Climate

22 pages, 7794 KB

Open AccessArticle

Contemporary Tendencies in Snow Cover, Winter Precipitation, and Winter Air Temperatures in the Mountain Regions of Bulgaria

by Dimitar Nikolov and Cvetan Dimitrov

Climate 2025, 13(10), 212; https://doi.org/10.3390/cli13100212 - 11 Oct 2025

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Abstract

Snow is an essential meteorological variable and an indicator of the changing climate. Its variations, particularly in snow depth and snow water equivalent, result mainly from changes in winter precipitation and air temperature. Recently, these conditions have been thoroughly investigated worldwide, revealing a [...] Read more.

Snow is an essential meteorological variable and an indicator of the changing climate. Its variations, particularly in snow depth and snow water equivalent, result mainly from changes in winter precipitation and air temperature. Recently, these conditions have been thoroughly investigated worldwide, revealing a general prevailing decline in precipitation and increasing tendencies in air temperatures. However, no systematic or up-to-date studies for Bulgaria exist. The main goal of the current project is to fill this national knowledge gap in the snow conditions in our mountains. For that purpose, we used 31 stations with altitudes ranging from 527 to 2925 m a.s.l. for the period between 1961 and 2020, covering two significant reference climatic periods. We extracted data about snow cover maximums, mean air temperatures, and precipitation amounts for the whole winter season in mountainous regions from October to April; however, we mainly present the results for the three winter months: December, January, and February. Most of the stations do not demonstrate any significant trends for snow depth maximums, except for the three lower stations in central west Bulgaria, which show significant increases. On the opposite end of the scale, two of the highest stations demonstrated notable decreases. The time series for the precipitation amounts are also predominantly indefinite. Significant decreasing trends can be found at the highest three alpine stations. The change in the mean seasonal air temperature is predominantly positive—17 of the stations show positive trends, and for 12, the increases are significant. The altitude of the strongest seasonal temperature rise lies between 1000 and 1700 m. Finally, due to the obvious nonlinearity of some of the time series, we decided to check for change points and a nonlinear approach to fit the data. This analysis demonstrates general changes in the investigated characteristics from the beginning of the 1970s to the middle of the 1980s. Full article

(This article belongs to the Special Issue Climate Change Scenarios and Impacts for the Mountain Regions at Middle Latitudes)

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23 pages, 7551 KB

Open AccessArticle

Development of Automatic Labels for Cold Front Detection in South America: A 2009 Case Study for Deep Learning Applications

by Dejanira Ferreira Braz, Luana Albertani Pampuch, Michelle Simões Reboita, Tercio Ambrizzi and Tristan Pryer

Climate 2025, 13(10), 211; https://doi.org/10.3390/cli13100211 - 8 Oct 2025

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Abstract

Deep learning models for atmospheric pattern recognition require spatially consistent training labels that align precisely with input meteorological fields. This study introduces an automatic cold front detection method using the ERA5 reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) at [...] Read more.

Deep learning models for atmospheric pattern recognition require spatially consistent training labels that align precisely with input meteorological fields. This study introduces an automatic cold front detection method using the ERA5 reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) at 850 hPa, specifically designed to generate physically consistent labels for machine learning applications. The approach combines the Thermal Front Parameter (TFP) with temperature advection (AdvT), applying optimized thresholds (TFP < 5 × 10⁻¹¹ K m⁻²; AdvT < −1 × 10⁻⁴ K s⁻¹), morphological filtering, and polynomial smoothing. Comparison against 1426 manual charts from 2009 revealed systematic spatial displacement, with mean offsets of ~502 km. Although pixel-level overlap was low, with Intersection over Union (IoU) = 0.013 and Dice coefficient (Dice) = 0.034, spatial concordance exceeded 99%, confirming both methods identify the same synoptic systems. The automatic method detects 58% more fronts over the South Atlantic and 44% fewer over the Andes compared to manual charts. Seasonal variability shows maximum activity in austral winter (31.3%) and minimum in summer (20.1%). This is the first automatic front detection system calibrated for South America that maintains direct correspondence between training labels and reanalysis input fields, addressing the spatial misalignment problem that limits deep learning applications in atmospheric sciences. Full article

(This article belongs to the Special Issue Meteorological Forecasting and Modeling in Climatology)

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46 pages, 3804 KB

Open AccessArticle

High-Resolution Temporal Variation of Thermal Discomfort Indices in the Eastern Mediterranean City of Athens, Greece, Since the Beginning of the 20th Century (1901–2024)

by Basil E. Psiloglou, Nikolas Gkinis and Christos Giannakopoulos

Climate 2025, 13(10), 210; https://doi.org/10.3390/cli13100210 - 6 Oct 2025

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Abstract

This study analyzes more than a century of hourly meteorological data (1901–2024) from the Thissio station in central Athens, Greece, to assess the long-term changes in human thermal discomfort. Three simple and widely used bioclimatic indices, Thom’s Discomfort Index (TDI), Humidex (HMDX), and [...] Read more.

