CSGM Publications

The 2024 North Atlantic (hereafter Atlantic) hurricane season started quickly, with the earliest Category 5 on record (Beryl) and three hurricanes forming through 14 August. Following Ernesto's dissipation on 20 August, the Atlantic hurricane season became extremely quiet during the climatological peak of hurricane season, with only one Category 2 hurricane (Francine) and one tropical storm through 23 September. Several environmental factors likely contributed to this unexpected, prolonged lull. During mid-to-late August, subseasonal conditions were broadly favorable for Atlantic hurricanes, but a northward shift in African easterly wave emergence latitude yielded fewer tropical cyclone seed disturbances that also traversed unfavorably cool ocean water. During early-to-mid September, subseasonal variability driven by the Madden-Julian oscillation was less conducive to hurricane activity, with several bouts of increased vertical wind shear across the central Atlantic. Throughout most of the lull, the tropical Atlantic was anomalously dry and subsident, suppressing hurricane formation chances.

Regional Climates is one chapter from the State of the Climate in 2024 annual report and is available from https://doi. org/10.1175/2025BAMSStateoftheClimate_Chapter7. 1. Compiled by NOAA’s National Centers for Environmental Information, State of the Climate in 2024 is based on contributions from scientists from around the world. It provides a detailed update on global climate indicators, notable weather events, and other data collected by environmental monitoring stations and instruments located on land, water, ice, and in space.

For over 30 years, detection and attribution (D&A) studies have informed key conclusions in international and national assessments of climate science, providing compelling evidence for the reality and seriousness of anthropogenic effects on the global climate. In the early twenty-first century, D&A methods were adapted to assess the contribution of climate change to longer-term trends in earth system processes and extreme weather events. More recently, attribution research quantified the health and economic impacts of climate change. Here we provide practical guidance to inform transdisciplinary collaboration among health, climate, and other relevant scientific disciplines and interested parties in designing, conducting, interpreting, and reporting robust and policy-relevant attribution analyses of human health outcomes. This guidance resulted from discussions among experts in health and climate science. Recommended steps include co-developing the research questions across disciplines; establishing a transdisciplinary analytic team with fundamental grounding in the core disciplines; engaging meaningfully with relevant interested parties and decision-makers to define an appropriate study design and analytic process, including defining the exposure event or trend; identifying, visualizing, and describing linkages in the causal pathway from exposure to weather/climate variables to the health outcome(s) of interest; choosing appropriate counterfactual climate data, and where applicable, to evaluate the skill of the climate and health impact model(s) used in D&A research; quantifying the attributable changes in climate variables; quantifying the attributable health impacts within the context of other determinants of exposure and vulnerability; and reporting key results, including a description of how recommendations were incorporated into the analytical plan. Implementation of guidance would benefit diverse interested parties including researchers, research funders, policymakers, and climate litigation by harmonizing methods and increasing confidence in findings.

Tropical cyclone (TC) seasonal landfall probability is challenging to forecast because of the limited seasonal predictability of steering flow patterns. Past studies mainly focus on the large-scale ocean and atmospheric conditions that lead to changes in seasonal tropical cyclone genesis frequency in a given basin, but less attention has focused on seasonal landfall probability inherent to changes in steering flow patterns linked to subtropical highs (STHs). Here, we examine SST anomaly patterns that control variability in summertime STH cells in the Northern and Southern Hemispheres. We link those ocean impacts to changes in early season TC landfall probability in the western North Pacific, North Atlantic, and south Indian Ocean Basins. STHs in the North Pacific, North Atlantic, and south Indian Ocean exhibit increased variability on their western peripheries linked to anomalous zonal SST gradients. In the Northern Hemisphere, an interbasin zonal contrast in SST anomalies fosters a westward extension in both North Pacific and North Atlantic STHs. As a result, TCs curve around STHs ∼6° in longitude farther west in the western North Pacific basin. In contrast, the Atlantic basin had the opposite effect due to minimal TC activity over the tropical Atlantic from inhibiting SST anomalies. The south Indian Ocean had a 9% increase in landfall probability for TCs that formed in the western half of the southern Indian Ocean during a positive localized SST dipole. The seasonal persistence of Southern Hemispheric STHs resembles aquaplanet simulations of STHs, in contrast to the seasonal evolution observed in their Northern Hemispheric counterparts.

