Diurnal Temperature Research Articles

Unravelling the elevation-dependent warming in the Indus Basin

The Elevation Dependent Warming (EDW) in the mountain regions have wider implications to its cryosphere, hydrological, and ecological systems. This paper explores an EDW in the Indus River Basin, considering Jhelum, Kabul, and Indus sub-basins to improve the accuracy and understanding of cryospheric and hydrological changes in the basin. We use the maximum (Tmax), minimum (Tmin), and mean (Tmean) near surface atmospheric temperature data from 21 ground stations for the 1988–2021 period and applied the Mann-Kendall (MK) trend tests for exploring the trends in the data. The results show that Tmax and Tmin has significant (p < 0.001) warming trends in the Upper Indus Basin (UIB) until 2210 mean above sea level (m asl). Tmax has increased with a rate of 0.031 °C yr−1 (p < 0.001) while Tmin increased with a rate of 0.029 °C yr−1 (p < 0.001), hence the “diurnal temperature range (DTR) also increased significantly” (0.015 °C yr−1, p < 0.001). In this study, a symmetric pattern of increasing trends has been observed in Tmax and Tmin. Moreover, Tmax has increasing trends throughout the period in the middle and high-altitude regions, except in Autumn and Monsoon seasons, respectively. While more significant and prominent increasing trend observed in Tmax during the winter season. Thus, this consistent warming trends in all seasons with more prominent trend in the winter season for Tmax can have harmful impact on the cryosphere of the region and ultimately, leading to water scarcity and extreme droughts.

Diurnal switches in diazotrophic lifestyle increase nitrogen contribution to cereals

Uncoupling of biological nitrogen fixation from ammonia assimilation is a prerequisite step for engineering ammonia excretion and improvement of plant-associative nitrogen fixation. In this study, we have identified an amino acid substitution in glutamine synthetase, which provides temperature sensitive biosynthesis of glutamine, the intracellular metabolic signal of the nitrogen status. As a consequence, negative feedback regulation of genes and enzymes subject to nitrogen regulation, including nitrogenase is thermally controlled, enabling ammonia excretion in engineered Escherichia coli and the plant-associated diazotroph Klebsiella oxytoca at 23 °C, but not at 30 °C. We demonstrate that this temperature profile can be exploited to provide diurnal oscillation of ammonia excretion when variant bacteria are used to inoculate cereal crops. We provide evidence that diurnal temperature variation improves nitrogen donation to the plant because the inoculant bacteria have the ability to recover and proliferate at higher temperatures during the daytime.

Modelling habitat suitability for Moringa oleifera and Moringa stenopetala under current and future climate change scenarios

Moringa oleifera Lam and Moringa stenopetala (Baker f.) Cufod are being widely promoted as multipurpose trees across the tropics for their nutritional, medicinal and soil health benefits. Different parts of these species are edible, have therapeutic values and their seeds are used for water purification. Although the two species are similar in many ways, they have contrasting distributions. However, their current promotion is not guided by adequate knowledge of the suitability of the target areas. Information is also scanty on the suitability of habitats for these species under the current and future climate change scenarios. Therefore, the objective of this study was to predict the habitat suitability of M. oleifera and M. stenopetala under current and future climate change scenarios using an ensemble of models assuming four shared socio-economic pathways, namely, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 for 2050 and 2070. The results suggest that areas that are highly suitable for M. oleifera will increase by 0.1% and 3.2% under SSP1-2.6 to SSP5-8.5 by 2050, respectively. By 2070, the area suitable for M. oleifera would likely decrease by 5.4 and 10.6% under SSP1-2.6 and SSP5-8.5 scenarios, respectively. The habitat that is highly suitable for M. stenopetala was predicted to increase by 85–98% under SSP3-7.0 and SSP5-8.5 scenarios by 2050 and by 2070, while suitable areas could increase by up to 143.6% under SSP5-8.5. The most influential bioclimatic variables for both species were mean diurnal temperature range, mean temperature of driest quarter, precipitation of wettest month, and isothermality. Additionally, soil pH, elevation and water holding capacity were influential variables in the distribution of M. oleifera, while soil pH, soil salinity and slope were influential in M. stenopetala distribution. This study has provided baseline information on the current distribution and possible future habitat suitability, which will be helpful to guide formulation of good policies and practices for promoting Moringa species outside their current range.