This study analyzes more than a century of hourly meteorological data (1901–2024) from the Thissio station in central Athens, Greece, to assess the long-term changes in human thermal discomfort. Three simple and widely used bioclimatic indices, Thom’s Discomfort Index (TDI), Humidex (HMDX), and Heat Index (HI), were calculated to capture the combined effects of air temperature and humidity. The results show a marked increase in the frequency, intensity, and duration of thermal discomfort since the 1980s, with a strong acceleration after 2000. The number of days with severe or dangerous heat stress has more than doubled compared with the mid-20th century, and periods of high discomfort now extend from June to September. The maximum values of HMDX and HI have exceeded critical health thresholds, highlighting increasing risks for the urban population. These findings demonstrate how rising temperature and humidity amplify heat stress in a Mediterranean city and emphasize the need for adaptation strategies in urban planning and public health to reduce vulnerability to extreme heat. Full article

(This article belongs to the Special Issue Confronting the Climate Change and Health Nexus: Interactions, Impacts, and Adaptation Strategies)

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34 pages, 2116 KB

Open AccessReview

Building Climate Resilient Fisheries and Aquaculture in Bangladesh: A Review of Impacts and Adaptation Strategies

by Mohammad Mahfujul Haque, Md. Naim Mahmud, A. K. Shakur Ahammad, Md. Mehedi Alam, Alif Layla Bablee, Neaz A. Hasan, Abul Bashar and Md. Mahmudul Hasan

Climate 2025, 13(10), 209; https://doi.org/10.3390/cli13100209 - 4 Oct 2025

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Abstract

This study examines the impacts of climate change on fisheries and aquaculture in Bangladesh, one of the most climate-vulnerable countries in the world. The fisheries and aquaculture sectors contribute significantly to the national GDP and support the livelihoods of 12% of the total [...] Read more.

This study examines the impacts of climate change on fisheries and aquaculture in Bangladesh, one of the most climate-vulnerable countries in the world. The fisheries and aquaculture sectors contribute significantly to the national GDP and support the livelihoods of 12% of the total population. Using a Critical Literature Review (CLR) approach, peer-reviewed articles, government reports, and official datasets published between 2006 and 2025 were reviewed across databases such as Scopus, Web of Science, FAO, and the Bangladesh Department of Fisheries (DoF). The analysis identifies major climate drivers, including rising temperature, erratic rainfall, salinity intrusion, sea-level rise, floods, droughts, cyclones, and extreme events, and reviews their differentiated impacts on key components of the sector: inland capture fisheries, marine fisheries, and aquaculture systems. For inland capture fisheries, the review highlights habitat degradation, biodiversity loss, and disrupted fish migration and breeding cycles. In aquaculture, particularly in coastal systems, this study reviews the challenges posed by disease outbreaks, water quality deterioration, and disruptions in seed supply, affecting species such as carp, tilapia, pangasius, and shrimp. Coastal aquaculture is also particularly vulnerable to cyclones, tidal surges, and saline water intrusion, with documented economic losses from events such as Cyclones Yaas, Bulbul, Amphan, and Remal. The study synthesizes key findings related to climate-resilient aquaculture practices, monitoring frameworks, ecosystem-based approaches, and community-based adaptation strategies. It underscores the need for targeted interventions, especially in coastal areas facing increasing salinity levels and frequent storms. This study calls for collective action through policy interventions, research and development, and the promotion of climate-smart technologies to enhance resilience and sustain fisheries and aquaculture in the context of a rapidly changing climate. Full article

(This article belongs to the Collection Adaptation and Mitigation Practices and Frameworks)

