Climate, Volume 11, Issue 11 (November 2023) – 18 articles

In the context of climate change, where the average temperature has risen in recent decades on the Mediterranean coast of the Iberian Peninsula, bioclimatic indicators show an increase in thermal discomfort. This is especially relevant in regions with a clear focus on mass and seasonal sun and beach tourism, with a large number of tourists experiencing discomfort in hot and humid summer environments. The research analyses the temporal evolution (1967–2022) of the coasts of the provinces of Alicante and Murcia (Spain) using the Climate Comfort Index (CCI), divided into four different regions. Used are 14 coastal meteorological observatories divided into four regions. Trend analysis was performed using the Mann–Kendall (MKT) and Theil–Sen (TSE) tests. The results revealed a loss of climate comfort during the summer season (−0.3 to −0.4/decade), as well as an expansion of the warm period toward June and early September, with an increase of 38.7 days in “hot” thermal comfort. The increase in thermal discomfort in the summer is influenced by an increase in average temperature (0.5 to 0.7 °C/decade) and a reduction in the average relative humidity (−1.0 to −2.1%/decade) and wind speed (−0.2 to −0.9 km/h/decade). In the last 22 years (2000–2022), decreases (p  ≤ 0.05) have been recorded in July and September (−0.2 to −0.4/decade), reaching “excessive heat” climatic comfort thresholds for the first time. Finally, there has been an increase in thermal comfort in winter, especially during December in recent years (2000–2022). Full article

This study investigated tropical cyclone (TC)-induced flooding in coastal regions of Australia due to the impact of TC Debbie in 2017 utilising a differential evolution-optimised random forest to model flood susceptibility in the region of Bowen, Airlie Beach, and Mackay in North Queensland. Model performance was evaluated using a receiver operating characteristic curve, which showed an area under the curve of 0.925 and an overall accuracy score of 80%. The important flood-influencing factors (FIFs) were investigated using both feature importance scores and the SHapely Additive exPlanations method (SHAP), creating a flood hazard map of the region and a map of SHAP contributions. It was found that the elevation, slope, and normalised difference vegetation index were the most important FIFs overall. However, in some regions, the distance to the river and the stream power index dominated for a similar flood hazard susceptibility outcome. Validation using SHAP to test the physical reasoning of the model confirmed the reliability of the flood hazard map. This study shows that explainable artificial intelligence allows for improved interpretation of model predictions, assisting decision-makers in better understanding machine learning-based flood hazard assessments and ultimately aiding in mitigating adverse impacts of flooding in coastal regions affected by TCs. Full article

On 20 July 2021, an extreme rainstorm battered Zhengzhou in China’s Henan Province, killing 302 people, including 14 individuals who drowned in a subway tunnel and 6 who drowned in a road tunnel. As the global climate warms, extreme weather events similar to the Zhengzhou flood will become more frequent, with increasingly catastrophic consequences for society. Taking a case study-based approach by focusing on the record-breaking Zhengzhou flood, this paper examines the governance capacity of inland cities in North China for managing extreme precipitation and flooding events from the perspective of the flood risk management process. Based on in-depth case analysis, our paper hypothesizes that inland cities in North China still have low risk perceptions of extreme weather events, which was manifested in insufficient pre-disaster preparation and prevention, poor risk communication, and slow emergency response. Accordingly, it is recommended that inland cities update their risk perceptions of extreme rainfall and flooding events, which are no longer low-probability, high-impact “black swans”, but turning into high-probability, high-impact “gray rhinos.” In particular, cities must make sufficient preparation for extreme weather events by revising contingency plans and strengthening their implementation, improving risk communication of meteorological warnings, and synchronizing emergency response with meteorological warnings. Full article

