Satellite Temperature Data Research Articles

Methods of Assimilation of Sea Surface Temperature Satellite Data and Their Influence on the Reconstruction of Hydrophysical Fields of the Black, Azov, and Marmara Seas Using the Institute of Numerical Mathematics Ocean Model (INMOM)

Methods of Assimilation of Sea Surface Temperature Satellite Data and Their Influence on the Reconstruction of Hydrophysical Fields of the Black, Azov, and Marmara Seas Using the Institute of Numerical Mathematics Ocean Model (INMOM)

Real-time Satellite Anomaly Data Tagging Based on DAE-LSTM

Abstract Spacecraft is the main carrier of human exploration of outer space, exploration and understanding of the Earth and the universe, and the development of spaceflight can promote human civilization andsocial development, and can meet the nee-ds of economic construction, scientific and technological development, security construction, social progress and other aspects. The current global number of satellites in orbit reaches 5,465, of which China has 541. The vigorous development of the space industry symbolizes the steady improvement of the country’s comprehensive national power and overall technology. During the operation, the satellite in orbit needs to transmit data to the ground, these data may be subject to interference from various aspects, or even equipment failure, we find these data in real time is very important to reduce losses. The data transmitted by satellite has obvious temporal characteristics, and Long Short-Term Memory (LSTM) network has obvious advantages for processing temporal data, so this paper proposes a BER marking model based on the combination of LSTM network and self-coding technology. By comparing the data before and after noise reduction, a threshold value can be determined, and the BERs can be accurately distinguished by this method. After testing with real satellite temperature data, the accuracy of the model detection reaches a high level.

Temporal behavior of air and sea surface temperature in a marine protected area of Cuba

The Cuban Archipelago -particularly its coastal zones- is exposed to Global Warming. The rise of air and sea surface temperature value is a good indicator of its consequences to biodiversity. Air temperature was measured using an Automatic Meteorological Station at the Jardines de la Reina National Park between 2016 and 2017. Sea surface temperature was measured using temperature data loggers twice in the years 2000 (January and September) and 2016 (from January to June) in coral, mangrove and seagrass habitats. Air and sea surface temperature satellite data of the same studied sites were analyzed in the period 2003-2017 using in situ measurements. Results showed that all temperature values were similar to those reported in similar studies in Cuba and the Caribbean, and that extreme values were within the tolerance ranges previously reported for the studied habitats. Air temperature did not have a significant trend; however, sea surface temperature had a significant increase (0.01 °C) during the studied period. These results show the great influence of the Caribbean Sea over the marine waters and climate of this area. A combined monitoring system was proposed using in situ data logger measurements and satellite data temperature analysis to watch this important marine reserve of the Caribbean Region

An Improved Sea‐Ice Velocity Retrieval Algorithm Based on 89 GHz Brightness Temperature Satellite Data in the Fram Strait

AbstractFram Strait is the passageway where most drifting sea ice exits the Arctic Ocean into the North Atlantic, and the sea‐ice velocity (SIV) is the most critical parameter for the variability of the sea ice area flux through Fram Strait. Sea ice flux estimates through the Fram Strait based on satellite remote sensing exist. However, they show discrepancies, which mainly result from the sparse valid satellite observations and the increased uncertainty of sea ice motion in the Fram Strait. In order to improve the sea ice flux estimates, we develop an improved sea‐ice velocity retrieval algorithm from 89 GHz brightness temperature fields of Advanced Microwave Scanning Radiometer for EOS and AMSR2. The improved retrieval algorithm employs an adjusted size of the template window and performs bilinear interpolation on candidate windows before the matching procedure. Instead of depending on external data sources, we construct the SIV uncertainty fields depending only on the maximum correlation coefficients of the image itself. Compared with two similar Passive Microwave (PM) sea ice velocity datasets, the new sea‐ice velocity has lower bias and root‐mean‐square error with respect to buoy observations. In addition, the data density of the new SIV is 14% and 36% higher than the two reference datasets, respectively. Monthly sea ice area flux estimates through the Fram Strait are acquired with the new daily sea‐ice velocity data and the existed sea‐ice concentration. And it indicates that the improved sea ice area flux estimated by PM sea ice velocity agrees well with the Synthetic‐aperture radar‐derived sea ice area flux.