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30 pages, 3428 KB

Open AccessReview

Tropical Fungi and LULUCF: Synergies for Climate Mitigation Through Nature-Based Culture (NbC)

by Retno Prayudyaningsih, Maman Turjaman, Margaretta Christita, Neo Endra Lelana, Ragil Setio Budi Irianto, Sarjiya Antonius, Safinah Surya Hakim, Asri Insiana Putri, Henti Hendalastuti Rachmat, Virni Budi Arifanti, Wahyu Catur Adinugroho, Said Fahmi, Rinaldi Imanuddin, Sri Suharti, Ulfah Karmila Sari, Asep Hidayat, Sona Suhartana, Tien Wahyuni, Sisva Silsigia, Tsuyoshi Kato, Ricksy Prematuri, Ahmad Faizal, Kae Miyazawa and Mitsuru Osaki Show full author list Hide full author list

Climate 2025, 13(10), 208; https://doi.org/10.3390/cli13100208 - 2 Oct 2025

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Abstract

Fungi in tropical ecosystems remain an understudied yet critical component of climate change mitigation, particularly within the Land Use, Land-Use Change, and Forestry (LULUCF) sector. This review highlights their dual role in reducing greenhouse gas (GHG) emissions by regulating carbon dioxide (CO₂ [...] Read more.

Fungi in tropical ecosystems remain an understudied yet critical component of climate change mitigation, particularly within the Land Use, Land-Use Change, and Forestry (LULUCF) sector. This review highlights their dual role in reducing greenhouse gas (GHG) emissions by regulating carbon dioxide (CO₂), methane (CH₄), and nitrous oxides (N₂O) while enhancing long-term carbon sequestration. Mycorrhizal fungi are pivotal in maintaining soil integrity, facilitating nutrient cycling, and amplifying carbon storage capacity through symbiotic mechanisms. We synthesize how fungal symbiotic systems under LULUCF shape ecosystem networks and note that, in pristine ecosystems, these networks are resilient. We introduce the concept of Nature-based Culture (NbC) to describe symbiotic self-cultures sustaining ecosystem stability, biodiversity, and carbon sequestration. Case studies demonstrate how the NbC concept is applied in reforestation strategies such as AeroHydro Culture (AHC), the Integrated Mangrove Sowing System (IMSS), and the 4N approach (No Plastic, No Burning, No Chemical Fertilizer, Native Species). These approaches leverage mycorrhizal networks to improve restoration outcomes in peatlands, mangroves, and semi-arid regions while minimizing land disturbance and chemical inputs. Therefore, by bridging fungal ecology with LULUCF policy, this review advocates for a paradigm shift in forest management that integrates fungal symbioses to strengthen carbon storage, ecosystem resilience, and human well-being. Full article

(This article belongs to the Special Issue Forest Ecosystems under Climate Change)

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14 pages, 21399 KB

Open AccessArticle

Temporal Variability of Major Stratospheric Sudden Warmings in CMIP5 Climate Change Scenarios

by Víctor Manuel Chávez-Pérez, Juan A. Añel, Citlalli Almaguer-Gómez and Laura de la Torre

Climate 2025, 13(10), 207; https://doi.org/10.3390/cli13100207 - 2 Oct 2025

Viewed by 335

Abstract

Major stratospheric sudden warmings are key processes in the coupling between the stratosphere and the troposphere, exerting a direct influence on mid-latitude climate variability. This study evaluates projected changes in the frequency of these phenomena during the 2006–2100 period using six high-top general [...] Read more.

Major stratospheric sudden warmings are key processes in the coupling between the stratosphere and the troposphere, exerting a direct influence on mid-latitude climate variability. This study evaluates projected changes in the frequency of these phenomena during the 2006–2100 period using six high-top general circulation models from the CMIP5 project under the Representative Concentration Pathway scenarios 2.6, 4.5, and 8.5. The analysis combines the full future period with a moving-window approach of 27 and 48 years, compared against both the satellite-era (1979–2005) and extended historical (1958–2005) periods. This methodology reveals that model responses are highly heterogeneous, with alternating periods of significant increases and decreases in event frequency, partially modulated by internal variability. The magnitude and statistical significance of the projected changes strongly depend on the chosen historical reference period, and most models tend to reproduce displacement-type polar vortex events preferentially over split-type events. These results indicate that assessments based solely on multi-model means or long aggregated periods may mask subperiods with robust signals, although some of these may arise by chance given the 5% significance threshold. This underscores the need for temporally resolved analyses to improve the understanding of stratospheric variability and its potential impact on climate predictability. Full article

