Studying the causes of summer(June–July–August)precipitation anomalies in the middle and lower reaches of the Yangtze River(MLYR)and accurately predicting rainy season precipitation are important to society and the ...Studying the causes of summer(June–July–August)precipitation anomalies in the middle and lower reaches of the Yangtze River(MLYR)and accurately predicting rainy season precipitation are important to society and the economy.In recent years,the sea surface temperature(SST)trend factor has been used to construct regression models for summer precipitation.In this study,through correlation analysis,winter SST anomaly predictors and the winter Central Pacific SST trend predictor(CPT)are identified as closely related to the following MLYR summer precipitation(YRSP).CPT can influence YRSP by inducing anomalous circulations over the North Pacific,guiding warm and moist air northward,and inhibiting the development of the anomalous anticyclone over the Northwest Pacific.This has improved the predictive skill of the seasonal regression model for YRSP.After incorporating the CPT,the correlation coefficient of the YRSP regression model improved by 40%,increasing from 0.45 to 0.63,and the root mean squared error decreased by 22%,from 1.15 to 0.90.展开更多
Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimila...Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimilation is quite challenging.This is because there is limited knowledge about the cross-component background error covariance(BEC)between LST and atmospheric state variables.This study aims to clarify whether there is a relationship between the error of LST and atmospheric variables,and whether this relationship varies spatially and temporally.To this end,the BEC coupled with atmospheric variables and LST was constructed(LST-BEC),and its characteristics were analyzed based on the 2023 mei-yu season.The general characteristics of LST-BEC show that the LST is mainly correlated with the atmospheric temperature and the correlation decreases gradually with a rise in atmospheric height,and the error standard deviation of the LST is noticeably larger than that of the low-level atmospheric temperature.The spatiotemporal characteristics of LST-BEC on the heavy-rain day and light-rain day show that the error correlation and error standard deviation of LST and low-level atmospheric temperature and humidity are closely related to the weather background,and also have obvious diurnal variations.These results provide valuable information for strongly coupled land-atmosphere assimilation.展开更多
The stratospheric Arctic vortex(SAV)plays a critical role in forecasting cold winters in the northern midlatitudes.In this study,we systematically examined the responses of SAV intensity to regional sea surface temper...The stratospheric Arctic vortex(SAV)plays a critical role in forecasting cold winters in the northern midlatitudes.In this study,we systematically examined the responses of SAV intensity to regional sea surface temperature(SST)changes using idealized SST patch experiments with a climate model.Our findings reveal that the SAV intensity is most sensitive to SST variations in the tropics and northern midlatitudes during boreal winter(December-January-February).Specifically,warming in the tropical Pacific and Atlantic leads to a weakening of the SAV,while warming in the tropical Indian Ocean,northern midlatitude Atlantic,and northwestern Pacific strengthens the SAV.Notably,the most substantial SAV weakening(strengthening)is triggered by warming in the tropical western Pacific(tropical central Indian Ocean),with a maximum magnitude of approximately 2.23 K K^(-1)(-1.77 K K^(-1)).The SST warming in the tropics influences the tropical convections,which excite Rossby wave trains.These wave trains can interfere with the climatological waves in the mid-high latitudes,while the SST warming in the northern midlatitudes can influence tropospheric planetary wavenumber-1 and wavenumber-2 directly.The changes in tropospheric planetary waves modulate the upward propagation of wave activities and impact the SAV intensity.Additionally,the response of the SAV to tropical SST changes,especially over the Indian Ocean and subtropics,exhibits significant nonlinearity.展开更多
With the continuous evolution of urban surface types,the impact of the urban heat island effect on the human population has intensified.Investigating the factors influencing urban thermal environments is crucial for p...With the continuous evolution of urban surface types,the impact of the urban heat island effect on the human population has intensified.Investigating the factors influencing urban thermal environments is crucial for providing theoretical support to urban planning and decision-making.In this study,Shenyang was selected to comprehensively analyse multiple factors,including topography,human activity,vegetation and landscape.Moreover,we used the random forest algorithm to explore nonlinear factors influencing land surface temperature(LST)over four years in the study area.The results revealed that from 2005 to 2020,the total areas with sub-high and high-temperature zones in northern Shenyang steadily increased.The area ratio of these zones increased from 20.18% in 2005 to 24.86% in 2020.Additionally,significant and strong correlations were observed between LST and variables such as the enhanced vegetation index(EVI),normalised difference vegetation index(NDVI),population density,proportion of cropland and proportion of impervious land.In 2010,proportion of impervious land exhibited the strongest correlation with LST at the 5 km scale,reaching 0.852(p<0.01).The 4 km grid scale was identified as the optimal grid size for this study,while the 2 km grid performed the worst.In 2020,NDVI emerged as the most significant factor influencing LST.These findings provide valuable guidance for improving urban planning and developing sustainable strategies.展开更多
The early life stages of marine organisms are pivotal in shaping community dynamics and resource availability.In this study,we focused on Portunus trituberculatus,a crustacean integral to China's fisheries economy...The early life stages of marine organisms are pivotal in shaping community dynamics and resource availability.In this study,we focused on Portunus trituberculatus,a crustacean integral to China's fisheries economy,and examined the effect of sea surface temperature(SST)in its critical early life stages on subsequent yields.To analyze the correlation between SST in different larval stages and the corresponding yield of P.trituberculatus,we simulated the transport and distribution of larvae from 2014 to 2022 by employing circulation models and Lagrangian particle tracking experiments(LPTE).In the five years(2014,2015,2016,2019,and 2020),particles were transported in a northwestern direction and moved in the direction of low SST.The distribution of particles in the megalopa stage(M stage)were located in the region of the lower temperature.In 2017,2018,and 2021,the particles were transported in a northeastern direction but they did not move with the gradient of low SST in these years,and the particles in the last M stage were located in the region where the SST was at the peak of the time period.In 2022,the distribution was observed for most of the particles in the southwestern part of Zhejiang coast,a small part of them were transported in the northwestern direction and a small amount of particles was distributed offshore along the northern area of the Zhejiang coast.The correlations between the SST at each stage of larvae with the corresponding year's yield showed that the yield of P.trituberculatus decreased significantly(R=-0.772,P=0.015)with increasing SST at the M stage.This study preliminarily explains the correlation between SST at the larval stage and the yield of P.trituberculatus and provides essential information for scientific stock enhancement in the future.展开更多
Land–atmosphere coupling and sea surface temperature(SST)anomalies both have essential impacts on weather and climate extremes.Based on the ERA5 reanalysis dataset and the CESM1.2.2 model,this study investigates the ...Land–atmosphere coupling and sea surface temperature(SST)anomalies both have essential impacts on weather and climate extremes.Based on the ERA5 reanalysis dataset and the CESM1.2.2 model,this study investigates the influence of land–atmosphere coupling on summer extreme hot-humid events(EHHE)over southern Eurasia under different SST backgrounds.The results suggest that coupling causes near-surface air temperature increases that exceed 0.5℃.From 1961 to 2020,the frequency of EHHE has continuously increased,and is closely related to soil moisture anomalies in the northern Indian Peninsula(IDP)and the middle and lower reaches of the Yangtze River(YRB).Numerical simulations further demonstrate that land–atmosphere coupling raises the risk of EHHE by 25.4%.In a typical El Niño SST background state,intensified land–atmosphere coupling tends to produce notable increases in the frequency of EHHE.The dominant processes that land–atmosphere coupling affects the EHHE variations are evidently different between these two regions.Land surface thermal anomalies predominate in the IDP,while moisture conditions are more critical in the YRB.When warm SST anomalies exist,dry soil anomalies in the IDP are prominent,and evaporation is constrained,increasing sensible heat flux.Positive geopotential height anomalies are significant,combined with adiabatic warming induced by descending motion and a noticeable warm center in the near-surface atmosphere.The southward shift of the westerly jet enhances divergence over YRB.The anticyclonic circulation anomalies over the western Pacific are conducive to guiding moisture transport to the YRB,providing a favorable circulation background for the development of summer EHHE.展开更多
