Sea surface temperatures (SSTs) in the tropical North Atlantic have historically served as reliable predictors of early-season rainfall across the Caribbean. In particular, rainfall onset has been linked to SSTs exceeding the convective threshold necessary to support deep convection. However, recent warming trends appear to have altered this relationship. Here, we show that although SSTs routinely exceed the convective threshold earlier in the season, early rainfall has not increased. This decoupling reflects a shift in the atmospheric state, with enhanced stability, evidenced by reduced convective available potential energy and increased convective inhibition, increasingly suppressing convection. Reduced rainfall results in a more persistent Caribbean Low-Level Jet (CLLJ), further inhibiting rainfall by promoting subsidence and dry air advection. Correlations indicate that dynamic atmospheric variables now explain a larger share of rainfall variability than absolute SSTs. These findings signal a regime shift in Caribbean rainfall dynamics and raise concerns about the declining utility of SST-based predictors under continued climate warming. These results have significant implications for seasonal forecasting and adaptation planning across Caribbean Small Island Developing States.

It is well-established that explosive volcanic eruptions typically lead to cooler surface temperatures in summer, but the picture in Northern Hemisphere winter is much more uncertain. Recent large, low-latitude eruptions have been followed by warm anomalies across Eurasia in winter and cold anomalies near Greenland, hypothesized to be part of a dynamical response to the volcanic forcing that drives a positive North Atlantic Oscillation (NAO). But the evidence for a dynamical, winter warming response is inconclusive because internal variability is large, many climate models do not simulate a dynamical response like this, and there are few such eruptions to study.New datasets that allow additional eruptions from the early 19th century to be studied are therefore particularly valuable and we will present new analyses of the winters following four large eruptions in 1809, 1815, 1831 and 1835 (alongside four later eruptions in 1883, 1902, 1982 and 1991). This analysis is made possible by a new gridded instrumental dataset combining marine and land air temperatures from the 1780s onwards developed in the ongoing GloSAT project. It is supplemented by analysis of an ensemble of historically-forced simulations with UKESM1.1 initialised in 1750, also from the GloSAT project, and by two reanalyses (20CRv3 from 1806 and ModE-RA from 1421).For the instrumental and reanalysis datasets, warming in Europe was found in the first post-eruption winter following six out of the eight cases studied, and in the second post-eruption winter in five. Similar results were found for cold anomalies near Greenland and for a positive winter NAO index. The anomaly magnitudes for individual cases were mostly within the range of internal variability but the consistency of the response across eruptions and datasets was significant in comparison with non-volcanic winters. The UKESM1.1 simulations showed a significant response (with Eurasian winter warming, Greenland cooling and positive NAO) for only the largest eruption (Tambora), suggesting a response may require a minimum forcing strength to occur.

The GloSAT project is developing a new observational analysis of global air temperature change over land and ocean since the late 18th century. A new global analysis processing system has been developed that uses a computationally efficient spatial statistical method to estimate air temperature anomaly fields from historical observations. This will be the first presentation of this analysis approach. This method, based on Gaussian Markov Random Fields, jointly estimates temperature anomaly fields over land and ocean based on weather station and ship-based air temperature observations. The increased computational efficiency of the approach compared to conventional kriging-based estimates allows for increased spatial resolution in the analysis. Observational uncertainties are represented within the analysis framework to propagate uncertainty into the output ensemble data set. This accounts for errors arising from uncorrelated effects and structured errors such as residual biases in observations from an individual weather station or ship after correction. Observational error models have been co-developed with project partners providing the input land and marine data products. Initial results from the application of the analysis system to GloSAT air temperature observation data will be demonstrated.

