Dry Days Research Articles

Climate change impact on Mediterranean viticultural regions and site-specific climate risk-reduction strategies

The global increase in extreme weather and climate events may dramatically impact agriculture, food safety, and socioeconomic dynamics. The Mediterranean basin is already exposed to extreme climatic events, severely challenging viticulture, a pivotal Mediterranean agro–industry. This study aims to understand better how climate is expected to evolve in six viticulturally important Mediterranean regions in Portugal, Italy, Turkey and Morocco, using a 4–member ensemble of climatic model projections under Representative Concentration Pathways (RCP) 4.5 and 8.5 for 2041–2070, and using the 1981–2010 period as a baseline. By comparing the main specific challenges these locations will face, we comparatively define the best strategies to reduce the impacts of climate change at the national and regional levels. Projections show increases in overall temperatures, up to + 3.6°C than the historical baseline, whilst precipitation projections indicate decreases that could reach 36% of the overall annual precipitation. Biological effective degree days, consecutive dry days, growing season length, tropical nights, or very heavy precipitation days, also show challenging prospects for viticulture in these countries. A screening of the adaptative strategies already undertaken in the studied countries suggests that growers are taking reactive rather than preventive strategies. Moreover, the discussion of the most suitable strategies in this study is region–specific, i.e., prioritised by the specific needs of each location. The conclusions drawn herein may support local growers, improving their decision–making based on the most adequate adaptive strategies to their conditions, thus optimising their sustainable production under changing climates.

Assessing Treatments to Mitigate End-Face Cracking in Air-Dried Acacia dealbata Logs

Acacia dealbata Link, known as Mimosa in Portugal, is an invasive hardwood species with potential for construction use, but research is limited. The available stock of small-diameter juvenile wood logs can help reduce this gap, but tangential cracking at log ends challenges fastener connections. This study evaluated different treatments to control and reduce end-face cracking in small wood logs during air drying, an economical and environmentally friendly procedure. The extreme two-thirds of sixteen Mimosa logs were subjected to two treatments: one with longitudinal kerfs 15 mm deep along the length (two and three kerfs) and the other with a hollow in the center up to half the length (16 mm and 30 mm diameters). Over 219 days of air drying and compared with the central part, kerfing treatments significantly reduced outer-wood tangential cracking (p < 0.001), with the three kerfs also reducing crack numbers (p < 0.05) but increasing significantly cracks near the pith (p < 0.01). The 30 mm central hollow significantly reduced central perforation cracking (p < 0.05). Prospectively, the results suggest that a combined treatment approach involving cross-cuts could help reduce and/or control end cracking, thereby improving the suitability of wild Mimosa logs for construction use.

Toughness Evolution of Flax-Fiber-Reinforced Composites under Repeated Salt Fog-Dry Aging Cycles.

This research examined the response of flax-fiber-reinforced composites (FFRCs) to simulated outdoor conditions involving repeated exposure to salt fog and drying. The study investigated the effect of cycles on the toughness of the FFRCs. To achieve this, the composites were exposed to humidity (salt fog) for 10 days, followed by 18 days of drying in cycles. A total of up to 3 cycles, each lasting 4 weeks, were conducted over a 12-week period. Throughout this process, changes in the material's weight, water absorption, and mechanical properties were monitored by water uptake and three-point bending tests. The findings revealed the significant impact of these humid-dry cycles on the mechanical response of the FFRCs. When exposed to humid environments without drying, the composite's toughness increased significantly, due to a weakening effect more pronounced for stiffness, with strength reductions of about 20%. However, subsequent drying partially restored the material's performance. After 18 days of drying, the composite regained most of its initial performance.

Future Prediction of Consecutive Dry Days (CDD) in Rapti River Basin Using Model ACCESS-CM2 Climate Projection

Future Prediction of Consecutive Dry Days (CDD) in Rapti River Basin Using Model ACCESS-CM2 Climate Projection

Historical and future extreme climate events in highly vulnerable small Caribbean Islands