Climate change is significantly influenced by both clouds and Earth’s surface temperature(EST).While numerous studies have investigated clouds and EST separately,the extent of clouds’impact on EST remains unclear.Ba...Climate change is significantly influenced by both clouds and Earth’s surface temperature(EST).While numerous studies have investigated clouds and EST separately,the extent of clouds’impact on EST remains unclear.Based on the inspiration and limitation of cloud radiative effect(CRE),this study provides a pioneering attempt to propose a novel indicator,cloud radiative effect on surface temperature(CREST),aiming to quantify how clouds affect EST globally while also analyzing the physical mechanism.Using reanalysis and remotely sensed data,a phased machine learning scheme in combination of surface energy balance theory is proposed to estimate EST under all-sky and hypothetical clear-sky conditions in stages,thereby estimating the newly defined CREST by subtracting the hypothetical clear-sky EST from the all-sky EST.The inter-annual experiments reveal the significant spatial heterogeneity in CREST across land,ocean,and ice/snow regions.As a global offset of the heterogeneity,clouds exhibit a net warming effect on global surface temperature on an annual scale(e.g.,0.26 K in 1981),despite their ability to block sunlight.However,the net warming effect has gradually weakened to nearly zero over the past four decades(e.g.,only 0.06 K in 2021),and it’s even possible to transform into a cooling effect,which might be good news for mitigating the global warming.展开更多
This study explores the impact of the tropical sea surface temperature(SST) independent of the preceding winter El Nino–Southern Oscillation(ENSO) events(ENSO-independent SST) on the interannual variability of the So...This study explores the impact of the tropical sea surface temperature(SST) independent of the preceding winter El Nino–Southern Oscillation(ENSO) events(ENSO-independent SST) on the interannual variability of the South China Sea Summer Monsoon(SCSSM) and the associated mechanisms. During summer, the ENSO-independent SST component dominates across tropical ocean regions. The tropical ENSO-independent SSTs during spring and summer in the Maritime Continent(MC), the equatorial central-eastern Pacific(CEP), and the tropical Atlantic Ocean(TAO) regions play a comparably significant role in the interannual variation of the SCSSM intensity, compared to the tropical SST dependent on the preceding winter ENSO. The ENSO-independent SST anomalies(SSTA) in the TAO during spring and summer exhibit significant persistence. They can influence the SCSSM through westward propagation of teleconnection, as well as through eastward-propagating Kelvin waves. In summer, the SSTA in the MC, CEP, and TAO regions contribute jointly to the variability of the SCSSM. The MC SSTA affects local convection and generates anomalous meridional circulation to impact the SCSSM intensity. The CEP SSTA directly influences the SCSSM via the Matsuno-Gill response mechanism and indirectly affects it via meridional circulation by modulating vertical motions over the MC through zonal circulation. The TAO SSTA impacts the SCSSM through both westward and eastward pathways, as well as by influencing zonal circulation patterns in the tropical and subtropical North Pacific. The results offer valuable insights into the factors influencing the interannual variability of the SCSSM intensity.展开更多
In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming ...In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.展开更多
Land surface temperature(LST) directly affects the energy balance of terrestrial surface systems and impacts regional resources, ecosystem evolution, and ecosystem structures. Xinjiang Uygur Autonomous Region is locat...Land surface temperature(LST) directly affects the energy balance of terrestrial surface systems and impacts regional resources, ecosystem evolution, and ecosystem structures. Xinjiang Uygur Autonomous Region is located at the arid Northwest China and is extremely sensitive to climate change. There is an urgent need to understand the distribution patterns of LST in this area and quantitatively measure the nature and intensity of the impacts of the major driving factors from a spatial perspective, as well as elucidate the formation mechanisms. In this study, we used the MOD11C3 LST product developed on the basis of Moderate Resolution Imaging Spectroradiometer(MODIS) to conduct regression analysis and determine the spatiotemporal variation and differentiation pattern of LST in Xinjiang from 2000 to 2020. We analyzed the driving mechanisms of spatial heterogeneity of LST in Xinjiang and the six geomorphic zones(the Altay Mountains, Junggar Basin, Tianshan Mountains, Tarim Basin, Turpan-Hami(Tuha) Basin, and Pakakuna Mountain Group) using geographical detector(Geodetector) and geographically weighted regression(GWR) models. The warming rate of LST in Xinjiang during the study period was 0.24℃/10a, and the spatial distribution pattern of LST had obvious topographic imprints, with 87.20% of the warming zone located in the Gobi desert and areas with frequent human activities, and the cooling zone mainly located in the mountainous areas. The seasonal LST in Xinjiang was at a cooling rate of 0.09℃/10a in autumn, and showed a warming trend in other seasons. Digital elevation model(DEM), latitude, wind speed, precipitation, normalized difference vegetation index(NDVI), and sunshine duration in the single-factor and interactive detections were the key factors driving the LST changes. The direction and intensity of each major driving factor on the spatial variations of LST in the study area were heterogeneous. The negative feedback effect of DEM on the spatial differentiation of LST was the strongest. Lower latitudes, lower vegetation coverage, lower levels of precipitation, and longer sunshine duration increased LST. Unused land was the main heat source landscape, water body was the most important heat sink landscape, grassland and forest land were the land use and land cover(LULC) types with the most prominent heat sink effect, and there were significant differences in different geomorphic zones due to the influences of their vegetation types, climatic conditions, soil types, and human activities. The findings will help to facilitate sustainable climate change management, analyze local climate and environmental patterns, and improve land management strategies in Xinjiang and other arid areas.展开更多
Ocean productivity is the foundation of marine food web,which continuously removes atmospheric carbon dioxide and supports life at sea and on land.Spatio-temporal variability of net primary productivity(NPP),sea surfa...Ocean productivity is the foundation of marine food web,which continuously removes atmospheric carbon dioxide and supports life at sea and on land.Spatio-temporal variability of net primary productivity(NPP),sea surface temperature(SST),sea surface salinity(SSS),mixed layer depth(MLD),and euphotic zone depth(EZD) in the northern B ay of Bengal(BoB) during three monsoon seasons were examined in this study based on remote sensing data for the period 2005 to 2020.To compare the NPP distribution between the coastal zones and open BoB,the study area was divided into five zones(Z1-Z5).Results suggest that most productive zones Z2 and Zl are located at the head bay area and are directly influenced by freshwater discharge together with riverine sediment and nutrient loads.Across Z1-Z5,the NPP ranges from 5 315.38 mg/(m^(2)·d) to 346.7 mg/(m^(2)·d)(carbon,since then the same).The highest monthly average NPP of 5 315.38 mg/(m^(2)·d) in February and 5 039.36 mg/(m^(2)·d) in June were observed from Z2,while the lowest monthly average of 346.72 mg/(m^(2)·d) was observed in March from Z4,which is an oceanic zone.EZD values vary from 6-154 m for the study area,and it has an inverse correlation with NPP concentration.EZD is deeper during the summer season and shallower during the wintertime,with a corresponding increase in productivity.Throughout the year,monthly SST shows slight fluctuation for the entire study area,and statistical analysis shows a significant correlation among NPP,and EZD,overall positive between NPP and MLD,whereas no significant correlation among SSS,and SST for the northern BoB.Long-term trends in SST and productivity were significantly po sitive in head bay zones but negatively productive in the open ocean.The findings in this study on the distribution of NPP,SST,SSS,MLD,and EZD and their seasonal variability in five different zones of BoB can be used to further improve the management of marine resources and overall environmental condition in response to climate changes in BoB as they are of utmost relevance to the fisheries for the three bordering countries.展开更多
