This dataset shows the locations of Cool Spaces and free drinking water fountains in Camden. Cool Spaces are free places where you can stay cool and take a break from the heat. They are open to everyone from June 1 to September 30, 2025. Each Cool Space has its own opening hours and facilities, just hover over the icons to see the details! Please note that Cool Spaces are not for emergencies. If you think you might have heatstroke or are unsure, please visit https://www.nhs.uk/conditions/heat-exhaustion-heatstroke for information on how to recognise the symptoms of heat exhaustion and heatstroke. If you would like to join and become a Cool Space or support in any way (spread the news on tips to beat the heat, contributing to drinking water machines, donation for water or spray bottles / hats/ sunscreen), please find the expression of interest form on https://www.camden.gov.uk/preparing-for-heatwaves.

[Updated 28/01/25 to fix an issue in the ‘Lower’ values, which were not fully representing the range of uncertainty. ‘Median’ and ‘Higher’ values remain unchanged. The size of the change varies by grid cell and fixed period/global warming levels but the average difference between the 'lower' values before and after this update is 0.0.]What does the data show? The Annual Count of Tropical Nights is the number of days per year where the minimum daily temperature is above 20°C. It measures how many times the threshold is exceeded (not by how much). It measures how many times the threshold is exceeded (not by how much) in a year. The results should be interpreted as an approximation of the projected number of days when the threshold is exceeded as there will be many factors such as natural variability and local scale processes that the climate model is unable to represent.The Annual Count of Tropical Nights is calculated for two baseline (historical) periods 1981-2000 (corresponding to 0.51°C warming) and 2001-2020 (corresponding to 0.87°C warming) and for global warming levels of 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C above the pre-industrial (1850-1900) period. This enables users to compare the future number of tropical nights to previous values. What are the possible societal impacts?The Annual Count of Tropical Nights indicates increased health risks and heat stress due to high night-time temperatures. It is based on exceeding a minimum daily temperature of 20°C, i.e. the temperature does not fall below 20°C for the entire day. Impacts include:Increased heat related illnesses, hospital admissions or death for vulnerable people.Increased heat stress, it is important the body has time to recover from high daytime temperatures during the lower temperatures at night.Other metrics such as the Annual Count of Summer Days (days above 25°C), Annual Count of Hot Summer Days (days above 30°C) and the Annual Count of Extreme Summer Days (days above 35°C) also indicate impacts from high temperatures, however they use different temperature thresholds.What is a global warming level?The Annual Count of Tropical Nights is calculated from the UKCP18 regional climate projections using the high emissions scenario (RCP 8.5) where greenhouse gas emissions continue to grow. Instead of considering future climate change during specific time periods (e.g. decades) for this scenario, the dataset is calculated at various levels of global warming relative to the pre-industrial (1850-1900) period. The world has already warmed by around 1.1°C (between 1850–1900 and 2011–2020), whilst this dataset allows for the exploration of greater levels of warming.The global warming levels available in this dataset are 1.5°C, 2°C, 2.5°C, 3°C and 4°C. The data at each warming level was calculated using a 21 year period. These 21 year periods are calculated by taking 10 years either side of the first year at which the global warming level is reached. This time will be different for different model ensemble members. To calculate the value for the Annual Count of Tropical Nights, an average is taken across the 21 year period. Therefore, the Annual Count of Tropical Nights show the number of tropical nights that could occur each year, for each given level of warming. We cannot provide a precise likelihood for particular emission scenarios being followed in the real world future. However, we do note that RCP8.5 corresponds to emissions considerably above those expected with current international policy agreements. The results are also expressed for several global warming levels because we do not yet know which level will be reached in the real climate as it will depend on future greenhouse emission choices and the sensitivity of the climate system, which is uncertain. Estimates based on the assumption of current international agreements on greenhouse gas emissions suggest a median warming level in the region of 2.4-2.8°C, but it could either be higher or lower than this level.What are the naming conventions and how do I explore the data?This data contains a field for each global warming level and two baselines. They are named ‘Tropical Nights’, the warming level or baseline, and ‘upper’ ‘median’ or ‘lower’ as per the description below. E.g. ‘Tropical Nights 2.5 median’ is the median value for the 2.5°C warming level. Decimal points are included in field aliases but not field names e.g. ‘Tropical Nights 2.5 median’ is ‘TropicalNights_25_median’. To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘Tropical Nights 2.0°C median’ values.What do the ‘median’, ‘upper’, and ‘lower’ values mean?Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future. For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, the Annual Count of Tropical Nights was calculated for each ensemble member and they were then ranked in order from lowest to highest for each location. The ‘lower’ fields are the second lowest ranked ensemble member. The ‘upper’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty.‘Lower’, ‘median’ and ‘upper’ are also given for the baseline periods as these values also come from the model that was used to produce the projections. This allows a fair comparison between the model projections and recent past. Useful linksThis dataset was calculated following the methodology in the ‘Future Changes to high impact weather in the UK’ report and uses the same temperature thresholds as the 'State of the UK Climate' report.Further information on the UK Climate Projections (UKCP).Further information on understanding climate data within the Met Office Climate Data Portal.

