Surface Temperature In Regions Research Articles

The first evaluation of the FY-3D/MERSI-2 sensor’s thermal infrared capabilities for deriving land surface temperature in volcanic regions: a case study of Mount Etna

ABSTRACT In November 2017, the China Meteorological Administration launched a new polar orbiting satellite in its Fengyun (FY) series: FY-3D. With its main purpose being the collection of meteorological data, FY-3D featured a comprehensive payload that is equally exploitable by various Earth Science disciplines. One of its sensors, the MEdium Resolution Spectral Imager-2 (MERSI-2), provides visible and infrared imagery at spatial resolutions of 250 – 1000 m. These characteristics make MERSI-2 suitable for volcanological remote sensing and make it comparable to the National Aeronautics and Space Administration’s (NASA’s) Moderate Resolution Imaging Spectroradiometer (MODIS) sensors which themselves, have been widely used in volcanological applications. This paper evaluates the first clear and near-coincident MODIS – MERSI-2 images of Mount Etna (Italy) during an active volcanic phase in 2019 and in turn, provides the first assessment of MERSI-2’s utility in observing volcanic activity in the Thermal InfraRed (TIR). To ensure the comparability of both scenes, data from each were converted to Land Surface Temperature (LST) and comparisons were encouraging, with an r2 of 0.92, a mean temperature discrepancy of 0.26 K and a root mean squared error of 0.75 K. Having ascertained comparability, we focussed on the absolute temperatures detected at the eruption site, with the highest being 317.3 K and 328.1 K for MODIS and MERSI-2, respectively. The 20 minute gap between the acquisitions is the most likely the cause of this temperature discrepancy, suggesting variations in lava effusion rates and activity were occurring at Mount Etna over such timescales. This study confirms the applicability of MERSI-2 for observing volcanic activity and emphasises the significance of TIR volcanic monitoring and the importance that additional spaceborne platforms might have in reducing temporal gaps between image acquisitions. Given its unique characteristics, future studies should investigate the applicability of MERSI-2 in more varied volcanic settings.

Satellite Observed Sensitivity of Tropical Clouds and Moisture to Sea Surface Temperature on Various Time and Space Scales: 2. Focus on Marine Low Level Clouds

AbstractThis study examines how satellite observed relative humidity (RH) profiles, cloud covers, and cloud altitudes vary with sea surface temperature (SST) in low cloud regions on different temporal and spatial scales over the tropical oceans (30°N–30°S). We split low clouds into optically opaque and optically thin clouds and characterize for the first time their altitude variations with SST using space lidar observations. On the process scale, the median instantaneous observations at high spatial resolution show simultaneously decreasing low opaque cloud top altitude, decreasing low opaque cloud cover, increasing middle‐tropospheric RH, and decreasing lower‐tropospheric RH with SST. Collectively, these observational results suggest decreasing opaque marine boundary layer cloud cover and enhanced mixing between the middle and lower troposphere with SST on the process scale, consistent with previous Large‐Eddy Simulation studies. The covariations between opaque cloud cover and RH with SST are quantified on all time and space scales (from the process scale to the annual tropical mean scale). Meanwhile, on the process scale, low optically thin clouds, coexisting with opaque clouds, rise with SST (consistent with the literature mechanism), while the low optically thin cloud cover is insensitive to SST (not consistent with the literature mechanism). These results are then compared to a general circulation model, which captures the observed sign of change of opaque cloud cover and middle‐tropospheric RH with SST but fails to reproduce the observed vertical shrinkage of low opaque clouds with SST and the variations of low thin clouds with SST.

Impacts of afforestation on land surface temperature in different regions of China

To assess the impacts of afforestation on land surface temperature (LST) in China and provide a basis for future afforestation and warming mitigation policies, adjacent forest and open land are compared using ten years of satellite data. Most regions in China exhibit a diurnal asymmetry in the magnitude and sign of the effects of afforestation, with daytime cooling and nighttime warming. Afforestation has annual daily cooling effects in most regions of China because the magnitude of annual nighttime warming is generally weaker than that of the annual daytime cooling. We attributed the warming and cooling effects of afforestation to the changes of evapotranspiration (ET) and albedo. The annual average albedo of forest is smaller than that of open land, and the albedo differences between forest and open land vary spatially, with larger differences in places with snow cover. In the annual average, ET over forest is greater than that over open land, with the largest values in the southern of Yangtze River. The daytime differences in LST between forest and open land are driven by the cooling effects of ET and warming effects of albedo, and the cooling effects of ET dominate. The nighttime warming effects of afforestation is related with the release of the energy stored in the soil during daytime. Evergreen broadleaf forest and deciduous broadleaf forest are recommended as the choice of afforestation in south and in north of the Yangtze River respectively to decrease the LST if the afforestation program in China is to be expanded.