Urban expansion of cities has caused changes in land use and land cover(LULC)in addition to transformations in the spatial characteristics of landscape structure.These alterations have generated heat islands and rise ...Urban expansion of cities has caused changes in land use and land cover(LULC)in addition to transformations in the spatial characteristics of landscape structure.These alterations have generated heat islands and rise of land surface temperature(LST),which consequently have caused a variety of environmental issues and threated the sustainable development of urban areas.Greenbelts are employed as an urban planning containment policy to regulate urban expansion,safeguard natural open spaces,and serve adaptation and mitigation functions.And they are regarded as a powerful measure for enhancing urban environmental sustainability.Despite the fact that,the relation between landscape structure change and variation of LST has been examined thoroughly in many studies,but there is a limitation concerning this relation in semi-arid climate and in greenbelts as well,with the lacking of comprehensive research combing both aspects.Accordingly,this study investigated the spatiotemporal changes of landscape pattern of LULC and their relationship with variation of LST within an inner greenbelt in the semi-arid Erbil City of northern Iraq.The study utilized remote sensing data to retrieve LST,classified LULC,and calculated landscape metrics for analyzing spatial changes during the study period.The results indicated that both composition and configuration of LULC had an impact on the variation of LST in the study area.The Pearson's correlation showed the significant effect of Vegetation 1 type(VH),cultivated land(CU),and bare soil(BS)on LST,as increase of LST was related to the decrease of VH and the increases of CU and BS,while,neither Vegetation 2 type(VL)nor built-up(BU)had any effects.Additionally,the spatial distribution of LULC also exhibited significant effects on LST,as LST was strongly correlated with landscape indices for VH,CU,and BS.However,for BU,only aggregation index metric affected LST,while none of VL metrics had a relation.The study provides insights for landscape planners and policymakers to not only develop more green spaces in greenbelt but also optimize the spatial landscape patterns to reduce the influence of LST on the urban environment,and further promote sustainable development and enhance well-being in the cities with semi-arid climate.展开更多
The aim of our study was to examine the contribution of surface waves from WAVEWATCH-III(WW3)to the variation in sea surface temperature(SST)in the Arctic Ocean.The simulated significant wave height(SWH)were validated...The aim of our study was to examine the contribution of surface waves from WAVEWATCH-III(WW3)to the variation in sea surface temperature(SST)in the Arctic Ocean.The simulated significant wave height(SWH)were validated against the products from Haiyang-2B(HY-2B)in 2021,obtaining a root mean squared error(RMSE)of 0.45 with a correlation of 0.96 and scatter index of 0.18.The wave-induced effects,i.e.,wave breaking and mixing induced by nonbearing waves resulting in changes in radiation stress and Stokes drift,were calculated from WW3,ERA-5 wind,SST,and salinity data from the National Centers for Environmental Prediction and were taken as forcing fields in the Stony Brook Parallel Ocean Model.The results showed that an RMSE of 0.81℃ with wave-induced effects was less than the RMSE of 1.11℃ achieved without the wave term compared with the simulated SST with the measurements from Argos.Considering the four wave effects and sea ice freezing,the SST in the Arctic Ocean decreased by up to 1℃ in winter.Regression analysis revealed that the SWH was linear in SST(values without subtraction of waves)in summer and autumn,but this behavior was not observed in spring or winter due to the presence of sea ice.The interannual variation also presented a negative relationship between the difference in SST and SWH.展开更多
The aim of this study is to investigate the sea surface temperature(SST) cooling as typhoons pass the Kuroshio Current.A numerical circulation model,denoted as the Stony Brook Parallel Ocean Model(sbPOM),was used to s...The aim of this study is to investigate the sea surface temperature(SST) cooling as typhoons pass the Kuroshio Current.A numerical circulation model,denoted as the Stony Brook Parallel Ocean Model(sbPOM),was used to simulate the SST,which includes four wave-induced effect terms(i.e.,radiation stress,nonbreaking waves,Stokes drift,and breaking waves) simulated using the third-generation wave model,called WAVEWATCH-Ⅲ(WW3).The significant wave height(SWH) measurements from the Jason-2 altimeter were used to validate the WW3-simulated results,yielding a root mean square error(RMSE) of less than 0.50 m and a correlation coefficient(COR) of approximately 0.93.The water temperature measured from the Advanced Research and Global Observation Satellite was applied to validate the model simulation.Accordingly,the RMSE of the SST is 0.92℃ with a COR of approximately 0.99.As revealed in the sbPOM-simulated SST fields,a reduction in the SST at the Kuroshio Current region was observed as a typhoon passed,although the water temperature of the Kuroshio Current is relatively high.The variation of the SST is consistent with that of the current,whereas the maximum SST lagged behind the occurrence of the peak SWH.Moreover,the Stokes drift plays an important role in the SST cooling after analyzing four wave-induced terms in the background of the Kuroshio Current.The sensitivity experiment also showed that the accuracy of the water temperature was significantly reduced when including breaking waves,which play a negative role in the inside part of the ocean.The variation in the mean mixing layer depth(MLD) showed that a typhoon could enhance the mean MLD in the Kuroshio Current area in September and October,whereas a typhoon has little influence on the mean MLD in the Kuroshio Current area in May.Moreover,the mean MLD rapidly decreased with the weakening of the strong wind force and wave-induced effects when a typhoon crossed the Kuroshio Current.展开更多
The significance of land surface temperature(LST)and near-surface air temperature(TAIR)extends to various applications,including the exploration of urban heat islands.Understanding urban heat islands is crucial for co...The significance of land surface temperature(LST)and near-surface air temperature(TAIR)extends to various applications,including the exploration of urban heat islands.Understanding urban heat islands is crucial for comprehending the intricate interactions among urbanization,climate dynamics,and human well-being.However,many aspects of these topics remain understudied.In this study,we conducted a comprehensive analysis of LST and TAIR,covering day and night and spanning all four seasons of a full year.We used global datasets and applied non-spatial and spatial analysis techniques in the Amman-Zarqa urban region,a typical arid to semiarid environment.The study had three primary objectives:(1)Assess how different human settlement types influence the variations in LST and TAIR across space and time.(2)Examine the spatial and temporal attributes of the relationships between TAIR and LST.(3)Synthesize insights regarding the spatial and temporal characteristics of urban heat islands in arid to semiarid environments.The findings unveiled that urban centers consistently exhibit the lowest daytime LST and maximum and minimum TAIR,across all seasons when compared to other human settlement types.Nighttime LST displayed more variable patterns.Urban centers act as surface urban cool islands during the day and canopy layer urban cool islands both day and night throughout the seasons.The presence of surface urban heat or cool islands at night is barely noticeable.Daytime and nighttime LST play a significant role in explaining the variability in maximum and minimum TAIR across all seasons,with the relationships exhibiting variations ranging from positive to non-significant to negative,influenced by location and seasonal changes.During the daytime,LST consistently exceeds TAIR across all seasons,whereas this relationship displays greater variability at night.The findings of this study hold significant implications for sustainable urban planning and efforts to combat the effects of urban heat islands.展开更多