(This article belongs to the Section Climate and Environment)

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21 pages, 3572 KB

Open AccessArticle

Enhancing Climate Modeling over the Upper Blue Nile Basin Using RegCM5-MOLOCH

by Eatemad Keshta, Doaa Amin, Ashraf M. ElMoustafa and Mohamed A. Gad

Climate 2025, 13(10), 206; https://doi.org/10.3390/cli13100206 (registering DOI) - 2 Oct 2025

Viewed by 317

Abstract

The Upper Blue Nile Basin (UBNB), which contributes about 60% to the annual Nile flow, plays a critical role in the Nile water management. However, its complex terrain and climate create significant challenges for accurate regional climate simulations, which are essential for climate [...] Read more.

The Upper Blue Nile Basin (UBNB), which contributes about 60% to the annual Nile flow, plays a critical role in the Nile water management. However, its complex terrain and climate create significant challenges for accurate regional climate simulations, which are essential for climate impact assessments. This study aims to address the challenges of climate simulation over the UBNB by enhancing the Regional Climate Model system (RegCM5) with its new non-hydrostatic dynamical core (MOLOCH) to simulate precipitation and temperature. The model is driven by ERA5 reanalysis for the period (2000–2009), and two scenarios are simulated using two different schemes of the Planetary Boundary Layer (PBL): Holtslag (Hol) and University of Washington (UW). The two scenarios, noted as (MOLOCH-Hol and MOLOCH-UW), are compared to the previously best-performing hydrostatic configuration. The MOLOCH-UW scenario showed the best precipitation performance relative to observations, with an accepted dry Bias% up to 22%, and a high annual cycle correlation >0.85. However, MOLOCH-Hol showed a very good performance only in the wet season with a wet bias of 4% and moderate correlation of ≈0.6. For temperature, MOLOCH-UW also outperformed, achieving the lowest cold/warm bias range of −2% to +3%, and high correlations of ≈0.9 through the year and the wet season. This study concluded that the MOLOCH-UW is the most reliable configuration for reproducing the climate variability over the UBNB. This developed configuration is a promising tool for the basin’s hydroclimate applications, such as dynamical downscaling of the seasonal forecasts and future climate change scenarios produced by global circulation models. Future improvements could be achieved through convective-permitting simulation at ≤4 km resolution, especially in the application of assessing the land use change impact. Full article

(This article belongs to the Section Climate Dynamics and Modelling)

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24 pages, 22609 KB

Open AccessArticle

Terrain-Based High-Resolution Microclimate Modeling for Cold-Air-Pool-Induced Frost Risk Assessment in Karst Depressions

by András Dobos, Réka Farkas and Endre Dobos

Climate 2025, 13(10), 205; https://doi.org/10.3390/cli13100205 - 30 Sep 2025

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Abstract

Cold-air pooling (CAP) and frost risk represent significant climate-related hazards in karstic and agricultural environments, where local topography and surface cover strongly modulate microclimatic conditions. This study focuses on the Mohos sinkhole, Hungary’s cold pole, situated on the Bükk Plateau, to investigate the [...] Read more.

Cold-air pooling (CAP) and frost risk represent significant climate-related hazards in karstic and agricultural environments, where local topography and surface cover strongly modulate microclimatic conditions. This study focuses on the Mohos sinkhole, Hungary’s cold pole, situated on the Bükk Plateau, to investigate the formation, structure, and persistence of CAPs in a Central European karst depression. High-resolution terrain-based modeling was conducted using UAV-derived digital surface models combined with multiple GIS tools (Sky-View Factor, Wind Exposition Index, Cold Air Flow, and Diurnal Anisotropic Heat). These models were validated and enriched by multi-level temperature measurements and thermal imaging under various synoptic conditions. Results reveal that temperature inversions frequently form during clear, calm nights, leading to extreme near-surface cold accumulation within the sinkhole. Inversions may persist into the day due to topographic shading and density stratification. Vegetation and basin geometry influence radiative and turbulent fluxes, shaping the spatial extent and intensity of cold-air layers. The CAP is interpreted as part of a broader interconnected multi-sinkhole system. This integrated approach offers a transferable, cost-effective framework for terrain-driven frost hazard assessment, with direct relevance to precision agriculture, mesoscale model refinement, and site-specific climate adaptation in mountainous or frost-sensitive regions. Full article

(This article belongs to the Section Climate and Environment)

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18 pages, 15842 KB

Open AccessSystematic Review

The Effects of Climate Change on Health: A Systematic Review from a One Health Perspective

by Indira A. Luza Eyzaguirre, Esley Lima de Sousa, Yago de Jesus Martins, Marcus E. B. Fernandes and Aldemir B. Oliveira-Filho

Climate 2025, 13(10), 204; https://doi.org/10.3390/cli13100204 - 29 Sep 2025

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Abstract

Climate change has been occurring due to global warming since the 1950s, causing impacts on natural and social systems, including health. This review article involves the One Health approach as a holistic approach that integrates environmental, human, and animal health, since there is [...] Read more.