Small Caribbean islands are on the frontline of climate change because of sea level rise, extreme rainfall and temperature events, and heavy hurricanes. The Archipelago of San Andrés, Providencia, and Santa Catalina (SAI), are Caribbean islands belonging to Colombia and declared a Biosphere Reserve by UNESCO. SAI is highly vulnerable to climate change impacts but no hydroclimatological study quantified the extreme climatic changes yet. This study analyzes historical (1960s-2020, 7 stations) and future (2071–2100, CMIP6 multi-model ensemble, for four scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) trends in mean and extreme precipitation and temperature duration, frequency, and intensity. We find that heatwaves have more than tripled in frequency and doubled their maximum duration since the end of the ‘80 s. Precipitation is historically reduced by 5%, with a reduction recorded in 5 stations and an increase in 2, while extreme rainfall events significantly increased in frequency and intensity in most stations. The hotter-and-drier climate is amplified in the future for all scenarios, with much drier extremes (e.g., -0.5─-17% wet days, +8%─30% consecutive dry days, and +60%─89% in hot days). Although we show that hurricanes Categories IV and V near SAI (< 600 km) more than doubled since the’60 s, only a small fraction of extreme rainfall in the archipelago is associated with hurricanes or tropical storms. La Niña events also have no substantial influence on extreme precipitation. Interestingly, opposite and heterogeneous historical extreme rainfall trends are found across such small territory (< 30 km2). Thus, downscaled hydrometeorological data and model simulations are essential to investigate future extreme climatic events and strengthen small Caribbean islands' climate change adaptation efforts.

Sun-Dried and Convective-Dried Octopus vulgaris Quality Parameters and Estimated Shelf Life During Ambient Temperature Storage

ABSTRACT Drying process was used in this study as a preserving method of octopus quality during storage. Octopus vulgaris quality attributes in terms of pH, water activity, color properties, total volatile basic nitrogen (TVB-N), trimethylamine (TMA), total viable count, and yeast and molds (YM) were evaluated. Samples were dried under sun drying and convective air drying and stored at ambient temperature. During storage, TVBN and TMA obtained were within the recommended level for good quality of dried samples. Accelerating shelf-life test was evaluated based on TVB-N, TMA, and YM, with shelf lives of 388 and 603 days for convective air drying and sun drying, respectively.

Extreme climate events and future population exposure under climate change in the Huaihe River basin of China based on CMIP6 multimodel ensembles projections

AbstractThe Huaihe River basin (HRB) of China located in the climate transition zone between warm temperate and subtropical areas is highly sensitive to climatic change. However, the changes in future climate extreme events under anthropogenic warming and the population exposure to these climate extremes in HRB remain unexplored. Here, using the eight commonly used extreme climate indices and based on the bias‐corrections of 16 global climate models (GCMs) in CMIP6, we present a projection and uncertainty analysis of extreme events and investigate the corresponding population exposure risk in HRB under three shared socioeconomic pathways (SSP1‐2.6, SSP2‐4.5, SSP5‐8.5). The 16‐GCM ensemble mean projects an evident warming trend under all three scenarios with a total increase of 25.6–68.0 days in summer days (&gt;25°C) by the end of the century in HRB. Larger increases (decreases) in maximum and minimum temperatures (frost days) are projected in the western HRB. Very heavy rain days (R20mm), maximum 5‐day precipitation (RX5day) and simple daily intensity index (SDII) will experience intensification across most of HRB (especially in southern and western HRB). The consecutive dry days is projected to decrease in northwestern HRB and increase in southern HRB. However, there is a large spatial variability in GCM uncertainty with a higher SSP scenario generally having higher uncertainty. Increases in summer days and R20mm exacerbate population exposure in HRB in near future (2030–2059), but in far future (2070–2099) although summer days (R20mm) continues to rise, population exposure is expected to decrease due to the rapid decline in population density.

Precipitation pulses and intraseasonal drought in Northeast China

30 years meteorological data were collected to analyze variations of precipitation amount, number of days, frequency and intervals using the Mann-Kendall (MK) and t test and relationships between rainfall patterns and climates over rainfed farmland. The results indicated that annual precipitation amount had a downward trend from 1989-2018. Whether in different years or months, small precipitation events(0&lt;P ≤5 mm) are a dominating feature, significantly and positively related to annual total precipitation, which mainly occur in early or late growing seasons (May or September). The precipitation intervals decrease along with the category, and are longer in the drought years than in the humid years. Percent of intervals &lt;6 days are more than 65%, the average dry days are 5. Short intervals(1-3 days) increase from May, get to the maximum in mid-growing season. Long intervals (&gt;4 days) are opposite. While in growing seasons, the average dry days are &lt;3 days.

