Journal Description
Climate
Climate
is a scientific, peer-reviewed, open access journal of climate science published online monthly by MDPI. The American Society of Adaptation Professionals (ASAP) is affiliated with Climate and its members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), GeoRef, AGRIS, and other databases.
- Journal Rank: JCR - Q2 (Meteorology and Atmospheric Sciences) / CiteScore - Q2 (Atmospheric Science)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 19.7 days after submission; acceptance to publication is undertaken in 3.4 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.0 (2023);
5-Year Impact Factor:
3.3 (2023)
Latest Articles
Historic Changes and Future Projections in Köppen–Geiger Climate Classifications in Major Wine Regions Worldwide
Climate 2024, 12(7), 94; https://doi.org/10.3390/cli12070094 - 27 Jun 2024
Abstract
A valuable tool for comprehending and characterizing climate patterns on a global scale is the Köppen–Geiger climate classification system. When it comes to wine production, the climate of a region plays an essential role in determining whether specific grape varieties can be cultivated,
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A valuable tool for comprehending and characterizing climate patterns on a global scale is the Köppen–Geiger climate classification system. When it comes to wine production, the climate of a region plays an essential role in determining whether specific grape varieties can be cultivated, largely determining the style of wine that can be made, and influencing the consistency of overall wine quality. In this study, the application of the Köppen–Geiger classification system to the latest Coupled Model Intercomparison Project (CMIP6) experiments has been explored. To establish a baseline for the historical period (1970–2000), the WorldClim dataset was used alongside a selection of an ensemble of 14 Global Climate Models. The evaluation of climate variability across winemaking regions is conducted by considering future climate projections from 2041 to 2060, which are based on different anthropogenic radiative forcing scenarios (Shared Socioeconomic Pathways, SSP2–4.5, and SSP5–8.5). The results are the most comprehensive documentation of both the historical climate classifications for most wine regions worldwide and the potential changes in these classifications in the future. General changes in climate types are projected to occur largely in a significant shift from a warm summer climate to a hot summer climate in temperate and dry zones worldwide (climate types C and B, respectively). This shift poses challenges for grape cultivation and wine production. The grape development process can be significantly affected by high temperatures, which could result in early ripening and changes in the grape berry’s aromatic compounds. As regions transition and experience different climates, wine producers are required to adapt their vineyard management strategies by implementing suitable measures that can effectively counter the detrimental impacts of abiotic stresses on grape quality and vineyard health. These adaptation measures may include changes in canopy and soil management, using different variety-clone-rootstock combinations, adopting irrigation methods, or shifting into other microclimatic zones, among other effective techniques. To ensure long-term sustainability, wine producers must consider the climatic change projections that are specific to their region, allowing them to make more informed decisions about vineyard management practices, reducing risks, and ultimately making the wine industry more resilient and adaptive to the ongoing effects of climate change.
Full article
(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)
Open AccessArticle
Geospatial Analysis of Flood Susceptibility in Nigeria’s Vulnerable Coastal States: A Detailed Assessment and Mitigation Strategy Proposal
by
Muhammad Bello, Saurabh Singh, Suraj Kumar Singh, Vikas Pandey, Pankaj Kumar, Gowhar Meraj, Shruti Kanga and Bhartendu Sajan
Climate 2024, 12(7), 93; https://doi.org/10.3390/cli12070093 - 27 Jun 2024
Abstract
This study employs advanced geospatial analytical techniques to evaluate the vulnerability of Nigeria’s coastal states and their constituent local government areas to flood hazards, which represent a critical and escalating risk within the coastal hazard paradigm intensified by climate change phenomena. The study’s
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This study employs advanced geospatial analytical techniques to evaluate the vulnerability of Nigeria’s coastal states and their constituent local government areas to flood hazards, which represent a critical and escalating risk within the coastal hazard paradigm intensified by climate change phenomena. The study’s objective is to utilize geospatial data to delineate and quantify the intensity and distribution of flood susceptibility, thus establishing a foundational framework for developing comprehensive disaster management strategies in response to the challenges posed by climate variability. The research uses satellite imagery and geographic information system (GIS)-based hydrological modeling to delineate regions susceptible to flooding, synthesizing topographical and hydrological data to stratify areas into discrete flood susceptibility categories. The findings indicate that the Delta coastal State of Nigeria contains extensive medium to high-risk flood zones spanning 8304.57 km2. While the Bayelsa coastal State of Nigeria presents critical areas at high to very high flood risk, encompassing 5506.61 km2 at high risk and 1826.88 km2 at very high risk, this highlights the urgent necessity for immediate and strategic mitigation measures. This research highlights the critical importance of geospatial technology in shaping disaster management and enhancing community resilience against increasing flood frequencies. As Nigeria’s coastal regions face escalating flood susceptibility, advanced geospatial methods are vital for assessing and mitigating these climate-induced threats, contributing to climate-resilient planning and aligning with Sustainable Development Goal 13: Climate Action. The study’s geospatial approach delivers precise flood risk evaluations and guides targeted mitigation efforts, marking significant progress in managing coastal hazards in a changing climate.