STUDIES ON SURFACE RADIO REFRACTIVITY OVER SOME SELECTED CITIES IN NORTH-CENTRAL, NIGERIA

This research investigated the variations of surface radio refractivity and its propagation effects on radio signal over the cities of Abuja and Ilorin, Nigeria. Six years (2015-2020) satellite data of Temperature, Pressure and Humidity both at the surface (12m) and at 100 m AGL, were used for the study. The data retrieved were used to determine the monthly, seasonal and annual surface radio refractivity values for the locations. Results show that the values of surface radio refractivity (Ns) in Abuja was slightly lower than Ilorin with average values of 335.62 and 351.07 N-Units obtained for the six years respectively. Average values of Ns, obtained during the dry season months in Abuja and Ilorin were 299.40 and 321.03(N-units) respectively while average values of 360.24 and 368.21 (N-units) were obtained during the wet season months in Abuja and Ilorin respectively. Higher values of Ns, were recorded generally during wet compared to the dry seasons’ months in all the years and study locations. The implication of this is higher attenuation of radio signal due to Ns during wet compared to the dry seasons’ months and as well as in Ilorin compared to Abuja. Correlation coefficients of -0.53, 0.98 and 0.53 were determined between (Ns) and; temperature, humidity and pressure respectively in Abuja while -0.30, 0.97 and 0.34 were determined between Ns and; temperature, humidity and pressure respectively in Ilorin. The overall findings of this work will be useful to radio engineers for the proper planning of reliable power budget over the study areas.

The Black Sea Physics Analysis and Forecasting System within the Framework of the Copernicus Marine Service

This work describes the design, implementation and validation of the Black Sea physics analysis and forecasting system, developed by the Black Sea Physics production unit within the Black Sea Monitoring and Forecasting Center as part of the Copernicus Marine Environment and Monitoring Service. The system provides analyses and forecasts of the temperature, salinity, sea surface height, mixed layer depth and currents for the whole Black Sea basin, excluding the Azov Sea, and has been operational since 2016. The system is composed of the NEMO (v 3.4) numerical model and an OceanVar scheme, which brings together real time observations (in-situ temperature and salinity profiles, sea level anomaly and sea surface temperature satellite data). An operational quality assessment framework is used to evaluate the accuracy of the products which set the basic standards for the future upgrades, highlighting the strengths and weaknesses of the model and the observing system in the Black Sea.

Lithosphere–Atmosphere–Ionosphere Coupling Effects Based on Multiparameter Precursor Observations for February–March 2021 Earthquakes (M~7) in the Offshore of Tohoku Area of Japan

The purpose of this paper is to discuss the lithosphere–atmosphere–ionosphere coupling (LAIC) effects with the use of multiparameter precursor observations for two successive Japanese earthquakes (EQs) (with a magnitude of around 7) in February and March 2021, respectively, considering a seemingly significant difference in seismological and geological hypocenter conditions for those EQs. The second March EQ is very similar to the famous 2011 Tohoku EQ in the sense that those EQs took place at the seabed of the subducting plate, while the first February EQ happened within the subducting plate, not at the seabed. Multiparameter observation is a powerful tool for the study of the LAIC process, and we studied the following observables over a 3-month period (January to March): (i) ULF data (lithospheric radiation and ULF depression phenomenon); (ii) ULF/ELF atmospheric electromagnetic radiation; (iii) atmospheric gravity wave (AGW) activity in the stratosphere, extracted from satellite temperature data; (iv) subionospheric VLF/LF propagation data; and (v) GPS TECs (total electron contents). In contrast to our initial expectation of different responses of anomalies to the two EQs, we found no such conspicuous differences of electromagnetic anomalies between the two EQs, but showed quite similar anomaly responses for the two EQs. It is definite that atmospheric ULF/ELF radiation and ULF depression as lower ionospheric perturbation are most likely signatures of precursors to both EQs, and most importantly, all electromagnetic anomalies are concentrated in the period of about 1 week–9 days before the EQ to the EQ day. There seems to exist a chain of LAIC process (cause-and-effect relationship) for the first EQ, while all of the observed anomalies seem to occur nearly synchronously in time for the send EQ. Even though we tried to discuss possible LAIC channels, we cannot come to any definite conclusion about which coupling channel is plausible for each EQ.

