High-resolution Temperature Research Articles (Page 1)

Abstract. This study presents Eulerian data from Winyah Bay, SC, USA collected during the passage of a tidal plume. The data captured the evolution and structure of the plume and include high-resolution velocity and temperature time series, supplemented by temperature – salinity profiles from a MicroCTD profiler. The observations identified a pre-existing plume extending to 4 m, with a water density of 1023.6 kg m−3, laying above denser ambient waters. Upon arrival, the newly discharged tidal plume introduced a fresher layer (1020.7 kg m−3) extending to 2.6 m, gradually thinning due to radial spreading. The plume's frontal propagation measured at 0.36 m s−1 with a calculated Froude number of 1.32, indicating gravity current dynamics. In the across-front direction a return flow developed under the plume that extended throughout the water column, resembling an estuarine-like circulation pattern. Mixing processes were examined using the available overturn potential energy (AOPE) in the water column as described in Smith (2020). The analysis showed that near the bed, bottom boundary layer turbulence is the main mixing mechanism both before and after the passage of the front. In the surface layer, before the arrival of the front, mixing is driven by wind-induced shear and overturning. Within the gravity current, despite the high turbulent kinetic energy dissipation rates in certain regions, shear-induced mixing was minimal. These findings were reflected in the density diffusivity estimates near the surface that varied from 10−6 m2 s−1 prior to the arrival of the front, increasing to 10−5 m2 s−1 very near the front and diminishing to 10−10 m2 s−1 within the plume despite the high velocity shear observed there. The limited mixing within the plume despite the high shear observed can be explained using the concept of a layer-interface structure, where layers of high turbulence and low stratification alternate with regions of low turbulence and higher stratification. Although not resolved by these observations, this structure has been observed in numerical simulations of mixing. The development of the counter-flow under the plume suggests that tide and/or wind induced straining may play an important role in enhancing stratification in plumes like the one studied here.

Temperature projections from general circulation models (GCMs), serving as an important approach of understanding future global warming, are essential for developing adaptation and mitigation strategies of climate change. However, the coarse spatial resolutions (~1–3°) limit their effectiveness at fine-scale (e.g., intra-urban) research. Here, we produced MoCHAT, a global monthly CMIP6-downscaled high-resolution (1 km) near-surface air temperature dataset. We utilized delta downscaling method to generate MoCHAT based on NEX-GDDP-CMIP6 and WorldClim. MoCHAT encompasses mean, maximum, and minimum air temperature of 16 GCMs. It covers both the historical period (1950–2014) and future scenarios (2015–2100) under three Shared Socioeconomic Pathways (SSPs) scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Validation with meteorological station observations and existing high-resolution climatic datasets showed that the mean absolute errors for these variables range from 1.60 to 2.38 K and overall biases below 2.0 K. With sufficiently long span and fine resolution, MoCHAT breaks through data resolution limitations and provides solid support for global fine-scale heat risk research.

Abstract This paper presents a novel high-resolution wireless temperature sensor based on microwave backscattering principles. The proposed design features a sandwich substrate-integrated waveguide (SIW) structure that incorporates a complementary split-ring resonator etched on the upper conductive layer of a printed circuit board (PCB) stack. This sandwich configuration integrates a temperature-sensitive CaTiO 3 dielectric core between two FR4 substrates ( ϵ r = 4.2), enabling enhanced electromagnetic field confinement and thermal frequency transduction. The sensor was fabricated using standard PCB processing techniques. For experimental characterization, the fabricated device was placed on a heating plate and interrogated wirelessly through a rectangular waveguide antenna connected to a vector network analyzer via a coaxial-to-waveguide converter. The compact sensor (36 mm × 36 mm × 3 mm) demonstrates stable operation over 25 °C–125 °C with 1.6 MHz °C −1 temperature-to-frequency resolution. The experimental results validate the design’s immunity to metallic interference while maintaining quadratic response characteristics ( R 2 = 0.999935) across the operational range. This study demonstrates the feasibility of the sandwich SIW sensor and its broad application prospects for wireless temperature measuring.

