Human activities have significantly impacted the land surface temperature(LST),endangering human health;however,the relationship between these two factors has not been adequately quantified.This study comprehensively ...Human activities have significantly impacted the land surface temperature(LST),endangering human health;however,the relationship between these two factors has not been adequately quantified.This study comprehensively constructs a Human Activity Intensity(HAI)index and employs the Maximal Information Coefficient,four-quadrant model,and XGBoostSHAP model to investigate the spatiotemporal relationship and influencing factors of HAI-LST in the Yellow River Basin(YRB)from 2000 to 2020.The results indicated that from 2000 to 2020,as HAI and LST increased,the static HAI-LST relationship in the YRB showed a positive correlation that continued to strengthen.This dynamic relationship exhibited conflicting development,with the proportion of coordinated to conflicting regions shifting from 1:4 to 1:2,indicating a reduction in conflict intensity.Notably,only the degree of conflict in the source area decreased significantly,whereas it intensified in the upper and lower reaches.The key factors influencing the HAI-LST relationship include fractional vegetation cover,slope,precipitation,and evapotranspiration,along with region-specific factors such as PM_(2.5),biodiversity,and elevation.Based on these findings,region-specific ecological management strategies have been proposed to mitigate conflict-prone areas and alleviate thermal stress,thereby providing important guidance for promoting harmonious development between humans and nature.展开更多
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
The basic principles of sea surface temperature （SST） remote sensing using infrared and microwave radiometers are introduced, and the differences between two sensors for retrieving sea surface temperature are invest...The basic principles of sea surface temperature （SST） remote sensing using infrared and microwave radiometers are introduced, and the differences between two sensors for retrieving sea surface temperature are investigated. The ground resolution, atmospheric effect, sea surface wind, skin depth and so on have important influence on precision of sea surface temperature retrieved by two sensors. The better understanding of the advantage and disadvantage of sea surface temperature detected by infrared and microwave radiometers would help us to imply SST remote sensing data more effectively and correctly.展开更多
A Hybrid Coordinate Ocean Model （HYCOM） is used to simulate the sea surface temperature of the Tropical and North Pacific. Based on the different combinations of two air-Sea flux data sets （COADS and ECMWF） and tw...A Hybrid Coordinate Ocean Model （HYCOM） is used to simulate the sea surface temperature of the Tropical and North Pacific. Based on the different combinations of two air-Sea flux data sets （COADS and ECMWF） and two bulk parameter formulas （non-constant and constant）, four numerical experiments are carried out. The following conclusions can be deduced from the numerical results. （1） The numerical results using non-constant bulk parameter formula are much better than those using constant one. In the Pacific area from 40°N to 20°S, the annual average SST obtained from the experiment using non-constant bulk parameter formula is 0.21 ℃ higher than that from the satellite-based SST climatology （the pathfinder data）. However, the difference is 0.63 ℃ for the experiment when the using constant one. （2） HYCOM successfully simulates the monthly variation of climatological SST in tropical and north Pacific basins and monthly spatial variation of Western Pacific Warm Pool. Especially in the Pacific area from 40°N to 20°S, the difference of the seasonal averaged SST between pathfinder data and the result of experiment 2 （using COADS data set and non-constant bulk parameter formula） is only about 0.02 ℃. （3）The simulation results using different Air-Sea flux data are different and the difference is very large in some regions. In the northwest of the model region, the annual average SST obtained from experiment 2 （using COADS data set） is 1℃ higher than that obtained from experiment 4 （using ECMWF data set）. Contrarily, the result of experiment 4 is 1 ℃ larger than that of experiment 2 in the southeast of the model region. The largest difference is about 4 ℃ occurred near the area of 58°N, 140°E and the Bohai sea.展开更多