The need for cross-comparison and validation of all-weather Land Surface Temperature(LST)products has arisen due to the release of multiple such products aimed at providing comprehensive all-weather monitoring capabil...The need for cross-comparison and validation of all-weather Land Surface Temperature(LST)products has arisen due to the release of multiple such products aimed at providing comprehensive all-weather monitoring capabilities.In this study,we focus on validating two well-established all-weather LST products(i.e.MLST-AS and TRIMS LST)against in-situ measurements obtained from four high-quality LST validation sites:Evora,Gobabeb,KIT-Forest,and Lake Constance.For the land sites,MLST-AS exhibits better accuracy,with RMSEs ranging from 1.6 K to 2.1 K,than TRIMS LST,the RMSEs of which range from 1.9 K to 3.1 K.Because MLST-AS pixels classified as“inland water”are masked out,the validation over Lake Constance is limited to TRIMS LST:it yields a RMSE of 1.6 K.Furthermore,the validation results show that MLST-AS and TRIMS LST exhibit better accuracy under clear-sky conditions than unclear-sky conditions across all sites.Since the accuracy of the all-weather LST products is considerably affected by the input clear-sky LST products,we further compare the all-weather LST with the corresponding input clear-sky LST to conduct an error source analysis.Considering the clear-sky pixels on MLST-AS directly using the estimates from MLST,the error source analysis is limited to examining TRIMS LST and its input(i.e.MODIS LST).The findings indicate that TRIMS LST is highly correlated with MODIS LST.The investigation and validation of the two selected all-weather LST products objectively evaluate their accuracy and stability,which provides important information for applications of these all-weather LST products.展开更多
Geothermal energy is a renewable and environmentally sustainable resource of increasing importance.However,areas with geothermal potential are not easily detected by traditional field investigations,requiring the deve...Geothermal energy is a renewable and environmentally sustainable resource of increasing importance.However,areas with geothermal potential are not easily detected by traditional field investigations,requiring the development of new,robust,and reliable models for detection.In this study,remote sensing data and ground-based variables were used to detect and analyze geothermal resource potential areas.General Land Surface Temperature(GLST)was integrated using 5 years of remote sensing data.Landsat 8 daytime GLST(Landsat-GLST),Moderate Resolution Imaging Spectroradiometer(MODIS)daytime GLST(MODIS-DLST),and MODIS nighttime GLST(MODIS-NLST)data were integrated with Landsat Nighttime Land Surface Temperature(Night-LST),which not only filled the gap of Landsat Night-LST but also improved the spatial resolution of MODIS nighttime temperatures.Specifically,three independent variables(Night-LST,Distance From Known Geothermal Resource Points[DFGP],and Distance From Geological Faults[DFF])were used to develop a weighted model to form a Geothermal Detection Index(GDI)based on Principal Component Analysis(PCA).Along with field verification,the GDI was successfully used to identify three geothermal activity areas in Tengchong City,Yunnan Province.Overall,this work provides a novel method for detecting geothermal potential to support the successful exploitation of geothermal resources.展开更多
Information is given on thermal radiation from the Sun, considered in practical engineering calculations of heat exchange. It was found that although the surface temperature of the Sun is assumed to be about 5800 K, t...Information is given on thermal radiation from the Sun, considered in practical engineering calculations of heat exchange. It was found that although the surface temperature of the Sun is assumed to be about 5800 K, the solar spectrum data measured by Kondratyev lead to a value of at least 7134 K. Such a higher value can be obtained by interpreting the Planck formula for the black radiation spectrum for the Kondratyev data. In addition, using the Stefan-Boltzmann law, the energetic emissivity of the Sun’s surface was determined to be 0.431. Furthermore, based on Petela’s formulae for exergy of thermal radiation, the exergetic emissivity of the Sun’s surface was also calculated at the level of 0.426.展开更多
The East African short rainy season (October-November-December) is one of the major flood seasons in the East African region. The amount of rainfall during the short rainy season is closely related to the lives of the...The East African short rainy season (October-November-December) is one of the major flood seasons in the East African region. The amount of rainfall during the short rainy season is closely related to the lives of the people and the socio-economic development of the area. By using precipitation data and sea surface temperature data, this study reveals the spatial and temporal variation patterns of extreme precipitation during the East African short rainy season. Key findings include significant rainfall variability, with Tanzania experiencing the highest amounts in December due to the southward shift of the Intertropical Convergence Zone (ITCZ), while other regions receive less than 100 mm. Extreme rainfall events (90th percentiles) are evenly distributed, averaging 2 to 10 days annually. Historical data shows maximum seasonal rainfall often peaks at 15 mm, with frequent occurrences of daily rainfall exceeding 10 mm during OND. Additionally, a positive correlation (0.48) between OND precipitation extremes and Indian Ocean Dipole (IOD) anomalies is statistically significant. These findings highlight the climatic variability and potential trends in extreme rainfall events in East Africa, providing valuable insights for regional climate adaptation strategies.展开更多
The Alborz Mountains are some of the highest in Iran,and they play an important role in controlling the climate of the country’s northern regions.The land surface temperature(LST)is an important variable that affects...The Alborz Mountains are some of the highest in Iran,and they play an important role in controlling the climate of the country’s northern regions.The land surface temperature(LST)is an important variable that affects the ecosystem of this area.This study investigated the spatiotemporal changes and trends of the nighttime LST in the western region of the Central Alborz Mountains at elevations of 1500-4000 m above sea level.MODIS data were extracted for the period of 2000-2021,and the Mann-Kendall nonparametric test was applied to evaluating the changes in the LST.The results indicated a significant increasing trend for the monthly average LST in May-August along the southern aspect.Both the northern and southern aspects showed decreasing trends for the monthly average LST in October,November,and March and an increasing trend in other months.At all elevations,the average decadal change in the monthly average LST was more severe along the southern aspect(0.60°C)than along the northern aspect(0.37°C).The LST difference between the northern and southern aspects decreased in the cold months but increased in the hot months.At the same elevation,the difference in the lapse rate between the northern and southern aspects was greater in the hot months than in the cold months.With increasing elevation,the lapse rate between the northern and southern aspects disappeared.Climate change was concluded to greatly decrease the difference in LST at different elevations for April-July.展开更多
基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)National Natural Science Foundation of China(42175061)。
文摘Studying the causes of summer(June–July–August)precipitation anomalies in the middle and lower reaches of the Yangtze River(MLYR)and accurately predicting rainy season precipitation are important to society and the economy.In recent years,the sea surface temperature(SST)trend factor has been used to construct regression models for summer precipitation.In this study,through correlation analysis,winter SST anomaly predictors and the winter Central Pacific SST trend predictor(CPT)are identified as closely related to the following MLYR summer precipitation(YRSP).CPT can influence YRSP by inducing anomalous circulations over the North Pacific,guiding warm and moist air northward,and inhibiting the development of the anomalous anticyclone over the Northwest Pacific.This has improved the predictive skill of the seasonal regression model for YRSP.After incorporating the CPT,the correlation coefficient of the YRSP regression model improved by 40%,increasing from 0.45 to 0.63,and the root mean squared error decreased by 22%,from 1.15 to 0.90.