The purpose of this study was to investigate which climate/heat indices perform best in predicting heat-induced loss of physical work capacity (PWC-loss). Integrating data from earlier studies, data from 982 exposures (75 conditions) exercising at a fixed cardiovascular load of 130b.min-1, in varying temperatures (15-50°C), humidities (20-80%), solar radiation (0-800W.m-2), wind (0.2-3.5m.s-1) and two clothing levels, were used to model the predictive power of ambient temperature, Universal Thermal Climate Index (UTCI), Wet Bulb Globe Temperature (WBGT), Modified Equivalent Temperature (mPET), Heat Index, Apparent Temperature (AT), and Wet Bulb Temperature (Twb) for the calculation of PWC-loss, skin temperature (Tskin) and core-to-skin temperature gradient, and Thermal perception( TSV) in the heat. R2, RMSD and Akaike stats were used indicating model performance.Indices not including wind/radiation in their calculation (Ta, Heat Index, AT, Twb) struggled to provide consistent predictions across variables. For PWC-loss and TSV, UTCI and WBGT had the highest predictive power. For Tskin, and core-to-skin temperature gradient, the physiological models UTCI and mPET worked best in semi-nude conditions, but clothed, AT, WBGT and UTCI worked best. For all index predictions, Ta, vapor pressure and Twb were shown to be the worst heat strain predictors. While UTCI and WBGT had similar model performance using the full dataset, WBGT did not work appropriately in windy, hot-dry, conditions where WBGT predicted lower strain due to wind, whereas the empirical data, UTCI and mPET indicated that wind in fact increased the overall level of thermal strain. The findings of the current study highlight the advantages of using a physiological model-based index like UTCI when evaluating heat stress in dynamic thermal environments.

Supplementary files for article Quantifying the impact of heat on human physical work capacity; part II: the observed interaction of air velocity with temperature, humidity, sweat rate, and clothing is not captured by most heat stress indices.Increasing air movement can alleviate or exacerbate occupational heat strain, but the impact is not well defined across a wide range of hot environments, with different clothing levels. Therefore, we combined a large empirical study with a physical model of human heat transfer to determine the climates where increased air movement (with electric fans) provides effective body cooling. The model allowed us to generate practical advice using a high-resolution matrix of temperature and humidity. The empirical study involved a total of 300 1-h work trials in a variety of environments (35, 40, 45, and 50 °C, with 20 up to 80% relative humidity) with and without simulated wind (3.5 vs 0.2 m∙s−1), and wearing either minimal clothing or a full body work coverall. Our data provides compelling evidence that the impact of fans is strongly determined by air temperature and humidity. When air temperature is ≥ 35 °C, fans are ineffective and potentially harmful when relative humidity is below 50%. Our simulated data also show the climates where high wind/fans are beneficial or harmful, considering heat acclimation, age, and wind speed. Using unified weather indices, the impact of air movement is well captured by the universal thermal climate index, but not by wet-bulb globe temperature and aspirated wet-bulb temperature. Overall, the data from this study can inform new guidance for major public and occupational health agencies, potentially maintaining health and productivity in a warming climate.

The Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports (ORCHESTRA) model dataset comprises of control and additional forcing model runs using a Nucleus for European Modelling of the Ocean (NEMO)-based 1/12 degree grid spacing model of the Southern Ocean. The model runs use the NEMO "extended" grid, although ice cavities are closed and cover 1951 - 2017. The dataset covers the full length of model runs and includes regular (5 day mean) output of the model state, as well as more frequent (1 day mean) output of surface variables and fluxes and 1 month mean of more extensive transport diagnostics. A range of forcing is provided by JRA55-do, an interannually-varying forcing set (Tsujino et al., 2018); forcing supplied by the UK Met Office (freshwater runoff, tidal friction, geothermal heating); Geophysical Fluid Dynamics Laboratory corrected normal year forcing version 2.0 (CORE2) normal year forcing and additional freshwater runoff to suppress polynya formation. All model runs were completed on Archer, the national HPC platform, by scientists at the British Antarctic Survey (BAS).

Winter wheat is an important crop in the UK, suited to the typical weather conditions in the current climate. In a changing climate the increased frequency and severity of adverse weather events, which are often localised, are considered a major threat to wheat production. In the present study we assessed a range of adverse weather conditions, which can significantly affect yield, under current and future climates based on adverse weather indices. We analysed changes in the frequency, magnitude and spatial patterns of 10 adverse weather indices, at 25 sites across the UK, using climate scenarios from the CMIP5 ensemble of global climate models (GCMs) and two greenhouse gas emissions (RCP4.5 and RCP8.5). The future UK climate is expected to remain favourable for wheat production, with most adverse weather indicators reducing in magnitude by the mid-21st century. Hotter and drier summers would improve sowing and harvesting conditions and reduce the risk of lodging. The probability of late frosts and heat stress during reproductive and grain filling periods would likely remain small in 2050. Wetter winter and spring could cause issues with waterlogging. The severity of drought stress during reproduction would generally be lower in 2050, however localised differences suggest it is important to examine drought at a small spatial scale. Prolonged water stress does not increase considerably in the UK, as may be expected in other parts of Europe. Climate projections based on the CMIP5 ensemble reveal considerable uncertainty in the magnitude of adverse weather conditions including waterlogging, drought and water stress. The variation in adverse weather conditions due to GCMs was generally greater than between emissions scenarios. Accordingly, CMIP5 ensembles should be used in the assessment of adverse weather conditions for crop production to indicate the full range of possible impacts, which a limited number of GCMs may not provide.

Supplementary Information Files for An advanced empirical model for quantifying the impact of heat and climate change on human physical work capacityOccupational heat stress directly hampers physical work capacity (PWC), with large economic consequences for industries and regions vulnerable to global warming. Accurately quantifying PWC is essential for forecasting impacts of different climate change scenarios, but the current state of knowledge is limited, leading to potential underestimations in mild heat, and overestimations in extreme heat. We therefore developed advanced empirical equations for PWC based on 338 work sessions in climatic chambers (low air movement, no solar radiation) spanning mild to extreme heat stress. Equations for PWC are available based on air temperature and humidity, for a suite of heat stress assessment metrics, and mean skin temperature. Our models are highly sensitive to mild heat and to our knowledge are the first to include empirical data across the full range of warm and hot environments possible with future climate change across the world. Using wet bulb globe temperature (WBGT) as an example, we noted 10% reductions in PWC at mild heat stress (WBGT = 18°C) and reductions of 78% in the most extreme conditions (WBGT = 40°C). Of the different heat stress indices available, the heat index was the best predictor of group level PWC (R2 = 0.96) but can only be applied in shaded conditions. The skin temperature, but not internal/core temperature, was a strong predictor of PWC (R2 = 0.88), thermal sensation (R2 = 0.84), and thermal comfort (R2 = 0.73). The models presented apply to occupational workloads and can be used in climate projection models to predict economic and social consequences of climate change.