Exposure biases are a pervasive non-climatic change in land air temperature records which have been introduced as a result of changes in the way thermometers were sheltered from solar radiation and the elements over time. Exposure biases have not been widely accounted for in observational records, due to difficulties detecting/correcting the bias using traditional homogenisation techniques; therefore, exposure biases still contribute significant uncertainty to the early period in global temperature compilations. Here, an empirical approach to address the bias arising from the introduction of Stevenson-type screens from the late-19th century is presented. The approach consists of: (1) an empirical analysis of 54 parallel measurement series to identify the characteristics of the exposure bias in four exposure classes; (2) the development of bias-estimation models based on an analysis of which variables influence the bias; and (3) the application of the models to an extended version of CRUTEM5 (CRUTEM5_ext), based on exposure metadata, to quantify and reduce the bias. Step one identified differences between the temperatures recorded in Stevenson screens and early exposures, which vary seasonally, diurnally, and with location and exposure class. The largest biases (in mean temperatures) were found in freestanding exposures (up to -0.78 degrees C annually) and in summer, while the smallest biases were generally found in wall-mounted exposures (near-0 degrees C annually) and in winter. Significant relationships between the bias and temperature, downward top of atmosphere and/or received shortwave downward solar radiation were found in each exposure class and led to the development of three regression-based bias-estimation models. Application of these models to 1,960 mid-latitude stations in CRUTEM5_ext, resulted in small (<= 0.016 degrees C) positive adjustments to the Northern Hemisphere mid-latitude mean before 1880, and larger (<=-0.1 degrees C) negative adjustments to the Northern and Southern Hemisphere mid-latitude means between 1882-1934 and 1856-1900, respectively. Larger adjustments were estimated regionally: up to -0.57 degrees C annually and -0.79 degrees C seasonally in individual grid cells. The transition from non-standard thermometer exposures to Stevenson-type screens introduced exposure biases into land air temperature records. This study uses parallel measurements to (a) characterize the exposure bias in four main classes of exposure and (b) develop exposure-specific models to estimate the bias at individual weather stations. Application of the models to mid-latitude stations in CRUTEM5 suggests the biases present in the mid-latitude annual means are relatively small (<=+/- 0.1 degrees C) but can be larger in individual grid cells (up to -0.57 degrees C). image

NASA's Atmospheric Waves Experiment (AWE) mission is a Heliophysics Small Explorers Mission of Opportunity designed to investigate how terrestrial weather affects space weather, via small-scale atmospheric gravity waves (GWs) produced in Earth's atmosphere. Following its launch to the International Space Station (ISS) in November 2023, AWE began a 2-year mission to explore the global distribution of AGWs, study the processes controlling their propagation throughout the upper atmosphere, and quantify their impacts on the ionosphere-thermosphere-mesosphere (ITM) system. The AWE science instrument is an ISS-compatible version of the Advanced Mesospheric Temperature Mapper (AMTM)-a wide field-of-view Shortwave Infrared (SWIR) imager that quantifies gravity wave-induced temperature disturbances in the hydroxyl (OH) airglow layer, which lies near the mesopause at similar to 87 km altitude. The AMTM's four identical telescopes make continuous nighttime observations of the P-1(2) and P-1(4) emission lines of the OH (3,1) band, as well as the atmospheric background simultaneously, from which the OH layer temperature is derived. AWE images are collected once per second, co-added, and processed into temperature swaths using correction algorithms derived from ground calibration test results. Global coverage of the GWs in the OH layer is achieved about every four days, which will enable regional and seasonal studies, as well as characterization of AGW 'hot spots.' This paper will present an overview of the AWE mission, including science objectives, measurement technique, instrument design and development, prelaunch performance and environmental testing, data processing, and a brief look at on-orbit science results.

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.

Long observational records of land surface air temperature are vital to our understanding of climate variability and change, as well as for testing predictions of climatic trends. However, of the relatively few long observational records which exist, many contain inhomogeneities or biases resulting from changing instrumentation, station location/surroundings and/or observing practises. One of the most significant issues is the exposure bias. Prior to the widespread adoption of louvered Stevenson-type screens in the late-19th century, various (often insufficient) approaches were used to shield thermometers. Each approach exposed the thermometer to differing levels of solar radiation, thus introducing inhomogeneities into individual station records and biases across regions, if similar approaches were used. Poorly shielded thermometers, for example, tended to read higher during the summer half year than those in Stevenson-type screens. Despite a number of studies documenting the presence of the exposure bias in early instrumental data, relatively few corrections have been applied or incorporated into global temperature datasets. This is largely due to the pervasive nature of the bias and a lack of observational metadata impeding bias identification or estimation of the appropriate correction. In this work we explore a range of datasets to identify the potential for exposure bias in early instrumental data. We analyse historical data, corrections applied to homogenized datasets, as well as the small number of parallel measurements from differentially-shielded thermometers, in order to better define the characteristics of the exposure bias. These characteristics are then used to identify potential instances of exposure bias in early instrumental temperature records. We consider differences in seasonal anomalies, which is a key feature of many exposure biases, as well as their geographical variation (focussing mostly, but not solely, on Europe). We analyse how these behave at stations where it is known that exposure bias has already been adjusted for (though perhaps not completely) versus those that have not been. We also make comparisons with proxy reconstructions of temperature as an independent reference that is not susceptible to the same biases as the early instrumental data. This work forms part of the NERC-funded GloSAT project which is developing a global surface air temperature dataset starting in 1781. The ultimate aim of the work reported here is to refine the error associated with these biases, in order to improve the representation of the exposure bias in error models used for gridded instrumental temperature datasets.