By dint of the summer precipitation data from 21 stations in the Dongting Lake region during 1960-2008 and the sea surface temperature(SST) data from NOAA,the spatial and temporal distributions of summer precipitation...By dint of the summer precipitation data from 21 stations in the Dongting Lake region during 1960-2008 and the sea surface temperature(SST) data from NOAA,the spatial and temporal distributions of summer precipitation and their correlations with SST are analyzed.The coupling relationship between the anomalous distribution in summer precipitation and the variation of SST has between studied with the Singular Value Decomposition(SVD) analysis.The increase or decrease of summer precipitation in the Dongting Lake region is closely associated with the SST anomalies in three key regions.The variation of SST in the three key regions has been proved to be a significant previous signal to anomaly of summer rainfall in Dongting region.展开更多
Satellite SST(sea surface temperature) from the Advanced Microwave Scanning Radiometer for the Earth Observing System(AMSR-E) is compared with in situ temperature observations from Argo profiling floats over the globa...Satellite SST(sea surface temperature) from the Advanced Microwave Scanning Radiometer for the Earth Observing System(AMSR-E) is compared with in situ temperature observations from Argo profiling floats over the global oceans to evaluate the advantages of Argo NST(near-surface temperature: water temperature less than 1 m from the surface). By comparing Argo nominal surface temperature(~5 m) with its NST, a diurnal cycle caused by daytime warming and nighttime cooling was found, along with a maximum warming of 0.08±0.36°C during 14:00–15:00 local time. Further comparisons between Argo 5-m temperature/Argo NST and AMSR-E SST retrievals related to wind speed, columnar water vapor, and columnar cloud water indicate warming biases at low wind speed(<5 m/s) and columnar water vapor >28 mm during daytime. The warming tendency is more remarkable for AMSR-E SST/Argo 5-m temperature compared with AMSR-E SST/Argo NST, owing to the effect of diurnal warming. This effect of diurnal warming events should be excluded before validation for microwave SST retrievals. Both AMSR-E nighttime SST/Argo 5-m temperature and nighttime SST/Argo NST show generally good agreement, independent of wind speed and columnar water vapor. From our analysis, Argo NST data demonstrated their advantages for validation of satellite-retrieved SST.展开更多
This is an exploratory investigation to search for the presence of an acceleration in global sea surface temperature rise, which is essential to identify anthropogenic contributions to the climate change during the 20...This is an exploratory investigation to search for the presence of an acceleration in global sea surface temperature rise, which is essential to identify anthropogenic contributions to the climate change during the 20 th century. A weighted statistical model with an acceleration parameter was built progressively to reconstruct the variations in the global sea surface temperature data considering statistically significant confounders and autoregressive disturbances in the process. From the preliminary residual analysis of a weighted regression model, emerged a parsimonious model with first order autoregressive disturbances with a deterministic trend, acceleration and periodicity of 69 yr and its 138 yr subharmonic. The final model solution, selected from 29 alternative combinations of the model parameters using Mallows' s Cp metric, revealed a statistically significant deterministic trend, 0.40 ± 0.03C/c(p < 0.01), and acceleration, 0.67 ± 0.11C/c^2(p < 0.01) explaining 33% of the global sea surface temperature variations. The combined yearly trend and acceleration in global sea surface temperature as predicted by the model,exhibit a strong correlation with the yearly increase in the global CO^2 concentrations observed during the 20th century.展开更多
A summer-time shipboard meteorological survey is described in the Northwest Indian Ocean. Shipboard observations are used to evaluate a satellite-based sea surface temperature（SST）, and then find the main factors th...A summer-time shipboard meteorological survey is described in the Northwest Indian Ocean. Shipboard observations are used to evaluate a satellite-based sea surface temperature（SST）, and then find the main factors that are highly correlated with errors. Two satellite data, the first is remote sensing product of a microwave, which is a Tropical Rainfall Measuring Mission Microwave Imager（TMI）, and the second is merged data from the microwave and infrared satellite as well as drifter observations, which is Operational Sea Surface Temperature and Sea Ice Analysis（OSTIA）. The results reveal that the daily mean SST of merged data has much lower bias and root mean square error as compared with that from microwave products. Therefore the results support the necessary of the merging infrared and drifter SST with a microwave satellite for improving the quality of the SST. Furthermore, the correlation coefficient between an SST error and meteorological parameters, which include a wind speed, an air temperature, a relative humidity, an air pressure, and a visibility. The results show that the wind speed has the largest correlation coefficient with the TMI SST error. However, the air temperature is the most important factor to the OSTIA SST error. Meanwhile,the relative humidity shows the high correlation with the SST error for the OSTIA product.展开更多