Association between diurnal temperature range and outpatient visits for urticaria disease in Lanzhou, China: a distributed lag nonlinear analysis.

A growing number of epidemiological studies have shown that daily temperatures are associated with urticaria. However, the relationship between daily changes in temperature and urticaria is unclear. To assess the diurnal temperature difference (DTR) effects on urticaria outpatient visits in Lanzhou, China. Urticaria outpatient visits data during 2011-2019 were collected from three major tertiary hospitals in Lanzhou. Daily temperature data from the official website of China Meteorological Administration. Assessment of the relationship between urticaria outpatient volume and DTR in Lanzhou City using a distributed lag nonlinear model. A total of 83,022 urticaria visits were enrolled. There was a nonlinear relationship between DTR and urticaria outpatient visits and a lagged effect of DTR impact. The effects of high DTR on urticaria visits were not seen in all populations but in the male population and in the 15-59 age group. High DTR (P95: 18.2°C) was associated with a 27% (95% CI: 0.01, 60.53%) and 31% (95% CI: 1.60, 68.99%) increase in the number of urticaria visits in the 21-day lag effect for the male cohort and the 15-59year old cohort, respectively, compared with 11.5°C, respectively. Our study suggests that DTR is a potential risk factor for urticaria. The results of this study may provide a scientific basis for local governments to improve preventive measures in the health care system.

Reversed asymmetric warming of sub-diurnal temperature over land during recent decades

In the latter half of the twentieth century, a significant climate phenomenon “diurnal asymmetric warming” emerged, wherein global land surface temperatures increased more rapidly during the night than during the day. However, recent episodes of global brightening and regional droughts and heatwaves have brought notable alterations to this asymmetric warming trend. Here, we re-evaluate sub-diurnal temperature patterns, revealing a substantial increase in the warming rates of daily maximum temperatures (Tmax), while daily minimum temperatures have remained relatively stable. This shift has resulted in a reversal of the diurnal warming trend, expanding the diurnal temperature range over recent decades. The intensified Tmax warming is attributed to a widespread reduction in cloud cover, which has led to increased solar irradiance at the surface. Our findings underscore the urgent need for enhanced scrutiny of recent temperature trends and their implications for the wider earth system.

Time-dependent regulation of respiration is widespread across plant evolution.

Establishing the temperature dependence of respiration is critical for accurate predictions of the global carbon cycle under climate change. Diurnal temperature fluctuations, or changes in substrate availability, lead to variations in leaf respiration. Additionally, recent studies hint that the thermal sensitivity of respiration could be time-dependent. However, the role for endogenous processes, independent from substrate availability, as drivers of temporal changes in the sensitivity of respiration to temperature across phylogenies has not yet been addressed. Here, we examined the diurnal variation in the response of respiration to temperatures (R-T relationship) for different lycophyte, fern, gymnospermand angiosperm species. We tested whether time-dependent changes in the R-T relationship would impact leaf level respiration modelling. We hypothesized that interactions between endogenous processes, like the circadian clock, and leaf respiration would be independent from changes in substrate availability. Overall, we observed a time-dependent sensitivity in the R-T relationship across phylogenies, independent of temperature, that affected modelling parameters. These results are compatible with circadian gating of respiration, but further studies should analyse the possible involvement of the clock. Our results indicate time-dependent regulation of respiration might be widespread across phylogenies, and that endogenous regulation of respiration is likely affecting leaf-level respiration fluxes.

Amine-functionalized MIL-101(Cr) fibers for direct air capture at cold temperatures using rapid temperature vacuum swing adsorption