Supplementary Information Files for Quantifying the impact of heat on human physical work capacity; part III: the impact of solar radiation varies with air temperature, humidity, and clothing coverageHeat stress decreases human physical work capacity (PWC), but the extent to which solar radiation (SOLAR) compounds this response is not well understood. This study empirically quantifed how SOLAR impacts PWC in the heat, considering wide, but controlled, variations in air temperature, humidity, and clothing coverage. We also provide correction equations so PWC can be quantifed outdoors using heat stress indices that do not ordinarily account for SOLAR (including the Heat Stress Index, Humidex, and Wet-Bulb Temperature). Fourteen young adult males (7 donning a work coverall, 7 with shorts and trainers) walked for 1 h at a fxed heart rate of 130 beats∙min−1, in seven combinations of air temperature (25 to 45°C) and relative humidity (20 or 80%), with and without SOLAR (800 W/m2 from solar lamps). Cumulative energy expenditure in the heat, relative to the work achieved in a cool reference condition, was used to determine PWC%. Skin temperature was the primary determinant of PWC in the heat. In dry climates with exposed skin (0.3 Clo), SOLAR caused PWC to decrease exponentially with rising air temperature, whereas work coveralls (0.9 Clo) negated this efect. In humid conditions, the SOLAR-induced reduction in PWC was consistent and linear across all levels of air temperature and clothing conditions. Wet-Bulb Globe Temperature and the Universal Thermal Climate Index represented SOLAR correctly and did not require a correction factor. For the Heat Stress Index, Humidex, and Wet-Bulb Temperature, correction factors are provided enabling forecasting of heat efects on work productivity.

Data contains multiple life history parameters of a host the Indian meal moth Plodia interpunctella and its parasitoid Venturia canescens measured either at high (60.8% RH) or low (32.5%) humidity, with simulated heat stress exposure either at 4th or 5th instar larvae, at different length of 0, 6, 72 hours. Data were collected by a single-generation life history experiment in which we investigated how humidity modified the stage-specific responses of host and parasitoid to heat stress. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/f7bd976b-f903-4b65-91bc-06bfbfad5608

An estimated 32 million people live with HIV-1 globally. Combined antiretroviral therapy suppresses viral replication but therapy interruption results in viral rebound from a latent reservoir mainly found in memory CD4+ T cells. Treatment is therefore lifelong and not curative. Eradication of this viral reservoir requires hematopoietic stem cell transplantation from hemizygous or homozygous DCCR5 donors, which is not broadly applicable. Alternative cure strategies include the pharmacological reactivation of latently infected cells to promote their immune-mediated clearance, or the induction of deep latency. HIV-1 latency is multifactorial and linked to the activation status of the infected CD4+ T cell. Hence to perturb latency, multiple pathways need to be simultaneously targeted without affecting CD4+ T cell function. Hsp90 has been shown to regulate HIV-1 latency, although knowledge on the pathways is limited. Because Hsp90 promotes the proper folding of numerous cellular proteins required for HIV-1 gene expression, we hypothesized that Hsp90 might be a master regulator of latency. We tested this hypothesis using a polyclonal Jurkat cell model of latency and ex-vivo latently infected primary CD4+ T cells. We found that, in the Jurkat model, Hsp90 is required for HIV-1 reactivation mediated by the T-cell receptor, phorbol esters, TNF-a, inhibition of FOXO-1, and agonists of TLR-7 and TLR-8. In primary cells, Hsp90 regulated HIV-1 gene expression induced by stimulation the T-cell receptor or in the presence of IL-7/IL-15 or a FOXO-1 inhibitor. Chemical inhibition of Hsp90 abrogated activation of the NF-kB, NFAT and AP-1 signal transduction pathways. Within the CD4+ T cell population, CDRA45+ CCR7+ “naïve” and CD45RA- CCR7- “effector memory” cells were most sensitive to Hsp90 inhibition, which did not perturb their phenotype or activation state. Our results indicate that Hsp90 is a master regulator of HIV-1 latency that can potentially be targeted in cure strategies