The temperature biases of 28 CMIP5 AGCMs are evaluated over the Tibetan Plateau(TP) for the period 1979–2005. The results demonstrate that the majority of CMIP5 models underestimate annual and seasonal mean surface 2...The temperature biases of 28 CMIP5 AGCMs are evaluated over the Tibetan Plateau(TP) for the period 1979–2005. The results demonstrate that the majority of CMIP5 models underestimate annual and seasonal mean surface 2-m air temperatures(Tas) over the TP. In addition, the ensemble of the 28 AGCMs and half of the individual models underestimate annual mean skin temperatures(Ts) over the TP. The cold biases are larger in Tasthan in Ts, and are larger over the western TP. By decomposing the Tsbias using the surface energy budget equation, we investigate the contributions to the cold surface temperature bias on the TP from various factors, including the surface albedo-induced bias, surface cloud radiative forcing, clear-sky shortwave radiation, clear-sky downward longwave radiation, surface sensible heat flux, latent heat flux,and heat storage. The results show a suite of physically interlinked processes contributing to the cold surface temperature bias.Strong negative surface albedo-induced bias associated with excessive snow cover and the surface heat fluxes are highly anticorrelated, and the cancelling out of these two terms leads to a relatively weak contribution to the cold bias. Smaller surface turbulent fluxes lead to colder lower-tropospheric temperature and lower water vapor content, which in turn cause negative clear-sky downward longwave radiation and cold bias. The results suggest that improvements in the parameterization of the area of snow cover, as well as the boundary layer, and hence surface turbulent fluxes, may help to reduce the cold bias over the TP in the models.展开更多
Remote sensing and geographic information systems (GIS) technologies were used to detect land use/cover changes (LUCC) and to assess their impacts on land surface temperature (LST) in the Zhujiang Delta. Multi-tempora...Remote sensing and geographic information systems (GIS) technologies were used to detect land use/cover changes (LUCC) and to assess their impacts on land surface temperature (LST) in the Zhujiang Delta. Multi-temporal Landsat TM and Landsat ETM+ data were employed to identify patterns of LUCC as well as to quantify urban expansion and the associated decrease of vegetation cover. The thermal infrared bands of the data were used to retrieve LST. The results revealed a strong and uneven urban growth,which caused LST to raise 4.56℃in the newly urbanized part of the study area. Overall, remote sensing and GIS technologies were effective approaches for monitoring and analyzing urban growth patterns and evaluating their impacts on LST.展开更多
Long-term change of sea surface temperature （SST） in the China Seas from 1900 to 2006 is examined based on two different observation datasets （HadlSSTI and HadSST3）. Similar to the Atlantic, SST in the China Seas ...Long-term change of sea surface temperature （SST） in the China Seas from 1900 to 2006 is examined based on two different observation datasets （HadlSSTI and HadSST3）. Similar to the Atlantic, SST in the China Seas has been well observed during the past 107 years. A comparison between the reconstructed （HadISSTI） and un-interpolated （HadSST3） datasets shows that the SST wanning trends from both datasets are consistent with each other in most of the China Seas. The warming trends are stronger in winter than in summer, with a maximum rate of SST increase exceeding 2.7℃ （100year）-I in the East China Sea and the Taiwan Strait during winter based on HadISSTI. However, the SST from both datasets experienced a sudden decrease after 1999 in the China Seas. The estimated trend from HadlSSTI is stronger than that fi＇om HadSST3 in the East China Sea and the east of Taiwan Island, where the difference in the linear SST warming trends are as large as about 1℃ （100year）-I when using respectively HadISST1 and HadSST3 datasets. When compared to the linear winter warnling trend of the land surface air temperature （1.6℃ （100 year）-1）, HadSST3 shows a more reasonable trend of less than 2.1℃（ 100 year）-1 than HadISST 1 ＇s trend of larger than 2.7℃ （ 100 year）-1 at the mouth of the Yangtze River. The restllts also indicate large uncertainties in the estimate of SST warming patterns.展开更多