Effects of Parity on Service per Conception, Gestation Length, Milk Yield, Calving Interval, and Calf Birth Weight of Crossbred Dairy Cows

AbstractThe average lactation number for a stable herd dairy cow would be 3.4 and many dairy farmers do not keep dairy cows for extended lactation numbers beyond the 6th lactation number. Thus, there is a limited number of information focused on the later lactation number or parity (6-10) effect on lactation traits. Therefore, this study was conducted to evaluate the effect of lactation number on the number of services per conception, gestation length, lactation milk yield, lactation length, calving interval, and calve weight in crossbred Holstein Friesian cows. The record data at Haramaya University dairy farm was collected and compiled to assess the effects of lactation numbers. Retrospective data records of 1863, 1742, 1280, 1280, 1329, 1170, and 848 data of dairy cows were respectively used for evaluating the number of services per conception, gestation length, lactation length, lactation milk yield, calving interval, and calf birth weight. The study revealed that lactation number significantly affected the total lactation milk yield, lactation length, calving interval, and calf birth weight but it did not affect the number of services per conception and gestation length. Based on this study result, crossbred Holstein Friesian cows could be productive until the 8th lactation number without a significant decrease in the lactation milk yield. Therefore; lactation number should be used as an important trait in the performance of dairy cattle. Further study should be conducted to evaluate the effect of lactation number on other lactation traits such as dry period, days open, and milk composition.Keywords: Birth weight; Calving interval; Gestation; Lactation; Milk yield; Parity

Critical Role of Vertical Radiative Cooling Contrast in Triggering Episodic Deluges in Small‐Domain Hothouse Climates

AbstractSeeley and Wordsworth (2021, https://doi.org/10.1038/s41586‐021‐03919‐z) showed that in small‐domain cloud‐resolving simulations the temporal pattern of precipitation transforms in extremely hot climates (≥320 K) from quasi‐steady to organized episodic deluges, with outbursts of heavy rain alternating with several dry days. They proposed a mechanism for this transition involving increased water vapor greenhouse effect and solar radiation absorption leading to net lower‐tropospheric radiative heating. This heating inhibits lower‐tropospheric convection and decouples the boundary layer from the upper troposphere during the dry phase, allowing lower‐tropospheric moist static energy to build until it discharges, resulting in a deluge. We perform cloud‐resolving simulations in polar night and show that the same transition occurs, implying that some revision of their mechanism is necessary. We perform further tests to show that episodic deluges can occur even if the lower‐tropospheric radiative heating rate is negative, as long as the magnitude of the upper‐tropospheric radiative cooling is about twice as large. We find that in the episodic deluge regime the period can be predicted from the time for radiation and reevaporation to cool the lower atmosphere.

Sensitivity and feature importance of climate factors and evaluation of different machine learning models for predicting fire hotspots in Kalimantan, Indonesia

&lt;p&gt;Hotspots as indicators of forest fires capable of quickly monitoring large areas are often predicted using various machine learning methods. However, there is still little research that analyzes the sensitivity and feature importance of each predictor that forms a machine learning prediction model. This study evaluates and compares several machine learning methods to predict hotspots in Kalimantan. Using the most accurate machine learning model, each climate factor used as a predictor is analyzed for its sensitivity and feature importance. Some of the machine learning methods used include random forest, gradient boosting, Bayesian regression, and artificial neural networks. Meanwhile, several measures of sensitivity and feature importance used are variance-based, density-based, and distribution-based sensitivity indices, as well as permutation and Shapley feature importance. Evaluation of the ML model concluded that the Bayesian linear regression model outperformed other ML models, based on RMSE and explained variance score. Meanwhile, tree-based models, such as random forest and gradient boosting, are indicative of overfit. Based on the results of sensitivity analysis and feature importance, the number of dry days is the most important feature for the Bayesian linear regression model in predicting the number of hotspots in Kalimantan.&lt;/p&gt;

The impact of extreme precipitation on water use efficiency along vertical vegetation belts in Hengduan Mountain during 2001 and 2020