Sea Level Seasonal, Interannual and Decadal Variability in the Tropical Pacific Ocean

The satellite altimeter data, temperature and salinity data, and 1.5-layer reduced gravity model are used to quantitatively evaluate the contributions of the steric effect and the dynamic process to sea level variations in the Tropical Pacific Ocean (TPO) on different time scales. Concurrently, it also analyses the influence of wind forcing over the different regions of the Pacific Ocean on the sea level variations in the TPO. Seasonal sea level variations in the TPO were the most important in the middle and eastern regions of the 5°–15°N latitude zone, explaining 40–60% of the monthly mean sea level variations. Both the steric effect and dynamic process jointly affected the seasonal sea level variations. Among them, the steric effect was dominant, contributing over 70% in most regions of the TPO, while the dynamic process primarily acted near the equator and southwest regions, contributing approximately 55–85%. At the same time, the seasonal dynamic sea level variations were caused by the combined actions of primarily local wind forcing, alongside subtropical north Pacific wind forcing. On the interannual to decadal time scale, the sea level interannual variations were significant in the northwestern, southwestern, and middle eastern regions of the TPO and explained 45–60% of the monthly mean sea level variations. The decadal sea level variations were the most intense in the eastern Philippine Sea, contributing 25–45% to the monthly mean sea level variations. The steric effect and the dynamic process can explain 100% of the interannual to decadal sea level variations. The contribution of the steric effect was generally high, accounting for more than 85% in the regions near the equator. The impact of the dynamic process was mainly concentrated in the northwest, northeast, and southern regions of the TPO, contributing approximately 55–80%. Local wind forcing is the leading role of interannual to decadal sea level variations. The combined actions of El Niño–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) can explain 90% of the interannual to decadal sea level variations in the northwestern and eastern of the TPO.

Temperature and Patterns of Occurrence and Abundance of Key Copepod Taxa in the Northeast Pacific

The Northeast Pacific is a highly heterogeneous and productive ecosystem, yet it is vulnerable to climate change and extreme events such as marine heat waves. Recent heat wave induced die-offs of fish, marine mammals, and seabirds in the Gulf of Alaska were associated with the loss of large, lipid-rich copepods, which are a vital food resource for forage fishes. The critical and temperature sensitive role of copepods in this ecosystem motivates our investigation into the impacts of temperature on copepod occurrence, abundance, and phenology. Here, we pair long term in situ copepod data from Continuous Plankton Recorder surveys with satellite temperature data to determine the influence of water temperature on three key copepod taxa: Neocalanus plumchrus, Calanus pacificus, and Oithona spp. Through the use of linear models and thermal threshold methods, we demonstrate that N. plumchrus is most vulnerable to warming and future marine heat waves in this region. Linear models demonstrate that N. plumchrus abundance is negatively related to temperature, and thermal threshold methods reveal that N. plumchrus has an upper thermal threshold of 11.5°C for occurrence, and 10.5°C for abundance. Additionally, examining N. plumchrus abundance before and during the 2014–2016 marine heat wave demonstrates reduced species abundance during past warming events. Oithona spp. and C. pacificus appear to be less vulnerable to warm temperatures. However, their presence will not be sufficient to supplement the loss of the larger-bodied and lipid-rich N. plumchrus. Our findings demonstrate the power of using long-term in situ data to determine thermal tolerances, and suggest the need to further examine the potential resilience of N. plumchrus to climate change.

Dinámica de la estructura de la comunidad bentónica en las formaciones coralinas someras del archipiélago de San Bernardo, Caribe colombiano

Los arrecifes de coral han sufrido una extensa degradación en las últimas décadas como resultado de perturbaciones antropogénicas y naturales. Este estudio presenta una caracterización histórica (1989-2015) de los cambios en la omposición del sustrato en formaciones coralinas en el archipiélago de San Bernardo. Adicionalmente, en el 2015 se evaluó la salud arrecifal (presencia de signos de deterioro) y se analizaron datos satelitales de temperatura. En general, la cobertura de coral mostró una tendencia estable entre 1989 y 2010. En 2013 y 2015 se registraron diferencias en el ensamblaje coralino las cuales pueden estar asociadas al incremento en la cobertura de las especies de los géneros Orbicella, Porites, Agaricia, Siderastrea y del hidrocoral Millepora complanata. Las menores coberturas observadas en 1989, 1991 y 2005 estuvieron posiblemente relacionados con eventos de mortalidades masivas de especies arrecifales por enfermedades y blanqueamiento. Se registró un comportamiento opuesto entre el sustrato abiótico y las algas, siendo este último grupo el componente dominante del sustrato desde el 2013. Espacialmente se presentaron diferentes tendencias. Las estaciones en Ceycen, Tintipán y Mangle presentaron mejores condiciones de desarrollo coralino en el tiempo, mientras que las estaciones en Cabruna y Palma, lugares más cercanos a los centros urbanos, presentaron indicios de tendencia hacia el deterioro. Adicionalmente, a partir de junio del 2015 se registraron valores de temperatura por encima del umbral de tolerancia al blanqueamiento (29,4 °C), por lo que posiblemente los corales enfrentaron un estrés térmico que causó blanqueamiento en 18 de las 19 estaciones evaluadas. Son esenciales las acciones de gestión sobre los impactos locales, acompañados de la información suministrada por los programas de monitoreo, para que los arrecifes puedan recuperarse de los impactos naturales y antropogénicos que los afectan.