Full article
(This article belongs to the Special Issue Coastal Hazards under Climate Change)
Open AccessArticle
Quantifying Drought Impacts Based on the Reliability–Resiliency–Vulnerability Framework over East Africa
by
Hassen Babaousmail, Brian Odhiambo Ayugi, Zulfiqar Hammad, Donnata Alupot, Kokou Romaric Posset, Richard Mumo and Adharsh Rajasekar
Climate 2024, 12(7), 92; https://doi.org/10.3390/cli12070092 - 27 Jun 2024
Abstract
Drought poses a significant threat to water resources in East Africa, necessitating a comprehensive assessment of its impacts for effective mitigation strategies. This study utilizes two global gridded SPEI datasets to analyze drought characteristics (i.e., frequency, duration, and severity) in East Africa from
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Drought poses a significant threat to water resources in East Africa, necessitating a comprehensive assessment of its impacts for effective mitigation strategies. This study utilizes two global gridded SPEI datasets to analyze drought characteristics (i.e., frequency, duration, and severity) in East Africa from 1981 to 2021. To estimate the sustainability of water resources over the region, the study employed the Reliability–Resiliency–Vulnerability framework (RRV) that aggregates the drought characteristics (i.e., frequency, duration, and severity). Drought is deemed to have occurred when the SPEI value falls below −1, so the threshold for water demand (RRV) is also computed at a threshold level of −1. The findings indicate pronounced changes in drought patterns across East Africa, with evidence of varying degrees of recovery and resilience in different regions. Employing the RRV framework over the East Africa region to determine how the region can cope with the effects of drought revealed a median range of RRV of 0.61 to 0.80, indicating a sustainable situation during the study period. This indicates that despite the recorded drought incidences, the water catchments of lakes, rivers, and major water towers are not threatened and, thus, less vulnerable. Although certain regions exhibit declining resilience and vulnerability to drought impacts, there is a need for targeted mitigation measures and policy interventions to safeguard water resources.
Full article
(This article belongs to the Topic Climate Change and Human Impact on Freshwater Water Resources: Rivers and Lakes)
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Open AccessArticle
Assessment of Modeled Mean Radiant Temperature in Hot and Dry Environments: A Case Study in Saudi Arabia
by
Ali Alzahrani and Mohamed Gadi
Climate 2024, 12(7), 91; https://doi.org/10.3390/cli12070091 - 27 Jun 2024
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Envi-met is the most-used simulation tool to assess outdoor thermal comfort in urban microclimates. Considering reported disparities between modeled and observed mean radiant temperature (MRT), failing to accurately predict the MRT may have a negative impact on the conclusions drawn by urban designers
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Envi-met is the most-used simulation tool to assess outdoor thermal comfort in urban microclimates. Considering reported disparities between modeled and observed mean radiant temperature (MRT), failing to accurately predict the MRT may have a negative impact on the conclusions drawn by urban designers and policy makers. Therefore, this study aims to validate the Envi-met model’s efficiency for predicting MRT in the hot arid climate of Mecca city. Sensitivity analyses were conducted to investigate the settings and inputs of Envi-met, including two- and six-directional methods for calculating MRT, shortwave radiation projection factors, Indexed View Sphere (IVS), Advanced Canopy Radiation Transfer (ACRT), and the localization of materials and vegetation. Two statistical metrics (RMSE and MAE) were employed to assess Envi-met’s performance for the two evaluation points. Envi-met produced the best results with the 6-directional, ƒp-RayM (in winter) and ƒp-City (in summer), IVS on and ACRT on mode, and localized soil condition, materials, and vegetation inputs. An analysis of the modeled MRT results illustrated that error magnitudes were decreased significantly as a result of sufficient settings and inputs; for example, RMSE was improved by 2.31 and 8.48 K in the winter and summer open site results, respectively, and by 7.30 K in the summer under-tree site. Overall, the results of winter and summer analyses demonstrate average RMSE of 4.99 K and MAE of 4.02 K. The findings illustrate that substantial enhancement of model performance can be achieved through the use of proper settings and inputs.