In semi-arid regions, climate change has affected crop growing season length and sowing time, potentially causing low yield of the rainfed staple crop pearl millet (Pennisetum glaucum L.) and food insecurity among smallholder farmers. In this study, we used 1994–2023 rainfall data from Namibia’s semi-arid North-Central Region (NCR), receiving November–April summer rainfall, to analyze rainfall patterns and trends and their implications on the growing season to propose climate adaptation options for the region. The results revealed high annual and monthly rainfall variabilities, with nonsignificant negative trends for November–February rainfalls, implying a shortening growing season. Furthermore, we determined the effects of sowing date on grain yields of the early-maturing Okashana-2 and local landrace Kantana pearl millet varieties and the optimal sowing window for the region, using data from a two-year split-plot field experiment conducted at the University of Namibia—Ogongo Campus, NCR, during the rainy season. Cubic polynomial regression models were applied to grain-yield data sets to predict grain production for any sowing date between January and March. Both varieties produced the highest grain yields under January sowings, with Kantana exhibiting a higher yield potential than Okashana-2. Kantana, sown by 14 January, had a yield advantage of up to 36% over Okashana-2, but its yield gradually reduced with delays in sowing. Okashana-2 exhibited higher yield stability across January sowings, surpassing Kantana’s yields by up to 9.4% following the 14 January sowing. We determined the pearl millet optimal sowing window for the NCR to be from 1–7 and 1–21 January for Kantana and Okashana-2, respectively. These results suggest that co-cultivation of early and late pearl millet varieties and growing early-maturing varieties under delayed seasons could stabilize grain production in northern Namibia and enhance farmers’ climate adaptation. Policymakers for semi-arid agricultural regions could utilize this information to adjust local seed systems and extension strategies. Full article

This paper addresses the riverine flood events that have occurred in Greece over the last 136 years (i.e., during the 1886–2022 period), focusing, amongst others, on the case of urban floods. The flood record of various sites of the country has been collected and analyzed to determine their spatial and temporal distribution. Greece is a country where flood data and records are very scarce. Therefore, as there is not an integrated catalog of Greek floods spanning from the 19th century to recently, this is the first attempt to create an integrated catalog for Greece. The sources used include published papers, local and regional newspapers and public bodies (mainly the Ministry of Environment and Energy and the official websites of Greek municipalities). Additionally, the main factors responsible for their occurrence have been issued, regarding the country’s climatic, geological and geomorphological setting, as well as human interventions. In addition, the atmospheric circulation driving factors of floods are assessed via an unsupervised neural network approach (i.e., Self-Organizing Maps). Based on the results of this research, an online GIS-based database has been created, depicting the areas that have been struck by riverine floods in Greece. By clicking a flood event in the online database, one can view several characteristics, depending on data availability, such as duration and height of the rainfall that caused them and number of fatalities. Long-term trends of mean and extremes seasonal precipitation also linked to the spatial distribution of floods. Our analysis shows that urban floods are a very large portion of the overall flood record, and they mainly occur in the two large urban centers, Athens and Thessaloniki, as well as near large rivers such as Pineios. Autumn months and mainly November are the periods with higher flood hazards, based on past records and cyclonic atmospheric circulation constitutes the principal driving factor. Our results indicate that a flood catalog at national level is of fundamental importance, as it can provide valuable statistical insights regarding seasonality, spatial distribution of floods, etc., while it can also be used by stakeholders and researchers for flood management and flood risk analysis and modelling. Full article

This study explores spatial and temporal changes in the rainfall climatology of Puerto Rico in order to identify areas where annual, seasonal or daily precipitation is increasing, decreasing, or remaining normal. Total annual, seasonal, and daily rainfall were retrieved from 23 historical rain gauges with consistent data for the 1956–2021 period. Mann–Kendall trend tests were done on the annual and seasonal rainfall series, and percentage change differences between two different climatologies (1956–1987 and 1988–2021) were calculated. Most of the stations did not exhibit statistically significant annual or seasonal trends in average rainfall. However, of the sites that did experience changes, most of them had statistically significant decreasing trends in mean precipitation. The annual, dry, and early wet season had more sites with negative trends when compared with positive trends, especially in the northwestern and southeastern region of the island. The late wet season was the only period with more sites showing statistically significant trends when compared with negative trends, specifically in the northern region of the island. Results for daily events show that extreme rainfall occurrences have generally decreased, especially in the western region of the island. When the 1955–1987 and 1988–2022 climatologies are compared, the results for annual average rainfall show two main regions with mean precipitation reductions, and those are the northwestern and southeastern areas of the island. The dry season was the only period with more areas exhibiting percentage increases in mean rainfall when the two climatologies were analyzed. The early and late wet season months exhibited similar patterns, with more areas on the island showing negative percentage decreases in average seasonal precipitation. The best predictor for the decreasing annual and seasonal trend in the northwest was a higher sea level pressure, and the variable that best explained the increasing trend in the northeast was total precipitable water. Full article