基金sponsored by the National Natural Science Foundation of China[grant number U2442218]。
文摘Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimilation is quite challenging.This is because there is limited knowledge about the cross-component background error covariance(BEC)between LST and atmospheric state variables.This study aims to clarify whether there is a relationship between the error of LST and atmospheric variables,and whether this relationship varies spatially and temporally.To this end,the BEC coupled with atmospheric variables and LST was constructed(LST-BEC),and its characteristics were analyzed based on the 2023 mei-yu season.The general characteristics of LST-BEC show that the LST is mainly correlated with the atmospheric temperature and the correlation decreases gradually with a rise in atmospheric height,and the error standard deviation of the LST is noticeably larger than that of the low-level atmospheric temperature.The spatiotemporal characteristics of LST-BEC on the heavy-rain day and light-rain day show that the error correlation and error standard deviation of LST and low-level atmospheric temperature and humidity are closely related to the weather background,and also have obvious diurnal variations.These results provide valuable information for strongly coupled land-atmosphere assimilation.
基金the financial support of National Key Research and Development Program of China(No.2022YFF0801701)National Natural Science Foundation of China(Grants 42375070)。
文摘The stratospheric Arctic vortex(SAV)plays a critical role in forecasting cold winters in the northern midlatitudes.In this study,we systematically examined the responses of SAV intensity to regional sea surface temperature(SST)changes using idealized SST patch experiments with a climate model.Our findings reveal that the SAV intensity is most sensitive to SST variations in the tropics and northern midlatitudes during boreal winter(December-January-February).Specifically,warming in the tropical Pacific and Atlantic leads to a weakening of the SAV,while warming in the tropical Indian Ocean,northern midlatitude Atlantic,and northwestern Pacific strengthens the SAV.Notably,the most substantial SAV weakening(strengthening)is triggered by warming in the tropical western Pacific(tropical central Indian Ocean),with a maximum magnitude of approximately 2.23 K K^(-1)(-1.77 K K^(-1)).The SST warming in the tropics influences the tropical convections,which excite Rossby wave trains.These wave trains can interfere with the climatological waves in the mid-high latitudes,while the SST warming in the northern midlatitudes can influence tropospheric planetary wavenumber-1 and wavenumber-2 directly.The changes in tropospheric planetary waves modulate the upward propagation of wave activities and impact the SAV intensity.Additionally,the response of the SAV to tropical SST changes,especially over the Indian Ocean and subtropics,exhibits significant nonlinearity.
基金National Natural Science Foundation of China,No.42204031。
文摘With the continuous evolution of urban surface types,the impact of the urban heat island effect on the human population has intensified.Investigating the factors influencing urban thermal environments is crucial for providing theoretical support to urban planning and decision-making.In this study,Shenyang was selected to comprehensively analyse multiple factors,including topography,human activity,vegetation and landscape.Moreover,we used the random forest algorithm to explore nonlinear factors influencing land surface temperature(LST)over four years in the study area.The results revealed that from 2005 to 2020,the total areas with sub-high and high-temperature zones in northern Shenyang steadily increased.The area ratio of these zones increased from 20.18% in 2005 to 24.86% in 2020.Additionally,significant and strong correlations were observed between LST and variables such as the enhanced vegetation index(EVI),normalised difference vegetation index(NDVI),population density,proportion of cropland and proportion of impervious land.In 2010,proportion of impervious land exhibited the strongest correlation with LST at the 5 km scale,reaching 0.852(p<0.01).The 4 km grid scale was identified as the optimal grid size for this study,while the 2 km grid performed the worst.In 2020,NDVI emerged as the most significant factor influencing LST.These findings provide valuable guidance for improving urban planning and developing sustainable strategies.
基金Supported by the National Key Research and Development Program of China(No.2019YFD0901304)the Public Welfare Technology Application Research Project of Zhejiang(No.LGN21C190009)the Science and Technology Project of Zhoushan(No.2022C41003)。
文摘The early life stages of marine organisms are pivotal in shaping community dynamics and resource availability.In this study,we focused on Portunus trituberculatus,a crustacean integral to China's fisheries economy,and examined the effect of sea surface temperature(SST)in its critical early life stages on subsequent yields.To analyze the correlation between SST in different larval stages and the corresponding yield of P.trituberculatus,we simulated the transport and distribution of larvae from 2014 to 2022 by employing circulation models and Lagrangian particle tracking experiments(LPTE).In the five years(2014,2015,2016,2019,and 2020),particles were transported in a northwestern direction and moved in the direction of low SST.The distribution of particles in the megalopa stage(M stage)were located in the region of the lower temperature.In 2017,2018,and 2021,the particles were transported in a northeastern direction but they did not move with the gradient of low SST in these years,and the particles in the last M stage were located in the region where the SST was at the peak of the time period.In 2022,the distribution was observed for most of the particles in the southwestern part of Zhejiang coast,a small part of them were transported in the northwestern direction and a small amount of particles was distributed offshore along the northern area of the Zhejiang coast.The correlations between the SST at each stage of larvae with the corresponding year's yield showed that the yield of P.trituberculatus decreased significantly(R=-0.772,P=0.015)with increasing SST at the M stage.This study preliminarily explains the correlation between SST at the larval stage and the yield of P.trituberculatus and provides essential information for scientific stock enhancement in the future.
基金supported by the National Science Foundation of China(Grant Nos.42088101 and 42275172).