Given that most of the world shows annual temperatures lower than 25 °C and some regions exhibit a large diurnal temperature difference in a single day, it is desirable to explore the CO2 sorption behavior of materials not only at ambient (25 °C) but also at cooler, “sub-ambient” conditions (defined here as < 25 °C). These cold temperatures may offer advantages for DAC such as higher gas adsorption capacities and lower absolute humidity, reducing concomitant water adsorption. Here, amine-functionalized MIL-101(Cr) fibers are evaluated at cold temperatures using rapid temperature vacuum swing adsorption (RTVSA). MIL-101(Cr)/cellulose acetate fibers loaded with macromolecular amines are evaluated as practical gas–solid contactors. As spun MIL-101(Cr) fibers show desirable properties for use as structured contactors such as high permeance and low pressure drop. Breakthrough and RTVSA experiments are conducted in the presence of humidity at sub-ambient temperatures to understand the CO2 adsorption and desorption behavior of the sorbent/contactor under conditions approaching practical operation. With optimized amine loading, the PEI-MIL-101(Cr) fibers give CO2 capacities comparable to the powder form of the sorbent, as well as sharp breakthrough curves at fast flow rates (1.4 m/s superficial velocity) suggesting the system is not limited by additional mass transfer resistances under the tested conditions. RTVSA shows fast desorption kinetics (14.4 mmol of CO2/g of fiber/h) at moderate desorption conditions, at 0.1 bar vacuum with temperatures below 80 °C. The entire cycle during RTVSA finishes in ∼ 25 min with ∼ 76 mol% CO2 purity as the product in this initial, modestly optimized study.

Combined modelling of annual and diurnal land surface temperature cycles

The land surface's thermal dynamics follows annual and diurnal cycles that are to a large extent controlled by solar geometry. Therefore, annual and diurnal variations of land surface temperature (LST) can be modelled with relatively simple functions controlled by a small number of parameters, typically from three to six. The parameter values of the models can be determined by fitting the respective functions to time series of LST observations. Commonly either annual or diurnal LST variations are modelled or they are modelled sequentially in a two-step process. Here, we combine an annual temperature cycle (ATC) model controlled by the solar zenith angle (ATCsza) with a four-parameter version of the diurnal temperature cycle (DTC) model GOT09: this yields a new annual-diurnal temperature cycle (ADTC) model that simultaneously describes the annual and diurnal surface temperature dynamics. The proposed ADTC model is controlled by physically meaningful parameters: annual minimum temperature, annual temperature amplitude, annual maximum of daily temperature amplitude, mean time of thermal noon and time lag of maximum temperature with respect to summer solstice. Thus, the entire annual-diurnal LST dynamics is described with only five parameters. The new model was tested by fitting it to one year of LST observations obtained for five globally representative tiles of the Moderate Resolution Imaging Spectroradiometer (MODIS), onboard EOS – TERRA and EOS – AQUA satellites. For these tiles, the mean of the root mean square error (RMSE) was 4.2 K. ADTC modelled LSTs were also compared against those obtained with the standard ATC model for the four MODIS overpass times at five representative sites: for these, an overall RMSE of 1.2 K between the two models was obtained. The ADTC derived LSTs were validated against in-situ measurements from three different sites, which yielded an overall RMSE of 3.4 K. Additional investigations over five areas with different land covers (i.e. urban, lake, forest, mountain area and desert) revealed the potential of the ADTC parameters to describe the corresponding surface and climate properties. Since it is driven by solar geometry, the ADTC model reproduces double LST peaks in the tropics naturally. Furthermore, all available observations are modelled simultaneously, which means that a single set of parameters is obtained for each pixel and year.

Growth and photosynthetic changes of Ulva prolifera in response to diurnal temperature variations

Growth and photosynthetic changes of Ulva prolifera in response to diurnal temperature variations

Quantitative analysis of diurnal CO2 flux variations above an alkaline playa

AbstractThe alkaline playas at Atlin, BC, provide a unique opportunity for studying the carbonate–bicarbonate system and carbonate mineral stability at the Earth's surface. In this study, dynamic closed chambers (DCCs) and pore‐gas sampling were used to directly quantify carbon dioxide (CO2) emission rates and characterize processes governing the CO2 exchange across the playa‐atmosphere interface. Data were collected at the Atlin site continuously over 27 days in 2020 and 14 days in 2021. Results indicate minimal net exchange of CO2 across the playa‐atmosphere interface during the monitoring periods, with average fluxes over the two periods of −0.03 and 0.09 µmol m−2 s−1 in 2020 and 2021, respectively. However, distinct diurnal oscillations of CO2 fluxes were measured with average daytime fluxes of 0.15 ± 0.34 µmol m−2 s−1 (2020) and 0.15 ± 0.19 µmol m−2 s−1 (2021) and nighttime fluxes of −0.24 ± 0.31 µmol m−2 s−1 (2020) and 0.04 ± 0.18 µmol m−2 s−1 (2021). These observations, supported by reactive transport modeling, indicate that CO2 exchange is predominantly governed by changes in CO2 solubility in alkaline porewater related to diurnal temperature fluctuations and variations in CO2 concentrations in ambient air above the ground surface. Even though CO2 concentrations exceed 8000 ppmv at 1‐m depth, CO2 emissions to the atmosphere were found to be minimal, likely due to high moisture contents, low connectivity, and tortuosity, limiting upward CO2 migration. These findings provide insights into CO2 flux dynamics in alkaline arid regions and show promise for the application of the DCC method for monitoring ex situ carbon mineralization at sites with enhanced mineral weathering.