Lead Authors: Marco Bindi (Italy), Sally Brown (UK), Ines Camilloni (Argentina), Arona Diedhiou (Ivory Coast/Senegal), Riyanti Djalante (Japan/Indonesia), Kristie L. Ebi (USA), Francois Engelbrecht (South Africa), Joel Guiot (France), Yasuaki Hijioka (Japan), Shagun Mehrotra (USA/India), Antony Payne (UK), Sonia I. Seneviratne (Switzerland), Adelle Thomas (Bahamas), Rachel Warren (UK), Guangsheng Zhou (China)

In this document we present historical and future climate profiles for Haiti both from available literature and from available station, gridded and modelled data. The document is sequenced according to climate variable with temperature considered first and then rainfall. Sea level rise and hurricanes are also considered, though more in a regional context than specific to Haiti. For each considered variable, the historical picture is presented first followed by future projections.

Los cambios climáticos observados y proyectados tienen graves implicaciones socioeconómicas para las islas del Caribe. Este artículo presenta información básica sobre el cambio climático, basada en estudios previos, observaciones disponibles y simulaciones de modelos climáticos, a escalas espaciales relevantes para las islas del Caribe. Utilizamos los datos del Modelo de Circulación General (GCM), incluidos en la fase 3 del Proyecto de Intercomparación de Modelos Acoplados (CMIP3), y los datos del modelo climático regional (RCM) del Centro Hadley del Reino Unido para proporcionar información actual y futura basada en escenarios sobre la precipitación y la temperatura en cada uno de los estados insulares. Las observaciones de estaciones en cuadrícula y los datos satelitales se utilizan para estudiar el clima del siglo XX y evaluar el rendimiento de los modelos climáticos. Centrándonos principalmente en la precipitación, también analizamos factores como la temperatura superficial del mar, la presión a nivel del mar y los vientos que afectan las variaciones estacionales de la precipitación. La media del conjunto del CMIP3 y el RCM captan con éxito las características de la circulación atmosférica a gran escala en la región, pero presentan dificultades para captar el ciclo estacional bimodal característico de la precipitación. Estudios previos han observado una futura sequía durante la estación húmeda en esta región bajo escenarios de cambio climático, pero la magnitud del cambio es altamente incierta tanto en las simulaciones GCM como RCM. La disminución proyectada es más pronunciada al inicio de la estación húmeda, eliminando la característica de sequía de mediados de verano en el Caribe occidental. Las simulaciones RCM muestran mejoras con respecto al GCM, principalmente debido a una mejor representación de la masa continental, pero su rendimiento depende críticamente del GCM impulsor. Este estudio destaca la necesidad de observaciones de alta resolución y simulaciones de conjuntos de modelos climáticos para comprender plenamente el cambio climático y sus impactos en las pequeñas islas del Caribe.