文摘Land–atmosphere coupling and sea surface temperature(SST)anomalies both have essential impacts on weather and climate extremes.Based on the ERA5 reanalysis dataset and the CESM1.2.2 model,this study investigates the influence of land–atmosphere coupling on summer extreme hot-humid events(EHHE)over southern Eurasia under different SST backgrounds.The results suggest that coupling causes near-surface air temperature increases that exceed 0.5℃.From 1961 to 2020,the frequency of EHHE has continuously increased,and is closely related to soil moisture anomalies in the northern Indian Peninsula(IDP)and the middle and lower reaches of the Yangtze River(YRB).Numerical simulations further demonstrate that land–atmosphere coupling raises the risk of EHHE by 25.4%.In a typical El Niño SST background state,intensified land–atmosphere coupling tends to produce notable increases in the frequency of EHHE.The dominant processes that land–atmosphere coupling affects the EHHE variations are evidently different between these two regions.Land surface thermal anomalies predominate in the IDP,while moisture conditions are more critical in the YRB.When warm SST anomalies exist,dry soil anomalies in the IDP are prominent,and evaporation is constrained,increasing sensible heat flux.Positive geopotential height anomalies are significant,combined with adiabatic warming induced by descending motion and a noticeable warm center in the near-surface atmosphere.The southward shift of the westerly jet enhances divergence over YRB.The anticyclonic circulation anomalies over the western Pacific are conducive to guiding moisture transport to the YRB,providing a favorable circulation background for the development of summer EHHE.
基金carried out under the co-funding of the National Natural Science Foundation of China(NSFC)project(Grant No.42022008)Zhuhai basic and applied research project(Grant No.ZH22017003200009PWC)the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(Grant No.311022003).
文摘Climate change is significantly influenced by both clouds and Earth’s surface temperature(EST).While numerous studies have investigated clouds and EST separately,the extent of clouds’impact on EST remains unclear.Based on the inspiration and limitation of cloud radiative effect(CRE),this study provides a pioneering attempt to propose a novel indicator,cloud radiative effect on surface temperature(CREST),aiming to quantify how clouds affect EST globally while also analyzing the physical mechanism.Using reanalysis and remotely sensed data,a phased machine learning scheme in combination of surface energy balance theory is proposed to estimate EST under all-sky and hypothetical clear-sky conditions in stages,thereby estimating the newly defined CREST by subtracting the hypothetical clear-sky EST from the all-sky EST.The inter-annual experiments reveal the significant spatial heterogeneity in CREST across land,ocean,and ice/snow regions.As a global offset of the heterogeneity,clouds exhibit a net warming effect on global surface temperature on an annual scale(e.g.,0.26 K in 1981),despite their ability to block sunlight.However,the net warming effect has gradually weakened to nearly zero over the past four decades(e.g.,only 0.06 K in 2021),and it’s even possible to transform into a cooling effect,which might be good news for mitigating the global warming.
基金National Natural Science Foundation of China(42175018, 42175020)Science and Technology Planning Project of Guangdong Province (2023B1212060019)+1 种基金Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)(311024001)Project supported by Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)(SML2023SP209)。
文摘This study explores the impact of the tropical sea surface temperature(SST) independent of the preceding winter El Nino–Southern Oscillation(ENSO) events(ENSO-independent SST) on the interannual variability of the South China Sea Summer Monsoon(SCSSM) and the associated mechanisms. During summer, the ENSO-independent SST component dominates across tropical ocean regions. The tropical ENSO-independent SSTs during spring and summer in the Maritime Continent(MC), the equatorial central-eastern Pacific(CEP), and the tropical Atlantic Ocean(TAO) regions play a comparably significant role in the interannual variation of the SCSSM intensity, compared to the tropical SST dependent on the preceding winter ENSO. The ENSO-independent SST anomalies(SSTA) in the TAO during spring and summer exhibit significant persistence. They can influence the SCSSM through westward propagation of teleconnection, as well as through eastward-propagating Kelvin waves. In summer, the SSTA in the MC, CEP, and TAO regions contribute jointly to the variability of the SCSSM. The MC SSTA affects local convection and generates anomalous meridional circulation to impact the SCSSM intensity. The CEP SSTA directly influences the SCSSM via the Matsuno-Gill response mechanism and indirectly affects it via meridional circulation by modulating vertical motions over the MC through zonal circulation. The TAO SSTA impacts the SCSSM through both westward and eastward pathways, as well as by influencing zonal circulation patterns in the tropical and subtropical North Pacific. The results offer valuable insights into the factors influencing the interannual variability of the SCSSM intensity.
基金supported by the Key Research Program of Frontier Sciences,Chinese Academy of Sciences(Grant No.ZDBS-LY-DQC010)the National Natural Science Foundation of China(Grant No.42175045).
文摘In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.
基金supported by the Third Xinjiang Scientific Expedition Program(2021xjkk0801).
文摘Land surface temperature(LST) directly affects the energy balance of terrestrial surface systems and impacts regional resources, ecosystem evolution, and ecosystem structures. Xinjiang Uygur Autonomous Region is located at the arid Northwest China and is extremely sensitive to climate change. There is an urgent need to understand the distribution patterns of LST in this area and quantitatively measure the nature and intensity of the impacts of the major driving factors from a spatial perspective, as well as elucidate the formation mechanisms. In this study, we used the MOD11C3 LST product developed on the basis of Moderate Resolution Imaging Spectroradiometer(MODIS) to conduct regression analysis and determine the spatiotemporal variation and differentiation pattern of LST in Xinjiang from 2000 to 2020. We analyzed the driving mechanisms of spatial heterogeneity of LST in Xinjiang and the six geomorphic zones(the Altay Mountains, Junggar Basin, Tianshan Mountains, Tarim Basin, Turpan-Hami(Tuha) Basin, and Pakakuna Mountain Group) using geographical detector(Geodetector) and geographically weighted regression(GWR) models. The warming rate of LST in Xinjiang during the study period was 0.24℃/10a, and the spatial distribution pattern of LST had obvious topographic imprints, with 87.20% of the warming zone located in the Gobi desert and areas with frequent human activities, and the cooling zone mainly located in the mountainous areas. The seasonal LST in Xinjiang was at a cooling rate of 0.09℃/10a in autumn, and showed a warming trend in other seasons. Digital elevation model(DEM), latitude, wind speed, precipitation, normalized difference vegetation index(NDVI), and sunshine duration in the single-factor and interactive detections were the key factors driving the LST changes. The direction and intensity of each major driving factor on the spatial variations of LST in the study area were heterogeneous. The negative feedback effect of DEM on the spatial differentiation of LST was the strongest. Lower latitudes, lower vegetation coverage, lower levels of precipitation, and longer sunshine duration increased LST. Unused land was the main heat source landscape, water body was the most important heat sink landscape, grassland and forest land were the land use and land cover(LULC) types with the most prominent heat sink effect, and there were significant differences in different geomorphic zones due to the influences of their vegetation types, climatic conditions, soil types, and human activities. The findings will help to facilitate sustainable climate change management, analyze local climate and environmental patterns, and improve land management strategies in Xinjiang and other arid areas.