The thermal infrared channel (IRS4) of HJ-1B satellite obtains view zenith angles (VZA) up to ±33°. The view angle should be taken into account when retrieving land surface temperature (LST) from IRS4 data. ...The thermal infrared channel (IRS4) of HJ-1B satellite obtains view zenith angles (VZA) up to ±33°. The view angle should be taken into account when retrieving land surface temperature (LST) from IRS4 data. This study aims at improving the mono-window algorithm for retrieving LST from IRS4 data. Based on atmospheric radiative transfer simulations,a model for correcting the VZA effects on atmospheric transmittance is proposed. In addition,a generalized model for calculating the effective mean atmospheric temperature is developed. Validation with the simulated dataset based on standard atmospheric profiles reveals that the improved mono-window algorithm for IRS4 obtains high accuracy for LST retrieval,with the mean absolute error (MAE) and root mean square error (RMSE) being 1.0 K and 1.1 K,respectively. Numerical experiment with the radiosonde profile acquired in Beijing in winter demonstrates that the improved mono-window algorithm exhibits excellent ability for LST retrieval,with MAE and RMSE being 0.6 K and 0.6 K,respectively. Further application in Qinghai Lake and comparison with the Moderate-Resolution Imaging Spectroradiometer (MODIS) LST product suggest that the improved mono-window algorithm is applicable and feasible in actual conditions.展开更多
A stratus-sea fog event that occurred over the Yellow and East China Seas on 3 June 2011 is investigated using observations and a numerical model, with a focus on the effects of background circulation and Sea Surface ...A stratus-sea fog event that occurred over the Yellow and East China Seas on 3 June 2011 is investigated using observations and a numerical model, with a focus on the effects of background circulation and Sea Surface Temperature Front （SSTF） on the transition of stratus into sea fog. Southerly winds of a synoptic high-pressure circulation transport water vapor to the Yellow Sea, creating conditions favorable for sea fog/stratus formation. The subsidence from the high-pressure contributes to the temperature inversion at the top of the stratus. The SSTF forces a secondary circulation within the ABL （Atmospheric Boundary Layer）, the sinking branch of which on the cold flank of SSTF helps lower the stratus layer fiLrther to reach the sea surface. The cooling effect over the cold sea surface counteracts the adiabatic warming induced by subsidence. The secondary circulation becomes weak and the fog patches are shrtmk heavily with the smoothed SSTE A conceptual model is proposed for the transition of stratus into sea fog over the Yellow and East China Seas. Finally, the analyses suggest that sea fog frequency will probably decrease due to the weakened SSTF and the reduced subsidence of secondary circulation under global wanning.展开更多
基金Shanxi Province Graduate Research Practice Innovation Project,No.2023KY465Project on the Reform of Graduate Education and Teaching in Shanxi Province,No.2021YJJG146+1 种基金Research Project of Shanxi Provincial Cultural Relics Bureau,No.22-8-14-1400-119National Key R&D Program of China,No.2021YFB3901300。
文摘Human activities have significantly impacted the land surface temperature(LST),endangering human health;however,the relationship between these two factors has not been adequately quantified.This study comprehensively constructs a Human Activity Intensity(HAI)index and employs the Maximal Information Coefficient,four-quadrant model,and XGBoostSHAP model to investigate the spatiotemporal relationship and influencing factors of HAI-LST in the Yellow River Basin(YRB)from 2000 to 2020.The results indicated that from 2000 to 2020,as HAI and LST increased,the static HAI-LST relationship in the YRB showed a positive correlation that continued to strengthen.This dynamic relationship exhibited conflicting development,with the proportion of coordinated to conflicting regions shifting from 1:4 to 1:2,indicating a reduction in conflict intensity.Notably,only the degree of conflict in the source area decreased significantly,whereas it intensified in the upper and lower reaches.The key factors influencing the HAI-LST relationship include fractional vegetation cover,slope,precipitation,and evapotranspiration,along with region-specific factors such as PM_(2.5),biodiversity,and elevation.Based on these findings,region-specific ecological management strategies have been proposed to mitigate conflict-prone areas and alleviate thermal stress,thereby providing important guidance for promoting harmonious development between humans and nature.
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.
文摘The basic principles of sea surface temperature （SST） remote sensing using infrared and microwave radiometers are introduced, and the differences between two sensors for retrieving sea surface temperature are investigated. The ground resolution, atmospheric effect, sea surface wind, skin depth and so on have important influence on precision of sea surface temperature retrieved by two sensors. The better understanding of the advantage and disadvantage of sea surface temperature detected by infrared and microwave radiometers would help us to imply SST remote sensing data more effectively and correctly.