(c) the authors, CC-BY 4.0Supplementary files for article Global reductions in manual agricultural work capacity due to climate changeManual outdoor work is essential in many agricultural systems. Climate change will make such work more stressful in many regions due to heat exposure. The physical work capacity metric (PWC) is a physiologically based approach that estimates an individual's work capacity relative to an environment without any heat stress. We computed PWC under recent past and potential future climate conditions. Daily values were computed from five earth system models for three emission scenarios (SSP1‐2.6, SSP3‐7.0, and SSP5‐8.5) and three time periods: 1991–2010 (recent past), 2041–2060 (mid‐century) and 2081–2100 (end‐century). Average daily PWC values were aggregated for the entire year, the growing season, and the warmest 90‐day period of the year. Under recent past climate conditions, the growing season PWC was below 0.86 (86% of full work capacity) on half the current global cropland. With end‐century/SSP5‐8.5 thermal conditions this value was reduced to 0.7, with most affected crop‐growing regions in Southeast and South Asia, West and Central Africa, and northern South America. Average growing season PWC could falls below 0.4 in some important food production regions such as the Indo‐Gangetic plains in Pakistan and India. End‐century PWC reductions were substantially greater than mid‐century reductions. This paper assesses two potential adaptions—reducing direct solar radiation impacts with shade or working at night and reducing the need for hard physical labor with increased mechanization. Removing the effect of direct solar radiation impacts improved PWC values by 0.05 to 0.10 in the hottest periods and regions. Adding mechanization to increase horsepower (HP) per hectare to levels similar to those in some higher income countries would require a 22% increase in global HP availability with Sub‐Saharan Africa needing the most. There may be scope for shifting to less labor‐intensive crops or those with labor peaks in cooler periods or shift work to early morning.

Income loss of average size dairy farms in different UK NUTS-1 regions due to heat stress (£/y) assuming no mitigation actions are taken.

Plants reprogram gene expression as an adaptive response to survive high temperatures. While the identity and functions of intracellular heat stress-responsive proteins have been extensively studied, the heat response of proteins secreted to the extracellular matrix is unknown. Here, we used Sorghum bicolor, a species adapted for growth in hot climates, to investigate the extracellular heat-induced responses. When exposed to 40 C for 72 h, heat-sensitive Arabidopsis cell suspension cultures died, while ICSB338 sorghum cell cultures survived by activation of a transcriptional response characterized by the induction of HSP70 and HSP90 genes. Quantitative proteomic analysis of proteins recovered from cell culture medium revealed specific heat stress-induced protein expression within the sorghum secretome. Of the 265 secreted proteins identified, 100 responded to heat, with the majority (85%) possessing a predicted signal peptide for targeting to the classical secretory pathway. The differentially expressed proteins have putative functions in detoxification (36%), metabolism (32%) and protein modifications (19%), while 13% are unclassified. Extracellular proteins play a vital role in cell-cell communications during stress adaptation. Our study reveals new insights into the adaptive response of sorghum to heat and provides a useful resource of extracellular proteins that could serve as targets for developing thermotolerant crops.

Gene expression was measured in control and heat resistance selected adult female flies before and at 8 time points after heat stress for 1h @ 36 degrees,Abstract The availability of full genome sequences has allowed the construction of microarrays, with which screening,of the full genome for changes in gene expression is possible. This method can provide a wealth of information about,biology at the level of gene expression and is a powerful method to identify genes and pathways involved in various,processes. In this study, we report a detailed analysis of the full heat stress response in Drosophila melanogaster,females, using whole genome gene expression arrays (Affymetrix Inc, Santa Clara, CA, USA). The study focuses on,up- as well as downregulation of genes from just before and at 8 time points after an application of short heat hardening,(368C for 1 hour). The expression changes were followed up to 64 hours after the heat stress, using 4 biological,replicates. This study describes in detail the dramatic change in gene expression over time induced by a short-term,heat treatment. We found both known stress responding genes and new candidate genes, and processes to be involved,in the stress response. We identified 3 main groups of stress responsive genes that were earlyâ??upregulated, earlyâ??,downregulated, and lateâ??upregulated, respectively, among 1222 differentially expressed genes in the data set. Comparisons,with stress sensitive genes identified by studies of responses to other types of stress allow the discussion of,heat-specific and general stress responses in Drosophila. Several unexpected features were revealed by this analysis,,which suggests that novel pathways and mechanisms are involved in the responses to heat stress and to stress in,general. The majority of stress responsive genes identified in this and other studies were downregulated, and the,degree of overlap among downregulated genes was relatively high, whereas genes responding by upregulation to heat,and other stress factors were more specific to the stress applied or to the conditions of the particular study. As an,expected exception, heat shock genes were generally found to be upregulated by stress in general.