The slow pace of global mitigation efforts has led to increased interest in Solar Radiation Modification (SRM) as a means for rapidly and artificially cooling the planet. Deploying SRM technologies, however, may directly alter renewable energy resources. This makes it a concern for Caribbean countries which are investing heavily in Variable Renewable Energy (VRE) to reduce their reliance on imported energy and meet climate change mitigation goals. In this study, solar irradiance output is extracted from the HadGEM2-ES global climate model run using the G4 (Stratospheric Aerosol Injection) SRM scenario from the Geoengineering Model Intercomparison Project (GeoMIP). The data is extracted for two future time periods corresponding to when global surface temperatures are projected to be 1.5C and 2.0C above pre-industrial levels using the HadGEM2-ES run under the Representative Concentration Pathway 4.5 (RCP4.5) scenario. Wind speed data are similarly extracted but for the HadGEM2-ES run using the G4, as well as the G4cdnc and G4seasalt (Marine Cloud Brightening) GeoMIP scenarios. The solar and wind data are used to evaluate changes in solar photovoltaic (PV) and wind farm power generation in the Caribbean in future ‘SRM versus non-SRM worlds’. Solar irradiance resources and PV energy generation generally decrease under SRM compared to RCP4.5...

Prior to 1995, the percentage of the Caribbean's hot season that was heatwave-prone rose from 0% to 10%, and in 2020, it surpassed 50%, increasing the need for building cooling. To increase the number of cooling alternatives, a study was carried out using Jamaica as a case study to see whether the nocturnal ambient conditions in the Caribbean are appropriate for the use of passive cooling via Phase Change Materials (PCM) technology. Buildings in the low- income country of Jamaica are mostly made of concrete, which is not the best thermal material for its tropical climate but is ideal for withstanding hurricane conditions. Using a PCM-24, an outdoor experiment conducted in Kingston, Jamaica, revealed that night-time conditions in August was able to solidify the PCM with the help of radiative cooling. A map was then produced by applying a solidification criterion of 4°C for 4 hours or longer below the melting temperature to data from 25 automated weather stations located throughout the island. The map indicated that over 60% of nights a year in Jamaica's core mountainous regions provide conditions conducive to establishing the PCM-24.

The World Climate Research Programme (WCRP) envisions a future where actionable climate information is universally accessible, supporting decision makers in preparing for and responding to climate change. In this perspective, we advocate for enhancing links between climate science and decision-making through a better and more decision-relevant understanding of climate impacts. The proposed framework comprises three pillars: climate science, impact science, and decision-making, focusing on generating seamless climate information from sub-seasonal, seasonal, decadal to century timescales informed by observed climate events and their impacts. The link between climate science and decision-making has strengthened in recent years, partly owing to undeniable impacts arising from disastrous weather extremes. Enhancing decision-relevant understanding involves utilizing lessons from past extreme events and implementing impact-based early warning systems to improve resilience. Integrated risk assessment and management require a comprehensive approach that encompasses good knowledge about possible impacts, hazard identification, monitoring, and communication of risks while acknowledging uncertainties inherent in climate predictions and projections, but not letting the uncertainty lead to decision paralysis. The importance of data accessibility, especially in the Global South, underscores the need for better coordination and resource allocation. Strategic frameworks should aim to enhance impact-related and open-access climate services around the world. Continuous improvements in predictive modeling and observational data are critical, as is ensuring that climate science remains relevant to decision makers locally and globally. Ultimately, fostering stronger collaborations and dedicated investments to process and tailor climate data will enhance societal preparedness, enabling communities to navigate the complexities of a changing climate effectively.

This chapter provides summaries of the 2023 temperature and precipitation conditions across seven broad regions: North America, Central America and the Caribbean, South America, Africa, Europe and the Middle East, Asia, and Oceania. In most cases, summaries of notable weather events are also included. Local scientists provided the annual summary for their respective regions and, unless otherwise noted, the source of the data used is typically the agency affiliated with the authors. The base period used for these analyses is 1991–2020, unless otherwise stated. Please note that on occasion different nations, even within the same section, may use unique periods to define their normal. Section introductions typically define the prevailing practices for that section, and exceptions will be noted within the text. In a similar way, many contributing authors use languages other than English as their primary professional language. To minimize additional loss of fidelity through re-interpretation after translation, editors have been conservative and careful to preserve the voice of the author. In some cases, this may result in abrupt transitions in style from section to section.

Small island states and territories are often seen as particularly vulnerable to climate change, which affects the shape of the land, its ecosystems and the resources that people depend on. Nature Climate Change asked a selection of scientists from different island states and territories to discuss the role that climate science and action has in supporting island communities.

Projections of the future climate of small island states and territories are currently limited by the coarse resolution of models. We call for rapid global and regional cooperation to develop projections compatible with small island scales, providing relevant local information and decision-making tools.

Tropical Small Island Developing States (SIDS), such as those in the Caribbean, are among the most vulnerable to the impacts of climate change, most notably sea-level rise. The current sea-level rise in the Caribbean is 3.40 ± 0.3 mm/year (1993–2019), which is similar to the 3.25 ± 0.4 mm/year global mean sea-level (GMSL) rise (1993–2018). Throughout the year, Caribbean seasonal sea-level variability is found to respond to sea surface temperature variability. Over the past few decades, the trend in Caribbean Sea-level rise is also found to be variable. Satellite altimetry and steric sea-level records of the Caribbean region reveal a shift in the late 2003-early 2004, which separates two distinct periods of sea-level rise. Thermal expansion dominates the sea-level trend from 1993–2003. Following this period, there is an increased trend in sea-level rise, with a dominance of mass changes from 2004–2019, as confirmed by GRACE data. During this period, the sea-level trend is 6.15 ± 0.5 mm/year, which is 67% faster than the most recent estimates of global mean sea-level rise provided by the Intergovernmental Panel on Climate Change (3.69 ± 0.5 mm/year for the period 2006–2018). Despite its reduced importance, increasing temperatures contribute greatly to sea-level rise in the Caribbean region through thermal expansion of ocean water, hence there is a need to limit the current trend of global warming.