Remote Sensing Satellite Imagery and In-Situ Data for Identifying Geothermal Potential Sites: Jaboi, Indonesia

Remote sensing makes it possible to map potential geothermal site for a large area effectively using thermal infrared. The purpose of the present research is to overlay ground temperature, resistivity and satellite retrieved temperature in identifying geothermal potential site in Jaboi, Sabang-Indonesia. The data of acquisition of the DEM imagery was January 3rd, 2009 and the Landsat 8 imagery is July 18th, 2017. The satellite data were applied to extract the land surface temperature and land classification across. Two supporting data in situ were used to validate the results from remote sensing. First dataset was ground temperature measurements with total 114 points and second dataset was vertical electrical sounding (VES) with total of 51 points. Satellite, VES and ground temperature data were processed and analysed using the Envi 5.3, PCI Geomatica 2016 and ArcMap 10.4. The results from each data were integrated to produce a map shows geothermal potential. Its integration produced four areas which were considered to have high geothermal potential. However, these areas vary in term of the clustering of the features of interest, for example lineament and drainage density of the area, high temperature in the surface area, fault existence and low resistivity subsurface. All the features must take into consideration to rank potential area which has higher potential. Finally, a map of geothermal potential across were successfully created as an insight for future reference.

An ensemble Kalman filter data assimilation system for the whole neutral atmosphere

Abstract. A data assimilation system with a four-dimensional local ensemble transform Kalman filter (4D-LETKF) is developed to make a new analysis dataset for the atmosphere up to the lower thermosphere using the Japanese Atmospherics General Circulation model for Upper Atmosphere Research. The time period from 10 January to 20 February 2017, when an international radar network observation campaign was performed, is focused on. The model resolution is T42L124, which can resolve phenomena at synoptic and larger scales. A conventional observation dataset provided by the National Centers for Environmental Prediction, PREPBUFR, and satellite temperature data from the Aura Microwave Limb Sounder (MLS) for the stratosphere and mesosphere are assimilated. First, the performance of the forecast model is improved by modifying the vertical profile of the horizontal diffusion coefficient and modifying the source intensity in the non-orographic gravity wave parameterization by comparing it with radar wind observations in the mesosphere. Second, the MLS observational bias is estimated as a function of the month and latitude and removed before the data assimilation. Third, data assimilation parameters, such as the degree of gross error check, localization length, inflation factor, and assimilation window, are optimized based on a series of sensitivity tests. The effect of increasing the ensemble member size is also examined. The obtained global data are evaluated by comparison with the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) reanalysis data covering pressure levels up to 0.1 hPa and by the radar mesospheric observations, which are not assimilated.

Evaluation of empirical Bayesian kriging

Using Bayesian bootstrap as the informative prior distribution is a key feature of the empirical Bayesian kriging method. We evaluate correctness of the method using two large simulation experiments. We also compare empirical Bayesian kriging performance with several popular geostatistical models implemented in R using two real datasets: the average annual precipitation in South Africa and the daytime land surface temperature satellite data. Results show that empirical Bayesian kriging performs better than other predictors, and increasingly so with data complexity.

An epilimnion and hypolimnion temperature model based on air temperature and lake characteristics

Water temperature is an essential ecological variable that influences life beings at several organizational levels, but its monitoring at the regional level is costly. An alternative is using models, which summarise the knowledge of the functioning of the system so that they can be used to answer specific questions. We present a model to calculate the epilimnion and hypolimnion temperature of inland water bodies based on air temperature and on their geographical and morphological characteristics. The seven model parameters were parameterized by using official monitoring data and the satellite temperature data of the data set LakeSST for French water bodies. The performance of the parameterised model was compared to that of two widely used models (FLake and air2water with four parameters). The model showed a good performance in the simulation of epilimnion temperatures, especially in the summer. For hypolimnion temperatures the performance was worse, but still comparable to that of other models. Because of its good performance and the few data needed to run the model, it is a good choice for managers interested in the thermal behaviour of inland water bodies.