基金The US Department of State for sponsoring undergraduate exchange program。
文摘Ocean productivity is the foundation of marine food web,which continuously removes atmospheric carbon dioxide and supports life at sea and on land.Spatio-temporal variability of net primary productivity(NPP),sea surface temperature(SST),sea surface salinity(SSS),mixed layer depth(MLD),and euphotic zone depth(EZD) in the northern B ay of Bengal(BoB) during three monsoon seasons were examined in this study based on remote sensing data for the period 2005 to 2020.To compare the NPP distribution between the coastal zones and open BoB,the study area was divided into five zones(Z1-Z5).Results suggest that most productive zones Z2 and Zl are located at the head bay area and are directly influenced by freshwater discharge together with riverine sediment and nutrient loads.Across Z1-Z5,the NPP ranges from 5 315.38 mg/(m^(2)·d) to 346.7 mg/(m^(2)·d)(carbon,since then the same).The highest monthly average NPP of 5 315.38 mg/(m^(2)·d) in February and 5 039.36 mg/(m^(2)·d) in June were observed from Z2,while the lowest monthly average of 346.72 mg/(m^(2)·d) was observed in March from Z4,which is an oceanic zone.EZD values vary from 6-154 m for the study area,and it has an inverse correlation with NPP concentration.EZD is deeper during the summer season and shallower during the wintertime,with a corresponding increase in productivity.Throughout the year,monthly SST shows slight fluctuation for the entire study area,and statistical analysis shows a significant correlation among NPP,and EZD,overall positive between NPP and MLD,whereas no significant correlation among SSS,and SST for the northern BoB.Long-term trends in SST and productivity were significantly po sitive in head bay zones but negatively productive in the open ocean.The findings in this study on the distribution of NPP,SST,SSS,MLD,and EZD and their seasonal variability in five different zones of BoB can be used to further improve the management of marine resources and overall environmental condition in response to climate changes in BoB as they are of utmost relevance to the fisheries for the three bordering countries.
文摘Urban expansion of cities has caused changes in land use and land cover(LULC)in addition to transformations in the spatial characteristics of landscape structure.These alterations have generated heat islands and rise of land surface temperature(LST),which consequently have caused a variety of environmental issues and threated the sustainable development of urban areas.Greenbelts are employed as an urban planning containment policy to regulate urban expansion,safeguard natural open spaces,and serve adaptation and mitigation functions.And they are regarded as a powerful measure for enhancing urban environmental sustainability.Despite the fact that,the relation between landscape structure change and variation of LST has been examined thoroughly in many studies,but there is a limitation concerning this relation in semi-arid climate and in greenbelts as well,with the lacking of comprehensive research combing both aspects.Accordingly,this study investigated the spatiotemporal changes of landscape pattern of LULC and their relationship with variation of LST within an inner greenbelt in the semi-arid Erbil City of northern Iraq.The study utilized remote sensing data to retrieve LST,classified LULC,and calculated landscape metrics for analyzing spatial changes during the study period.The results indicated that both composition and configuration of LULC had an impact on the variation of LST in the study area.The Pearson's correlation showed the significant effect of Vegetation 1 type(VH),cultivated land(CU),and bare soil(BS)on LST,as increase of LST was related to the decrease of VH and the increases of CU and BS,while,neither Vegetation 2 type(VL)nor built-up(BU)had any effects.Additionally,the spatial distribution of LULC also exhibited significant effects on LST,as LST was strongly correlated with landscape indices for VH,CU,and BS.However,for BU,only aggregation index metric affected LST,while none of VL metrics had a relation.The study provides insights for landscape planners and policymakers to not only develop more green spaces in greenbelt but also optimize the spatial landscape patterns to reduce the influence of LST on the urban environment,and further promote sustainable development and enhance well-being in the cities with semi-arid climate.
基金supported by the National Natural Science Foundation of China(Nos.42076238 and 42376174)the Natural Science Foundation of Shanghai(No.23ZR1426900).
文摘The aim of our study was to examine the contribution of surface waves from WAVEWATCH-III(WW3)to the variation in sea surface temperature(SST)in the Arctic Ocean.The simulated significant wave height(SWH)were validated against the products from Haiyang-2B(HY-2B)in 2021,obtaining a root mean squared error(RMSE)of 0.45 with a correlation of 0.96 and scatter index of 0.18.The wave-induced effects,i.e.,wave breaking and mixing induced by nonbearing waves resulting in changes in radiation stress and Stokes drift,were calculated from WW3,ERA-5 wind,SST,and salinity data from the National Centers for Environmental Prediction and were taken as forcing fields in the Stony Brook Parallel Ocean Model.The results showed that an RMSE of 0.81℃ with wave-induced effects was less than the RMSE of 1.11℃ achieved without the wave term compared with the simulated SST with the measurements from Argos.Considering the four wave effects and sea ice freezing,the SST in the Arctic Ocean decreased by up to 1℃ in winter.Regression analysis revealed that the SWH was linear in SST(values without subtraction of waves)in summer and autumn,but this behavior was not observed in spring or winter due to the presence of sea ice.The interannual variation also presented a negative relationship between the difference in SST and SWH.
基金supported by the National Natural Science Foundation of China(Nos.42076238,42176012,and 42130402)the National Key Research and Development Program of China(No.2021YFC3101702)the Shanghai Frontiers Research Center of the Hadal Biosphere.
文摘The aim of this study is to investigate the sea surface temperature(SST) cooling as typhoons pass the Kuroshio Current.A numerical circulation model,denoted as the Stony Brook Parallel Ocean Model(sbPOM),was used to simulate the SST,which includes four wave-induced effect terms(i.e.,radiation stress,nonbreaking waves,Stokes drift,and breaking waves) simulated using the third-generation wave model,called WAVEWATCH-Ⅲ(WW3).The significant wave height(SWH) measurements from the Jason-2 altimeter were used to validate the WW3-simulated results,yielding a root mean square error(RMSE) of less than 0.50 m and a correlation coefficient(COR) of approximately 0.93.The water temperature measured from the Advanced Research and Global Observation Satellite was applied to validate the model simulation.Accordingly,the RMSE of the SST is 0.92℃ with a COR of approximately 0.99.As revealed in the sbPOM-simulated SST fields,a reduction in the SST at the Kuroshio Current region was observed as a typhoon passed,although the water temperature of the Kuroshio Current is relatively high.The variation of the SST is consistent with that of the current,whereas the maximum SST lagged behind the occurrence of the peak SWH.Moreover,the Stokes drift plays an important role in the SST cooling after analyzing four wave-induced terms in the background of the Kuroshio Current.The sensitivity experiment also showed that the accuracy of the water temperature was significantly reduced when including breaking waves,which play a negative role in the inside part of the ocean.The variation in the mean mixing layer depth(MLD) showed that a typhoon could enhance the mean MLD in the Kuroshio Current area in September and October,whereas a typhoon has little influence on the mean MLD in the Kuroshio Current area in May.Moreover,the mean MLD rapidly decreased with the weakening of the strong wind force and wave-induced effects when a typhoon crossed the Kuroshio Current.
基金funded by Natural Sciences and Engineering Research Council of Canada(NSERC)[RGPIN-2022-04342].