文摘A Hybrid Coordinate Ocean Model （HYCOM） is used to simulate the sea surface temperature of the Tropical and North Pacific. Based on the different combinations of two air-Sea flux data sets （COADS and ECMWF） and two bulk parameter formulas （non-constant and constant）, four numerical experiments are carried out. The following conclusions can be deduced from the numerical results. （1） The numerical results using non-constant bulk parameter formula are much better than those using constant one. In the Pacific area from 40°N to 20°S, the annual average SST obtained from the experiment using non-constant bulk parameter formula is 0.21 ℃ higher than that from the satellite-based SST climatology （the pathfinder data）. However, the difference is 0.63 ℃ for the experiment when the using constant one. （2） HYCOM successfully simulates the monthly variation of climatological SST in tropical and north Pacific basins and monthly spatial variation of Western Pacific Warm Pool. Especially in the Pacific area from 40°N to 20°S, the difference of the seasonal averaged SST between pathfinder data and the result of experiment 2 （using COADS data set and non-constant bulk parameter formula） is only about 0.02 ℃. （3）The simulation results using different Air-Sea flux data are different and the difference is very large in some regions. In the northwest of the model region, the annual average SST obtained from experiment 2 （using COADS data set） is 1℃ higher than that obtained from experiment 4 （using ECMWF data set）. Contrarily, the result of experiment 4 is 1 ℃ larger than that of experiment 2 in the southeast of the model region. The largest difference is about 4 ℃ occurred near the area of 58°N, 140°E and the Bohai sea.
基金Supported by The Special Foundation of Chinese Meteorological Bureau Climate Changes Program(200920)The Special Foundation of Hunan Major Scientific and Technological Research Program(2008FJ1006)~~
文摘By dint of the summer precipitation data from 21 stations in the Dongting Lake region during 1960-2008 and the sea surface temperature(SST) data from NOAA,the spatial and temporal distributions of summer precipitation and their correlations with SST are analyzed.The coupling relationship between the anomalous distribution in summer precipitation and the variation of SST has between studied with the Singular Value Decomposition(SVD) analysis.The increase or decrease of summer precipitation in the Dongting Lake region is closely associated with the SST anomalies in three key regions.The variation of SST in the three key regions has been proved to be a significant previous signal to anomaly of summer rainfall in Dongting region.
基金Supported by the National Basic Research Program of China(973 Program)(No.2013CB430301)the National Natural Science Foundation of China(Nos.41321004,41206022,41406022)the National Special Research Fund for Non-Profit Marine Sector(No.201305032)
文摘Satellite SST(sea surface temperature) from the Advanced Microwave Scanning Radiometer for the Earth Observing System(AMSR-E) is compared with in situ temperature observations from Argo profiling floats over the global oceans to evaluate the advantages of Argo NST(near-surface temperature: water temperature less than 1 m from the surface). By comparing Argo nominal surface temperature(~5 m) with its NST, a diurnal cycle caused by daytime warming and nighttime cooling was found, along with a maximum warming of 0.08±0.36°C during 14:00–15:00 local time. Further comparisons between Argo 5-m temperature/Argo NST and AMSR-E SST retrievals related to wind speed, columnar water vapor, and columnar cloud water indicate warming biases at low wind speed(<5 m/s) and columnar water vapor >28 mm during daytime. The warming tendency is more remarkable for AMSR-E SST/Argo 5-m temperature compared with AMSR-E SST/Argo NST, owing to the effect of diurnal warming. This effect of diurnal warming events should be excluded before validation for microwave SST retrievals. Both AMSR-E nighttime SST/Argo 5-m temperature and nighttime SST/Argo NST show generally good agreement, independent of wind speed and columnar water vapor. From our analysis, Argo NST data demonstrated their advantages for validation of satellite-retrieved SST.