Abstract Sponsored by the National Science and Technology Council of Taiwan, the programs Sailing to the Blue Sea (SBS), Kuroshio to Turbulence Exchange (KTEX), and the U.S.-Taiwan collaboration program Island Arc Turbulent Eddy Regional Exchange (ARCTERX) jointly conducted a multidisciplinary field campaign aboard the R/V New Ocean Researcher 1 from March 25 to April 19, 2024. The cruise completed a round trip from Kaohsiung to Palau, executing coordinated oceanic and atmospheric observations in the western North Pacific. The scientific objectives of this campaign were to: (1) investigate the physical, biological, and biogeochemical properties of a targeted cyclonic mesoscale eddy in the western North Pacific and its impact on oceanic weather through air-sea interactions; (2) quantify water mass transformation and nutrient flux variability from the North Equatorial Current (NEC) to the Kuroshio; (3) examine the diurnal warm layer and its coupling with atmospheric boundary layer variability in the subtropical and tropical regions; (4) detect potential ground motion in the Philippine Sea basin at the eastern flank of the Gagua Ridge, east to Taiwan; and (5) measure along-track gravity anomaly across the Philippine Sea basin. The campaign successfully sampled a cyclonic eddy centered at (131°E, 18°N), hydrographic transects across the Kuroshio and the NEC, and high-resolution upper ocean temperature profiles in the tropical ocean. To facilitate detailed analyses of the complex cruise data, the ship-based and autonomous observations are introduced here.

This study identifies, characterizes and corrects for directional effects in high-resolution (HR) Land Surface Temperature (LST) maps based on a comparison of sharpened Sentinel-3 (S3) and ECOSTRESS data at 70-meter resolution. Firstly, the two HR LST datasets were assembled. A Data Mining Sharpener (DMS) derived HR LST to overcome the lack of HR data. This technique sharpened 1 kilometer spatial resolution LST from the S3 Sea and Land Surface Temperature Radiometer (SLSTR), for the Flanders region from 2019 to 2024. The DMS uses a bagging ensemble, that incorporates Sentinel-2 (S2) Multi-Spectral Instrument (MSI) reflectance bands and Copernicus Digital Elevation Model (DEM) data, to enhance the spatial resolution of S3 SLSTR LST. Quasi-simultaneous ECOSTRESS LST acquisitions, for the same region, were acquired to serve as a secondary data source. Secondly, the combined dataset, containing multi-angular observation pairs, was used for analysing directional effects. After cross-calibrating the observation pairs, directional effects are identified through pixel-by-pixel comparisons. A Vinnikov-Roujean-Lagouarde (RL) parametric model simulated directional effects up to 1.6 K. Additionally, case-specific parametric models have been established, characterizing specific morning, night, seasonal, land cover and vegetation density effects. A validation study demonstrates that the proposed correction methodology decreases LST differences of the observation pairs, with tailored strategies for specific conditions yielding the best results. Our study underscores the importance of considering directional effects in HR LST retrievals and provides a global correction framework for upcoming HR thermal missions, including LSTM, TRISHNA and SBG.

Extreme heat is a critical public health threat, particularly in low- and middle-income countries. While its direct health impacts are well documented, less is known about how air pollution modifies heat-related risks. We analyzed daily hospital admissions for circulatory and respiratory diseases in Brazil (2008–2018), combined with high-resolution temperature and pollution (PM₂.₅ and O₃) data. Using generalized additive models and random-effects meta-analysis, we found that PM₂.₅ consistently amplified the effect of heat on respiratory admissions, with a 20.1% increase in risk under high PM₂.₅ conditions (95% CI 4.8–35.4%). In contrast, O₃ showed heterogeneous effects, including a national-level protective association at high concentrations (− 7.6%, 95% CI − 9.6 to − 5.6%). Regional analyses revealed stronger interactions in the North and Southeast. These findings indicate that PM₂.₅ exacerbates, and O₃ variably modifies, heat-related hospitalizations in Brazil, underscoring the need for regionally tailored adaptation and air quality policies.

Evaluating high-resolution mean radiant temperature within an urban street canopy: Resolving spatiotemporal variations with LiDAR/thermal infrared scanning and data-driven simulation

Nationwide high-resolution heat risk projections and intervention cost analysis for the elderly in Japan under climate and demographic changes.