Attribution of local land surface temperature variations response to irrigation over the North China Plain

Irrigation substantially alters land surface temperature (LST) in different regions of the world. Studies have recently focused on quantifying irrigation-induced LST change based on remote sensing technology due to its high spatiotemporal resolution. However, the biophysical mechanisms of irrigation on LST remains poorly understood. Here we first investigated the impact of irrigation on LST during 2003–2012 over the North China Plain (NCP), which is one of the most intensively irrigated areas around the word. We then attributed the mechanisms underlying LST change between adjacent irrigated and non-irrigated croplands based on two surface energy balance-based methods: the Decomposed Temperature Metric (DTM) method and the intrinsic biophysical mechanism (IBM) method. The results indicate that at annual scale, irrigation produce an overall cooling effect over the NCP, with the mean observed LST change of −0.098 K, calculated LST change of −0.096 K for DTM method and −0.165 K for IBM method, respectively. Furthermore, the agreement between the annual observed and calculated LST difference indicate that DTM is a more robust method than IBM in quantifying irrigation-induced LST change over the NCP. The attribution method DTM reveals that components of albedo and emissivity has an average cooling effect of −0.012 K and −0.005 K, respectively, while incoming radiation lead to a weak warming effect of +0.01 K. The enhanced turbulent fluxes of latent heat flux dominate the cooling effect (−0.174 K on average), further offsets the sensible heat flux warming effect (+0.085 K). Another attribution method IBM demonstrates that the annual cooling effect of irrigation is mostly induced by changes in aerodynamic resistance (−0.175 K), whereas the biophysical contributions of albedo (−0.0005 K) and Bowen ratio (+0.001 K) have a negligible impact on LST. This study provides a useful reference for assessing local climate impact of irrigation when implementing environmental protection projects.

Eye Region Surface Temperature and Corticosterone Response to Acute Stress in a High-Arctic Seabird, the Little Auk.

Simple SummaryThermography, which is a method of measuring the heat emitted by various regions of the body, may be useful in detection of a heat increase in response to stress in vertebrates. Using this method, we studied how body surface temperature in eye-region (TEYE) changes in response to short-term stress (capturing and handling) in a wild-living, medium-sized polar seabird, the Little Auk. To this end, we measured TEYE in birds twice: first time—just after their capturing and initial handling and then second—after 30 min of keeping them in a bag. To control birds’ stress response, at the same time we made thermography, and we also collected blood samples from all the individuals, to establish the level of corticosterone (CORT, stress hormone). We found that both TEYE and CORT increased in response to the experimental procedure, although the strength of the TEYE and CORT increase were not related to each other. This indicates that thermography is a good tool for detection of initiation of birds’ reaction to a stress, which may be further useful in other studies, e.g., where there is a need to establish birds’ stress response non-invasively. Measuring changes in surface body temperature (specifically in eye-region) in vertebrates using infrared thermography is increasingly applied for detection of the stress reaction. Here we investigated the relationship between the eye-region temperature (TEYE; measured with infrared thermography), the corticosterone level in blood (CORT; stress indicator in birds), and some covariates (ambient temperature, humidity, and sex/body size) in a High-Arctic seabird, the Little Auk Alle alle. The birds responded to the capture-restrain protocol (blood sampling at the moment of capturing, and after 30 min of restrain) by a significant TEYE and CORT increase. However, the strength of the TEYE and CORT response to acute stress were not correlated. It confirms the results of a recent study on other species and all together indicates that infrared thermography is a useful, non-invasive measure of hypothalamic-pituitary-adrenal (HPA) axis reactivity under acute activation, but it might not be a suitable proxy for natural variation of circulating glucocorticoid levels.