Abrupt changes in global tropospheric temperature

The temporal evolution of the temperature of the lower troposphere, middle troposphere, tropopause and lower stratosphere on a global, hemispheric and latitudinal basis is studied using the recent Version 6 of the UAH MSU/AMSU global satellite temperature data set. The analysis showed that any long-term increase or decrease in temperature is not smooth and uniform, i.e., it is not slow and monotonous. In contrast, it grows or decreases monotonously in a short period, then almost stabilizes for some time, and then repeats the same pattern. In other words, the long-term temperature trend is not linear but follows the stepwise increase or decrease. In more concrete, the temperature time series over the period 12/1978–07/2018 is composed by a noisy pattern superposed on a stepwise function with abrupt shifts in 1986, 1994 and 2014. In addition, we noticed that the superposition of the stepwise function on the ENSO time series provides a new composite time series, which fits very well with the observed temperature. If the latter is delayed for almost 4 months this fit is even better. This pattern applies to the temperature of the troposphere on a global, hemispheric and tropical basis. It does not apply to the temperature of the troposphere over the extratropics and polar regions, as well as to the temperature of the lower stratosphere. In particular, the extra-tropics of the northern hemisphere displays an Arctic Oscillation stair-shaped behaviour.Perhaps the stepwise pattern in temperature evolution may be due to the fact that the gradual changes in the periodic or quasi-periodic tropospheric temperature components may trigger sudden changes which with positive feedbacks, lead to a self-enhancing change. This can be so strong that the temperature reaches critical values and then with sudden changes goes from one equilibrium state to another.

Evaluation of atmospheric empirical model based on TIMED/SABER satellite temperature data

A total of 15 years of global temperature data from 2002–2016 as measured by TIMED/SABER were taken as standard to compare with those of USSA-76 and NRLMSISE-00. The accuracy of the two atmospheric models was analyzed by calculating daily mean and monthly mean temperature deviations and standard deviations of temperature deviations at different altitudes. The confidence of the model under different temperature deviations is calculated through setting the deviation between the models and the satellite observation temperature. The results show that the temperature data calculated by the two atmospheric models are in good agreement with the temperature observed by satellite. The daily mean and monthly mean accuracy of the NRLMSISE-00 are higher than those of the USSA-76. In the UMLT region, the two atmospheric models have yet to be improved to characterize the true atmosphere at the mid-high latitudes of upper mesosphere in summer and winter. The overall ability of the NRLMSISE-00 to represent the true atmosphere is superior to the USSA-76. In addition, the confidence decreases with the increase of altitude in the same latitude area and temperature deviation requirements. The confidence decreases with increasing latitude in the same altitude and temperature deviation requirements. By analyzing the differences between the atmospheric models and satellite observations. This paper provides a reference for the application of atmospheric models in engineering and provides the basis for the subsequent correction of atmospheric modes.

BRISC: bootstrap for rapid inference on spatial covariances

In geostatistics, inference on spatial covariance parameters of the Gaussian process is often critical to scientists for understanding structural dependence in data. Finite‐sample inference customarily proceeds either using posterior distributions from fully a Bayesian approach or via resampling/subsampling techniques in a frequentist setting. Resampling methods, in particular, the bootstrap, have become more attractive in the modern age of big data as, unlike Bayesian models that require sequential sampling from Markov chain Monte Carlo, they naturally lend themselves to parallel computing resources. However, a spatial bootstrap involves an expensive Cholesky decomposition to decorrelate the data. In this manuscript, we develop a highly scalable parametric spatial bootstrap that uses sparse Cholesky factors for parameter estimation and decorrelation. The proposed bootstrap for rapid inference on spatial covariances (BRISC) algorithm requires linear memory and computations and is embarrassingly parallel, thereby delivering substantial scalability. Simulation studies highlight the accuracy and computational efficiency of our approach. Analysing large satellite temperature data, BRISC produces inference that closely matches that delivered from a state‐of‐the‐art Bayesian approach, while being several times faster. The R package BRISC is now available for download from GitHub (https://github.com/ArkajyotiSaha/BRISC) and will be available on CRAN soon. Copyright © 2018 John Wiley & Sons, Ltd.