Homogenization of climatic time series aims to remove non-climatic biases which come from the technical changes in climate observations. The method comparison tests of the Spanish MULTITEST project (2015–2017) showed that ACMANT was likely the most accurate homogenization method available at that time, although the tested ACMANTv4 version gave suboptimal results when the test data included synchronous breaks for several time series. The technique of combined time series comparison was introduced to ACMANTv5 to better treat this specific problem. Recently performed tests confirm that ACMANTv5 adequately treats synchronous inhomogeneities, but the accuracy has slightly worsened in some other cases. The results for a known daily temperature test dataset for four U.S. regions show that the residual errors after homogenization may be larger with ACMANTv5 than with ACMANTv4. Further tests were performed to learn more about the efficiencies of ACMANTv4 and ACMANTv5 and to find solutions for the problems occurring with the new version. Planned changes in ACMANTv5 are presented in the paper along with related test results. The overall results indicate that the combined time series comparison can be kept in ACMANT, but smaller networks should be generated in the automatic networking process of the method. To improve further the homogenization methods and to obtain more reliable and more solid knowledge about their accuracies, more synthetic test datasets mimicking the true spatio-temporal structures of real climatic data are needed. Full article

Tornadoes present an undisputable danger to communities throughout the United States. Despite this known risk, there is a limited understanding of how tornado frequency varies spatially at the mesoscale across county or city area domains. Furthermore, while previous studies have examined the relationships between various climate indices and continental or regional tornado frequency, little research has examined their influence at a smaller scale. This study examines the relationships between various climate indices and regional tornado frequency alongside the same relationships at the mesoscale in seven cities with anomalous tornado patterns. The results of a correlation analysis and generalized linear modeling show common trends between the regions and cities. The strength of the relationships varied by region, but, overall, the ENSO had the greatest influence on tornado frequency, followed in order by the PNA, AO, NAO, MJO, and PDO. However, future research is critical for understanding how the effects of climate indices on tornado frequency vary at different spatial scales, or whether other factors are responsible for the atypical tornado rates in certain cities. Full article

The Climate Risk and Vulnerability Assessment (CRVA) is a systematic process used to identify gaps in regional climate adaptation strategies. The CRVA method assesses regional vulnerability, adaptation capacity, exposure, and sensitivity to climate change to support improved adaptation policies. This CRVA study assesses Georgia’s climate exposure, geographic sensitivity, and socio-economic sensitivity by focusing on the impacts of climate change on regional hydrology. The projected change in climate extreme indices, defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), is assessed against the 1961–1990 baseline under future Representative Concentration Pathway (RCP) scenarios. These indices encompass various climate factors such as the maximum daily temperature, warmth duration, total precipitation, heavy and extreme precipitation, maximum 5-day precipitation, and consecutive drought duration. This evaluation helps us understand the potential climate exposure impacts on Georgia. The climate-induced geographic sensitivity is examined based on water stress, drought risk, and changes in soil productivity using the Normalized Difference Vegetation Index (NDVI). The climate-induced socio-economic sensitivity is determined using the Gross Domestic Product per capita (GDP), Human Development Index, Education Index, and population density. The highest vulnerability to climate change was found in the Kakheti and Kvemo Kartli regions, with the vulnerability index values ranging from 6 to 15, followed by Mtskheta-Mtianeti, Samtskhe–Javakheti, and Shida Kartli with vulnerability index values ranging from 2 to 8. The location of these regions upstream of the Alazani-Iori, Khrami-Debeda, and Mktvari river basins indicates that the country’s water resources are vulnerable to climate change impacts in the future under the RCP 4.5 and 8.5 scenarios. Full article

Resistance to clean energy policy in the United States stems partly from public hesitancy and skepticism toward anthropogenic climate change. This article examines self-declared climate change skeptics’ views of clean energy policy along a continuum of skeptical thought, spanning from epistemic denial to attribution doubt. To perform this, we use data from an online survey administered in the US Pacific Northwest and a series of pilot interviews conducted with skeptics in the same region. Results reveal that skeptics’ support for clean energy policy is consistently linked with their environmental concern across the skepticism continuum. Conspiracy ideation and distrust in science lead to a reduction in support. However, the positive effect of environmental concern trumps the effects of these beliefs. Important and hopeful implications of these findings for climate change communication and policy are discussed. Full article