Full article
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Open AccessArticle
On the Unforced or Forced Nature of the Atlantic Multidecadal Oscillation: A Linear and Nonlinear Causality Analysis
by
Umberto Triacca and Antonello Pasini
Climate 2024, 12(7), 90; https://doi.org/10.3390/cli12070090 - 26 Jun 2024
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In recent years, there has been intense debate in the literature as to whether the Atlantic Multidecadal Oscillation (AMO) is a genuine representation of natural climate variability or is substantially driven by external factors. Here, we perform an analysis of the influence of
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In recent years, there has been intense debate in the literature as to whether the Atlantic Multidecadal Oscillation (AMO) is a genuine representation of natural climate variability or is substantially driven by external factors. Here, we perform an analysis of the influence of external (natural and anthropogenic) forcings on the AMO behaviour by means of a linear Granger causality analysis and by a nonlinear extension of this method. Our results show that natural forcings do not have any causal role on AMO in both linear and nonlinear analyses. Instead, a certain influence of anthropogenic forcing is found in a linear framework.
Full article
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Open AccessReview
Climate Change and Human Health in the Arctic: A Review
by
Elena A. Grigorieva
Climate 2024, 12(7), 89; https://doi.org/10.3390/cli12070089 - 22 Jun 2024
Abstract
Over recent decades, the Arctic has begun facing a range of climate-related challenges, from rising temperatures to melting ice caps and permafrost thaw, with significant implications for ecosystems and human well-being. Addressing the health impacts of these issues requires a comprehensive approach, integrating
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Over recent decades, the Arctic has begun facing a range of climate-related challenges, from rising temperatures to melting ice caps and permafrost thaw, with significant implications for ecosystems and human well-being. Addressing the health impacts of these issues requires a comprehensive approach, integrating scientific research, community engagement, and policy interventions. This study conducts a literature review to assess the effects of climate change on human health in northern latitudes and to compile adaptation strategies from the Arctic countries. A literature search was performed between January and April 2024 for papers published after 2000, using the electronic databases Web of Science, Pubmed, Science Direct, Scopus, Google Scholar, and eLibrary.RU, with specific questions formulated to direct the search: (i) What are the climate changes? (ii) How does climate change affect human health? (iii) What adaptation measures and policies are required? The key phrases “climate change”, “human health”, “adaptation practices”, and “Arctic” were employed for searching. Ultimately, 56 relevant studies were identified, reviewing health risks such as infectious diseases, mental health issues, and diseases connected with extreme weather events; wildfires and their associated pollution; permafrost degradation; pure water; and food quality. The paper also examines mitigation and adaptation strategies at all levels of governance, emphasizing the need for international cooperation and policy action to combat negative health outcomes, investments in healthcare infrastructure, emergency preparedness, and public health education. Incorporating diverse perspectives, including Indigenous knowledge, Community-Based Adaptation, EcoHealth and One Health approaches, is crucial for effectively addressing the health risks associated with climate change. In conclusion, the paper proposes adaptation strategies to mitigate the health impacts of climate change in the Arctic.
Full article
(This article belongs to the Special Issue Climate Impact on Human Health)
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Open AccessArticle
Long-Term Energy System Modelling for a Clean Energy Transition and Improved Energy Security in Botswana’s Energy Sector Using the Open-Source Energy Modelling System
by
Ranea Saad, Fernando Plazas-Niño, Carla Cannone, Rudolf Yeganyan, Mark Howells and Hannah Luscombe
Climate 2024, 12(6), 88; https://doi.org/10.3390/cli12060088 - 14 Jun 2024
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This research examines Botswana’s significant reliance on coal and imported fossil fuels for electricity generation, contributing to high carbon emissions and energy insecurity influenced by volatile fuel prices and supply challenges. The study utilizes the Open-Source Energy Modelling System (OSeMOSYS) to explore cost-effective
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This research examines Botswana’s significant reliance on coal and imported fossil fuels for electricity generation, contributing to high carbon emissions and energy insecurity influenced by volatile fuel prices and supply challenges. The study utilizes the Open-Source Energy Modelling System (OSeMOSYS) to explore cost-effective renewable energy strategies to meet Botswana’s Nationally Determined Contributions (NDCs) and enhance energy security by 2050, analysing six scenarios: Least Cost (LC), Business-As-Usual (BAU), Net Zero by 2050 (NZ), Coal Phase Out by 2045 (CPO), Fossil Fuel Phase Out by 2045 (FFPO), and Import Phase Out by 2045 (IMPPO). Our key findings highlight the critical role of solar technologies—photovoltaic (PV), storage, and concentrated solar power (CSP)—in transitioning to a sustainable energy future, especially under the Net Zero and Import Phase Out scenarios. This research demonstrates the economic and environmental benefits of transitioning away from fossil fuels, with the Fossil Fuel Phase Out scenario yielding a USD 31 million saving over the Business-As-Usual approach and reducing investment costs by USD 2 billion, albeit with a slight increase in light fuel oil imports. The study underscores the need for substantial capital investments, particularly in the Net Zero and Import Phase Out scenarios, necessitating private sector financing. Policy recommendations include adopting detailed strategies for solar PV and storage expansion, updating renewable energy targets, phasing out coal and natural gas, and bolstering the regulatory framework. These strategies are crucial for Botswana to achieve decarbonization and energy independence, aligning with global climate goals and national energy security objectives.