Abstract Background Exposure to extreme temperature is associated with increased unplanned hospitalizations, but it remains unclear whether and why vulnerability varies across regions. This study investigates how regional characteristics modify the relationship between temperature and emergency hospitalizations in Germany. Methods We analyzed weekly emergency hospital admissions by German municipalities from 2005 to 2021 using the Diagnosis-Related Groups Statistic, linked with high-resolution temperature data from the E-OBS database. We calculated the number of days per week falling into one of eleven temperature bins, with 9-16 °C defined as the reference (comfort zone). A municipality-level fixed effects Poisson model was fitted and adjusted for temperature, week, year, gender, and age group. To determine effect modification, we fit stratified models by socioeconomic deprivation, urbanicity, life expectancy, and age structure of the region. Results We observe 112,480,765 emergency hospitalizations over the study period. One additional day above the comfort zone temperature was associated with an increased hospitalization rate in the same week, and minor changes in the following week. In contrast, one additional day below the comfort zone was associated with a decreased hospitalization rate in the same week but an increase in the following week. Preliminary results suggest effect modification by regional characteristics, particularly by socioeconomic deprivation. Conclusions The unplanned character of increased hospitalizations following extreme temperatures presents challenges for adequate care provision. We highlight that some regions, especially those with higher socioeconomic deprivation, may be more vulnerable to the growing health consequences of climate change in Germany. Key messages • Regional characteristics modify the association between extreme temperatures and emergency hospitalizations in Germany. • In the face of climate change, focusing on these regional characteristics allows for understanding which regions need to be prioritized for adequate care provisioning.

Escalating heatwave exposure of the elderly across China.

Abstract. High-resolution climate datasets are of critical importance for the comprehension of spatial and temporal variations in climate and hydrology. However, their development is significantly influenced by the availability, density, and quality of observational data. Building on the China global land surface air temperature 2.0 (C-LSAT 2.0) station data, we collected and integrated nearly 3000 additional station observations and conducted quality control and homogenization processing to complete the updates to the C-LSAT 2.1 dataset. The coverage of the C-LSAT 2.1 dataset has been significantly enhanced, further improving the representativeness of global land diurnal temperature range (DTR) data with greater spatial heterogeneity. Compared to C-LSAT 2.0, C-LSAT 2.1 shows consistent overall trends, except for a slight post-2010 increase for the Southern Hemisphere LSAT anomaly. Furthermore, we employed a “thin-plate spline (climatology) and adjusted inverse distance weighted (anomaly fields)” technical framework to develop a high-resolution (0.5°×0.5°) LSAT (C-LSAT HRv1) and DTR (C-LDTR HRv1) dataset covering January 1901–December 2023. Apart from discrepancies in 1901–1950 due to the limited number of observational stations, the C-LSAT HRv1 and C-LDTR HRv1 datasets effectively capture global and regional variation patterns for subsequent periods. The C-LSAT 2.1 dataset can be downloaded from https://doi.org/10.6084/m9.figshare.28255394.v1 (Wei et al., 2025a), while the C-LSAT HRv1 and C-LDTR HRv1 datasets are available at https://doi.org/10.6084/m9.figshare.28255505.v2 (Wei et al., 2025c) and https://doi.org/10.6084/m9.figshare.28255568.v2 (Wei et al., 2025b), respectively. They are also accessible via http://www.gwpu.net (last access: 11 July 2025).

We quantify future urban heat exposure and adaptation capacity for the 1563 largest global cities, for the first time globally integrating climate projections, urban morphology, and economic capacity. We use high-resolution mean annual temperature (MAT) projections under SSP1-2.6, SSP3-7.0, and SSP5-8.5. These are combined with Local Climate Zone (LCZ) profiles and downscaled socioeconomic data, evaluated consistently within morphological city boundaries. With this framework, we identify cities projected to exceed a 29 °C MAT threshold by 2071–2100. The number of threshold-exceeding cities is projected to rise from 17 (2011–2040) to 217 (2071–2100), exposing up to 320 million residents. Cities with compact built-up forms show higher exposure, while responsiveness to eight expert-curated adaptation measures (e.g., reflective materials, greening, water bodies) and GDP distributions reveal large regional disparities in adaptive capacity. European cities face the steepest relative warming (median + 4 °C under SSP5-8.5), while African and South American cities, despite smaller increases (+2.7 to 3.2 °C), confront higher baseline heat. Our framework demonstrates how morphology- and economy-informed adaptation planning can spatially target measures to safeguard urban habitability in a warming world.

Abstract A nearly 5-month record of high-resolution temperature and acoustic backscatter profiles from the upper insular slope off southwest Puerto Rico reveals complex sound scattering layer (SSL) dynamics over a mesophotic coral ecosystem (MCE). The SSLs exhibited both diel and reverse diel vertical migration, thin layer (< 5 m) and multiple layer formations, depth modulation due to internal waves, and vertical layering in the absence of water column stratification. The long-term observations also capture SSL and water column dynamics across changing seasons and two category five hurricanes, Irma and María. The SSLs, likely comprosed of zooplankton, represent an important food source for both the sessile (e.g., corals and sponges) and mobile (e.g., fish) MCE taxa, and their effective vertical mobility underscores their importance to trophic connectivity between the upper and lower slope MCEs, as well as the shelf. Our results also underscore the challenges in adequately resolving zooplankton aggregations using conventional sampling techniques.