In the context of climate change, extreme precipitation events are continuously increasing and impact the water‑carbon coupling of ecosystems. The vertical vegetation zonation, as a characteristic of mountain ecosystems, reflects the differences in vegetation response to climate change at different elevations. In this study, we used the water use efficiency (WUE) as an indicator to evaluate the water‑carbon relationship. By using MODIS data, we analyzed the spatiotemporal patterns of gross primary productivity (GPP), evapotranspiration (ET), and WUE from 2001 to 2020, as well as the responses of WUE to extreme wetness factor Number of precipitation days (R0.1), extreme dryness factor Consecutive dry days (CDD), and meteorological factors under the vertical vegetation zonation. Our results showed that annual GPP and ET displayed a significant increasing trend between 2001 and 2020, whereas WUE showed a weak decreasing trend. Spatially, GPP and WUE decreased with increasing elevation. Analyzing the WUE of mountainous ecosystems as a unified whole may not precisely capture the reactions of vegetation to severe rainfall occurrences. In fact, across different vegetation belts in mountainous areas, there exists a negative correlation between WUE and R0.1, and a positive correlation with CDD. In terms of meteorological factors, the temporal variation of GPP was primarily associated with vapor pressure deficit (VPD) and temperature (Ta), while those of ET was mainly related to soil water content (SWC). WUE was affected by a combination of meteorological factors and had a certain degree of variation between different altitude intervals. These findings contribute to a better understanding and prediction of the relationship between extreme rainfall climate and water‑carbon coupling in mountainous areas.

Spatio-temporal change of winter wheat yield and its quantitative responses to compound frost-dry events – An example of the Huang-Huai-Hai Plain of China from 2001 to 2020

Extreme climate events such as frost and drought have great influence on wheat growth and yield. Understanding the effects of frost, drought and compound frost-dry events on wheat growth and yield is of great significance for ensuring national food security. In this study, wheat yield prediction model (SCYMvp) was developed by combining crop growth model (CGM), satellite images and meteorological variables. Wheat yield maps in the Huang-Huai-Hai Plain (HHHP) during 2001–2020 were generated using SCYMvp model. Meanwhile, accumulative frost days (AFD), accumulative dry days (ADD) and accumulative frost-dry days (AFDD) in different growth periods of wheat were calculated, and the effects of frost and drought on wheat yield were quantified by the first difference method and linear mixed model. The results showed that wheat yield increased significantly, while the rising trend was obvious at more than half of the regions. Extreme climate events (ECEs) showed a relatively stable change trend, although the change trend was significant only in a few areas. Compared with frost and drought in the early growth period, ECEs in the middle growth period (spring ECEs) had more negative effects on wheat growth and yield. Wheat yield was negatively correlated with spring ECEs, and yield loss was between 4.6 and 49.8 kg/ha for each 1 d increase of spring ECEs. The effects of spring ECEs on wheat yield were ranked as AFDD > AFD > ADD. The negative effect of ADD on wheat yield in the late growth period was higher than that in the other periods. The negative effects of spring ECEs on yield in southern regions were higher than those in northern regions. Overall, due to the adverse effects of frost and drought on wheat yield in the middle and late growth periods, the mean annual yield loss was 6.4 %, among which spring AFD caused the greatest loss to wheat yield (3.1 %). The results have important guiding significance for formulating climate adaptation management strategies.

Simultaneous increase in temperature and dry days in West African transboundary Benue River Basin

Simultaneous increase in temperature and dry days in West African transboundary Benue River Basin

Evaluating Hydrogeomorphic Condition Across Ecosystem States in a Non-tidal, Brackish Peat Marsh of the Florida Coastal Everglades, USA

Emergent marsh and open water have been identified as alternate stable states in tidal marshes with large, relative differences in hydrogeomorphic conditions. In the Florida coastal Everglades, concern has been raised regarding the loss of non-tidal, coastal peat marsh via dieback of emergent vegetation and peat collapse. To aid in the identification of alternate stable states, our objective was to characterize the variability of hydrogeomorphic and biologic conditions using a field survey and long-term monitoring of hydrologic and geomorphic conditions across a range of vegetated (emergent, submerged) and unvegetated (open water) communities, which we refer to as “ecosystem states,” in a non-tidal, brackish peat marsh of the coastal Everglades. Results show (1) linear relationships among field-surveyed geomorphic, hydrologic, and biologic variables, with a 35-cm mean difference in soil surface elevation between emergent and open water states, (2) an overall decline in soil elevation in the submerged state that was related to cumulative dry days, and (3) a 2× increase in porewater salinity during the dry season in the emergent state that was also related to the number of dry days. Coupled with findings from previous experiments, we propose a conceptual model that describes how seasonal hydrologic variability may lead to ecosystem state transitions between emergent and open water alternate states. Since vegetative states are only moderately salt tolerant, as sea-level rise pushes the saltwater front inland, the importance of continued progress on Everglades restoration projects, with an aim to increase the volume of freshwater being delivered to coastal wetlands, is the primary management intervention available to mitigate salinization and slow ecosystem state shifts in non-tidal, brackish peat marshes.