Fading regulation of diurnal temperature ranges on drought-induced growth loss for drought-tolerant tree species

Warming-induced droughts caused tree growth loss across the globe, leading to substantial carbon loss to the atmosphere. Drought-induced growth loss, however, can be regulated by changes in diurnal temperature ranges. Here, we investigated long term radial growth responses of 23 widespread distributed tree species from 2327 sites over the world and found that species’ drought tolerances were significantly and positively correlated with diurnal temperature range-growth loss relationships for the period 1901-1940. Since 1940, this relationship has continued to fade, likely due to asymmetric day and night warming trends and the species’ ability to deal with them. The alleviation of reduced diurnal temperature ranges on drought-induced growth loss was mainly found for drought resistant tree species. Overall, our results highlight the need to carefully consider diurnal temperature ranges and species-specific responses to daytime and nighttime warming to explore tree growth responses to current and future warmer and drier climates.

A Climatological Survey of Corsica for Power System Analyses

Climate and climate change can impact present and future energy production and demand. In light of this issue, this paper conducts climatological analyses focused on the following meteorological quantities: shortwave downward irradiance (SDI), precipitation (Pr), relative humidity (RH), air temperature (Ta), 10 m wind speed (v10), and diurnal temperature range (DTR) for four locations in Corsica. The climate analyses of these atmospheric variables consist of three parts: (1) analysis of the historical trends; (2) correlation analysis; and (3) analysis of climate projections for the decades to come. It is observed that climate change is causing alterations in the trends of Pr, RH, Ta, v10, and DTR. The correlation analysis reveals a positive correlation for the Ta-SDI and v10-Pr pairs (both annually and seasonally), and a negative correlation for Ta-RH (annually and in summer). For the other variable pairs, the sign of the correlations varies depending on the time period and site considered. The trends in the projections from the multi-model ensemble simulations are consistent or inconsistent with each other depending on the time period (annual or seasonal) considered. The observed historical trends suggest that medium-term planning of the Corsican electric power system should already consider ongoing climate change. The correlation analysis provides insights into the combined effect of different atmospheric variables on electrical power systems (EPSs). Climate projections suggest studying long-term planning that is a compromise among the different (but equally likely) outputs of different climate models.

Design of a Data Acquisition, Correction and Retrieval of Na Doppler Lidar for Diurnal Measurement of Temperature and Wind in the Mesosphere and Lower Thermosphere Region

Based on the resonance fluorescence scattering mechanism, a narrowband sodium (Na) lidar can measure temperature and wind in the mesosphere and lower thermosphere (MLT) region. By using a narrowband spectral filter, background light noise during the day can be suppressed, allowing for continuous observations. To obtain full-diurnal-cycle temperature and wind measurement results, a complex and precise retrieval process is required, along with necessary corrections to minimize measurement errors. This paper introduces the design of a data acquisition unit for three frequencies in three directions of the Na lidar system in the Chinese Meridian Project (Phase II) and investigates the calibration and retrieval methods for obtaining diurnal temperature and horizontal wind in the MLT region, using a Na Doppler lidar with Faraday anomalous dispersion optical filter (FADOF). Furthermore, these methods are applied to observations conducted by a Na lidar in Beijing, China. The wind and temperature results over full diurnal cycles obtained from the all-solid-state Na Doppler lidar are reported for the first time and compared with temperature measurements from satellite, as well as wind observations from a meteor radar. The comparison demonstrates a reasonable agreement between the results, indicating the rationality of the lidar-retrieved results and the feasibility and effectiveness of the data correction and retrieval method.