Reported herein are long-lived, red-luminescent silver nanoclusters (AgNCs) protected by the small-molecule ligand thiolactic acid, which exhibit exceptional stability (shelf life exceeding three years, photostability ∼100%), water-solubility, and high biocompatibility, making them suitable for diverse applications such as sensing and live-cell imaging. The AgNCs display extremely sensitive (>2% K-1) temperature-dependent luminescence, monitored by a dual approach of changes in photoluminescence intensity and excited-state lifetime, enabling precise local thermal environment monitoring with a very high-resolution temperature sensing down to subdegree levels (<0.5 K). MTT assay, confocal fluorescence imaging, and fluorescence lifetime imaging microscopy (FLIM) analysis of mammalian cells suggest that the non-cytotoxic AgNCs specifically stain lysosomes in live cells, functioning as an organelle-specific biomarker and providing critical insights into lysosomal dynamics and intracellular temperature fluctuations. The unique properties of these AgNCs, corroborated by detailed mechanistic studies, open new avenues for studying nanoscale subcellular physiology and developing temperature-sensitive diagnostics and preservation strategies.

Heat-related morbidity and mortality are increasing due to climate change, emphasizing the need to identify vulnerable areas and people exposed to extreme temperatures. To improve heat stress impact assessment, we developed a replicable machine learning model that integrates remote sensing, ground station, and geospatial data to estimate daily air temperature at a spatial resolution of 100 m × 100 m across the region of Tuscany, Italy. Using a two-stage approach, we first imputed missing land surface temperature data from MODIS using gradient-boosted trees and spatio-temporal predictors. Then, we modeled daily maximum and minimum air temperatures by incorporating monitoring station observations, satellite-derived data (MODIS, Landsat 8), topography, land cover, meteorological variables (ERA5-land), and vegetation indices (NDVI). The model achieved high predictive accuracy, with R2 values of 0.95 for Tmax and 0.92 for Tmin, and root mean square errors (RMSE) of 1.95 °C and 1.96 °C, respectively. It effectively captured both temporal (R2: 0.95; 0.94) and spatial (R2: 0.92; 0.72) temperature variations, allowing for the creation of high-resolution maps. These results highlight the potential of integrating Earth Observation and machine learning to generate high-resolution temperature maps, offering valuable insights for urban planning, climate adaptation, and epidemiological studies on heat-related health effects.

Assessing cold exposure risk during cold waves in Beijing using high spatiotemporal resolution population data and temperature variations.

Differential proportional divider resistance method for high resolution temperature measurement

High-resolution temperature monitoring with fiber Bragg gratings based on dual-wavelength differential detection

Thermal hotspot detection in landfills using high-resolution land surface temperature data: A case study of active and closed sites.

Noncontact opticalnanothermometers are increasingly recognizedfor their high temperature resolution (δT), excellent relativethermal sensitivity (Sr > 1% K–1),rapidresponse times (t < 0.1 s), and robust long-term optical stability.In this study, upconversion nanoparticles (UCNPs) based on Y2Mo4O15 nanophosphors, codoped with 2% Er3+, 1% Tm3+, and x% Yb3+ (x = 5, 10,15 and 20%), were synthesized using the sol–gel method. Thecrystal structure, morphology, luminescence mechanisms, and temperature-sensingcapabilities of these nanoparticles were systematically characterized.Under 975 nm laser excitation, the UCNPs exhibited intense upconversionluminescence, with emission peaks corresponding to well-defined energy-leveltransitions of Er3+ and Tm3+ ions. Temperature-dependentluminescence spectra were measured over the 300–520 K rangeusing the fluorescence intensity ratio technique. The material exhibitsboth thermally coupled levels (TCLs) and nonthermally coupled levels,resulting from intraionic and interionic transitions involving Er3+–Er3+, Tm3+–Tm3+, Er3+–Tm3+, and Tm3+–Er3+ interactions. This complex energy-transfer network significantlyenhances the temperature-sensing performance. Among the investigatedtransitions, the intensity ratio I700/I806 derivedfrom the TCL approach showed the highest relative sensitivity, reachingSr = 2.18% K–1 at 300 K. Additionally,the system achieved a minimum temperature uncertainty of δT= 0.26 K. These findings highlight the superior thermometric performanceof the synthesized nanophosphors and underscore their potential foroptimization through the synergistic interplay of multiple luminescentcenters. This work validates the applicability of these nanomaterialsfor advanced optical nanothermometry and provides a foundation fordeveloping next-generation temperature nanosensors.