China has long sought to address climate change in line with other development goals. However, research supporting this alignment often employs data-driven models that downplay the policies and institutions needed to achieve the multiple benefits that studies feature in their analyses. This oversight is troubling because it neglects gaps between goals and the actual integration of climate and development or co-control of air pollution and greenhouse gases (GHGs). Additionally, this oversight may overlook growing implementation challenges as China pursues synergies between net-zero emissions, biodiversity, and circularity. This article illustrates these challenges by tracing the goals and policies/institutions in China over three phases: (1) integration (1979–2010), (2) co-control (2011–2019), and (3) synergies (2020–present). This article argues that China needs to strengthen the science–policy interface and ensure that new market-based policy instruments (such as emissions trading programs) as well as the leadership responsibility system incentivize reductions in overall GHG emissions while shrinking ecological footprints in the shifts to synergies.
{"title":"The Shift to Synergies in China’s Climate Planning: Aligning Goals with Policies and Institutions","authors":"Qianyi Cai, Eric Zusman, Guobi Meng","doi":"10.3390/cli11120234","DOIUrl":"https://doi.org/10.3390/cli11120234","url":null,"abstract":"China has long sought to address climate change in line with other development goals. However, research supporting this alignment often employs data-driven models that downplay the policies and institutions needed to achieve the multiple benefits that studies feature in their analyses. This oversight is troubling because it neglects gaps between goals and the actual integration of climate and development or co-control of air pollution and greenhouse gases (GHGs). Additionally, this oversight may overlook growing implementation challenges as China pursues synergies between net-zero emissions, biodiversity, and circularity. This article illustrates these challenges by tracing the goals and policies/institutions in China over three phases: (1) integration (1979–2010), (2) co-control (2011–2019), and (3) synergies (2020–present). This article argues that China needs to strengthen the science–policy interface and ensure that new market-based policy instruments (such as emissions trading programs) as well as the leadership responsibility system incentivize reductions in overall GHG emissions while shrinking ecological footprints in the shifts to synergies.","PeriodicalId":37615,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139215288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The UN vision of climate resilience contains three independent outcomes: resilient people and livelihoods, resilient business and economies, and resilient environmental systems. This article analyzes the positive contributions of low-carbon energy technologies to climate resilience by reviewing and critically assessing the existing pool of studies published by researchers and international organizations that offer comparable data (quantitative indicators). Compilation, critical analysis, and literature review methods are used to develop a methodological framework that is in line with the UN vision of climate resilience and makes it possible to compare the input of low-carbon energy technologies climate resilience by unit of output or during their lifecycle. The framework is supported by the three relevant concepts—energy trilemma, sharing economy/material footprint, and Planetary Pressures-Adjusted Human Development Index. The study identifies indicators that fit the suggested framework and for which the data are available: total material requirement (TMR), present and future levelized cost of electricity (LCOE) without subsidies, CO2 emissions by fuel or industry, lifecycle CO2-equivalent emissions, and mortality rates from accidents and air pollution. They are discussed in the paper with a focus on multi-country and global studies that allow comparisons across different geographies. The findings may be used by decision-makers when prioritizing the support of low-carbon technologies and planning the designs of energy systems.
{"title":"The Contribution of Low-Carbon Energy Technologies to Climate Resilience","authors":"L. Proskuryakova","doi":"10.3390/cli11120231","DOIUrl":"https://doi.org/10.3390/cli11120231","url":null,"abstract":"The UN vision of climate resilience contains three independent outcomes: resilient people and livelihoods, resilient business and economies, and resilient environmental systems. This article analyzes the positive contributions of low-carbon energy technologies to climate resilience by reviewing and critically assessing the existing pool of studies published by researchers and international organizations that offer comparable data (quantitative indicators). Compilation, critical analysis, and literature review methods are used to develop a methodological framework that is in line with the UN vision of climate resilience and makes it possible to compare the input of low-carbon energy technologies climate resilience by unit of output or during their lifecycle. The framework is supported by the three relevant concepts—energy trilemma, sharing economy/material footprint, and Planetary Pressures-Adjusted Human Development Index. The study identifies indicators that fit the suggested framework and for which the data are available: total material requirement (TMR), present and future levelized cost of electricity (LCOE) without subsidies, CO2 emissions by fuel or industry, lifecycle CO2-equivalent emissions, and mortality rates from accidents and air pollution. They are discussed in the paper with a focus on multi-country and global studies that allow comparisons across different geographies. The findings may be used by decision-makers when prioritizing the support of low-carbon technologies and planning the designs of energy systems.","PeriodicalId":37615,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139251789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David Espín-Sánchez, Jorge Olcina-Cantos, C. Conesa-García
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).