Climate change has been occurring due to global warming since the 1950s, causing impacts on natural and social systems, including health. This review article involves the One Health approach as a holistic approach that integrates environmental, human, and animal health, since there is a significant gap in knowledge about the impacts of climate change on health. The questions that guide this research are as follows: What is the state of the art in studies on climate change and One Health? What are the main topics addressed in studies on climate change and One Health at a global level? The main objective is to conduct a systematic review of studies on climate change and its relationship with One Health to assess the main topics studied, involving climate change and health at a global level, and identify the gaps and challenges of these studies. The review demonstrated the exponential growth of studies that relate climate change to One Health, especially in the last three decades, with more records of studies that address infectious diseases such as arboviruses. Furthermore, studies on climate and its impact on mental health were detected, causing depression, anxiety, post-traumatic stress disorder (PTSD), solastalgia, and eco-anxiety, especially in vulnerable populations such as indigenous communities, women, children, family farmers, and the elderly. The One Health approach was shown to be restricted to health-related issues. Thus, theoretical and experimental studies are still needed to assess the real impact of climate change on the various axes involving human health and its relationship with anthropogenic activities, environmental health, and animal health. Full article

(This article belongs to the Special Issue Climate Impact on Human Health)

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24 pages, 4911 KB

Open AccessReview

Hail Netting in Apple Orchards: Current Knowledge, Research Gaps, and Perspectives for Digital Agriculture

by Danielle Elis Garcia Furuya, Édson Luis Bolfe, Franco da Silveira, Jayme Garcia Arnal Barbedo, Tamires Lima da Silva, Luciana Alvim Santos Romani, Letícia Ferrari Castanheiro and Luciano Gebler

Climate 2025, 13(10), 203; https://doi.org/10.3390/cli13100203 - 28 Sep 2025

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Abstract

Hailstorms are a major climatic threat to apple production, causing substantial economic losses in orchards worldwide. Anti-hail nets have been increasingly adopted to mitigate this risk, but the scientific literature on their effectiveness and future applications remains scattered, especially considering advances in digital [...] Read more.

Hailstorms are a major climatic threat to apple production, causing substantial economic losses in orchards worldwide. Anti-hail nets have been increasingly adopted to mitigate this risk, but the scientific literature on their effectiveness and future applications remains scattered, especially considering advances in digital agriculture. This study synthesizes current knowledge on the use of anti-hail nets in apple orchards through a systematic review and explores future perspectives involving digital technologies. A PRISMA-based review was conducted using three databases, revealing information regarding the studied countries, netting colors, and apple varieties, among others. A clear research gap was identified in integrating anti-hail nets with remote sensing and Artificial Intelligence (AI). This paper also analyzes studies from Vacaria, Brazil, a key apple-producing region and part of the Semear Digital project, highlighting local efforts to use hail netting in commercial orchards. Potential applications of AI algorithms and remote sensing are proposed for hail netting assessment, orchard monitoring, and decision-making support. These technologies can improve predictive modeling, quantify areas, and enhance precision management. Findings suggest combining traditional protective methods with technological innovations to strengthen orchard resilience in regions exposed to extreme weather. Full article

(This article belongs to the Special Issue Climate Risk in Agriculture, Analysis, Modeling and Applications)

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28 pages, 10416 KB

Open AccessArticle

One Country, Several Droughts: Characterisation, Evolution, and Trends in Meteorological Droughts in Spain Within the Context of Climate Change

by David Espín Sánchez and Jorge Olcina Cantos

Climate 2025, 13(10), 202; https://doi.org/10.3390/cli13100202 - 26 Sep 2025

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Abstract

In this paper, we analyse drought variability in Spain (1950–2024) using the Standardised Precipitation–Evapotranspiration Index (SPEI) at 6-, 12-, and 24-month scales. Using 43 long-record meteorological observatories (AEMET), we compute SPEI from quality-controlled (QC), homogenised series, and derive coherent drought regions via clustering [...] Read more.