Environmental conditions are quite effective during propagation and industrial application of Baker’s yeast (Saccharomyces cerevisiae). The change of temperature is one of the most important conditions which affects the dough-leaving capacity of yeast cells. Accordingly, heat changes play an essential role in the commercial and economic impact of the yeast. Recent technologies in genomics have been used for analysis of global gene expression profiles such as microarray and RNA sequencing to solve the problems related with industrial application of yeast. Hereby, the aim of this study is to explore the effects of heat stresses on global gene expression profiles and to identify the candidate genes for the heat stress response in commercial baker’s yeast by using microarray technology and comparative statistical data analyses. Data from all hybridizations and array normalization were analyzed using the GeneSpringGX 12.1 (Agilent) and the R 2.15.2 program language. In the analysis of this dataset, all required statistical methods are performed comparatively in each step and the best performed ones are used in further computations. Hence, as the first step of the analyses, different background normalization algorithms such as MAS5.0, RMA, MBEI and GC-RMA were applied and the algorithm which gives the most accurate findings was chosen for the normalization procedure. As a result, expression values, computed from CEL files, were processed by Robust Multiarray Analysis (RMA) which is the selected procedure for the normalization of the systematic differences between samples. In order to determine differentially expressed genes under heat stress treatments, two different methods, namely, the fold-change and the hypothesis testing approaches are executed. In the fold-change method, various cut-off values are implemented while different multiple testing procedures are performed for the hypothesis testing. Under the heat shock and temperature-shift stress conditions, up/down regulated differentially expressed probes were functionally categorized into the different groups via the cluster analyses. Transcriptome changes under the heat shock and temperature-shift stress treatments show that the number of differentially up-regulated genes among the heat shock proteins (HSPs) and transcription factors (TFs) changed significantly. Consequently, the identification of thousands of genes related with heat stress treatments via microarray technology and comparative statistical analysis resulted in the creation of big picture which provides the understanding of the importance for the baker’s yeast industrial applications.

Phoenix dactylifera seedlings were exposed to heat, drought and combined heat & drought conditions in growth chambers. Leaf samples were collected for total RNA isolation (RNAseq, Illumina HiSeq 1000), and water soluble metabolites. The RNAseq of four biological replicates (two individuals per replicate) were compared against the control condition. Transcriptomics data suggests the combine heat and drought resembled heat response, whereas drought resembled more to control. The hallmarks of heat stress were visible in the transcriptomics data, such as protein misfolding, response to hydrogen peroxide and cell wall modification, as well as ABA signaling in the case of drought. Since the plants were exposed to the stress for several days before harvesting, the early signs of heat stress such as calcium and NO signaling were not detected anymore. In addition, data suggest a significant enrichment of circadian rhythm motifs in the differentially expressed genes in heat and combined heat and drought stresses, suggesting new stress avoidance strategies.

Plants and animals share similar mechanisms in the heat-shock (HS) response, such as synthesis of the conserved HS proteins (Hsps). However, because plants are confined to a growing environment, in general they require unique features to cope with heat stress. We have analyzed the function of a novel Hsp, heat-stress-associated 32-kD protein (Hsa32), which is highly conserved in land plants but absent in most other organisms. The gene responds to HS at the transcriptional level in moss, Arabidopsis, and rice. Like other Hsps, Hsa32 protein accumulates greatly in Arabidopsis seedlings after HS treatment. Disruption of Hsa32 by T-DNA insertion does not affect growth and development under normal conditions. However, the acquired thermotolerance in the knockout line was compromised following a long recovery period (> 24 h) after an acclimation HS treatment, when a severe HS challenge killed the mutant but not the wild-type plants, but no significant difference was observed if they were challenged within a short recovery period. Microarray analysis of the knockout mutant indicates that only the expression of Hsa32 was significantly altered in HS response. Taken together, our results suggest that Hsa32 is not required for the induction but maintenance of acquired thermotolerance. This report provides direct evidence that a plant-specific Hsp plays an important role in thermotolerance.