Climate change has emerged across many regions. Some observed regional climate changes, such as amplified Arctic warming and land-sea warming contrasts have been predicted by climate models. However, many other observed regional changes, such as changes in tropical sea surface temperature and monsoon rainfall are not well simulated by climate model ensembles even when taking into account natural internal variability and structural uncertainties in the response of models to anthropogenic radiative forcing. This suggests climate model predictions may not fully reflect what our future will look like. The discrepancies between models and observations are not well understood due to several real and apparent puzzles and limitations such as the “signal-to-noise paradox” and real-world record-shattering extremes falling outside of the possible range predicted by models. Addressing these discrepancies, puzzles and limitations is essential, because understanding and reliably predicting regional climate change is necessary in order to communicate effectively about the underlying drivers of change, provide reliable information to stakeholders, enable societies to adapt, and increase resilience and reduce vulnerability. The challenges of achieving this are greater in the Global South, especially because of the lack of observational data over long time periods and a lack of scientific focus on Global South climate change. To address discrepancies between observations and models, it is important to prioritize resources for understanding regional climate predictions and analyzing where and why models and observations disagree via testing hypotheses of drivers of biases using observations and models. Gaps in understanding can be discovered and filled by exploiting new tools, such as artificial intelligence/machine learning, high-resolution models, new modeling experiments in the model hierarchy, better quantification of forcing, and new observations. Conscious efforts are needed toward creating opportunities that allow regional experts, particularly those from the Global South, to take the lead in regional climate research. This includes co-learning in technical aspects of analyzing simulations and in the physics and dynamics of regional climate change. Finally, improved methods of regional climate communication are needed, which account for the underlying uncertainties, in order to provide reliable and actionable information to stakeholders and the media.

The limited success of international efforts to reduce global warming at levels established in the Paris Agreement, and the increasing frequency and strength of climate impacts, highlight the urgent need of adaptation, particularly in developing countries. Unfortunately, current levels of adaptation initiatives are not enough to counteract the observed impacts and projected risks from climate change in Latin America and the Caribbean (LAC). In this paper, we review and highlight relevant issues that have limited the capacity to transform climate knowledge and parties’ ambitions into action in the region. Current vulnerabilities and climatic impact-drivers in LAC are diverse, complex, and region-specific and their effects are expected to be exacerbated by climate change. However, the advancement of regional and domestic climate agendas has been hindered by scientific gaps, political support, institutional capacity, and financial, technical, human, and economic limitations that are common to many LAC countries. Transforming climate data into multidimensional metrics with useful thresholds for different sectors and understanding their contribution for feasible adaptation strategies are delayed by regional and local conundrums such as lack of inclusive governance, data availability, equity, justice, and transboundary issues. We discuss ways to move forward to develop local and regional climate resilient development actions and a more sustainable future in LAC. The climate science community in LAC needs to strengthen its local, national, and international connections and with decision/policymakers and society to establish a three-way engagement by proposing suitable adaptation actions and international negotiations to reduce the risks and vulnerability associated with climate extremes, climate variability and climate change in the region. The discussions and insights presented in this work could be extrapolated to other countries in the Global South.

Observational and modeling studies indicate significant changes in the global hydroclimate in the twentieth and early twenty-first centuries due to anthropogenic climate change. In this review, we analyze the recent literature on the observed changes in hydroclimate attributable to anthropogenic forcing, the physical and biological mechanisms underlying those changes, and the advantages and limitations of current detection and attribution methods. Changes in the magnitude and spatial patterns of precipitation minus evaporation (P–E) are consistent with increased water vapor content driven by higher temperatures. While thermodynamics explains most of the observed changes, the contribution of dynamics is not yet well constrained, especially at regional and local scales, due to limitations in observations and climate models. Anthropogenic climate change has also increased the severity and likelihood of contemporaneous droughts in southwestern North America, southwestern South America, the Mediterranean, and the Caribbean. An increased frequency of extreme precipitation events and shifts in phenology has also been attributed to anthropogenic climate change. While considerable uncertainties persist on the role of plant physiology in modulating hydroclimate and vice versa, emerging evidence indicates that increased canopy water demand and longer growing seasons negate the water-saving effects from increased water-use efficiency.