Several large-scale climate patterns influenced climate conditions and weather patterns across the globe during 2010. The transition from a warm El Niño phase at the beginning of the year to a cool La Niña phase by July contributed to many notable events, ranging from record wetness across much of Australia to historically low Eastern Pacific basin and near-record high North Atlantic basin hurricane activity. The remaining five main hurricane basins experienced below- to well-below-normal tropical cyclone activity. The negative phase of the Arctic Oscillation was a major driver of Northern Hemisphere temperature patterns during 2009/10 winter and again in late 2010. It contributed to record snowfall and unusually low temperatures over much of northern Eurasia and parts of the United States, while bringing above-normal temperatures to the high northern latitudes. The February Arctic Oscillation Index value was the most negative since records began in 1950. The 2010 average global land and ocean surface temperature was among the two warmest years on record. The Arctic continued to warm at about twice the rate of lower latitudes. The eastern and tropical Pacific Ocean cooled about 1°C from 2009 to 2010, reflecting the transition from the 2009/10 El Niño to the 2010/11 La Niña. Ocean heat fluxes contributed to warm sea surface temperature anomalies in the North Atlantic and the tropical Indian and western Pacific Oceans. Global integrals of upper ocean heat content for the past several years have reached values consistently higher than for all prior times in the record, demonstrating the dominant role of the ocean in the Earth's energy budget. Deep and abyssal waters of Antarctic origin have also trended warmer on average since the early 1990s. Lower tropospheric temperatures typically lag ENSO surface fluctuations by two to four months, thus the 2010 temperature was dominated by the warm phase El Niño conditions that occurred during the latter half of 2009 and early 2010 and was second warmest on record. The stratosphere continued to be anomalously cool. Annual global precipitation over land areas was about five percent above normal. Precipitation over the ocean was drier than normal after a wet year in 2009. Overall, saltier (higher evaporation) regions of the ocean surface continue to be anomalously salty, and fresher (higher precipitation) regions continue to be anomalously fresh. This salinity pattern, which has held since at least 2004, suggests an increase in the hydrological cycle. Sea ice conditions in the Arctic were significantly different than those in the Antarctic during the year. The annual minimum ice extent in the Arctic—reached in September—was the third lowest on record since 1979. In the Antarctic, zonally averaged sea ice extent reached an all-time record maximum from mid-June through late August and again from mid-November through early December. Corresponding record positive Southern Hemisphere Annular Mode Indices influenced the Antarctic sea ice extents. Greenland glaciers lost more mass than any other year in the decade-long record. The Greenland Ice Sheet lost a record amount of mass, as the melt rate was the highest since at least 1958, and the area and duration of the melting was greater than any year since at least 1978. High summer air temperatures and a longer melt season also caused a continued increase in the rate of ice mass loss from small glaciers and ice caps in the Canadian Arctic. Coastal sites in Alaska show continuous permafrost warming and sites in Alaska, Canada, and Russia indicate more significant warming in relatively cold permafrost than in warm permafrost in the same geographical area. With regional differences, permafrost temperatures are now up to 2°C warmer than they were 20 to 30 years ago. Preliminary data indicate there is a high probability that 2010 will be the 20th consecutive year that alpine glaciers have lost mass. Atmospheric greenhouse gas concentrations continued to rise and ozone depleting substances continued to decrease. Carbon dioxide increased by 2.60 ppm in 2010, a rate above both the 2009 and the 1980–2010 average rates. The global ocean carbon dioxide uptake for the 2009 transition period from La Niña to El Niño conditions, the most recent period for which analyzed data are available, is estimated to be similar to the long-term average. The 2010 Antarctic ozone hole was among the lowest 20% compared with other years since 1990, a result of warmer-than-average temperatures in the Antarctic stratosphere during austral winter between mid-July and early September.

The seasonality, patterns and the climate associations of the reported cases of dengue in the Caribbean were studied by analyzing the annual and monthly variability of reported cases as well as those of climate parameters (temperature and precipitation). More attention was given to Trinidad and Tobago, Barbados, and Jamaica, as those countries contributed mostly to the reported cases. The data were for the period 1980–2003. Results showed that the incidence of dengue in the Caribbean were higher in the last decade (1990s) compared to that in the previous decade (1980s). The yearly patterns of dengue exhibited a well-defined seasonality. The epidemics appeared to occur in the later half of the year following onset of rainfall and increasing temperature. Analysis revealed that the association of the epidemics with temperature was stronger, especially in relation to the onset of dengue, and the probability of epidemics was high during El Niño periods. In years with early warmer periods epidemics appeared to occur early, which was a scenario more probable in the year after an El Niño (an El Niño + 1 year). Indices linked to temperatures that are useful for gauging the potential for onset of dengue were examined. An index based on a moving average temperature (MAT) appeared to be effective in gauging such potential and its average (AMAT) signals a threshold effect. MAT index has potential use in adaptation and mitigation strategies.