Marine aquaculture in the pacific coast of Costa Rica: Identifying the optimum areas for a sustainable development

Sustainable marine aquaculture requires the definition of adequate areas for its development, where the productive activity has a lower impact on the environment and avoid conflicts with other coastal activities. The aim of this research is to identify the potential areas for marine aquaculture operations in the central and northern Pacific coast of Costa Rica, considering five fish species of commercial interest and three operation scale scenarios (large, medium and small scale). The mapping procedure considers the biological suitability for the species to have an optimum development, the structural suitability for the fish cages to endure the environmental conditions (mainly waves and currents), and the operational suitability for operation and maintenance activities associated to the fish production (e.g. feeding, harvesting, maintenance). Sea surface temperature, salinity, water clarity, wind speed and currents in open coasts regions were obtained from global models and satellite data. Currents and wave data in the Gulf of Nicoya, one of the main estuaries of the country, were modeled numerically. Available docking sites, marine protected areas and tourism sites were used and obtained from the corresponding national official entities. Results show a high potential for marine aquaculture projects, specifically for large and medium scale operations. Three out of five study species present high suitability in most of the study site, and the other two species present promising results in the Gulf of Nicoya. Small scale operations have several areas with high suitability for marine aquaculture projects, with extensions ranging from 101 km2 to 2 118 km2 depending on the species. At a regional scale, the Pacific coast of Costa Rica presents high potential for fish aquaculture, being a promising development medium for coastal communities as long as it is environmentally sustainable and compatible with other coastal activities such as tourism.

The effects of sky view factor on ground surface temperature in cold regions – A case from Xi'an, China

Integrated implementation of spatial and climate information is important for urban thermal environmental optimization. Sky view factor (SVF) is an urban form evaluation index widely used to study the relationship between geometrical parameters and microclimate characteristics. This relationship depends on the climate condition and the time scale of the study. We studied the influence of SVF on microclimate of typical high-rise street canyons of Xi'an in winter and conducted comparative simulations based on different street canyon geometries, which calculated hourly ground surface temperature (GST). We used 2 kinds of method to establish the correlation between SVF and GST - the statistical regression and physical model regression. With the statistical regression, we found a significant negative correlation coefficient of −0.87 between SVF and nighttime GST and a positive correlation coefficient of 0.53 between the SVF and daytime GST. The results based on physical model regression, however, showed that an increase of 0.1 in SVF caused daytime GST drops by 0.06 °C–0.49 °C. Whether separating the change in direct solar radiation levels accompanied by the changes in SVF was the main factor that leads to the difference in determine the relationship between SVF and daytime GST under the two methods. For the environment with large shadow fraction (SF), such as high-rise street canyons, we recommend the physical model regression as the regression mechanism between SVF and GST. Results of this study can be used in environmental urban planning standards.

Опыт разработки методики долгосрочного прогноза сроков вскрытия ото льда рек бассейна р. Вятки

An attempt is made to develop a method for long-term forecasting of the ice breakup time for the Vyatka River basin, to identify the impact of the distribution of sea surface temperature and geopotential height in the informative regions at the levels H100 and H500 over the Northern Hemisphere on the river ice breakup. The location and boundaries of the informative regions in the fields of H100 and H500 were revealed by the discriminant analysis, the EOF expansion coefficients of the fields of anomalies of monthly mean values of H100 and H500 for January and February and the anomalies of monthly mean sea surface temperature in the North Atlantic and Northwest Pacific were used as potential predictors. The stepwise regression analysis allowed deriving good and satisfactory (S/σ = 0.45–0.73) complex prognostic equations for forecasting the ice breakup time for the Vyatka River basin. The essential influence of H100 and H500 geopotential height fields and the spatial distribution of sea surface temperature anomalies in the North Atlantic and Northwest Pacific in January and February on the river ice breakup time is revealed. It is proposed to improve the method by considering the impact of air temperature, maximum ice thickness per winter, and other indirect characteristics on the processes of river ice breakup in the Vyatka River basin. Keywords: ice regime, long-range forecast, river ice breakup, expansion coefficients, geopotential height fields, spring ice phenomena, energy-active zones of the oceans, complex prognostic equation