There is a dearth of studies characterizing historical sea level variability at the local scale for the islands in the Caribbean. This is due to the lack of reliable long term tide gauge data. There is, however, a significant need for such studies given that small islands are under increasing threat from rising sea levels, storm surges, and coastal flooding due to global warming. The growing length of satellite altimetry records provides a useful alternative to undertake sea level analyses. Altimetry data, spanning 1993–2019, are used herein to explore multi-timescale sea level variability near the south coast of Jamaica, in the northwest Caribbean. Caribbean basin dynamics and largescale forcing mechanisms, which could account for the variability, are also investigated. The results show that the average annual amplitude off the south coast of Jamaica is approximately 10 cm with a seasonal peak during the summer (July–August). The highest annual sea levels occur within the Caribbean storm season, adding to the annual risk. The annual trend over the 27 years is 3.3 ± 0.4 mm/yr when adjusted for Glacial Isostatic Adjustment (GIA), instrumental drift, and accounting for uncertainties. This is comparable to mean global sea level rise, but almost twice the prior estimates for the Caribbean which used altimetry data up to 2010. This suggests an accelerated rate of rise in the Caribbean over the last decade. Empirical Orthogonal Function (EOF) and correlation analyses show the long-term trend to be a basin-wide characteristic and linked to warming Caribbean sea surface temperatures (SSTs) over the period. When the altimetry data are detrended and deseasoned, the leading EOF mode has maximum loadings over the northwest Caribbean, including Jamaica, and exhibits interannual variability which correlates significantly with a tropical Pacific-tropical Atlantic SST gradient index, local wind strength, and the Caribbean Low Level Jet (CLLJ). Correlations with the El Niño Southern Oscillation (ENSO) in summer, seen in this and other studies, likely arise through the contribution of the ENSO to the SST gradient index and the ENSO’s modulation of the CLLJ peak strength in July. The results demonstrate the usefulness of altimetry data for characterizing sea level risk on various timescales for small islands. They also suggest the potential for developing predictive models geared towards reducing those risks.

The Pantanal biome, at the confluence of Brazil, Bolivia and Paraguay, is the largest continental wetland on the planet and an invaluable reserve of biodiversity. The exceptional 2020 fire season in Pantanal drew particular attention due to the severe wildfires and the catastrophic natural and socio-economic impacts witnessed within the biome. So far, little progress has been made in order to better understand the influence of climate extremes on fire occurrence in Pantanal. Here, we evaluate how extreme hot conditions, through heatwave events, are related to the occurrence and the exacerbation of fires in this region. A historical analysis using a statistical regression model found that heatwaves during the dry season explained 82% of the interannual variability of burned area during the fire season. In a future perspective, an ensemble of CORDEX-CORE simulations assuming different Representative Concentration Pathways (RCP2.6 and RCP8.5), reveal a significant increasing trend in heatwave occurrence over Pantanal. Compared to historical levels, the RCP2.6 scenario leads to more than a doubling in the Pantanal heatwave incidence during the dry season by the second half of the 21st century, followed by a plateauing. Alternatively, RCP8.5 projects a steady increase of heatwave incidence until the end of the century, pointing to a very severe scenario in which heatwave conditions would be observed nearly over all the Pantanal area and during practically all the days of the dry season. Accordingly, favorable conditions for fire spread and consequent large burned areas are expected to occur more often in the future, posing a dramatic short-term threat to the ecosystem if no preservation action is undertaken.

Within this paper, a PLC system that takes advantage of the loop resonance of an entire DC-PV string configured as a circular signal path is developed and implemented. Low cost and extremely simple transceivers intended to be installed within each PV module of a string have been designed and successfully tested. In addition, an anti-saturation coil has been conceived to avoid saturation of the core when the entire DC current of the string flows through it. Bi-directional half-duplex communication was successfully executed with up to a 1 MHz carrier frequency (150 kbps bitrate), using a simple ASK modulation scheme. The transmission and reception performance are presented, along with the overall system cost in comparison to the previous literature.

Climate change already challenges people’s livelihood globally and it also affects plant health. Rising temperatures facilitate the introduction and establishment of unwanted organisms, including arthropods, pathogens, and weeds (hereafter collectively called pests). For example, a single, unusually warm winter under temperate climatic conditions may be sufficient to assist the establishment of invasive plant pests, which otherwise would not be able to establish. In addition, the increased market globalization and related transport of recent years, coupled with increased temperatures, has led to favorable conditions for pest movement, invasion, and establishment worldwide. Most published studies indicate that, in general, pest risk will increase in agricultural ecosystems under climate-change scenarios, especially in today’s cooler arctic, boreal, temperate, and subtropical regions. This is also mostly true for forestry. Some pests have already expanded their host range or distribution, at least in part due to changes in climate. Examples of these pests, selected according to their relevance in different geographical areas, are summarized here. The main pathways used by them, directly and/or indirectly, are also discussed. Understanding these pathways can support decisions about mitigation and adaptation measures. The review concludes that preventive mitigation and adaptation measures, including biosecurity, are key to reducing the projected increases in pest risk in agriculture, horticulture, and forestry. Therefore, the sustainable management of pests is urgently needed. It requires holistic solutions, including effective phytosanitary regulations, globally coordinated diagnostic and surveillance systems, pest risk modeling and analysis, and preparedness for pro-active management.