Understanding the factors that influence the diversity and distribution of butterfly species is crucial for prioritizing conservation. The Eastern Ghats of India is an ideal site for such a study, where butterfly diversity studies have yet to receive much attention. This study emphasized the butterfly assemblages of three prominent habitats in the region: open forests, riparian forests, and dense forests. We hypothesized that riparian forests would be the most preferred habitat for the butterflies, as they provide suitable microclimatic conditions for butterflies. The study collected samples for 35 grids of 2 × 2 km² for each habitat during the dry months (December–June). We considered the relative humidity, temperature, light intensity, elevation, and canopy cover to assess their influences on butterfly richness and abundance. We also considered the impact of disturbances on their distribution. We used structural equation modeling and canonical correspondence analysis to quantify the correlation and causation between the butterflies and their environment. The study recorded 1614 individual butterflies of 79 species from 57 genera and 6 families. During the study, we found that temperature was the most significant factor influencing butterfly richness. Relative humidity was also important and had a positive impact on butterfly richness. Riparian forests, where daytime temperatures are relatively low, were the most preferred microhabitat for butterflies. Open forests had greater species diversity, indicating the critical significance of an open canopy for butterflies. Though riparian forests need greater attention concerning butterfly distribution, maintaining open and dense forests are crucial for preserving butterfly diversity. Full article

The grasslands of North America are threatened by woody encroachment. Restoring historical fire regimes has been used to manage brush encroachment. However, fire management may be insufficient due to the nonlinear and hysteretic responses of vegetation recovery following encroachment and the social–political constraints affecting fire management. We synthesized the fire thresholds required to control woody encroachment by typical encroaching species in North America, especially the Great Plains region, and identified the social–political constraints facing fire management in selected grassland national parks. Our synthesis revealed the resistance, hysteresis, and irreversibility of encroached grasslands using fire and emphasized the need for a combination of brush management methods if the impacts of climate change are to be addressed. Frequent fires alone may maintain grassland states, reflecting resistance. However, high-intensity fires exceeding fire-mortality thresholds are required to exclude non-resprouting shrubs and trees, indicating hysteresis. Fire alone may be insufficient to reverse encroachment by resprouting species, exhibiting reversibility. In practice, appropriate fire management may restore resistant grassland states. However, social–political constraints have restricted the use of frequent and high-intensity fires, thereby reducing the effectiveness of management actions to control woody encroachment of grasslands in national parks. This research proposes a resilience-based framework to manage woody encroachment in grassland national parks and similar protected areas. Full article

Properties in the United States face increasing exposure to tropical storm-level winds due to climate change. Driving this increasing risk are severe hurricanes that are more likely to occur when hurricanes form in the future and the northward shift of Atlantic-formed hurricanes, increasing the estimated exposure of buildings and infrastructure to damaging winds. The wind model presented here combines open data and science by utilizing high-resolution topography, computer-modeled hurricane tracks, and property data to create hyper-local tropical cyclone wind exposure information for the Contiguous United States (CONUS) from current time to 2053 under RCP 4.5. This allows for a detailed evaluation of probable wind speeds by several return periods, probabilities of cyclonic thresholds being reached or surpassed, and a comparison of this cyclone-level wind exposure between the current year and 30 years into the future under climatic changes. The results of this research reveal extensive exposure along the Gulf and Southeastern Atlantic Coasts, with significant growing exposure in the Mid-Atlantic and Northeastern regions of the country. Full article

People-centred reforestation is one of the ways to achieve natural climate solutions. Ghana has established a people-centred reforestation programme known as the Modified Taunya System (MTS) where local people are assigned degraded forest reserves to practice agroforestry. Given that the MTS is a people-centred initiative, socioeconomic factors are likely to have impact on the reforestation drive. This study aims to understand the role of translocal practices of remittances and visits by migrants on the MTS. Using multi-sited, sequential explanatory mixed methods and the lens of socioecological systems, the study shows that social capital and socioeconomic obligations of cash remittances from, as well as visits by migrants to their communities of origin play positive roles on reforestation under the MTS. Specifically, translocal households have access to, and use remittances to engage relatively better in the MTS than households that do not receive remittances. This shows that translocal practices can have a positive impact on the environment at the area of origin of migrants where there are people-centred environmental policies in place. Full article