Full article
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Open AccessArticle
Analysing the Transformative Changes of Nationally Determined Contributions and Long-Term Targets
by
Panagiotis Fragkos, Dirk-Jan van de Ven, Russell Horowitz and Eleftheria Zisarou
Climate 2024, 12(6), 87; https://doi.org/10.3390/cli12060087 - 11 Jun 2024
Abstract
As the imperative to address climate change intensifies, understanding the effectiveness of policy interventions becomes paramount. In the context of addressing these urgent challenges and given the inadequacy of current policies to address this issue, this study examines the extent to which Nationally
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As the imperative to address climate change intensifies, understanding the effectiveness of policy interventions becomes paramount. In the context of addressing these urgent challenges and given the inadequacy of current policies to address this issue, this study examines the extent to which Nationally Determined Contributions (NDCs) and Long-Term Targets (LTTs) can contribute to achieving ambitious climate goals. Recognizing the critical need for effective climate action, we employ the advanced modelling tools PROMETHEUS and GCAM to assess the implications of different scenarios–Current Policies (CP), Nationally Determined Contributions (NDC), and combination of NDCs with Long-Term Targets (NDC_LTT)–on the future development of energy system and emission. This study, by employing these well-known models, seeks to provide an improved understanding of the impacts of NDCs on global emission trajectories and whether the integration of NDCs and LTTs can help close the gap towards Paris-compatible pathways. The study analyzes various sectors including buildings, transportation, electricity generation, and industry to provide insights into the limitations of existing policies and the potential of enhanced commitments to drive transformative changes in a global scale. The effectiveness of these policies varies across different sectors, highlighting the challenges that need to be addressed for achieving the required emission reduction targets in the medium- and long-term. Key findings indicate significant shifts in energy consumption, fuel mix, technology adoption, and emission trajectories, particularly under the synergistic action represented by the NDC_LTT scenario.
Full article
(This article belongs to the Section Climate and Economics)
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Open AccessArticle
Homogenization of the Long Instrumental Daily-Temperature Series in Padua, Italy (1725–2023)
by
Claudio Stefanini, Francesca Becherini, Antonio della Valle and Dario Camuffo
Climate 2024, 12(6), 86; https://doi.org/10.3390/cli12060086 - 7 Jun 2024
Abstract
The Padua temperature series is one of the longest in the world, as daily observations started in 1725 and have continued almost unbroken to the present. Previous works recovered readings from the original logs, and digitalized and corrected observations from errors due to
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The Padua temperature series is one of the longest in the world, as daily observations started in 1725 and have continued almost unbroken to the present. Previous works recovered readings from the original logs, and digitalized and corrected observations from errors due to instruments, calibrations, sampling times and exposure. However, the series underwent some changes (location, elevation, observing protocols, and different averaging methods) that affected the homogeneity between sub-series. The aim of this work is to produce a homogenized temperature series for Padua, starting from the results of previous works, and connecting all the periods available. The homogenization of the observations has been carried out with respect to the modern era. A newly released paleo-reanalysis dataset, ModE-RA, is exploited to connect the most ancient data to the recent ones. In particular, the following has been carried out: the 1774–2023 daily mean temperature has been homogenized to the modern data; for the first time, the daily values of 1765–1773 have been merged and homogenized; and the daily observations of the 1725–1764 period have been connected and homogenized to the rest of the series. Snowfall observations, extracted from the same logs from which the temperatures were retrieved, help to verify the robustness of the homogenization procedure by looking at the temperature frequency distribution on snowy days, before and after the correction. The possibility of adding new measurements with no need to apply transformations or homogenization procedures makes it very easy to update the time series and make it immediately available for climate change analysis.