A heating system using flat plate collectors to control the inside greenhouse microclimate in Tunisia

The continuous increase in the level of greenhouse gas emissions and the rise in fuel prices are the main driving forces behind the efforts for more effectively utilize various sources of renewable energy. In many parts of the world and specifically in Tunisia, the direct solar radiation is considered to be one of the most promising sources of energy. Annual sunshine can reach 3288 kWh/m2/year be 6 kWh/m2/day. A greenhouse using means active conventional heating consumes 1 litter of fuel/m2/year which leads to 10 kWh/m2/year. Tunisia surface of greenhouse crops is about 1000 hectares this corresponds to 107 l of foil and 108 kWh .In order to reduce the cost of heating the agricultural greenhouse we used the vacuum solar collectors .Their efficiency depends at the same time upon the ambient climatic conditions and the thermal performances of vacuum solar collectors. Capillary polypropylene exchangers are used to attenuate the differences between the diurnal and nocturnal air temperatures under the tunnel greenhouses. Water circulates in these exchangers at hydraulic closed circuit. In this work we have realized an experimental study of a solar energy heating system. Two types of studies have been done. During the day the suspended exchangers recover the energy in excess for the plants comfort. This recovered energy is stored into the greenhouse ground through the buried exchangers the first one concern the functioning temperature of the heating system installed near the greenhouse and used to heat the water stocked in a tank of 300 litters. In the second type, the energy stored in the ground will be restored through the underground exchangers during the night; thermal energy already stored in the tanks is brought back by the suspended exchangers to heat the air greenhouse. In order to prove the efficiency of our system, we present thermal results relative to the effect of the heater system on the greenhouse microclimate and the agronomic results of the greenhouse culture of tomato. These results are very interesting compared to an unheated greenhouse and had a high effect on tomato quality.

The effects of diurnal temperature range on mortality and emergency department presentations in Victoria state of Australia: A time-series analysis

State of Victoria, Australia (SVA) has a wide variation of diurnal temperatures (DTR). DTR has been reported to be associated with risk of mortality and morbidity. We examined the association between exposure to DTR and risk of all-cause mortality and emergency department (ED) presentations in the SVA. We obtained data on daily counts of deaths and ED presentations, and weather data from 1 st January 2000─2019. We applied a quasi-Poisson time-series regression analysis to examine the association between daily DTR exposures and risk of mortality and ED presentations. The analyses were queried by age, sex, seasons, ED presentations triages, and departure status. Risk of mortality and ED presentation increased by 0.33% (95% CI: 0.24%–0.43%), and 0.094% (95% CI: 0.077%–0.11%) in relation to one degree increase in the daily DTR. The association between DTR and ED presentations was stronger in children (0–15 years) (0.38% [95% CI: 0.34%–0.42%]) and the elderly (75+ years) (0.34% [95% CI: 0.29%–0.39%]). Resuscitation, which was consistently accounted for the highest vulnerability to DTR variation, increased by 0.79% (95% CI: 0.60%–0.99%). This study suggests that the risk of mortality and ED presentations associates with the increase of DTR. Children, the elderly, and their caregivers need to be made aware of the health risk posed by DTR.

Reference evapotranspiration projections in Southern Spain (until 2100) using temperature-based machine learning models

This study firstly examines the performance of temperature-based machine learning models for estimating reference evapotranspiration (ET0), an essential parameter for water management in agriculture, ecosystems, and hydrology. Data from 122 Automated Weather Stations (AWS) across different regions in Southern Spain has been studied and four machine learning models have been developed and assessed: Multilayer Perceptron (MLP), Extreme Learning Machine (ELM), Random Forest (RF), and Support Vector Machine (SVM). The results indicate that all machine learning models outperform the traditional Hargreaves-Samani method in estimating ET0. Specifically, ELM performed, on average, as the best in terms of Global Performance Indicator (GPI) for those locations situated in the first region (GPI = 0.1860), while MLP outperformed the rest for those located in the second (GPI = 0,1162). Besides, the configuration using minimum, mean and maximum air temperature (Tx, Tm, Tn, respectively), the diurnal temperature range (DTR), and Extraterrestrial solar radiation features (Ra) was found to be the fittest for the second region (GPI = 0.0734) and that using Tx, Tn, Tm and Ra in the first one in (GPI = 0.1938). Once the models were validated, they were applied to future 5 km gridded projection datasets, using different Representative Concentration Pathway (RCP) scenarios, in order to estimate ET0 up to the year 2100. In general, the projected ET0 was found to increase significantly in the future, with Mann Kendall Z values that ranged from 7.11 to 10.37 in the RCP4.5 scenario and from 10.84 to 12.57 in the RCP8.5 scenario. Thus, the ET0 is expected to increase from 1300 to 1600 mm to 1500–1700 mm using the RCP4.5 and to 1900 mm using the RCP8.5 in Andalusia, with the highest increase occurring in the south coastal region. This study provides important insights into the application of machine learning models to estimate ET0 and its implications for future water management strategies.