In this paper, we analyse drought variability in Spain (1950–2024) using the Standardised Precipitation–Evapotranspiration Index (SPEI) at 6-, 12-, and 24-month scales. Using 43 long-record meteorological observatories (AEMET), we compute SPEI from quality-controlled (QC), homogenised series, and derive coherent drought regions via clustering and assess trends in the frequency, duration, and intensity of dry episodes (SPEI ≤ −1.5), including seasonality and statistical significance (p < 0.05). Short-term behaviour (SPEI-6) has become more complex in recent decades, with the emergence of a “Catalonia” type and stronger June–October deficits across the northern interior; Mediterranean coasts show smaller or non-significant changes. Long-term behaviour (SPEI-24) is more structural, with increasing persistence and duration over the north-eastern interior and Andalusia–La Mancha, consistent with multi-year drought. Overall, short and long scales converge on rising drought severity and persistence across interior Spain, supporting multi-scale monitoring and region-specific adaptation in agriculture, water resources, and forest management. Key figures are as follows: at 6 months—frequency 0.09/0.08 per decade (Centre–León/Catalonia), duration 0.59/0.50 months per decade, intensity −0.12 to −0.10 SPEI per decade; at 24 months—frequency 0.5 per decade (Cantabrian/NE interior), duration 0.8/0.7/0.4 months per decade (Andalusia–La Mancha/NE interior/Cabo de Gata–Almería), intensity −0.06 SPEI per decade; Mediterranean changes are smaller or non-significant. Full article

(This article belongs to the Section Weather, Events and Impacts)

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22 pages, 4411 KB

Open AccessArticle

Near-Surface Temperature Climate Change in the Caspian Region: A Study Using Meteorological Station Data, Reanalyses, and CMIP6 Models

by Ilya Serykh, Svetlana Krasheninnikova, Said Safarov, Elnur Safarov, Ebrahim Asadi Oskouei, Tatiana Gorbunova, Roman Gorbunov and Yashar Falamarzi

Climate 2025, 13(10), 201; https://doi.org/10.3390/cli13100201 - 25 Sep 2025

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Abstract

The climatic variability of near-surface air temperature (NSAT) over the Caspian region (35–60° N; 40–65° E) was analyzed in this study. The analysis was based on a comparison of data from various sources: weather stations, NOAA OISSTv2 satellite-based data, atmospheric reanalyses ECMWF ERA5, [...] Read more.

The climatic variability of near-surface air temperature (NSAT) over the Caspian region (35–60° N; 40–65° E) was analyzed in this study. The analysis was based on a comparison of data from various sources: weather stations, NOAA OISSTv2 satellite-based data, atmospheric reanalyses ECMWF ERA5, NASA MERRA-2, and NCEP/NCAR, and the outputs from 33 Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). CMIP6 models results from the historical and Shared Socioeconomic Pathways (SSPs) experiments were utilized. Over the period 1940–2023, NSAT exhibited variable changes across the Caspian region. Weather stations in the northwestern part of the region indicated NSAT increases of 0.9 ± 0.2 °C for 1985–2023. In the central-western part of the Caspian region, the increase in average NSAT between 1940–1969 and 1994–2023 was 1.4 °C with a spatial standard deviation of 0.3 °C. In the southern part of the Caspian region, the increase in average NSAT between 1986–2004 and 2005–2023 was 0.8 ± 0.1 °C. Importantly, all 33 CMIP6 models, as well as the ERA5 reanalysis, captured an average NSAT increase of approximately 1.3 ± 0.5 °C for the whole Caspian region between 1940–1969 and 1994–2023. From the ERA5 data, the increase in NSAT was more pronounced in the north (~1.6 °C) than in the central Caspian region, with the most significant warming observed in the mountainous regions of Iran (up to 3.0 °C). Under various CMIP6 SSPs scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), projections indicate an increase in average NSAT across the study region. Comparing the periods 1994–2023 and 2070–2099, the projected NSAT increases are 1.7 ± 0.7 °C, 2.8 ± 0.8 °C, 4.0 ± 0.9 °C, and 5.2 ± 1.2 °C, respectively. For the earlier period of 2024–2053 relative to 1994–2023, the projected NSAT increases are 1.2 ± 0.4 °C, 1.3 ± 0.4 °C, 1.4 ± 0.4 °C, and 1.7 ± 0.5 °C. Notably, the projected increase in NSAT is slower over the Caspian Sea compared to the surrounding land areas. Full article