Full article
(This article belongs to the Special Issue The Importance of Long Climate Records)
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Open AccessArticle
Decarbonising the EU Buildings|Model-Based Insights from European Countries
by
Theofano Fotiou, Panagiotis Fragkos and Eleftheria Zisarou
Climate 2024, 12(6), 85; https://doi.org/10.3390/cli12060085 - 7 Jun 2024
Abstract
The European Union faces the pressing challenge of decarbonising the buildings sector to meet its climate neutrality goal by 2050. Buildings are significant contributors to greenhouse gas emissions, primarily through energy consumption for heating and cooling. This study uses the advanced PRIMES-BuiMo model
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The European Union faces the pressing challenge of decarbonising the buildings sector to meet its climate neutrality goal by 2050. Buildings are significant contributors to greenhouse gas emissions, primarily through energy consumption for heating and cooling. This study uses the advanced PRIMES-BuiMo model to develop state-of-the-art innovative pathways and strategies to decarbonise the EU buildings sector, providing insights into energy consumption patterns, renovation rates and equipment replacement dynamics in the EU and in two representative Member States, Sweden and Greece. The model-based analysis shows that the EU’s transition towards climate neutrality requires significant investment in energy efficiency of buildings combined with decarbonisation of the fuel mix, mostly through the uptake of electric heat pumps replacing the use of fossil fuels. The Use Case also demonstrates that targeted policy interventions considering the national context and specificities are required to ensure an efficient and sustainable transition to zero-emission buildings. The analysis of transformational strategies in Greece and Sweden provides an improved understanding of the role of country-specific characteristics on policy effectiveness so as to inform more targeted and contextually appropriate approaches to decarbonise the buildings sector across the EU.
Full article
(This article belongs to the Section Climate and Economics)
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Open AccessArticle
Atmospheric Blocking Events over the Southeast Pacific and Southwest Atlantic Oceans in the CMIP6 Present-Day Climate
by
Vanessa Ferreira, Osmar Toledo Bonfim, Luca Mortarini, Roilan Hernandez Valdes, Felipe Denardin Costa and Rafael Maroneze
Climate 2024, 12(6), 84; https://doi.org/10.3390/cli12060084 - 6 Jun 2024
Abstract
This study examines the representation of blocking events in the Southeast Pacific and Southwest Atlantic regions using a set of 13 global climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6). Historical runs were employed to analyze blocking conditions in
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This study examines the representation of blocking events in the Southeast Pacific and Southwest Atlantic regions using a set of 13 global climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6). Historical runs were employed to analyze blocking conditions in the recent past climate, spanning from 1985 to 2014, with ERA5 data utilized to represent observed blocking events. The majority of CMIP6 models underestimate the total number of blocking events in the Southeast Pacific. The MPI–ESM1–2–HR and MPI–ESM1–2–LR models come closest to replicating the number of blocking events observed in ERA5, with underestimations of approximately −10% and −9%, respectively. Nonetheless, these models successfully capture the seasonality and overall duration of blocking events, as well as accurately represent the position of blocking heights over the Southeast Pacific. Conversely, CMIP6 models perform poorly in representing blocking climatology in the Southwest Atlantic. These models both overestimate and underestimate the total number of blocking events by more than 25% compared to ERA5. Furthermore, they struggle to reproduce the seasonal distribution of blockings and face challenges in accurately representing the duration of blocking events observed in ERA5.
Full article
(This article belongs to the Section Climate Dynamics and Modelling)
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Open AccessArticle
The Added Value of Statistical Seasonal Forecasts
by
Folmer Krikken, Gertie Geertsema, Kristian Nielsen and Alberto Troccoli
Climate 2024, 12(6), 83; https://doi.org/10.3390/cli12060083 - 4 Jun 2024
Abstract
Seasonal climate predictions can assist with timely preparations for extreme episodes, such as dry or wet periods that have associated additional risks of droughts, fires and challenges for water management. Timely warnings for extreme warm summers or cold winters can aid in preparing
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Seasonal climate predictions can assist with timely preparations for extreme episodes, such as dry or wet periods that have associated additional risks of droughts, fires and challenges for water management. Timely warnings for extreme warm summers or cold winters can aid in preparing for increased energy demand. We analyse seasonal forecasts produced by three different methods: (1) a multi-linear statistical forecasting system based on observations only; (2) a non-linear random forest model based on observations only; and (3) process-based dynamical forecast models. The statistical model is an empirical system based on multiple linear regression that is extended to include the trend over the previous 3 months in the predictors, and overfitting is further reduced by using an intermediate multiple linear regression model. This results in a significantly improved El Niño forecast skill, specifically in spring. Also, the Indian Ocean dipole (IOD) index forecast skill shows improvements, specifically in the summer and autumn months. A hybrid multi-model ensemble is constructed by combining the three forecasting methods. The different methods are used to produce seasonal forecasts (three-month means) for near-surface air temperature and monthly accumulated precipitation seasonal forecast with a lead time of one month. We find numerous regions with added value compared with multi-model ensembles based on dynamical models only. For instance, for June, July and August temperatures, added value is observed in extensive parts of both Northern and Southern America, as well as Europe.