Опыт разработки методики долгосрочного прогноза сроков вскрытия ото льда рек бассейна р. Вятки

An attempt is made to develop a method for long-term forecasting of the ice breakup time for the Vyatka River basin, to identify the impact of the distribution of sea surface temperature and geopotential height in the informative regions at the levels H100 and H500 over the Northern Hemisphere on the river ice breakup. The location and boundaries of the informative regions in the fields of H100 and H500 were revealed by the discriminant analysis, the EOF expansion coefficients of the fields of anomalies of monthly mean values of H100 and H500 for January and February and the anomalies of monthly mean sea surface temperature in the North Atlantic and Northwest Pacific were used as potential predictors. The stepwise regression analysis allowed deriving good and satisfactory (S/σ = 0.45–0.73) complex prognostic equations for forecasting the ice breakup time for the Vyatka River basin. The essential influence of H100 and H500 geopotential height fields and the spatial distribution of sea surface temperature anomalies in the North Atlantic and Northwest Pacific in January and February on the river ice breakup time is revealed. It is proposed to improve the method by considering the impact of air temperature, maximum ice thickness per winter, and other indirect characteristics on the processes of river ice breakup in the Vyatka River basin. Keywords: ice regime, long-range forecast, river ice breakup, expansion coefficients, geopotential height fields, spring ice phenomena, energy-active zones of the oceans, complex prognostic equation

Sensitivity of WRF-derived hydrometeorological extremes to sea surface temperatures in regions with complex topography and diverse climate

This study investigates the impact of sea surface temperature (SST) describing the lower boundary of Weather Research and Forecasting (WRF) model on the extreme weather events that occurred on the Mediterranean (MED) and the Eastern Black Sea (EBS) regions of Turkey. For each region, one extreme event case is selected and characterized as a summer convective system in EBS and as a winter synoptic system in MED region. The SST impact on the WRF model forecasts of these events is accomplished in two ways. First, the SST analysis is conducted by making a 10-days simulation for each event with and without activating the SST options (update and skin options) available in the model configuration. In these runs, the selected initial and boundary condition datasets, Global Forecasting System (GFS) for the MED region and the ERA5 for the EBS regions, provide corresponding internal SST data. Second, the prediction performance of the model is evaluated among the simulations of non-external, time-varying (GFS and ERA5 SST) and external, time–varying, high-resolution SST products (The Group for High Resolution Sea Surface Temperature; GHRSST, Medspiration, and NCEP) for each event. The results show that the WRF model simulations, even for short-term event predictions, are highly sensitive to time-variant SST options. The overestimation and high spreading feature of maximum and total precipitation are realistically reduced by time-variant SST products. The Medspiration and the NCEP sources for the MED region and the GHRSST and the Medspiration sources for the EBS region yielded warmer SSTs among the simulations. By establishing the amplified air-sea interactions, these sources provide more appropriate peak precipitation distributions in both regions. Furthermore, based on this study, the effect of using high-resolution SST (GHRSST and Medspiration) is more prominent in predicting convective event developed over complex topography of the EBS while the resolution effect is not much critical for synoptic system simulation even under the complex topography in MED. Lastly, the highest mean correlation of conditional hourly rain is calculated as 0.65 with the Medspiration product on MED and 0.48 with the GHRSST product on the EBS region.

Retrieval and analysis of land surface temperature in permafrost regions in Northeast China based on AMSR2 data

Retrieval and analysis of land surface temperature in permafrost regions in Northeast China based on AMSR2 data

Forest-fire aerosol–weather feedbacks over western North America using a high-resolution, online coupled air-quality model