Prediction of Oncomelania hupensis distribution in association with climate change using machine learning models

BackgroundOncomelania hupensis is the sole intermediate host of Schistosoma japonicum. Its emergence and recurrence pose a constant challenge to the elimination of schistosomiasis in China. It is important to accurately predict the snail distribution for schistosomiasis prevention and control.MethodsData describing the distribution of O. hupensis in 2016 was obtained from the Yunnan Institute of Endemic Disease Control and Prevention. Eight machine learning algorithms, including eXtreme Gradient Boosting (XGB), support vector machine (SVM), random forest (RF), generalized boosting model (GBM), neural network (NN), classification and regression trees (CART), k-nearest neighbors (KNN), and generalized additive model (GAM), were employed to explore the impacts of climatic, geographical, and socioeconomic variables on the distribution of suitable areas for O. hupensis. Predictions of the distribution of suitable areas for O. hupensis were made for various periods (2030s, 2050s, and 2070s) under different climate scenarios (SSP126, SSP245, SSP370, and SSP585).ResultsThe RF model exhibited the best performance (AUC: 0.991, sensitivity: 0.982, specificity: 0.995, kappa: 0.942) and the CART model performed the worst (AUC: 0.884, sensitivity: 0.922, specificity: 0.943, kappa: 0.829). Based on the RF model, the top six important variables were as follows: Bio15 (precipitation seasonality) (33.6%), average annual precipitation (25.2%), Bio2 (mean diurnal temperature range) (21.7%), Bio19 (precipitation of the coldest quarter) (14.5%), population density (13.5%), and night light index (11.1%). The results demonstrated that the overall suitable habitats for O. hupensis were predominantly distributed in the schistosomiasis-endemic areas located in northwestern Yunnan Province under the current climate situation and were predicted to expand north- and westward due to climate change.ConclusionsThis study showed that the prediction of the current distribution of O. hupensis corresponded well with the actual records. Furthermore, our study provided compelling evidence that the geographical distribution of snails was projected to expand toward the north and west of Yunnan Province in the coming decades, indicating that the distribution of snails is driven by climate factors. Our findings will be of great significance for formulating effective strategies for snail control.Graphical

Identifying Major Diurnal Patterns and Drivers of Surface Urban Heat Island Intensities across Local Climate Zones

Deepening the understanding of diurnal characteristics and driving mechanisms of surface urban heat islands (SUHIs) across different local climate zones (LCZs) and time scales is of great significance for guiding urban surface heat mitigation. However, a comprehensive investigation of SUHIs from the diurnal, local, multi-seasonal, and interactive perspectives remains a large gap. Here, we generalized major diurnal patterns of LCZ-based SUHI intensities (SUHIIs) throughout 2020 over the urban area of Beijing, China, based on diurnal temperature cycle modeling, block-level LCZ mapping, and hierarchical clustering. A geographical detector was then employed to explore the individual and interactive impacts of 10 morphological, socioeconomic, and meteorological factors on the multi-temporal spatial differentiations of SUHIIs. Results indicate six prevalent diurnal SUHII patterns with distinct features among built LCZ types. LCZs 4 and 5 (open high- and mid-rise buildings) predominantly display patterns one, two, and five, characterized by an afternoon increase and persistently higher values during the night. Conversely, LCZs 6, 8, and 9 (open, large, and sparsely built low-rise buildings) mainly exhibit patterns three, four, and six, with a decrease in SUHII during the afternoon and lower intensities at night. The maximum/minimum SUHIIs occur in the afternoon–evening/morning for patterns 1–3 but in the morning/afternoon for patterns 5–6. In all four seasons, the enhanced vegetation index (EVI) and gross domestic product (GDP) have the top two individual effects for daytime spatial differentiations of SUHIIs, while the air temperature (TEM) has the largest explanatory power for nighttime differentiations of SUHIIs. All factor interactions are categorized as two-factor or nonlinear enhancements, where nighttime interactions exhibit notably greater explanatory powers than daytime ones. The strongest interactions are EVI ∩ GDP (q = 0.80) during the day and TEM ∩ EVI (q = 0.86) at night. The findings of this study contribute to an improved interpretation of the diurnal continuous dynamics of local SUHIIs in response to various environmental conditions.