{"title":"Temporal Changes in Tourists’ Climate-Based Comfort in the Southeastern Coastal Region of Spain","authors":"David Espín-Sánchez, Jorge Olcina-Cantos, C. Conesa-García","doi":"10.3390/cli11110230","DOIUrl":"https://doi.org/10.3390/cli11110230","url":null,"abstract":"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).","PeriodicalId":37615,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139262889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Flood Hazard Assessment in Australian Tropical Cyclone-Prone Regions","authors":"Michael Kaspi, Yuriy Kuleshov","doi":"10.3390/cli11110229","DOIUrl":"https://doi.org/10.3390/cli11110229","url":null,"abstract":"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.","PeriodicalId":37615,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136348417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Managing Extreme Rainfall and Flooding Events: A Case Study of the 20 July 2021 Zhengzhou Flood in China","authors":"Xiaofan Zhao, Huimin Li, Qin Cai, Ye Pan, Ye Qi","doi":"10.3390/cli11110228","DOIUrl":"https://doi.org/10.3390/cli11110228","url":null,"abstract":"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.","PeriodicalId":37615,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135036923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simon Kamwele Awala, Kudakwashe Hove, Johanna Shekupe Valombola, Helena Nalitende Nafuka, Evans Kamwi Simasiku, Barthlomew Chataika, Lydia Ndinelao Horn, Simon Angombe, Levi S. M. Akundabweni, Osmund D. Mwandemele
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.
{"title":"Co-Cultivation and Matching of Early- and Late-Maturing Pearl Millet Varieties to Sowing Windows Can Enhance Climate-Change Adaptation in Semi-Arid Sub-Saharan Agroecosystems","authors":"Simon Kamwele Awala, Kudakwashe Hove, Johanna Shekupe Valombola, Helena Nalitende Nafuka, Evans Kamwi Simasiku, Barthlomew Chataika, Lydia Ndinelao Horn, Simon Angombe, Levi S. M. Akundabweni, Osmund D. Mwandemele","doi":"10.3390/cli11110227","DOIUrl":"https://doi.org/10.3390/cli11110227","url":null,"abstract":"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.","PeriodicalId":37615,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135138223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"A GIS-Based Assessment of Flood Hazard through Track Records over the 1886–2022 Period in Greece","authors":"Niki Evelpidou, Constantinos Cartalis, Anna Karkani, Giannis Saitis, Kostas Philippopoulos, Evangelos Spyrou","doi":"10.3390/cli11110226","DOIUrl":"https://doi.org/10.3390/cli11110226","url":null,"abstract":"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.","PeriodicalId":37615,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135392023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Examining the Spatiotemporal Changes in the Annual, Seasonal, and Daily Rainfall Climatology of Puerto Rico","authors":"José Javier Hernández Ayala, Rafael Méndez Tejeda","doi":"10.3390/cli11110225","DOIUrl":"https://doi.org/10.3390/cli11110225","url":null,"abstract":"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.","PeriodicalId":37615,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135589674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Time Series Homogenization with ACMANT: Comparative Testing of Two Recent Versions in Large-Size Synthetic Temperature Datasets","authors":"Peter Domonkos","doi":"10.3390/cli11110224","DOIUrl":"https://doi.org/10.3390/cli11110224","url":null,"abstract":"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.","PeriodicalId":37615,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135635392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Regional to Mesoscale Influences of Climate Indices on Tornado Variability","authors":"Cooper P. Corey, Jason C. Senkbeil","doi":"10.3390/cli11110223","DOIUrl":"https://doi.org/10.3390/cli11110223","url":null,"abstract":"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.","PeriodicalId":37615,"journal":{"name":"Climate","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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