of analysis. Mean total precipitation at the statewide scale underwent a small decreasing trend of 0.15 mm year−1, with considerable interannual variability being a dominant feature. The majority of stations experienced no statistically significant change in extreme precipitation at the annual scale. Monsoon season mean precipitation followed a similar pattern to annual means, with an overall reduction of 0.14 mm year−1 across the state. One fourth of stations, all located at elevations lower than 650 m, recorded decreases in monsoon precipitation intensity. Winter season analysis presents a different picture, displaying a positive statewide trend of 0.11 mm year−1 in mean precipitation. One tenth of stations recorded increases in extreme precipitation intensity and decreases in the number of consecutive dry days. Results of our observational analysis indicate a lack of a clear consensus on the climatological trends of mean/extreme precipitation in Arizona during the study period. Our findings are in contrast to those from other similarly arid areas across the world and highlight the role of regional differences in modulating the potential hydrometeorological impacts associated with climate change. However, while we do not find widespread, significant, modification in the spectrum of precipitation changes examined, the hydrologic system of the state has been – and will continue to be - impacted by the ongoing temperature increase associated with the buildup of greenhouse gases and continued population growth.

Variability of Extreme Events in Coastal and Inland Areas of South Korea during 1961–2020

The increased concentrations of greenhouse gases have led to global warming and an increased frequency and intensity of extreme weather events. Such changes in weather patterns may have unexpected implications for everyday life and water resource management in coastal and inland areas; thus, it is critical to understand the pattern of the changes. This study investigated how extreme weather events have changed in inland and coastal South Korea in the past 60 years (1961–2020) at different temporal scales, from monthly to yearly. This study quantified extreme weather events using multiple meteorological indices such as consecutive dry days (CDD), consecutive wet days (CWD), tropical nights, and icy and frosty days. The trends in the extreme weather indices were statistically tested using a non-parametric test. The results showed increases in the minimum and maximum air temperature and the frequency of warm and cold nights and days. The number of CDD and maximum five-day precipitation (RX5day) at the coastal and inland stations increased in the extreme precipitation-related index. The number of warm days and warm nights increased significantly at the majority of weather stations over the 60 year study period. The number of CWD increased during the selected period, but this was not statistically significant. In addition, we found that the temporal variations in the indices became greater over time, which implies the frequency and severity of extreme events such as drought and storm events may increase in the future. This study could help researchers determine the climatic areas at the selected stations that are critical for optimal water resource management planning and/or modeling.

Comparison of multimodel ensembles of global and regional climate models projections for extreme precipitation over four major river basins in southern Africa— assessment of the historical simulations

This study assesses the performance of large ensembles of global (CMIP5, CMIP6) and regional (CORDEX, CORE) climate models in simulating extreme precipitation over four major river basins (Limpopo, Okavango, Orange, and Zambezi) in southern Africa during the period 1983–2005. The ability of the model ensembles to simulate seasonal extreme precipitation indices is assessed using three high-resolution satellite-based datasets. The results show that all ensembles overestimate the annual cycle of mean precipitation over all basins, although the intermodel spread is large, with CORDEX being the closest to the observed values. Generally, all ensembles overestimate the mean and interannual variability of rainy days (RR1), maximum consecutive wet days (CWD), and heavy and very heavy precipitation days (R10mm and R20mm, respectively) over all basins during all three seasons. Simple daily rainfall intensity (SDII) and the number of consecutive dry days (CDD) are generally underestimated. The lowest Taylor skill scores (TSS) and spatial correlation coefficients (SCC) are depicted for CDD over Limpopo compared with the other indices and basins, respectively. Additionally, the ensembles exhibit the highest normalized standard deviations (NSD) for CWD compared to other indices. The intermodel spread and performance of the RCM ensembles are lower and better, respectively, than those of GCM ensembles (except for the interannual variability of CDD). In particular, CORDEX performs better than CORE in simulating extreme precipitation over all basins. Although the ensemble biases are often within the range of observations, the statistically significant wet biases shown by all ensembles underline the need for bias correction when using these ensembles in impact assessments.