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25 pages, 20264 KB

Open AccessArticle

Assessing Urban Resilience Through Physically Based Hydrodynamic Modeling Under Future Development and Climate Scenarios: A Case Study of Northern Rangsit Area, Thailand

by Detchphol Chitwatkulsiri, Kim Neil Irvine, Lloyd Hock Chye Chua, Lihoun Teang, Ratchaphon Charoenpanuchart, Fa Likitswat and Alisa Sahavacharin

Climate 2025, 13(10), 200; https://doi.org/10.3390/cli13100200 - 24 Sep 2025

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Abstract

Urban flooding represents a growing concern on a global scale, particularly in regions characterized by rapid urbanization and increased climate variability. This study concentrates on the Rangsit area in Pathum Thani Province, Thailand, an urbanizing peri-urban area north of Bangkok and within the [...] Read more.

Urban flooding represents a growing concern on a global scale, particularly in regions characterized by rapid urbanization and increased climate variability. This study concentrates on the Rangsit area in Pathum Thani Province, Thailand, an urbanizing peri-urban area north of Bangkok and within the Chao Phraya River Basin where transitions in land use and the intensification of rainfall induced by climate change are elevating flood risks. A physically based hydrodynamic model was developed utilizing PCSWMM to assess current and future flood scenarios that considered future build-out plans and climate change scenarios. The model underwent calibration and validation using a continuous modeling approach that conservatively focused on wet year conditions, based on available rainfall and water level data. In assessing future scenarios, we considered land use projections based on regional development plans and climate projections downscaled under RCP4.5 and RCP8.5 pathways. Results indicate that both urban expansion and intensifying rainfall are likely to increase flood magnitudes, durations, and impacted areas, although in this rapidly developing peri-urban area, land use change was the most important driver. The findings suggest that a physically based modeling approach could support a smart-control framework that could effectively inform evidence-based urban planning and infrastructure investments. These insights are of paramount importance for flood-prone regions in Thailand and Southeast Asia, where dynamic modeling tools must underpin governance, climate adaptation, and risk communication. Furthermore, given the greater impact of future build-out on flood risk, as compared to climate change, there is an opportunity to effectively and proactively improve flood resilience through the implementation of integrated Nature-based Solution and hard engineering approaches, in combination with effective flood management policy. Full article

(This article belongs to the Special Issue Modelling for the Influences of Climate and Landscape Processes on Hydrology)

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19 pages, 1442 KB

Open AccessArticle

Benova and Cenova Models in the Homogenization of Climatic Time Series

by Peter Domonkos

Climate 2025, 13(10), 199; https://doi.org/10.3390/cli13100199 - 23 Sep 2025

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Abstract

For the correct evaluation of climate trends and climate variability, it is important to remove non-climatic biases from the observed data. Such biases, referred to as inhomogeneities, occur for station relocations or changes in the instrumentation or instrument installation, among other reasons. Most [...] Read more.

For the correct evaluation of climate trends and climate variability, it is important to remove non-climatic biases from the observed data. Such biases, referred to as inhomogeneities, occur for station relocations or changes in the instrumentation or instrument installation, among other reasons. Most inhomogeneities are related to a sudden change (break) in the technical conditions of the climate observations. In long time series (>30 years), usually multiple breaks occur, and their joint impact on the long-term trends and variability is more important than their individual evaluation. Benova is the optimal method for the joint calculation of correction terms for removing inhomogeneity biases. Cenova is a modified, imperfect version of Benova, which, however, can also be used in discontinuous time series. In the homogenization of section means, the use of Benova should be preferred, while in homogenizing probability distribution, only Cenova can be applied. This study presents the Benova and Cenova methods, discusses their main properties and compares their efficiencies using the benchmark dataset of the Spanish MULTITEST project (2015–2017), which is the largest existing dataset of this kind so far. The root mean square error (RMSE) of the annual means and the mean absolute trend bias were calculated for the Benova and Cenova results. When the signal-to-noise ratio (SNR) is high, the errors in the Cenova results are higher, from 14% to 24%, while when the SNR is low, or concerted inhomogeneities in several time series occur, the advantage of Benova over Cenova might disappear. Full article

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