文摘This is an exploratory investigation to search for the presence of an acceleration in global sea surface temperature rise, which is essential to identify anthropogenic contributions to the climate change during the 20 th century. A weighted statistical model with an acceleration parameter was built progressively to reconstruct the variations in the global sea surface temperature data considering statistically significant confounders and autoregressive disturbances in the process. From the preliminary residual analysis of a weighted regression model, emerged a parsimonious model with first order autoregressive disturbances with a deterministic trend, acceleration and periodicity of 69 yr and its 138 yr subharmonic. The final model solution, selected from 29 alternative combinations of the model parameters using Mallows' s Cp metric, revealed a statistically significant deterministic trend, 0.40 ± 0.03C/c(p < 0.01), and acceleration, 0.67 ± 0.11C/c^2(p < 0.01) explaining 33% of the global sea surface temperature variations. The combined yearly trend and acceleration in global sea surface temperature as predicted by the model,exhibit a strong correlation with the yearly increase in the global CO^2 concentrations observed during the 20th century.
基金China Ocean Mineral Resources Research and Development Association Project under contract No.DY125-12-R-03the National Natural Science Foundation of China under contract Nos 41476021 and 41321004the Scientific Research Fund of Second Institute of Oceanography,State Oceanic Administration China under contract No.JT1205
文摘A summer-time shipboard meteorological survey is described in the Northwest Indian Ocean. Shipboard observations are used to evaluate a satellite-based sea surface temperature（SST）, and then find the main factors that are highly correlated with errors. Two satellite data, the first is remote sensing product of a microwave, which is a Tropical Rainfall Measuring Mission Microwave Imager（TMI）, and the second is merged data from the microwave and infrared satellite as well as drifter observations, which is Operational Sea Surface Temperature and Sea Ice Analysis（OSTIA）. The results reveal that the daily mean SST of merged data has much lower bias and root mean square error as compared with that from microwave products. Therefore the results support the necessary of the merging infrared and drifter SST with a microwave satellite for improving the quality of the SST. Furthermore, the correlation coefficient between an SST error and meteorological parameters, which include a wind speed, an air temperature, a relative humidity, an air pressure, and a visibility. The results show that the wind speed has the largest correlation coefficient with the TMI SST error. However, the air temperature is the most important factor to the OSTIA SST error. Meanwhile,the relative humidity shows the high correlation with the SST error for the OSTIA product.
基金supported by the National Natural Science Foundation of China (Grant Nos. 91437219 and 91637312)the Third Tibetan Plateau Scientific Experiment (Grant No. GYHY201406001)+1 种基金the Key Research Program of Frontier Sciences, Chinese Academy of Sciences (Grant No. QYZDY-SSW-DQC018)the Special Program for Applied Research on Super Computation of the NSFC–Guangdong Joint Fund (second phase)
文摘The temperature biases of 28 CMIP5 AGCMs are evaluated over the Tibetan Plateau(TP) for the period 1979–2005. The results demonstrate that the majority of CMIP5 models underestimate annual and seasonal mean surface 2-m air temperatures(Tas) over the TP. In addition, the ensemble of the 28 AGCMs and half of the individual models underestimate annual mean skin temperatures(Ts) over the TP. The cold biases are larger in Tasthan in Ts, and are larger over the western TP. By decomposing the Tsbias using the surface energy budget equation, we investigate the contributions to the cold surface temperature bias on the TP from various factors, including the surface albedo-induced bias, surface cloud radiative forcing, clear-sky shortwave radiation, clear-sky downward longwave radiation, surface sensible heat flux, latent heat flux,and heat storage. The results show a suite of physically interlinked processes contributing to the cold surface temperature bias.Strong negative surface albedo-induced bias associated with excessive snow cover and the surface heat fluxes are highly anticorrelated, and the cancelling out of these two terms leads to a relatively weak contribution to the cold bias. Smaller surface turbulent fluxes lead to colder lower-tropospheric temperature and lower water vapor content, which in turn cause negative clear-sky downward longwave radiation and cold bias. The results suggest that improvements in the parameterization of the area of snow cover, as well as the boundary layer, and hence surface turbulent fluxes, may help to reduce the cold bias over the TP in the models.
基金Project supported by the Science and Technology Project Foundation of Guangzhou (No. 2005Z3-D0551)the Science and Technology Project Foundation of Guangzhou Education Bureau (No. 62026)
文摘Remote sensing and geographic information systems (GIS) technologies were used to detect land use/cover changes (LUCC) and to assess their impacts on land surface temperature (LST) in the Zhujiang Delta. Multi-temporal Landsat TM and Landsat ETM+ data were employed to identify patterns of LUCC as well as to quantify urban expansion and the associated decrease of vegetation cover. The thermal infrared bands of the data were used to retrieve LST. The results revealed a strong and uneven urban growth,which caused LST to raise 4.56℃in the newly urbanized part of the study area. Overall, remote sensing and GIS technologies were effective approaches for monitoring and analyzing urban growth patterns and evaluating their impacts on LST.