Abstract. The influence of both anthropogenic and forest-fire emissions, and their subsequent chemical and physical processing, on the accuracy of weather and air-quality forecasts, was studied using a high-resolution, online coupled air-quality model. Simulations were carried out for the period 4 July through 5 August 2019, at 2.5 km horizontal grid cell size, over a 2250×3425 km2 domain covering western Canada and USA, prior to the use of the forecast system as part of the FIREX-AQ ensemble forecast. Several large forest fires took place in the Canadian portion of the domain during the study period. A feature of the implementation was the incorporation of a new online version of the Canadian Forest Fire Emissions Prediction System (CFFEPSv4.0). This inclusion of thermodynamic forest-fire plume-rise calculations directly into the online air-quality model allowed us to simulate the interactions between forest-fire plume development and weather. Incorporating feedbacks resulted in weather forecast performance that exceeded or matched the no-feedback forecast, at greater than 90 % confidence, at most times and heights in the atmosphere. The feedback forecast outperformed the feedback forecast at 35 out of 48 statistical evaluation scores, for PM2.5, NO2, and O3. Relative to the climatological cloud condensation nuclei (CCN) and aerosol optical properties used in the no-feedback simulations, the online coupled model's aerosol indirect and direct effects were shown to result in feedback loops characterized by decreased surface temperatures in regions affected by forest-fire plumes, decreases in stability within the smoke plume, increases in stability further aloft, and increased lower troposphere cloud droplet and raindrop number densities. The aerosol direct and indirect effect reduced oceanic cloud droplet number densities and increased oceanic raindrop number densities, relative to the no-feedback climatological simulation. The aerosol direct and indirect effects were responsible for changes to the near-surface PM2.5 and NO2 concentrations at greater than the 90 % confidence level near the forest fires, with O3 changes remaining below the 90 % confidence level. The simulations show that incorporating aerosol direct and indirect effect feedbacks can significantly improve the accuracy of weather and air-quality forecasts and that forest-fire plume-rise calculations within an online coupled model change the predicted fire plume dispersion and emissions, the latter through changing the meteorology driving fire intensity and fuel consumption.

Improvement in the Prediction of Summer Precipitation in the North China−Hetao Region Using the Tropospheric Temperature Over the Tibetan Plateau in Spring

We investigated the relationship between the spring tropospheric temperature over the Tibetan Plateau (TPT) and summer precipitation in eastern China on an interannual timescale using the monthly mean ERA-Interim reanalysis dataset, the HadISST dataset and the daily mean precipitation dataset for China. We found that there is a significant positive correlation between the spring TPT and summer precipitation in the North China−Hetao region. The relationship is manifested in the context of the East Asia–Pacific pattern teleconnection. In the high spring TPT index years, the geopotential height anomalies over East Asia and the western North Pacific present a negative phase of the East Asia–Pacific pattern teleconnection in the subsequent summer. This circulation pattern is beneficial for the water vapor transport from the western Pacific to inland, which further transport to the North China−Hetao region from the Yangtze River–Yellow rivers region. Anomalous upward motion occurs in the North China–Hetao region, which increases precipitation. The East Asian subtropical westerly jet shifts further north and the South Asian high weakens and shrinks westward. These conditions all favor an increase in precipitation over the North China–Hetao region. The spring TPT plays an important part in the prediction of summer precipitation in the North China−Hetao region. The improvement in the use of the spring TPT to predict summer precipitation in the North China–Hetao region is examined by comparing the prediction equations with and without the prediction factor of the spring TPT on the basis of the sea surface temperatures in key regions. After considering the impact of the spring TPT, the explanatory variance of the prediction equation for precipitation in the North China–Hetao region increases by 17.3%.

Wetlands Cool Land Surface Temperature in Tropical Regions but Warm in Boreal Regions

Wetlands play a critical role in global hydrological and biogeochemical cycles. Regulating the regional climate is one of the most important ecosystem services of natural wetlands. However, the impact of wetlands on local temperature on the global scale and the attribution is still unclear. This study utilizes the satellite-based products (land surface temperature (LST), albedo, and evapotranspiration (ET)) to evaluate the difference in LST between wetlands and their adjacent landcover types and the possible drivers. Here we show that on average for the whole year, wetlands have a cooling effect in tropical regions, but have a warming effect in boreal regions. The impacts of wetlands on LST show great seasonality in the boreal regions; i.e., the wetlands have a warming effect in winter but a cooling effect in summer. The difference in albedo and ET between wetlands and the other landcover types only interprets 30% of temporal variation of the difference in LST. Due to the large water storage in wetlands, the ground heat flux (G) may interpret the rest of the impact, absorbing energy in summer and releasing energy in winter in wetlands, which has often been neglected in previous studies. Our results indicate that it is critical to comprehensively consider the effects of wetland restoration in different regions to realize potential climatic benefits in the future.