Trend analysis of extreme rainfall indices from CHIRPS precipitation estimates over the Lake Tana sub-basin, Abbay Basin of Ethiopia.

Ethiopia is among the African nations most susceptible to climate change because of its frequent droughts and heavy rainfall. Therefore, hydrological and water management problems require an investigation of regional variability and extreme rainfall patterns. This study analyzed the spatiotemporal trends of extreme rainfall in the Lake Tana sub-basin (LTSB) of Ethiopia's upper Blue Nile basin (UBNB) between 1981 and 2019. The trend and geographic patterns of ten extreme rainfall indices are evaluated using high-resolution data from Climate Hazards Group InfraRed Precipitation Stations (CHIRPS). The researcher used RClimDex, an R software tool, to analyze the ten severe rainfall indices. The variability of the extreme rain indices was also assessed by applying the standard anomaly index (SAI). The trend analysis shows that the majority of rainfall indices decreased in the majority of station locations. Among the rainfall locations, the decreasing trend was only significant in 40% consecutive wet days (CWD), 13.33% (R95p and R99p), and 6.66% highest rainfall amount in a 1-day period (RX1day). In contrast, significant positive patterns were revealed in the incidence of rainfall events of number of heavy precipitation days (R10mm), annual total wet day rainfall (PRCPTOT), and consecutive dry days (CDD), with significant positive trends of 26.66% (R10mm) and 40% (PRCPTOT). Furthermore, a spatial distribution result of extreme rainfall trends reveals considerable variations between stations location. Thus, these findings point to the necessity of creating adaptation and mitigation plans for climate change variability within the sub-basin.

The Bioclimates of India in Relation to the Vegetational Criteria

The purpose of a climatic classification is to characterise the climatic regions in terms of meteorological elements like temperature and precipitation which are the most decisive factors in determining the landscape of the earth. The plant-climate relation is so close that it is possible to differentiate the types of climates such as equatorial, tropical, mediterranean, with their different shades such as humid, sub-humid, arid using the characters of the plant-cover. In a physical classification of the climate, an arid or a humid region is defined on the basis of annual precipitation, the number of dry days or dry months in the year or by means of several climatic formulae.In the present work emphasis is laid on the term "bioclimate". It is defined as the climate in relation to the life and is expressed by an index of aridity-humidity. This index is proposed on the basis of combining three essential ecological factors viz. temperature, precipitation and dry period. Correlations are obtained between the above index of aridity-humidity and four distinct criteria of the plant-kingdom : (1) Floristic criteria, (2) Vegetational criteria, (3) Morpho-ecological criteria and (4) Agronomic criteria.

Longitudinal assessment of extreme climate events in Kinnaur district, Himachal Pradesh, north-western Himalaya, India.

It is vital to keep an eye on changes in climatic extremes because they set the stage for current and potential future climate, which usually have a reasonable adverse impact on ecosystems and society. The present study examines the variability and trends in precipitation and temperature across seasons in the Kinnaur district, offering valuable insights into the complex dynamics ofthe Himalayan climate. Using Climatic Research Unit gridded Time Series (CRU TS) datasets from 1951 to 2021, the study analyzes the data to produce 28 climate indices based on India Meteorological Department (IMD) convention indices and Expert Team on Climate Change Detection and Indices (ETCCDI). Although there may be considerable variation in climate indices in terms of absolute values within different products, there is consensus in both long-term trends and inter-annual variability. Analysis shows that even within a small area, there is variability in the magnitude and direction of historic temperature trends. Initially, the datawere subjected to rigorous quality control procedures, which involved identifying anomalies. Statistical analysis like trend analysis, employing Mann-Kendall test and Sen's slope estimator, reveal significant (p < 0.05) increase in consecutive dry days (CDD) at 0.03days/year and decrease in consecutive wet days (CWD) at 0.02days/year. Notably, the frequency of heavy precipitation occurrences showed an increasing trend. Changes in precipitation in the Western Himalaya are driven by a complex interplay of orographic effects, monsoonal dynamics, atmospheric circulation patterns, climate change, and localized factors such as topography, atmospheric circulation patterns, moisture sources, land-sea temperature contrasts, and anthropogenic influences. Moreover, in case of temperature indices, there is significant increasing trend observed. Temperature indices indicate a significant annual increase in warm nights (TN90p) at 0.06%/year and warm days (TX90p) at 0.11%/year. Extreme temperature events have been trending upward, with monthly daily maximum temperature (TXx) increasing by 1.5°C yearly. This study enhances our comprehension of the global warming phenomenon and underscores the importance of acknowledging alterations in the water cycle and their repercussions on hydrologic resources, agriculture, and livelihoods in the cold desert of the northwestern Indian Himalaya.