Full article
(This article belongs to the Special Issue Seasonal Forecasting Climate Services for the Energy Industry)
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Open AccessArticle
Assessment of the Vulnerability of Households Led by Men and Women to the Impacts of Climate-Related Natural Disasters in the Coastal Areas of Myanmar and Vietnam
by
Aung Tun Oo, Ame Cho and Dao Duy Minh
Climate 2024, 12(6), 82; https://doi.org/10.3390/cli12060082 - 2 Jun 2024
Abstract
Farm households along the coastlines of Myanmar and Vietnam are becoming increasingly vulnerable to flooding, saltwater intrusion, and rising sea levels. There is little information available on the relative vulnerability of men- and women-headed households, and the governments of Myanmar and Vietnam have
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Farm households along the coastlines of Myanmar and Vietnam are becoming increasingly vulnerable to flooding, saltwater intrusion, and rising sea levels. There is little information available on the relative vulnerability of men- and women-headed households, and the governments of Myanmar and Vietnam have not identified or implemented any adaptive measures aimed specifically at vulnerable peoples. This study aims to fill these gaps and assess the relative climate change vulnerability of men- and women-headed farm households. This study considers 599 farm households from two regions of Myanmar and 300 households from Thua Thien Hue province of Vietnam for the period 2021–2022. We offer a livelihood vulnerability index (LVI) analysis of men- and women-headed farm households using 46 indicators arranged into seven major components. The aggregate LVI scores indicate that farm households in Myanmar are more vulnerable (scores of 0.459 for men and 0.476 for women) to climate-related natural disasters than farm households in Vietnam (scores of 0.288 for men and 0.292 for women), regardless of the gender of the head of household. Total vulnerability indexing scores indicate that women-headed households are more vulnerable than men-headed households in both countries. Poor adaptive capacity and highly sensitive LVI dimensional scores explain the greater vulnerability of women-headed farm households. The findings also highlight the importance of the adaptive capacity components reflected in the LVI analysis in reducing farm households’ vulnerability.
Full article
(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)
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Open AccessReview
Beyond the First Tipping Points of Southern Hemisphere Climate
by
Terence J. O’Kane, Jorgen S. Frederiksen, Carsten S. Frederiksen and Illia Horenko
Climate 2024, 12(6), 81; https://doi.org/10.3390/cli12060081 - 31 May 2024
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Analysis of observations, reanalysis, and model simulations, including those using machine learning methods specifically designed for regime identification, has revealed changes in aspects of the Southern Hemisphere (SH) circulation and Australian climate and extremes over the last half-century that indicate transitions to new
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Analysis of observations, reanalysis, and model simulations, including those using machine learning methods specifically designed for regime identification, has revealed changes in aspects of the Southern Hemisphere (SH) circulation and Australian climate and extremes over the last half-century that indicate transitions to new states. In particular, our analysis shows a dramatic shift in the metastability of the SH climate that occurred in the late 1970s, associated with a large-scale regime transition in the SH atmospheric circulation, with systematic changes in the subtropical jet, blocking, zonal winds, and storm tracks. Analysis via nonstationary clustering reveals a regime shift coincident with a sharp transition to warmer oceanic sea surface temperatures and increased baroclinicity in the large scales of the Antarctic Circumpolar Circulation (ACC), extending across the whole hemisphere. At the same time, the background state of the tropical Pacific thermocline shoaled, leading to an increased likelihood of El Niño events. The SH climate shift in the late 1970s is the first hemispheric regime shift that can be directly attributed to anthropogenic climate change. These changes in dynamics are associated with additional regional tipping points, including reductions in mean and extreme rainfall in south-west Western Australia (SWWA) and streamflow into Perth dams, and also with increases in mean and extreme rainfall over northern Australia since the late 1970s. The drying of south-eastern Australia (SEA) occurred against a background of accelerating increases in average and extreme temperatures across the whole continent since the 1990s, implying further inflection points may have occurred. Analysis of climate model simulations capturing the essence of these observed shifts indicates that these systematic changes will continue into the late 21st century under high greenhouse gas emission scenarios. Here, we review two decades of work, revealing for the first time that tipping points characteristic of regime transitions are inferred to have already occurred in the SH climate system.