Bushfire management which incorporates fire potential indices is still in its infancy in Jamaica and the Caribbean. In this study three bushfire potential indices—Keetch–Byram Drought Index (KBDI), Vapour Pressure Deficit (VPD) and Water Potential (Ψw)—are calculated for south-central Jamaica where bushfire frequencies are highest. The skills of the indices are evaluated using their representation of the normalised bushfire climatology, monthly and seasonal (December–March/DJFM; April–June/AMJ; July–August/JA and September–November/SON) fire variability for the periods 2013–2017, 2010–2019 and 2001–2019. Fire data are obtained from the MODIS C6 Archive and Jamaica Fire Brigade (JFB). The relationship between the fire indices and large-scale oceanic and atmospheric features are also examined. The results suggest that Ψw exhibits strong correlations with the MODIS and JFB climatologies and represents well the maxima in March and July and the local minima in May–June and October. Ψw and VPDI also show good hit rates for moderate and high-risk categories in south-central Jamaica (though with relatively high false alarm rates). Regression models premised on Ψw and VPD respectively show good skill in representing AMJ (R2 = 57–58%), SON (R2 = 57–58%) and JA (R2 = 57–60%) fire variability. Variability during DJFM is poorly captured by any fire index. Although the KBDI represents the normalised climatology reasonably well its peaks occur one month later, that is, in April and August. KBDI exhibits strong and statistically significant correlations with JFB and MODIS climatologies, but seasonal models premised on KBDI do not perform as well as for the other two indices except in JA. All indices had a statistically significant relationship on both monthly and 1 month lag time scales for NINO3 and TNA-NINO3 large-scale climate indices. The indices, and in particular Ψw, show good prospects for producing seasonal bushfire outlooks for south-central Jamaica and Jamaica in general. These results also suggest the usefulness of monitoring large-scale oceanic patterns as part of the monitoring framework for bushfires in the island.

The Eastern Caribbean chain of islands is commonly known to exhibit high-enthalpy systems for geothermal energy exploitation. The northernmost Caribbean Community member state of Jamaica possesses physical manifestations of 12 hot springs across the island. Previous investigations indicate that of the potential 12 hot springs, Bath, Windsor and Milk River springs have cogent geothermometry of their thermal fluids with estimated temperature ranges of (80–102°C), (128–156°C), and (158–206°C), respectively. The paper provides numerical findings for each geothermal system of interest and performs Monte Carlo simulations to optimize calculated findings. The determined quantitative findings are considered under the context of environmental savings and policy regime conditions for driving geothermal energy development. The three areas of interest are situated within the Rio Minho Basin, the Dry Harbour Mountains and the Blue Mountain South Basin. Through the consideration of a 25-year lifetime for production, a collective total of 94.81 MWe of geothermal power reserves can be absorbed into the national energy mix, displacing an estimated 0.38 million barrels of oil imports, resulting in approximately 0.44 million tonnes of carbon dioxide emissions being avoided per year. This article is part of the theme issue ‘Developing resilient energy systems’.

Tropical dry forests are among the most threatened ecosystems in the world, and those occurring in the insular Caribbean are particularly vulnerable. Climate change represents a significant threat for the Caribbean region and for small islands like Jamaica. Using the Hellshire Hills protected area in Jamaica, a simple model was developed to project future abundance of arthropods and lizards based on current sensitivities to climate variables derived from rainfall and temperature records. The abundances of 20 modelled taxa were predicted more often by rainfall variables than temperature, but both were found to have strong impacts on arthropod and lizard abundance. Most taxa were projected to decrease in abundance by the end of the century under drier and warmer conditions. Where an increase in abundance was projected under a low emissions scenario, this change was reduced or reversed under a high emissions climate change scenario. The validation process showed that, even for a small population, there was reasonable skill in predicting its annual variability. Results of this study show that this simple model can be used to identify the vulnerability of similar sites to the effects of shifting climate and, by extension, their conservation needs.

Climate change models project that, within the Caribbean basin, rainfall intensity is likely to increase toward the end of this century, although the region is projected to be drier overall. This may affect the frequency and severity of floods in Jamaica and the Caribbean Small Island Developing States. We investigate how flood hazards may be affected by increases in global mean surface temperature of 1.5, 2.0 and 2.5°C above pre-industrial levels using a case study of a Jamaican watershed. Rainfall projections from the PRECIS regional climate model for the Caribbean are analysed. Six members from the Quantifying Uncertainty in Model Predictions (AENWH, AEXSA, AEXSC, AEXSK, AEXSL and AEXSM) were used to create 100-year flood inundation maps for the Hope river for different global warming levels using hydrological and hydraulic models. Model runs projected peak discharges at 2.0, 2.5 and 1.5°C warming that were higher than discharges in the historical record of events that damaged sections of the watershed. Projections from the hydraulic model show increased flow area, depth and extent for 1.5 followed by 2.0 and 2.5°C rises in temperature. These results imply continued flood risk for the vulnerable areas of the watershed. This article is part of the theme issue 'Developing resilient energy systems'.