Anthropogenic activity is considered a central driver of current climate change. A recent paper, studying the consensus regarding the hypothesis that the recent increase in global temperature is predominantly human-made via the emission of greenhouse gasses (see text for reference), argued that the scientific consensus in the peer-reviewed scientific literature pertaining to this hypothesis exceeds 99%. This conclusion was reached after the authors scanned the abstracts and titles of some 3000 papers and mapped them according to their (abstract) statements regarding the above hypothesis. Here, we point out some major flaws in the methodology, analysis, and conclusions of the study. Using the data provided in the study, we show that the 99% consensus, as defined by the authors, is actually an upper limit evaluation because of the large number of “neutral” papers which were counted as pro-consensus in the paper and probably does not reflect the true situation. We further analyze these results by evaluating how so-called “skeptic” papers fit the consensus and find that biases in the literature, which were not accounted for in the aforementioned study, may place the consensus on the low side. Finally, we show that the rating method used in the study suffers from a subjective bias which is reflected in large variations between ratings of the same paper by different raters. All these lead to the conclusion that the conclusions of the study does not follow from the data. Full article

Temperate conifer forests stressed by climate change could be lost through tree regeneration decline in the interior of high-severity fires, resulting in type conversion to non-forest vegetation from seed-dispersal limitation, competition, drought stress, and reburns. However, is fire triggering this global change syndrome at a high rate? To find out, I analyzed a worst-case scenario. I calculated fire rotations (FRs, expected period to burn once across an area) across ~56 million ha of forests (~80% of total forest area) in 11 western USA states from 2000 to 2020 for total high-severity fire area, interior area (>90 m inward), and reburned area. Unexpectedly, there was no trend in area burned at high severity from 2000 to 2020 across the four forest types studied. The vulnerable interior area averaged only 21.9% of total high-severity fire area, as 78.1% of burned area was within 90 m of live seed sources where successful tree regeneration is likely. FRs averaged 453 years overall, 2089 years in interiors, and 19,514 years in reburns. Creation of vulnerable interior area in a particular location is thus, on average, a 2000+ year event, like a very rare natural disaster, and reburns that may favor type conversion to non-forest have almost no effect. This means that, from 2021 to 2050 at most, only 3.0–4.2% of total forest area may become a vulnerable interior area, based on a likely high aridity-based climate projection of future fire and a higher scenario, where rates in the exceptional 2020 fire year have become the norm. These findings show that increased management to reduce high-severity fires is not currently needed, as the risk to forests from this global change syndrome is likely quite low up to 2050. Faster and larger disturbances (e.g., severe droughts) are more likely to cause most tree mortality or forest loss that occurs by 2050. Full article

Water conflicts have been a significant issue in Brazil, especially in the Sao Francisco River basin. Subseasonal forecasts, up to a 60-day forecast range, can provide information to support decision-makers in managing water resources in the river basin, especially before drought events. This report aims to evaluate 5-year mean subseasonal simulations generated by the Eta regional model for the period from 2011 to 2016 and assess the usefulness of this information to support decision-making in water resource conflicts in the Sao Francisco River basin. The capability of the Eta model to reproduce the drought events that occurred between the years 2011 and 2016 was compared against the Climate Prediction Center Morphing (CMORPH) precipitation data. Two sets of 60-day simulations were produced: one started in September (SO) and the other in January (JF) of each year. These months were chosen to evaluate the model’s capability to reproduce the onset and the middle of the rainy seasons in central Brazil, where the upper Sao Francisco River is located. The SO simulations reproduced the observed spatial distribution of precipitation but underestimated the amounts. Precipitation errors exhibited large variability across the subbasins. The JF simulations also reproduced the observed precipitation distribution but overestimated it in the upper and lower subbasins. The JF simulations better captured the interannual variability in precipitation. The 60-day simulations were discretized into six 10-day accumulations to assess the intramonthly variability. They showed that the simulations captured the onset of the rainy season and the small periods of rainy months that occurred in these severe drought years. This research is a critical step to indicate subbasins where the model simulation needs to be improved and provide initial information to support water allocation in the region. Full article