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Climate Risk in Agriculture, Analysis, Modeling and Applications
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Climate Risk in Agriculture, Analysis, Modeling and Applications

A Special Issue of Climate (ISSN 2225-1154).

Deadline for manuscript submissions: 31 October 2026 | Viewed by 5621

Editors

Dr. Ioannis Charalampopoulos

E-Mail Website
Guest Editor
Faculty of Crop Sciences, Agricultural University of Athens, Athens, Greece
Interests: agroclimatology; bioclimatology; biometeorology; landscape change; computational data analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Fotoula Droulia

E-Mail Website
Guest Editor
Laboratory of General and Agricultural Meteorology, Department of Crop Science, Agricultural University of Athens, 11855 Athens, Greece
Interests: environment; environmental impact assessment

Special Issue Information

Dear Colleagues,

Climate risk in agriculture is one of the important issues determining the food security, livelihood of communities, and ecosystem sustenance throughout the world. Because temperature is rising, extreme events such as droughts, floods, and heat waves will further affect agriculture.

Climate risk analysis and modeling involve understanding the interdependency between complex climate parameters and agricultural systems. Similarly, some advanced modeling techniques for crop and climate impact assessment can help simulate and project the most likely impacts of strategic adaptation actions.

Applications of climate risk modeling in crop resilient practices and management, optimization of irrigation practices, and implementation of sustainable farming techniques will be worked out. Climate risk analysis can also serve as a very useful tool for effective and equitable agricultural insurance services. By incorporating climate risk analysis into agricultural planning, we can make farming communities more resilient and ensure food security in this era of climate change.

Dr. Ioannis Charalampopoulos
Dr. Fotoula Droulia
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Climate is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • agriculture
  • climate change
  • drought/flood
  • irrigation
  • food-water-energy nexus
  • pest management
  • organic farming
  • agro technology

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Published Papers (3 papers)

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Research

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38 pages, 12508 KB  
Article
Modeling and Mapping Climate Risk for Olive Cultivation in Greece Using an AI-Assisted Geospatial Analysis System
by Konstantinos Papadopoulos-Dorlis, Fotoula Droulia, Peter A. Roussos, Emmanouil Psomiadis and Ioannis Charalampopoulos
Climate 2026, 14(9), 199; https://doi.org/10.3390/cli14090199 - 20 Sep 2026
Abstract
Greek olive groves are subject to multiple thermal, water, biotic, and extreme-weather pressures, yet national-scale maps of their combined historical exposure remain limited. The present study quantified climate risk for olive cultivation across Greece using twenty agroclimatic indicators grouped into four thematic categories. [...] Read more.
Greek olive groves are subject to multiple thermal, water, biotic, and extreme-weather pressures, yet national-scale maps of their combined historical exposure remain limited. The present study quantified climate risk for olive cultivation across Greece using twenty agroclimatic indicators grouped into four thematic categories. Using hourly ERA5-Land data (1995–2024) and quality-controlled ESWD reports (2014–2024), each indicator recorded how often predefined adverse thresholds were met at the grid-cell level during the reference period. We integrated the resulting layers using a weighted multi-criteria decision analysis, with lethal frost applied as a separate constraint, to produce a composite spatial distribution of climate risk and district-level summaries linked to CORINE Land Cover 2018, olive grove class (2.2.3). Composite risk was spatially heterogeneous: cold and frost recurrence predominated in northern and upland areas, whereas water-related indicators occurred most persistently in southern and island districts, including eastern Crete. Most of the mapped olive grove area fell into intermediate composite classes rather than at the extremes of the score range. Comparison with a recent nationwide olive suitability assessment showed agreement in major western and southern producing districts, but also contrasting patterns where high suitability coincided with elevated recurrence-based risk. The resulting products provide a national historical baseline for climate-risk recurrence in Greek olive groves, offer a spatial basis for regionally targeted adaptation planning, and demonstrate the applicability of an AI-assisted geospatial framework for reproducible national-scale climate-risk assessment of perennial crops. Full article
(This article belongs to the Special Issue Climate Risk in Agriculture, Analysis, Modeling and Applications)
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16 pages, 5877 KB  
Article
Climate Change Impacts on Agroforestry Suitability in the Amazon: CMIP6-Based Projections for Theobroma grandiflorum
by Waléria Pereira Monteiro Corrêa, Leonardo de Sousa Miranda, Luciano Jorge Serejo dos Anjos, Thaiane Soeiro da Silva Dias, José Felipe Gazel Menezes and Everaldo Barreiros de Souza
Climate 2026, 14(8), 168; https://doi.org/10.3390/cli14080168 - 18 Aug 2026
Viewed by 493
Abstract
Climate change is expected to significantly alter surface air temperature and precipitation regimes across the Amazon Basin, with direct implications for agroforestry systems and climate-sensitive perennial crops. This study projects the impacts of anthropogenic global warming on the habitat suitability of Theobroma grandiflorum [...] Read more.
Climate change is expected to significantly alter surface air temperature and precipitation regimes across the Amazon Basin, with direct implications for agroforestry systems and climate-sensitive perennial crops. This study projects the impacts of anthropogenic global warming on the habitat suitability of Theobroma grandiflorum (cupuaçu), a keystone species for Amazonian agroforestry, local livelihoods, and the bioeconomy. Using an ensemble species distribution modeling (SDM) framework, we applied multiple algorithms and two CMIP6 global climate models (BCC-CSM2-MR and MIROC6) under the SSP3-7.0 and SSP5-8.5 scenarios for the near-future (2021–2040) and far-future (2061–2080). Contrary to the range contractions projected for many Amazonian endemics, our ensemble projections reveal a consistent trend of expanding climatically suitable area, primarily into adjacent ecological transition zones. This expansion is driven largely by basin-wide increases in mean annual temperature, the most influential predictor in our modeling study. Quantitatively, we project a net habitat expansion of 32.2% (415,114 km2) under high-concordance future scenarios. A core climate refuge of 955,570 km2, representing 74.2% of the current suitable range, is identified as a high priority for in situ conservation. Conversely, approximately 25.8% of the current range (331,919 km2) may become climatically unsuitable, particularly in parts of the western Amazon. These findings suggest that reducing thermal constraints in currently marginal areas could open opportunities for integrating cupuaçu into climate-resilient agroforestry systems beyond its present distribution. Such heterogeneous responses of Amazonian agroforestry species to climate change highlight the importance of incorporating species-specific climate sensitivities into adaptation planning, land-use strategies, and climate-resilient bioeconomy policies under future warming scenarios. Full article
(This article belongs to the Special Issue Climate Risk in Agriculture, Analysis, Modeling and Applications)
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Review

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24 pages, 4911 KB  
Review
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
Cited by 5 | Viewed by 4149
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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