Cassava (Manihot esculenta Crantz) is an important food crop, especially in developing countries, because of its resilience and ability to grow in conditions generally inhospitable for other crops. However, tropical crops like cassava are not as frequently modeled compared with crops from temperate locations. The objective of this research was to calibrate the CSM-MANIHOT-Cassava model of the Decision Support System for Agrotechnology Transfer, DSSAT beta v4.8 and use the model to evaluate the potential benefits of irrigation on yield. We established two field trials with two water treatments (rainfed and irrigated) and four cultivars that had not been studied previously. We simulated in-season biomass and end-of-season yield, evaluating the model performance with different statistical measures. There was good agreement between simulated and measured values; the best results showed a deviation of 9.7%, normalized RMSE of 18%, and d-index of 0.98 for biomass, with corresponding values of 11, 24, and 0.98, respectively, for yield. Good simulations of yield correlated with accurate simulations for leaf area index and harvest index. The varieties showed differential responses to irrigation, suggesting that there are diverse levels of drought tolerance even within the same environmental conditions. The model was able to simulate total crop failure in harsh drought conditions, suggesting it can be used as a key decision-making tool in unfavorable conditions that will be occasioned by climate change.

There is an increasing need to develop bushfire monitoring and early warning systems for Jamaica and the Caribbean. However, there are few studies that examine fire variability for the region. In this study the MODIS C6 Fire Archive for 2001–2019 is used to characterize bushfire frequencies across Jamaica and to relate the variability to large-scale climate. Using additive mixed model and backward linear regression, the MODIS represents 80% and 73% of the local Jamaica Fire Brigade (JFB) data variability for 2010–2015, respectively. However, the MODIS values are smaller by a factor of approximately 30. The MODIS climatology over Jamaica reveals a primary peak in March and a secondary maximum in July, coinciding with months of minimum rainfall. A significant positive linear trend is observed for July-August bushfire events over 2001–2019 and represents 29% of the season’s variability. Trends in all-island totals in other seasons or annually were not statistically significant. However, positive annual trends in Zone 2 (eastern Jamaica) are statistically significant and may support an indication that a drying trend is evolving over the east. Significant 5-year and 3.5-year periodicities are also evident for April–June and September–November variability, respectively. Southern Jamaica and particularly the parish of Clarendon, known for its climatological dryness, show the greatest fire frequencies. The study provides evidence of linkages between fire occurrences over Jamaica and oceanic and atmospheric variability over the Atlantic and Pacific. For example, all-island totals show relatively strong association with the Atlantic Multidecadal Oscillation. The study suggests that development of an early warning system for bushfire frequency that includes climate indices is possible and shows strong potential for fire predictions.

Six members of the Hadley Centre’s Perturbed Physics Ensemble for the Quantifying Uncertainty in Model Predictions (QUMP) project are downscaled using the PRECIS (Providing Regional Climates for Impact Studies) RCM (Regional Climate Model). Climate scenarios at long-term temperature goals (LTTGs) of 1.5, 2.0, and 2.5 °C above pre-industrial warming levels are generated for the Caribbean and six sub-regions for annual and seasonal timescales. Under a high emissions scenario, the LTTGs are attained in the mid-2020s, end of the 2030s, and the early 2050s, respectively. At 1.5 °C, the region is slightly cooler than the globe, land areas warmer than ocean, and for the later months, the north is warmer than the south. The far western and southern Caribbean including the eastern Caribbean island chain dry at 1.5 °C (up to 50%). At 2.0 °C, the warming and drying intensify and there is a reversal of a wet tendency in parts of the north Caribbean. Drying in the rainfall season accounts for much of the annual change. There is limited further intensification of the region-wide drying at 2.5 °C. Changes in wind strength in the Caribbean low-level jet region may contribute to the patterns seen. There are implications for urgent and targeted adaptation planning in the Caribbean.