文摘The significance of land surface temperature(LST)and near-surface air temperature(TAIR)extends to various applications,including the exploration of urban heat islands.Understanding urban heat islands is crucial for comprehending the intricate interactions among urbanization,climate dynamics,and human well-being.However,many aspects of these topics remain understudied.In this study,we conducted a comprehensive analysis of LST and TAIR,covering day and night and spanning all four seasons of a full year.We used global datasets and applied non-spatial and spatial analysis techniques in the Amman-Zarqa urban region,a typical arid to semiarid environment.The study had three primary objectives:(1)Assess how different human settlement types influence the variations in LST and TAIR across space and time.(2)Examine the spatial and temporal attributes of the relationships between TAIR and LST.(3)Synthesize insights regarding the spatial and temporal characteristics of urban heat islands in arid to semiarid environments.The findings unveiled that urban centers consistently exhibit the lowest daytime LST and maximum and minimum TAIR,across all seasons when compared to other human settlement types.Nighttime LST displayed more variable patterns.Urban centers act as surface urban cool islands during the day and canopy layer urban cool islands both day and night throughout the seasons.The presence of surface urban heat or cool islands at night is barely noticeable.Daytime and nighttime LST play a significant role in explaining the variability in maximum and minimum TAIR across all seasons,with the relationships exhibiting variations ranging from positive to non-significant to negative,influenced by location and seasonal changes.During the daytime,LST consistently exceeds TAIR across all seasons,whereas this relationship displays greater variability at night.The findings of this study hold significant implications for sustainable urban planning and efforts to combat the effects of urban heat islands.
基金supported by the ESA-MOST Dragon 5 Cooperation Programme[grant number 59318]the National Natural Science Foundation of China[grant number 42271387]the Outstanding Youth Fund of Sichuan Province[grant number 2023NSFSC1907].
文摘The need for cross-comparison and validation of all-weather Land Surface Temperature(LST)products has arisen due to the release of multiple such products aimed at providing comprehensive all-weather monitoring capabilities.In this study,we focus on validating two well-established all-weather LST products(i.e.MLST-AS and TRIMS LST)against in-situ measurements obtained from four high-quality LST validation sites:Evora,Gobabeb,KIT-Forest,and Lake Constance.For the land sites,MLST-AS exhibits better accuracy,with RMSEs ranging from 1.6 K to 2.1 K,than TRIMS LST,the RMSEs of which range from 1.9 K to 3.1 K.Because MLST-AS pixels classified as“inland water”are masked out,the validation over Lake Constance is limited to TRIMS LST:it yields a RMSE of 1.6 K.Furthermore,the validation results show that MLST-AS and TRIMS LST exhibit better accuracy under clear-sky conditions than unclear-sky conditions across all sites.Since the accuracy of the all-weather LST products is considerably affected by the input clear-sky LST products,we further compare the all-weather LST with the corresponding input clear-sky LST to conduct an error source analysis.Considering the clear-sky pixels on MLST-AS directly using the estimates from MLST,the error source analysis is limited to examining TRIMS LST and its input(i.e.MODIS LST).The findings indicate that TRIMS LST is highly correlated with MODIS LST.The investigation and validation of the two selected all-weather LST products objectively evaluate their accuracy and stability,which provides important information for applications of these all-weather LST products.
基金supported by the National Natural Science Foundation of China[Grant No.41961064]Yunnan Fundamental Research Projects[Grant No.202001BB050030]+2 种基金the Plateau Mountain Ecology and Earth’s Environment Discipline Construction Project[Grant No.C1762101030017]Joint Foundation Project between Yunnan Science and Technology Department and Yunnan University[Grant No.C176240210019]Joint Foundation Project between Yunnan Science and Technology Department and Yunnan University[Grant No.2018FY-019].
文摘Geothermal energy is a renewable and environmentally sustainable resource of increasing importance.However,areas with geothermal potential are not easily detected by traditional field investigations,requiring the development of new,robust,and reliable models for detection.In this study,remote sensing data and ground-based variables were used to detect and analyze geothermal resource potential areas.General Land Surface Temperature(GLST)was integrated using 5 years of remote sensing data.Landsat 8 daytime GLST(Landsat-GLST),Moderate Resolution Imaging Spectroradiometer(MODIS)daytime GLST(MODIS-DLST),and MODIS nighttime GLST(MODIS-NLST)data were integrated with Landsat Nighttime Land Surface Temperature(Night-LST),which not only filled the gap of Landsat Night-LST but also improved the spatial resolution of MODIS nighttime temperatures.Specifically,three independent variables(Night-LST,Distance From Known Geothermal Resource Points[DFGP],and Distance From Geological Faults[DFF])were used to develop a weighted model to form a Geothermal Detection Index(GDI)based on Principal Component Analysis(PCA).Along with field verification,the GDI was successfully used to identify three geothermal activity areas in Tengchong City,Yunnan Province.Overall,this work provides a novel method for detecting geothermal potential to support the successful exploitation of geothermal resources.
文摘Information is given on thermal radiation from the Sun, considered in practical engineering calculations of heat exchange. It was found that although the surface temperature of the Sun is assumed to be about 5800 K, the solar spectrum data measured by Kondratyev lead to a value of at least 7134 K. Such a higher value can be obtained by interpreting the Planck formula for the black radiation spectrum for the Kondratyev data. In addition, using the Stefan-Boltzmann law, the energetic emissivity of the Sun’s surface was determined to be 0.431. Furthermore, based on Petela’s formulae for exergy of thermal radiation, the exergetic emissivity of the Sun’s surface was also calculated at the level of 0.426.
文摘The East African short rainy season (October-November-December) is one of the major flood seasons in the East African region. The amount of rainfall during the short rainy season is closely related to the lives of the people and the socio-economic development of the area. By using precipitation data and sea surface temperature data, this study reveals the spatial and temporal variation patterns of extreme precipitation during the East African short rainy season. Key findings include significant rainfall variability, with Tanzania experiencing the highest amounts in December due to the southward shift of the Intertropical Convergence Zone (ITCZ), while other regions receive less than 100 mm. Extreme rainfall events (90th percentiles) are evenly distributed, averaging 2 to 10 days annually. Historical data shows maximum seasonal rainfall often peaks at 15 mm, with frequent occurrences of daily rainfall exceeding 10 mm during OND. Additionally, a positive correlation (0.48) between OND precipitation extremes and Indian Ocean Dipole (IOD) anomalies is statistically significant. These findings highlight the climatic variability and potential trends in extreme rainfall events in East Africa, providing valuable insights for regional climate adaptation strategies.
文摘The Alborz Mountains are some of the highest in Iran,and they play an important role in controlling the climate of the country’s northern regions.The land surface temperature(LST)is an important variable that affects the ecosystem of this area.This study investigated the spatiotemporal changes and trends of the nighttime LST in the western region of the Central Alborz Mountains at elevations of 1500-4000 m above sea level.MODIS data were extracted for the period of 2000-2021,and the Mann-Kendall nonparametric test was applied to evaluating the changes in the LST.The results indicated a significant increasing trend for the monthly average LST in May-August along the southern aspect.Both the northern and southern aspects showed decreasing trends for the monthly average LST in October,November,and March and an increasing trend in other months.At all elevations,the average decadal change in the monthly average LST was more severe along the southern aspect(0.60°C)than along the northern aspect(0.37°C).The LST difference between the northern and southern aspects decreased in the cold months but increased in the hot months.At the same elevation,the difference in the lapse rate between the northern and southern aspects was greater in the hot months than in the cold months.With increasing elevation,the lapse rate between the northern and southern aspects disappeared.Climate change was concluded to greatly decrease the difference in LST at different elevations for April-July.