基金supported by the National Basic Research Program of China(2012-CB955602)National Key Program for Developing Basic Science(2010CB428904)Natural Science Foundation of China(40830106,40921004 and 41176006)
文摘Long-term change of sea surface temperature （SST） in the China Seas from 1900 to 2006 is examined based on two different observation datasets （HadlSSTI and HadSST3）. Similar to the Atlantic, SST in the China Seas has been well observed during the past 107 years. A comparison between the reconstructed （HadISSTI） and un-interpolated （HadSST3） datasets shows that the SST wanning trends from both datasets are consistent with each other in most of the China Seas. The warming trends are stronger in winter than in summer, with a maximum rate of SST increase exceeding 2.7℃ （100year）-I in the East China Sea and the Taiwan Strait during winter based on HadISSTI. However, the SST from both datasets experienced a sudden decrease after 1999 in the China Seas. The estimated trend from HadlSSTI is stronger than that fi＇om HadSST3 in the East China Sea and the east of Taiwan Island, where the difference in the linear SST warming trends are as large as about 1℃ （100year）-I when using respectively HadISST1 and HadSST3 datasets. When compared to the linear winter warnling trend of the land surface air temperature （1.6℃ （100 year）-1）, HadSST3 shows a more reasonable trend of less than 2.1℃（ 100 year）-1 than HadISST 1 ＇s trend of larger than 2.7℃ （ 100 year）-1 at the mouth of the Yangtze River. The restllts also indicate large uncertainties in the estimate of SST warming patterns.
基金Under the auspices of Opening Funding of State Key Laboratory for Remote Sensing ScienceNational High-tech Research and Development Program (863 Program) (No. 2007AA120205, 2007AA120306)
文摘The thermal infrared channel (IRS4) of HJ-1B satellite obtains view zenith angles (VZA) up to ±33°. The view angle should be taken into account when retrieving land surface temperature (LST) from IRS4 data. This study aims at improving the mono-window algorithm for retrieving LST from IRS4 data. Based on atmospheric radiative transfer simulations,a model for correcting the VZA effects on atmospheric transmittance is proposed. In addition,a generalized model for calculating the effective mean atmospheric temperature is developed. Validation with the simulated dataset based on standard atmospheric profiles reveals that the improved mono-window algorithm for IRS4 obtains high accuracy for LST retrieval,with the mean absolute error (MAE) and root mean square error (RMSE) being 1.0 K and 1.1 K,respectively. Numerical experiment with the radiosonde profile acquired in Beijing in winter demonstrates that the improved mono-window algorithm exhibits excellent ability for LST retrieval,with MAE and RMSE being 0.6 K and 0.6 K,respectively. Further application in Qinghai Lake and comparison with the Moderate-Resolution Imaging Spectroradiometer (MODIS) LST product suggest that the improved mono-window algorithm is applicable and feasible in actual conditions.
文摘A stratus-sea fog event that occurred over the Yellow and East China Seas on 3 June 2011 is investigated using observations and a numerical model, with a focus on the effects of background circulation and Sea Surface Temperature Front （SSTF） on the transition of stratus into sea fog. Southerly winds of a synoptic high-pressure circulation transport water vapor to the Yellow Sea, creating conditions favorable for sea fog/stratus formation. The subsidence from the high-pressure contributes to the temperature inversion at the top of the stratus. The SSTF forces a secondary circulation within the ABL （Atmospheric Boundary Layer）, the sinking branch of which on the cold flank of SSTF helps lower the stratus layer fiLrther to reach the sea surface. The cooling effect over the cold sea surface counteracts the adiabatic warming induced by subsidence. The secondary circulation becomes weak and the fog patches are shrtmk heavily with the smoothed SSTE A conceptual model is proposed for the transition of stratus into sea fog over the Yellow and East China Seas. Finally, the analyses suggest that sea fog frequency will probably decrease due to the weakened SSTF and the reduced subsidence of secondary circulation under global wanning.