The Caribbean, along with other small island developing states (SIDS), have advocated for restricting global warming to 1.5 °C above pre-industrial levels by the end of the current century. Solar radiation management (SRM) may be one way to achieve this goal. This paper examines the mean Caribbean climate under various scenarios of an SRM-altered versus an SRM-unaltered world for three global warming targets, namely, 1.5, 2.0 and 2.5 °C above pre-industrial levels. Data from the Geoengineering Model Intercomparison Project Phase 1 (GeoMIP1) were examined for two SRM scenarios: the G3 experiment where there is a gradual injection of sulfur dioxide (SO2) into the tropical lower stratosphere starting in 2020 and terminating after 50 years, and the G4 experiment where a fixed 5 Teragram (Tg) of SO2 per year is injected into the atmosphere starting in 2020 and ending after 50 years. The results show that SRM has the potential to delay attainment of the 1.5, 2.0 and 2.5 °C global warming targets. The extent of the delay varies depending on the SRM methodology but may be beyond mid-century for the 1.5 °C goal. In comparison, however, the higher temperature thresholds are both still attained before the end of century once SRM is ceased, raising questions about the value of the initial delay. The application of SRM also significantly alters mean Caribbean climate during the global warming target years (determined for a representative concentration pathway 4.5 (RCP4.5) world without SRM). The Caribbean is generally cooler but drier during the 1.5 °C years and similarly cool but less dry for years corresponding to the higher temperature targets. Finally, the mean Caribbean climate at 1.5 °C differs if the global warming target is achieved under SRM versus RCP4.5. The same is true for the higher warming targets. The implications of all the results are discussed as a background for determining whether SRM represents a viable consideration for Caribbean SIDS to achieve their “1.5 to stay alive” goal.

The Coupled Model Intercomparison Project Phase 6 (CMIP6) dataset is used to examine projected changes in temperature and precipitation over the United States (U.S.), Central America and the Caribbean. The changes are computed using an ensemble of 31 models for three future time slices (2021–2040, 2041–2060, and 2080–2099) relative to the reference period (1995–2014) under three Shared Socioeconomic Pathways (SSPs; SSP1-2.6, SSP2-4.5, and SSP5-8.5). The CMIP6 ensemble reproduces the observed annual cycle and distribution of mean annual temperature and precipitation with biases between − 0.93 and 1.27 °C and − 37.90 to 58.45%, respectively, for most of the region. However, modeled precipitation is too large over the western and Midwestern U.S. during winter and spring and over the North American monsoon region in summer, while too small over southern Central America. Temperature is projected to increase over the entire domain under all three SSPs, by as much as 6 °C under SSP5-8.5, and with more pronounced increases in the northern latitudes over the regions that receive snow in the present climate. Annual precipitation projections for the end of the twenty-first century have more uncertainty, as expected, and exhibit a meridional dipole-like pattern, with precipitation increasing by 10–30% over much of the U.S. and decreasing by 10–40% over Central America and the Caribbean, especially over the monsoon region. Seasonally, precipitation over the eastern and central subregions is projected to increase during winter and spring and decrease during summer and autumn. Over the monsoon region and Central America, precipitation is projected to decrease in all seasons except autumn. The analysis was repeated on a subset of 9 models with the best performance in the reference period; however, no significant difference was found, suggesting that model bias is not strongly influencing the projections.

Climate change represents an unprecedented challenge to the world’s biosphere and to the global community. It also represents a unique challenge for plant health. Human activities and increased market globalization, coupled with rising temperatures, has led to a situation that is favourable to pest movement and establishment. This scientific review assesses the potential effects of climate change on plant pests and consequently on plant health. The evidence assessed strongly indicates that climate change has already expanded some pests’ host range and geographical distribution, and may further increase the risk of pest introduction to new areas. This calls for international cooperation and development of harmonized plant protection strategies to help countries successfully adapt their pest risk management measures to climate change.

The existence of several gridded precipitation products (GPP) has facilitated studies related to climate change, climate modeling, as well as a better understanding of the physical processes underpinning this key variable. Due to complexities in estimating rainfall, gridded datasets exhibit different levels of accuracy across regions, even when they are developed at relatively high resolution or using sophisticated procedures. The performance of 16 GPP are evaluated over the Caribbean region, which includes the Caribbean Islands, and portions of Central South America. Monthly data for sixty weather stations are used as a reference for the period 1983–2010. The 16 GPP include six products based on station data only, two that combine ground station and satellite information, two merging station and reanalysis information, four based on reanalysis, and two using multisource information. The temporal resolution of the GPP ranged between daily and monthly and spatial resolution from 0.033° to 0.5°. The methodological approach employed combined a comparison of regional and sub-regional precipitation annual cycles, the Kling–Gupta efficiency (KGE) index, as well as several metrics derived from the standardized precipitation index (SPI). Overall, the best performances were obtained from GPCC025 and MSWEP2, likely reflecting the positive impact of the large number of station data utilized in their development. It is also demonstrated that a higher spatial resolution does not always mean better accuracy. There is a need for this kind of assessment when undertaking climate studies in regions like the Caribbean where resolution is a significant consideration. ERA5 performed best among the reanalyses analyzed and has the potential to be used to develop regionally based GPP by applying bias correction or downscaling techniques. The methodological approach employed provides a comprehensive and robust evaluation of the relative strengths and weaknesses of GPP in the Caribbean region.