Quantifying annual microplastic emissions of an urban catchment: Surface runoff vs wastewater sources

Urban clusters are recognized as hotspots of microplastic pollution, and the associated urban rivers convey microplastics into the global oceans. Despite this knowledge, the relative contributions of various sources to the annual microplastic emissions from urban catchments remain scarcely quantified. Here, we quantified microplastic emissions from a riverine urban catchment in Japan. The total microplastics (size range: 10–5000 μm) released from the catchment amounted to 269.1 tons/annum, of which 78.1% is contributed by surface runoff and other uncontrolled emissions (UCE), and 21.1% emerges from the regulated wastewater (controlled emissions; CE), implying that approximately one-fifth is intercepted and removed by the wastewater treatment plants (WWTPs). This further indicated higher microplastic pollution by unmanaged surface runoff compared to untreated wastewater. In the dry season, WWTPs contributed significantly to the reduction of total microplastic emissions (95%) compared to wet periods (8%). On an annual scale, the treated effluent occupies only 0.1% of the total microplastics released to the river network (212.4 tons/annum), while the remaining portion is dominated by UCE, i.e., primarily surface runoff emissions (98.9%), and trivially by the background microplastic inputs that are potentially derived through atmospheric depositions in dry days (1.0%). It was shown that moderate and heavy rainfall events which occur during 18% of the year (within the context of Japan), leading to 95% of the annual microplastic emissions, are crucial for pollution control of urban rivers. Furthermore, our study demonstrated that surface area-normalized microplastic emissions from an urban catchment (∼0.8 tons/km2/annum) is globally relevant, especially for planning microplastic interventions for developed cities.

People’s Perception of Climate Change Impacts on Subtropical Climatic Region: A Case Study of Upper Indus, Pakistan

In developing countries like Pakistan, the preservation of the environment, as well as people’s economies, agriculture, and way of life, are believed to be hampered by climate change. Understanding how people perceive climate change and its signs is essential for creating a variety of adaptation solutions. In this study, we aim to bridge the gap in current research within this area, which predominantly relies on satellite data, by integrating qualitative assessments of people’s perceptions of climate change, thereby providing valuable ground-based observations of climate variability and its impacts on local communities. Field-based data were collected at different altitudes (upstream (US), midstream (MS), and downstream (DS)) of the Upper Indus Basin using both quantitative and qualitative assessments in 2017. The result shows that these altitudes are highly variable in many contexts: socioeconomic indicators of education, agriculture, income, women empowerment, health, access to basic resources, and livelihood diversifications are highly variable in the Indus Basin. The inhabitants of the Indus Basin perceive the climate changing around them and report impacts of this change as increase in overall temperatures (US 96.9%, MS 97%, DS 93.6%) and erratic rainfall patterns (US 44.1%, MS 73.3%, DS 51.0%) resulting in increased water availability for crops (US 38.6%, MS 39.7%, DS 54.8%) but also increasing number of dry days (US 56.7%, MS 85.5%, DS 67.1%). Communities at these altitudes said that agriculture was their primary source of income, making them particularly vulnerable to the effects of climate change and the dangers that go along with it. The insights are useful for determining what information and actions are required to support local climate-related hazard management in subtropical climate regions. Moreover, it is vital to launch a campaign to raise awareness of potential hazards, as well as to provide training and an early warning system.