Spatial Coverage of Monitoring Networks: A Climate Observing System Simulation Experiment

AbstractObserving systems consisting of a finite number of in situ monitoring stations can provide high-quality measurements with the ability to quality assure both the instruments and the data but offer limited information over larger geographic areas. This paper quantifies the spatial coverage represented by a finite set of monitoring stations by using global data—data that are possibly of lower resolution and quality. For illustration purposes, merged satellite temperature data from Microwave Sounding Units are used to estimate the representativeness of the Global Climate Observing System Reference Upper-Air Network (GRUAN). While many metrics exist for evaluating the representativeness of a site, the ability to have highly accurate monthly averaged data is essential for both trend detection and climatology evaluation. The calculated correlations of the monthly averaged upper-troposphere satellite-derived temperatures over the GRUAN stations with all other pixels around the globe show that the current 9 certified GRUAN stations have moderate correlations (r ≥ 0.7) for approximately 10% of the earth, but an expanded network incorporating another 15 stations would result in moderate correlations for just over 60% of the earth. This analysis indicates that the value of additional stations can be quantified by using historical, satellite, or model data and can be used to reveal critical gaps in current monitoring capabilities. Evaluating the value of potential additional stations and prioritizing their initiation can optimize networks. The expansion of networks can be evaluated in a manner that allows for optimal benefit on the basis of optimization theory and economic analyses.

Oblique propagation of monsoon gravity waves during the northern hemisphere 2007 summer

AbstractWe present a combination of satellite observation and high‐resolution model output to understand monsoon convection as a source of high‐latitude mesospheric gravity waves (GWs). The GWs generated over the Northern Hemisphere (NH) monsoon region during the 2007 summer and the role of the winds in focusing these GWs toward the high‐latitude middle atmosphere are analyzed using the Sounding of the Atmosphere using Broadband Emission Radiometry/Thermosphere Ionosphere Mesosphere Energetics and Dynamics (SABER/TIMED) satellite temperature data and the high‐resolution Navy Operational Global Atmospheric Prediction System‐Advanced Level Physics High Altitude (NOGAPS/ALPHA) model results. In the NH, above the stratosphere, the monsoon GW Momentum Flux (GWMF) exhibits a poleward tilt that follows the slanted structure of the easterly jet. The correlation coefficients (>0.5) between the time series of NH tropical stratospheric GWMF and the global winds also have a slanted structure that coincide with the easterly jet, confirming the modeling theory that stratospheric monsoon GWs are refracted into the summer easterly jet and can reach the high‐latitude mesosphere. Since Polar Mesospheric Clouds (PMCs) are sensitive indicators of changes in the polar summer mesosphere, we compared the time series of tropical stratospheric GWMF to the PMC occurrence frequency (OF) obtained from the Cloud Imaging and Particle Size/Aeronomy of Ice in the Mesosphere satellite data to assess the influence of this wave focusing in the mesosphere. There is a significant positive correlation between the high‐latitude PMC OF and the tropical stratospheric GWMF suggesting a definite influence of monsoon GWs on the high‐latitude mesosphere. The disagreement in correlation at the end of the PMC season is attributed to the enhancement of the quasi 5 day planetary wave dominating over the influence of monsoon GWs on PMCs.

Warming Trends and Bleaching Stress of the World's Coral Reefs 1985-2012.

Coral reefs across the world’s oceans are in the midst of the longest bleaching event on record (from 2014 to at least 2016). As many of the world’s reefs are remote, there is limited information on how past thermal conditions have influenced reef composition and current stress responses. Using satellite temperature data for 1985–2012, the analysis we present is the first to quantify, for global reef locations, spatial variations in warming trends, thermal stress events and temperature variability at reef-scale (~4 km). Among over 60,000 reef pixels globally, 97% show positive SST trends during the study period with 60% warming significantly. Annual trends exceeded summertime trends at most locations. This indicates that the period of summer-like temperatures has become longer through the record, with a corresponding shortening of the ‘winter’ reprieve from warm temperatures. The frequency of bleaching-level thermal stress increased three-fold between 1985–91 and 2006–12 – a trend climate model projections suggest will continue. The thermal history data products developed enable needed studies relating thermal history to bleaching resistance and community composition. Such analyses can help identify reefs more resilient to thermal stress.