Rainfall extremes in Northern Vietnam: a comprehensive analysis of patterns and trends

This study examines the characteristics and trends of extreme rainfall in Northern Vietnam from 1961 to 2018, using daily rainfall data collected from 37 meteorological stations. The study reveals that the average annual rainfall varies significantly across stations, ranging from 1140 mm to 4758 mm. The rainy season accounts for 73% to 92% of the total annual rainfall. Most stations show a declining trend in the annual total rainfall during wet days (PRCPTOT) and the number of wet days (WDAY), while rainfall intensity (SDII) has increased in most stations, particularly during the dry season. This can be attributed to an increase in PRCPTOT and a decrease in WDAY in the dry season. The study also finds a general decreasing trend in the annual maximum 1-day precipitation (RX1day) and consecutive 5-day precipitation (RX5day), as well as for the number of moderate (R16mm) and heavy (R50mm) rainfall days. However, most stations in Northern Vietnam demonstrate no trend in the annual maximum number of consecutive dry days (CDD) and the annual maximum number of consecutive wet days (CWD). Furthermore, the frequency of extreme rainfall events in Northern Vietnam exceeding the 5-year and 10-year return values of 1961-2018 has decreased in recent decades at many stations. Overall, the findings of this study provide insights into the changing patterns of extreme rainfall in Northern Vietnam, with significant implications for climate change adaptation and disaster risk reduction efforts in the region.

Variability in Projected North American Mean and Extreme Temperature and Precipitation Trends for the 21st Century: Model‐To‐Model Differences Versus Internal Variability

AbstractWhile climate change is expected to alter mean and extreme temperature and precipitation over the 21st century, regional changes in these fields remain difficult to project. For a given future emissions scenario, the uncertainty in future projections can be attributed to either model‐to‐model differences, which can presumably be reduced if models are improved, or internal variability, which cannot be constrained to a single outcome but can be used to quantify a range of plausible outcomes. This study examines the range of possible trends in North American mean and extreme temperature and precipitation across phase 6 of the Coupled Model Intercomparison Project models under the SSP3‐7.0 emissions scenario. While model‐to‐model differences primarily govern the spread in mean and extreme temperature trends across these model simulations, the spread in mean and extreme precipitation trends is dominated by internal variability in many regions. A storylines approach—a type of regression‐based analysis—is used to identify key dynamical drivers that explain the variance in future trends across model simulations. The dynamical drivers considered include trends in global mean surface temperature (GMST) and four common modes of climate variability. Combinations of these drivers can reinforce each other to create high‐impact storylines. For example, model simulations with large positive GMST and El Niño‐Southern Oscillation trends are associated with a large reduction in the annual maximum number of consecutive dry days in the American Southwest. However, limiting these storylines to only models with climate sensitivities consistent with observational constraints reduces the likelihood of a large reduction of consecutive dry days in this region.

Projected Changes in Extreme Wet and Dry Conditions in Greece

Earth’s changing climate may have different effects around the planet. Regional changes in temperature and precipitation extremes are associated with damaging natural hazards. Decreases in precipitation are expected to occur in some places at mid-latitudes, for instance the Mediterranean, which has been classified as a climate change hotspot. Droughts are among the most damaging natural hazards with severe consequences in the socio-economic sectors, the environment, and living beings. In contrast, extreme heavy precipitation events may become more frequent. This study aims to project changes in precipitation extremes and assess drought variability and change across Greece. A better knowledge of the potential changes in drought variability under climate change is vital for managing potential risks and impacts associated with dry conditions. The spatiotemporal characteristics of heavy precipitation and drought events in Greece are investigated using extreme precipitation indices such as consecutive wet/dry days, total wet-day precipitation, fraction of total wet-day rainfall, maximum daily precipitation, and heavy precipitation days. The standardized precipitation index and the standardized precipitation and evapotranspiration index are also calculated to assess seasonal dryness variability. The analysis is performed using a sub-set of high-resolution simulations from EURO-CORDEX, under two different representative concentration pathway scenarios. The results show that the region is subject to future dry conditions. Total annual precipitation is found to decrease in most of the country, with western and southern parts tending to be the most vulnerable areas. The annual precipitation is estimated to decrease by 5–20% and 5–25% (RCP4.5 and RCP8.5 respectively) toward the period 2041–2070 and by 10–25% and 15–40% (RCP4.5 and RCP8.5) toward 2071–2100. Drought-related indices reveal positive trends, particularly under the high greenhouse-gas emission scenario, with the number of consecutive dry days increasing by 20–50% and 40–80% (during 2041–2070 and 2071–2100, respectively). On the contrary, extreme precipitation events tend to decrease in the future.

Water balance components and climate extremes over Brazil under 1.5°C and 2.0°C of global warming scenarios.

The online version contains supplementary material available at 10.1007/s10113-023-02042-1.