Full article
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Open AccessArticle
Assessment of Rural Flood Risk and Factors Influencing Household Flood Risk Perception in the Haut-Bassins Region of Burkina Faso, West Africa
by
Madou Sougué, Bruno Merz, Amadé Nacanabo, Gnibga Issoufou Yangouliba, Ibrahima Pouye, Jean Mianikpo Sogbedji and François Zougmoré
Climate 2024, 12(6), 80; https://doi.org/10.3390/cli12060080 - 31 May 2024
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In the past two decades, several floods have affected people and their properties in Burkina Faso, with unprecedented flooding occurring in Ouagadougou in September 2009. So far, most studies have focused on Ouagadougou and surrounding localities and have paid little attention to other
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In the past two decades, several floods have affected people and their properties in Burkina Faso, with unprecedented flooding occurring in Ouagadougou in September 2009. So far, most studies have focused on Ouagadougou and surrounding localities and have paid little attention to other flood-prone regions in Burkina Faso. Consequently, there is a data and knowledge gap regarding flood risk in the Haut-Bassins region, which in turn hinders the development of mitigation strategies and risk reduction measures in affected communities. This study demonstrates how data collected at the household level can be used to understand flood risk and its components at the village level in this data-scarce region. Using an indicator-based method, we analyzed both flood risk and flood risk perception at the village level. Moreover, we determined the factors influencing flood risk perception at the household level using an ordered logit model. We found that 12 out of the 14 villages in our sample group had experienced high levels of flood risk. The management of runoff from the nearest urban areas as well as poorly designed civil engineering infrastructures, such as roads, were highlighted by households as significant factors that increased their vulnerability. Additionally, we found that the perceived flood risk consistently exceeds the estimated flood risk, with an insignificant positive correlation between both risk indices. Regression results indicate that flood risk perception is mainly influenced by informational and behavioral factors of households. The findings of this study can provide valuable information to municipal and regional authorities involved in disaster risk management within the study area. Moreover, our/this method is transferable to other data-scarce regions.
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Open AccessArticle
Numerical Modeling of Atmospheric Temperature and Stratospheric Ozone Sensitivity to Sea Surface Temperature Variability
by
Sergei P. Smyshlyaev, Andrew R. Jakovlev and Vener Ya Galin
Climate 2024, 12(6), 79; https://doi.org/10.3390/cli12060079 - 27 May 2024
Abstract
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The results of numerical experiments with a chemistry–climate model of the lower and middle atmosphere are presented to study the sensitivity of the polar stratosphere of the Northern and Southern Hemispheres to sea surface temperature (SST) variability, both as a result of interannual
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The results of numerical experiments with a chemistry–climate model of the lower and middle atmosphere are presented to study the sensitivity of the polar stratosphere of the Northern and Southern Hemispheres to sea surface temperature (SST) variability, both as a result of interannual variability associated with the Southern Oscillation, and because of long-term increases in SST under global warming. An analysis of the results of model experiments showed that for both scenarios of SST changes, the response of the polar stratosphere for the Northern and Southern Hemispheres is very different. In the Arctic, during the El Niño phase, conditions are created for the polar vortex to become less stable, and in the Antarctic, on the contrary, for it to become more stable, which is expressed in a weakening of the zonal wind in the winter in the Arctic and its increase in the Antarctic, followed by a spring decrease in temperature and concentration of ozone in the Antarctic and their increase in the Arctic. Global warming creates a tendency for the polar vortex to weaken in winter in the Arctic and strengthen it in the Antarctic. As a result, in the Antarctic, the concentration of ozone in the polar stratosphere decreases both in winter (June–August) and, especially, in spring (September–November). Global warming may hinder ozone recovery which is expected as a result of the reduced emissions of ozone-depleting substances. The model results demonstrate the dominant influence of Brewer–Dobson circulation variability on temperature and ozone in the polar stratosphere compared with changes in wave activity, both with changes in SST in the Southern Oscillation and with increases in SST due to global warming.
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Open AccessFeature PaperReview
Applying Machine Learning in Numerical Weather and Climate Modeling Systems
by
Vladimir Krasnopolsky
Climate 2024, 12(6), 78; https://doi.org/10.3390/cli12060078 - 26 May 2024
Abstract
In this paper major machine learning (ML) tools and the most important applications developed elsewhere for numerical weather and climate modeling systems (NWCMS) are reviewed. NWCMSs are briefly introduced. The most important papers published in this field in recent years are reviewed. The
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In this paper major machine learning (ML) tools and the most important applications developed elsewhere for numerical weather and climate modeling systems (NWCMS) are reviewed. NWCMSs are briefly introduced. The most important papers published in this field in recent years are reviewed. The advantages and limitations of the ML approach in applications to NWCMS are briefly discussed. Currently, this field is experiencing explosive growth. Several important papers are published every week. Thus, this paper should be considered as a simple introduction to the problem.