Ecological Fitness of Vibrio cholerae, Vibrio parahaemolyticus, and Vibrio vulnificus in a Small-Scale Population Dynamics Study

The potential spread of infectious diseases in response to climate change and rising sea surface temperatures in temperate regions has been a growing concern for the past several decades. Extreme heat waves in the North Atlantic and North Sea regions have been correlated with an increase in human Vibrio infections; of particular concern to human health are Vibrio cholerae, Vibrio parahaemolyticus, and Vibrio vulnificus. While these species are well-known to cause disease in humans, most environmental strains are not pathogenic. Studying not only the behavior of the pathogenic strains, but that of non-pathogenic environmental isolates, may better elucidate their ecological relationship in their native microbiome and the dispersal of these species in coastal regions. Using red fluorescent protein-tagged and gentamycin-resistant V. cholerae, V. parahaemolyticus, and V. vulnificus strains, we investigated whether increasing temperatures confer greater competitive fitness to these species when incubated within a natural North Sea water sample still containing its microbiome in a small-scale niche investigation. Increased incubation temperatures alone did not confer a competitive advantage to V. cholerae, V. parahaemolyticus, and V. vulnificus. The microbial community could limit Vibrio growth at all temperatures. To the best of our knowledge, we also demonstrate the first (albeit unintentional) genetic modification of multiple species of marine bacteria through the introduction of a genetically modified V. vulnificus strain into a natural water sample in a contained system.

Mapping Surficial Soil Particle Size Fractions in Alpine Permafrost Regions of the Qinghai–Tibet Plateau

Spatial information of particle size fractions (PSFs) is primary for understanding the thermal state of permafrost in the Qinghai-Tibet Plateau (QTP) in response to climate change. However, the limitation of field observations and the tremendous spatial heterogeneity hamper the digital mapping of PSF. This study integrated log-ratio transformation approaches, variable searching methods, and machine learning techniques to map the surficial soil PSF distribution of two typical permafrost regions. Results showed that the Boruta technique identified different covariates but retained those covariates of vegetation and land surface temperature in both regions. Variable selection techniques effectively decreased the data redundancy and improved model performance. In addition, the spatial distribution of soil PSFs generated by four log-ratio models presented similar patterns. Isometric log-ratio random forest (ILR-RF) outperformed the other models in both regions (i.e., R2 ranged between 0.36 to 0.56, RMSE ranged between 0.02 and 0.10). Compared with three legacy datasets, our prediction better captured the spatial pattern of PSFs with higher accuracy. Although this study largely improved the accuracy of spatial distribution of soil PSFs, further endeavors should also be made to improve model accuracy and interpretability for a better understanding of the interaction and processes between environmental predictors and soil PSFs at permafrost regions.

Development of a new ENSO index to assess the effects of ENSO on temperature over southern Vietnam

The aim of this study was to assess the effects of El Nino and the Southern Oscillation (ENSO) on the temperature in southern Vietnam (TSV) and to establish a new ENSO index for the study area (named southern Vietnam Enso Index, VEI). Data used in this study included TSV, sea surface temperature (SST) in Nino regions, sea level pressure (SLP) at Tahiti and Darwin, and ENSO indices. The results showed that, among all ENSO indices, the oceanic Nino Index (ONI) and Japan Meteorological Agency ENSO index (JEI) gave a better correlation with TSV, but their correlation coefficients (R) were relatively low. That may suggest that these indices could be used with low efficiency for climate monitoring and prediction. The VEI was built based on the pair of SST in Nino 3.4 and Nino.West, which gained a higher correlation coefficient with the temperature in southern Vietnam in comparison with other ENSO indices. The lag time between VEI and TSV was about 5 months, which was one month longer than the one between ONI and TSV. Moreover, analyzing the temperature difference between the warm and cold phases also indicated that using VEI led to a higher contrast than using ONI. In brief, the newly established VEI could be more suitable for the study area.