Association between air temperature and risk of hospitalization for genitourinary disorders: An environmental epidemiological study in Lanzhou, China.

The aim of this study was to investigate the relationship between air temperature and the risk of hospitalization for genitourinary disorders. Distributed lag non-linear models (DLNM) were used to estimate the association between air temperature and the risk of hospitalization for genitourinary disorders, with subgroup analysis by gender and age to identify the susceptible population of temperature-sensitive genitourinary system diseases. Low mean temperature (MT) (RR = 2.001, 95% CI: 1.856~2.159), high MT (RR = 2.884, 95% CI: 2.621~3.173) and low diurnal temperature range (DTR) (RR = 1.619, 95% CI: 1.508~1.737) were all associated with the increased risk of hospitalization for genitourinary disorders in the total population analysis, and the high MT effect was stronger than the low MT effect. Subgroup analysis found that high MT was more strongly correlated in male (RR = 2.998, 95% CI: 2.623~3.427) and those <65 years (RR = 3.003, 95% CI: 2.670~3.344), and low DTR was more strongly correlated in female (RR = 1.669, 95% CI: 1.510~1.846) and those <65 years (RR = 1.643, 95% CI: 1.518~1.780). The effect of high MT on the risk of hospitalization for genitourinary disorders is more significant than that of low MT. DTR was independently associated with the risk of hospitalization for genitourinary disorders.

Generating 60–100 m, hourly, all-weather land surface temperatures based on the Landsat, ECOSTRESS, and reanalysis temperature combination (LERC)

Satellite-derived land surface temperatures (LSTs) often encounter a tradeoff between spatial and temporal resolutions, as well as severe cloud contamination. While extensive efforts have focused on resolution enhancement and under-cloud reconstruction, generating fine-resolution (≤100 m) diurnal LSTs under all-weather conditions remains a challenge, which hampers fine-scale monitoring of climatological, hydrological, and ecological processes. The latest 70-m ECOSTRESS observations at varying times of day provide an unprecedented opportunity for detailed mapping of diurnal LST dynamics, and reanalysis products with spatiotemporal continuity offer promising references for all-weather thermal dynamics. However, these advantages have rarely been integrated to concurrently achieve high spatiotemporal resolution and completeness. Here, we present a simple yet effective framework for reconstructing 60–100 m, hourly, all-weather LSTs based on the Landsat, ECOSTRESS and Reanalysis temperature Combination (termed LERC). The framework involves three steps: (i) preliminary under-cloud estimations within annual cycles of several times by fitting an enhanced annual temperature cycle (EATC) model to clear Landsat/ECOSTRESS scenes and China Land Data Assimilation System (CLDAS) LST fluctuations; (ii) optimized daily estimations at each selected time by correcting biases of the preliminary under-cloud estimations and re-modeling the EATC with temporally densified samples; and (iii) hourly seamless estimations by interpolating the two nearest daily estimations with reference to the weighted diurnal changes in CLDAS. LERC was evaluated in an urban-dominated region throughout 2020, resulting in an average root-mean-squared-error of 2.0 K (3.0 K) against 50 Landsat and ECOSTRESS images (hourly ground measurements at 13 sites). Compared to the enhanced spatial and temporal adaptive reflectance fusion model, classic ATC model, diurnal temperature cycle model, and three sophisticated all-weather products, LERC demonstrates outperformance in terms of general accuracy, spatiotemporal variability, and robustness against sparse input. LERC has great potentials for generating long-term reliable all-weather LST records with a high spatiotemporal resolution to promote broad applications.