Is climate really changing? Insights from analysis of 30-year daily CHIRPS and station rainfall data in Zimbabwe

Climate change debate has been ongoing for at least two decades world over. However, an understanding of how much change has occurred in developing countries remains limited. Using a combination of daily Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and gauge rainfall data, this study analysed whether rainfall characteristics over 30 years (1989 to 2018) in Zimbabwe exhibited any significant trends. Firstly, Kappa statistic and a confusion matrix were used to test the appropriateness of CHIRPS satellite derived rainfall estimates for carrying out trend analysis. Thereafter, the Mann Kendall test, Sen's slope and kriging were used, to detect trends, ascertain magnitude of change and map the spatial variation in rainfall characteristics, respectively. The rainfall characteristics included: Total Number of Wet Days (TNWD), Maximum Number of Consecutive Wet Days (MNCWD), Maximum Number of Consecutive Dry Days (MNCDD) and Maximum Rainfall per Day (MRD). Validation results showed that overall accuracy ranged from 0.862 to 0.897 while kappa statistic ranged from 0.739 to 0.81, suggesting a substantial agreement between satellite derived- and gauge rainfall. No statistically significant trends were detected for the four rainfall characteristics analysed at 95% confidence interval. Although no significant trends were detected at 95% confidence interval to signal climate change it was observed that MNCDD, MRD and TNWD were increasing while MNCWD was generally decreasing. This key finding opens new opportunities for geographically targeted and integrated intervention strategies for agricultural and water management in Zimbabwe. This is particularly important considering that Zimbabwe mainly depends on rain fed agriculture and understanding of the key rainfall characteristics can enable proper planning and decision making in terms of adaptation that which can ensure water availability and food security. Food security is fundamental in achieving national security. In addition, this study opens opportunities for further studies on the factors that influence the trends through using sub-daily and daily satellite data for a relatively longer period i.e., >30 years. It is therefore our contention that fine spatial and temporal scales adopted in this study yield better characterisation of changes in rainfall regimes, hence brings out better insights on understanding intra-seasonal fluctuations for climate change detection studies.

Contribution of Climate Scenarios RCP4.5 and RCP8.5 to the Study of Climate Change Impacts on Cocoa Farming in C&amp;#244;te d’Ivoire

In the particular context of climate change in Côte d’Ivoire and the vulnerability of farmers to its effects, one of the major issues is how these changes could impact cocoa yields of cocoa production areas. Thus, the objective of this study is to sustainably increase the resilience of all cocoa farming stakeholders to the impacts of climate change. The study was carried out in the central and southern areas of Côte d’Ivoire with a focus on eleven localities that have many communities of cocoa producers and a humid climate. The rainfall and temperature observation data using come from the CRU, they cover the historical period from 1971 to 2000 at 0.5o × 0.5o horizontal scale. As for the RCP4.5 and RCP8.5 climate scenarios, they come from the CORDEX database and cover the 2021-2050 period. The methodology is based on the calculation of climatic indices sensitive to cocoa cultivation which are the number of consecutive dry days (CDD), the number of consecutive wet days (CWD), the amount of rain during the rainy season and the maximum temperature above 33℃. The results show that for all the localities studied, indices such as CDD and CWD could experience an increase. In addition, the total amount of rain during the long rainy season (April to June) is calculated on the basis of the threshold of 700 mm representing the minimum annual precipitation during the rainy season necessary for good growth of the cocoa tree. It reveals that for the two scenarios the cumulative rainfall will all be greater than 700 mm. Regarding temperatures, the central and southern areas could have a low number of hot days (temperature greater than or equal to 33℃ which is the tolerable threshold for cocoa cultivation). The eleven localities, therefore, remain favorable areas for cocoa cultivation in terms of climatic conditions based on temperature and rainfall, despite the regional dimension of the effects of climate change and the associated constraints.

Performance of CHIRPS dataset for monthly and annual rainfall-indices in Northern Argentina