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(This article belongs to the Special Issue Addressing Climate Change with Artificial Intelligence Methods)
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Open AccessArticle
Precipitation Extremes and Trends over the Uruguay River Basin in Southern South America
by
Vanessa Ferreira, Osmar Toledo Bonfim, Rafael Maroneze, Luca Mortarini, Roilan Hernandez Valdes and Felipe Denardin Costa
Climate 2024, 12(6), 77; https://doi.org/10.3390/cli12060077 - 22 May 2024
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This study analyzes the spatial distribution and trends in five extreme daily rainfall indices in the Uruguay River Basin (URB) from 1993 to 2022 using the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset. The main findings reveal a predominantly positive trend
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This study analyzes the spatial distribution and trends in five extreme daily rainfall indices in the Uruguay River Basin (URB) from 1993 to 2022 using the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset. The main findings reveal a predominantly positive trend in heavy precipitation (R95p) and extreme precipitation (R99p) events over the mid URB, while a negative trend is observed in the upper and low URB. Significant trends in the frequency of heavy and extreme rainfall were observed during autumn (MAM), with positive trends across most of the mid and upper URB and negative trends in the low URB. In the upper URB, negative trends in the frequency of extremes were also found during spring (SON) and summer (DJF). Overall, there was a reduction in the number of consecutive wet days (CWD), particularly significant in the upper URB and the northern half of the mid URB. Additionally, the upper URB experienced an overall increase in the duration of consecutive dry days (CDD).
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Open AccessArticle
Reliability and Exploratory Factor Analysis of a Measure of the Psychological Distance from Climate Change
by
Alan E. Stewart
Climate 2024, 12(5), 76; https://doi.org/10.3390/cli12050076 - 18 May 2024
Abstract
Psychological distance from climate change has emerged as an important construct in understanding sustainable behavior and attempts to mitigate and/or adapt to climate change. Yet, few measures exist to assess this construct and little is known about the properties of the existing measures.
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Psychological distance from climate change has emerged as an important construct in understanding sustainable behavior and attempts to mitigate and/or adapt to climate change. Yet, few measures exist to assess this construct and little is known about the properties of the existing measures. In this article, the author conducted two studies of a psychological distance measure developed by Wang and her colleagues. In Study 1, the author assessed the test–retest reliability of the measure over a two-week interval and found the scores to be acceptably stable over time. In Study 2, the author conducted two exploratory factor analyses, using different approaches to the correlation and factor extraction. Similar results were observed for each factor analysis: one factor was related to items that specified greater psychological distance from climate change; a second factor involved items that specified closeness to climate change; and a third involved the geographic/spatial distance from climate change. The author discussed the results and provided recommendations on ways that the measure may be used to research the construct of psychological distance from climate change.
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(This article belongs to the Special Issue Anthropogenic Climate Change: Social Science Perspectives - Volume II)
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Open AccessArticle
The Machine Learning Attribution of Quasi-Decadal Precipitation and Temperature Extremes in Southeastern Australia during the 1971–2022 Period
by
Milton Speer, Joshua Hartigan and Lance Leslie
Climate 2024, 12(5), 75; https://doi.org/10.3390/cli12050075 - 17 May 2024
Abstract
Much of eastern and southeastern Australia (SEAUS) suffered from historic flooding, heat waves, and drought during the quasi-decadal 2010–2022 period, similar to that experienced globally. During the double La Niña of the 2010–2012 period, SEAUS experienced record rainfall totals. Then, severe
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Much of eastern and southeastern Australia (SEAUS) suffered from historic flooding, heat waves, and drought during the quasi-decadal 2010–2022 period, similar to that experienced globally. During the double La Niña of the 2010–2012 period, SEAUS experienced record rainfall totals. Then, severe drought, heat waves, and associated bushfires from 2013 to 2019 affected most of SEAUS, briefly punctuated by record rainfall over parts of inland SEAUS in the late winter/spring of 2016, which was linked to a strong negative Indian Ocean Dipole. Finally, from 2020 to 2022 a rare triple La Niña generated widespread extreme rainfall and flooding in SEAUS, resulting in massive property and environmental damage. To identify the key drivers of the 2010–2022 period’s precipitation and temperature extremes due to accelerated global warming (GW), since the early 1990s, machine learning attribution has been applied to data at eight sites that are representative of SEAUS. Machine learning attribution detection was applied to the 52-year period of 1971–2022 and to the successive 26-year sub-periods of 1971–1996 and 1997–2022. The attributes for the 1997–2022 period, which includes the quasi-decadal period of 2010–2022, revealed key contributors to the extremes of the 2010–2022 period. Finally, some drivers of extreme precipitation and temperature events are linked to significant changes in both global and local tropospheric circulation.
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(This article belongs to the Special Issue Addressing Climate Change with Artificial Intelligence Methods)
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