Remote Control of Sea Surface Temperature on the Variability of Tropical Cyclone Activity Affecting Vietnam’s Coastline

AbstractThis study examines the teleconnection between sea surface temperature (SST) in different ocean regions and tropical cyclone (TC) activity affecting Vietnam’s coastal region. Using spatial correlation and principal component analyses, it is found that the variability of TCs affecting Vietnam during 1982–2018 is remotely connected with SST in the Indian Ocean, the southwestern Pacific Ocean, and the northern Philippine Sea. Among the three regions, SST in the northern Philippine Sea displays the most significant inverse relationship with TC activity in the South China Sea (SCS), with lower June–November TC accumulated energy (ACE) for warmer northern Philippine Sea SST. Further analyses of large-scale atmospheric circulations show that this teleconnection between the northern Philippine Sea SST and TC activity in the SCS is linked to the East Asian subtropical jet (EASJ). Principal component analyses of the 200-hPa zonal wind associated with EASJ capture indeed a strong relationship between the second principal component, which characterizes the EASJ intensity, and ACE. Specifically, higher EASJ intensity corresponding to colder northern Philippine Sea SST would enhance large-scale ascending motion and low-level cyclonic anomalies in the SCS, which are favorable for TC formation and result in an overall increased ACE. Examination of the correlation between this second principal component and the northern Philippine Sea SST confirms that this correlation is statistically significant at a 95% confidence level. In this regard, these results support the Pacific–Japan teleconnection between the northern Philippine Sea SST and TC activity in the SCS.

The impact of impervious surface, vegetation, and soil areas on land surface temperatures in a semi-arid region using Landsat satellite images enriched with Ndaisi method data.

Impervious surfaces are a significant issue of both urbanization and environmental assessment. However, it is a problem to classify impervious surface (IS) and soil areas as separate classes in land cover classification. The objectives of this study are to obtain impervious surface, vegetation, and soil areas clearly of an urban complex with a semi-arid climate and to better determine the relationships of IS, vegetation, and soil areas with land surface temperatures (LSTs). For this purpose, IS, vegetation, and soil areas in a semi-arid city of Turkey-Kayseri city were identified by using Normalized Difference Anthropogenic Impervious Surface Index (NDAISI) data and support vector machine (SVM) method together in the classification of different areas. Landsat 5, 7, and 8 satellite images of 1987, 2000, and 2013 were used, respectively, in this study. Afterward, the effects of these areas on LSTs were analyzed. Regression analysis was used to determine the relationships between land cover areas and surface temperatures. To better demonstrate these relationships, besides common pixel-based and classical regional-based approaches, a new density-based regional analysis approach was proposed. This study is an innovative one in terms of detecting IS and indicating relationships between land cover areas and surface temperatures in semi-arid regions. Another innovation of the study is related to the results produced. The results showed that decreasing LST values were observed with increasing IS and vegetation cover values and increasing LST values were observed with increasing soil areas. The present findings may provide significant contributions to the literature and will facilitate the development of urban planning strategies in semi-arid regions.

Evaluating FY3C-VIRR reconstructed land surface temperature in cloudy regions

ABSTRACT Missing values in land surface temperature (LST) data are often observed in the cloud-sheltered area, thereby seriously limiting the spatiotemporal continuity of LST. In this work, Remotely Sensed Daily Land Surface Temperature Reconstruction model(RSDAST) is used to gap-fill the pixels sheltered by clouds in FY-3 C/VIRR LST. Result shows that the cloud pixels in VIRR and MODIS original LST (OLST) product can be reconstructed accurately, but the reconstruction accuracy of MODIS LST is better compared to VIRR based on the RSDAST model. In addition, the reconstruction accuracy of VIRR and MODIS LST decreases with the increase in cloud coverage, and the reduction of the reconstruction accuracy of VIRR LST is larger than that of MODIS data. The number of effective dry-wet edge fitted by VIRR RLST/NDVI scatterplot was higher than that of OLST/NDVI, and the number of clear sky pixels in Reconstructed TVDI (RTVDI) images increased significantly, indicating that the RSDAST expands the temporal resolution and spatial coverage of infrared remote sensing data under cloudy conditions. Moreover, in DOY150–DOY243, the correlation between RTVDI and soil moisture is better than that of Original TVDI (OTVDI), indicating that the RSDAST improves the monitoring ability of soil moisture in these conditions.