The existence of several gridded precipitation products (GPP) has facilitated studies related to climate change, climate modeling, as well as a better understanding of the physical processes underpinning this key variable. Due to complexities in estimating rainfall, gridded datasets exhibit different levels of accuracy across regions, even when they are developed at relatively high resolution or using sophisticated procedures. The performance of 16 GPP are evaluated over the Caribbean region, which includes the Caribbean Islands, and portions of Central South America. Monthly data for sixty weather stations are used as a reference for the period 1983–2010. The 16 GPP include six products based on station data only, two that combine ground station and satellite information, two merging station and reanalysis information, four based on reanalysis, and two using multisource information. The temporal resolution of the GPP ranged between daily and monthly and spatial resolution from 0.033° to 0.5°. The methodological approach employed combined a comparison of regional and sub-regional precipitation annual cycles, the Kling–Gupta efficiency (KGE) index, as well as several metrics derived from the standardized precipitation index (SPI). Overall, the best performances were obtained from GPCC025 and MSWEP2, likely reflecting the positive impact of the large number of station data utilized in their development. It is also demonstrated that a higher spatial resolution does not always mean better accuracy. There is a need for this kind of assessment when undertaking climate studies in regions like the Caribbean where resolution is a significant consideration. ERA5 performed best among the reanalyses analyzed and has the potential to be used to develop regionally based GPP by applying bias correction or downscaling techniques. The methodological approach employed provides a comprehensive and robust evaluation of the relative strengths and weaknesses of GPP in the Caribbean region.

The Wider Caribbean continues to experience increases in storm intensity, drought risk, ocean temperatures, ocean acidity, sea levels and wave heights in relation to global warming. Projections of future climate changes are such that there are likely to be significant negative impacts on marine resources and key sectors of the ocean economy such as tourism, fisheries, and shipping and trade. The chapter explores the implications of past and future Caribbean climate change on living and non-living marine resources within the Wider Caribbean, the urgency of responding to the associated challenges which emerge and some of the responses that could be considered to enable sustainability and viability of the Blue Economy.

This paper examines a pathway for small islands to replace fossil fuels by renewable sources, such as wind and solar, up to 100% to economically achieve energy security and satisfy The Paris Agreement to limit temperature rise as close as possible to 1.5 °C, in an economically beneficial manner. Using Jamaica, as an example, it is shown that the introduction of intermittent renewable energy to an island grid, which is electrically isolated, relying totally on itself for backup, causes serious frequency fluctuations and load shedding. Simulations show that a Battery Energy Storage System (BESS) using Li-ion batteries can be employed to economically overcome these problems. It is also noted that the cost of batteries with longer discharge capacity is on the decline and their use is expected to be become economical in about 10 years. Looking at the reported pathway to satisfy The Paris Agreement, a 2-phase pathway is suggested. In the Phase 1 (2020–2030) 30% integration of intermittent renewables with BESS backup can be implemented in a manner that is not economically burdensome whilst the remaining fossil fuel system can provide the firm energy needed. In Phase 2 (2030–2055), more renewables can be implemented, provided sufficient long term storage, including batteries, can be added to provide firm energy. By 2030 the cost of such storage is expected to fall resulting in increased deployment without a financial burden to the islands. Ideally, during the period 2020 to 2055, there should be no new additions of fossil fuel plants and retiring plants should be replaced by renewable energy plants; although an account is necessary for plants already in the planning and development stages. The leeway period of 2020–2030 should be used for the preparation and planning of adding up to 100% renewables in all sectors.

This study assesses the skill of four statistical models in hindcasting North Atlantic annual tropical cyclone (TC) frequency over 1950–2008 with the aim of projecting future activity. Three of the models are motivated by operational statistical forecast schemes and are premised on standard hurricane predictors including sea surface temperatures (SSTs) and near-surface zonal winds. The fourth model uses an SST gradient index previously proposed for Caribbean seasonal rainfall prediction. The statistical models, created from backward regression, explain 24–48% of the observed variability in 1950–2008 annual TC frequency. The future state of the predictors is extracted from the ECHAM5, HadCM3, MRI CGCM2.3.2a, and MIROC3.2 global climate model (GCM) simulations under the Coupled Model Intercomparison Project Phase 3. Models utilizing SST and near-surface wind predictors suggest significant increases in mean annual frequency by 2–8 TCs by 2070–2090, compared to a single surface wind predictor model, indicating that positive trends in SSTs under global warming have a larger relative influence on projections than changes in the variability of the surface winds. Wind-only models exhibit declines in TC frequency, while the SST gradient model yields little change relative to the present-day mean. Backward regression reapplied against the 1990–2008 period, analogous to future warmer oceanic and atmospheric state relative to the earlier years in the record, retains only the Caribbean low-level jet (CLLJ)-type predictors, explaining up to 82% of TC frequency variability and suggesting a more dominant role for the CLLJ in a warmer climate. Projections using the new models show either a more conservative increase or a stronger decrease in frequency, consistent with a stronger CLLJ.