In this study, we analyze the performance of CHIRPS in comparison with data from 50 rain gauges (OBS) in Northern Argentina (NA) for the 1982–2019 period. The methodology consists in a point-to-pixel comparison using the correlation coefficient (RHO), the mean relative error (MRE), the mean absolute error (MAE) and the Nash-Sutcliffe efficiency (NSE). We analyze monthly rainfall, annual rainfall indices and their trends, differentiating between anchor and no-anchor stations. A comparative analysis is performed further between two NA sub-regions: Northwestern Argentina (NWA) and Northeastern Argentina (NEA). Results indicate that CHIRPS dataset better represents the interannual variability in wetter (drier) months in NWA (NEA). For all months, RHO values are higher in NEA than NWA. For annual rainfall indices, RHO values in most of the stations of NA are non-significant or low for some number-days (with threshold of 1 mm) and very extreme indices, with the exception of the eastern extreme of NA. The less extreme indices (PRCPTOT, R95pad and R99pad) are observed to have higher RHO values (> 0.5 in all cases) in NA, as well as better MRE, MAE and NSE values. Monthly values and annual indices are underestimated in general, especially in NWA no-anchor stations. Most of the significant linear trends observed in rainfall indices are not detected with CHIRPS. As an exception, a relatively better performance for the maximum number of consecutive dry days (CDD) is observed in the sense that CHIRPS detect the positive linear trends in NWA but do not locate them with precision in comparison with OBS data. CHIRPS is not recommended for studies in NA related with the aspects (mean values, interannual variability, linear trends) of rainfall analyzed in this work, especially for the extreme rainfall.

Fire Risk in Traditional Villages of Sumba, Indonesia

Fire is a global problem for traditional villages, especially those dominated by the use of wood and thatch. These places are often crowded, which leads to the rapid spread of fire. The traditional villages on the island of Sumba are architecturally striking, with their tall houses interspersed with ancestral tombs. They are set on an island of grassland landscapes managed using fire. There is little local ability to suppress village fires as they are remote from firefighting services and access to the dwellings is poor. Documentary evidence along with satellite imagery of hotspots have been used to trace the fires on Sumba since 2001. Little meteorological data are accessible for Sumba, so we have used global homogenized records, reassessments and projections of climate to examine long-term change in Sumba. There is a dry season in July–September, which corresponds with the period of most frequent fires. The number of dry-season fires correlates with the number of consecutive dry days, which has been used to establish a likely increase in the potential for fires in the future. There is increased effort to reduce the impact of village fires. Approaches could include reducing the flammability of traditional materials, detection systems and enhanced support of village firefighting capabilities. These may be difficult to introduce given the importance of the architectural heritage and the religious context of village layout, design and governance.

Analysis of Quadratic Correlation between Dryness Indices and Wine Grape Yield to Estimate Future Climate Impacts in Hungary

In many regions, water availability influences grape yield fluctuations more than thermal conditions. This study analyzes dryness indices calculated from observed and simulated RCM data to establish statistical relationships with observed yield data, considered an indicator of food safety. Five dryness indices were analyzed: the number of days without rain, the maximum number of consecutive dry days, climatic water balance, dryness index, and vineyard water indicator. These indices were analyzed for three periods: 1986–2005 (recent past), 2016–2035 (near future) and 2081–2100 (distant future). After this analysis, quadratic regression connections were established between the indices and available wine grape yields in the 22 wine regions of Hungary for 2005–2021 without information on grape varieties and for 2017–2021 with data on grape varieties. Linear agro-technological trends were extracted from these wine grape yield series, whereas the residuals exhibited significant quadratic regression in slightly over 50% of the indices and regions, according to the F-test for the 17 year series. For the short series, these proportions are 29 and 27% for the selected seven white and seven red wine grapes. According to the most significant quadratic regressions, combined with the projected dryness indices, we can expect less average yields with higher interannual variability in the future.

Climate Change over the Mediterranean Region: Local Temperature and Precipitation Variations at Five Pilot Sites

The Mediterranean region is one of the most responsive areas to climate change and was identified as a major “hot-spot” based on global climate change analyses. This study provides insight into local climate changes in the Mediterranean region under the scope of the InTheMED project, which is part of the PRIMA programme. Precipitation and temperature were analyzed in an historical period and until the end of this century for five pilot sites, located between the two shores of the Mediterranean region. We used an ensemble of 17 Regional Climate Models, developed in the framework of the EURO-CORDEX initiative, under two Representative Concentration Pathways (RCP4.5 and RCP8.5). Over the historical period, the temperature presents upward trends, which are statistically significant for some sites, while precipitation does not show significant tendencies. These trends will be maintained in the future as predicted by the climate models projections: all models indicate a progressive and robust warming in all study areas and moderate change in total annual precipitation, but some seasonal variations are identified. Future changes in droughts events over the Mediterranean region were studied considering the maximum duration of the heat waves, their peak temperature, and the number of consecutive dry days. All pilot sites are expected to increase the maximum duration of heat waves and their peak temperature. Furthermore, the maximum number of consecutive dry days is expected to increase for most of the study areas.