Radiometric Temperature Research Articles

The impact of cool and green roofs on summertime temperatures in the cities of Jerusalem and Tel Aviv

Experiments were conducted to assess the potential impact of cool and/or green roofs to mitigate summertime conditions in two cities of Israel, Jerusalem and Tel Aviv, which differ in elevation, humidity, and housing density. Tel Aviv is located along the coastal plain and characterized by low- and medium-density housing in a humid climate. Jerusalem is in the central mountains (elevation >750 m), and characterized by medium- and high-density housing in a dry climate. The fraction of potential roofs available for reflective cooling and the fraction of green versus impervious surface areas were estimated from “Google Earth.” Both were utilized as input into the Urban Canopy Model (UCM) within the Weather Research and Forecasting model, along with the residential building density. Increasing the albedo (cool roofs) had a larger impact on roof surface radiometric temperatures than covering the roof with irrigated soil and vegetation. Cool roof surface temperature differences were about 20 °C, compared to between 10 and 15 °C for wet soils with vegetation. The impact of varying albedo on 2-m. surface temperatures was about 0.4 °C, and the impact of varying soil moisture 0.1 °C. Increasing the leaf area index from 1.5 to 4.5 had a comparatively small impact on 2 m temperatures. Imposed anthropomorphic heating added about 0.2 °C to 2-m surface temperatures, which was less than values found in other studies conducted with more sophisticated building energy models. The surface temperature and heat index within Tel Aviv were more sensitive to mitigation efforts than those in Jerusalem, but both cities could benefit from mitigation efforts.

A Methodology for Comparing the Surface Urban Heat Island in Selected Urban Agglomerations Around the World from Sentinel-3 SLSTR Data

Retrieval of land surface temperature (LST) from satellite data allows to estimate the surface urban heat island (SUHI) as the difference between the LST obtained in the urban area and the LST of its surroundings. However, this definition depends on the selection of the urban and surroundings references, which translates into greater difficulty in comparing SUHI values in different urban agglomerations across the world. In order to avoid this problem, a methodology is proposed that allows reliable quantification of the SUHI. The urban reference is obtained from the European Space Agency Climate Change Initiative Land Cover and three surroundings references are considered; that is, the urban adjacent (Su), the future adjacent (Sf), and the peri-urban (Sp), which are obtained from mathematical expressions that depend exclusively on the urban area. In addition, two formulations of SUHI are considered: SUHIMAX and SUHIMEAN, which evaluate the maximum and average SUHI of the urban area for each of the three surrounding references. As the urban population growth phenomenon is a world-scale problem, this methodology has been applied to 71 urban agglomerations around the world using LST data obtained from the sea and land surface temperature radiometer (SLSTR) on board Sentinel-3A. The results show average values of SUHIMEAN of (1.8 ± 0.9) °C, (2.6 ± 1.3) °C, and (3.1 ± 1.7) °C for Su, Sf, and Sp, respectively, and an average difference between SUHIMAX and SUHIMEAN of (3.1 ± 1.1) °C. To complete the study, two additional indices have been considered: the Urban Thermal Field Variation Index (UFTVI) and the Discomfort Index (DI), which proved to be essential for understanding the SUHI phenomenon and its consequences on the quality of life of the inhabitants.

Land Surface Temperature and Emissivity Retrieval From Nighttime Middle-Infrared and Thermal-Infrared Sentinel-3 Images

The Sea and Land Surface Temperature Radiometer (SLSTR) onboard the two Sentinel-3 satellites provides daily global coverage observation at daytime and nighttime. The split-window (SW) algorithm is currently used to retrieve the land surface temperature (LST) from SLSTR images; however, this algorithm has to utilize visible and near-infrared (VNIR) images and land cover to determine pixel emissivity. For nighttime observation, VNIR cannot be observed, and this limitation complicates the LST retrieval from nighttime images using the SW algorithm. This article proposed a three-channel temperature–emissivity separation (TES) algorithm that estimates the nighttime LST and emissivity from one middle-infrared (MIR) and two thermal-infrared (TIR) nighttime Sentinel-3 SLSTR images. The sensitive analysis showed that the algorithm could theoretically retrieve the LST and emissivity with errors less than 0.8 K and 0.015, respectively. Ground validation showed that the nighttime LST retrieval error was approximately 1.84 K and the bias was approximately −0.33 K. Finally, the TES algorithm was applied to obtain the LST and emissivity images over northern China as an example. The emissivity retrieved from the nighttime observation can be used in the daytime SW algorithm to improve its feasibility in the LST retrieval process.

A novel on water environment monitoring method based on millimeter wave radiometric characteristics

AbstractAiming at the increasingly serious water pollution problem, this article proposes a floating waste monitoring method based on the characteristics of millimeter wave radiation. The method is based on the basic principles of microwave radiation and the radiometric characteristics of floating wastes. In this method, we establish a multilayer media model of floating wastes and get the radiometric temperature of different pollutants. The database of wastes based on radiometric temperature of water surface has been proposed and established. Simulation and experimental show that there is a significant difference between the floating wastes and the surface water radiometric temperature, which can be distinguished different pollutants through contrast and achieved the purpose of environmental monitoring.

Investigation and validation of algorithms for estimating land surface temperature from Sentinel-3 SLSTR data

Land surface temperature (LST) is an important indicator of global ecological environment and climate change. The Sea and Land Surface Temperature Radiometer (SLSTR) onboard the recently launched Sentinel-3 satellites provides high-quality observations for estimating global LST. The algorithm of the official SLSTR LST product is a split-window algorithm (SWA) that implicitly assumes and utilizes knowledge of land surface emissivity (LSE). The main objective of this study is to investigate alternative SLSTR LST retrieval algorithms with an explicit use of LSE. Seventeen widely accepted SWAs, which explicitly utilize LSE, were selected as candidate algorithms. First, the SWAs were trained using a comprehensive global simulation dataset. Then, using simulation data as well as in-situ LST, the SWAs were evaluated according to their sensitivity and accuracy: eleven algorithms showed good training accuracy and nine of them exhibited low sensitivity to uncertainties in LSE and column water vapor content. Evaluation based on two global simulation datasets and a regional simulation dataset showed that these nine SWAs had similar accuracy with negligible systematic errors and RMSEs lower than 1.0 K. Validation based on in-situ LST obtained for six sites further confirmed the similar accuracies of the SWAs, with the lowest RMSE ranges of 1.57–1.62 K and 0.49−0.61 K for Gobabeb and Lake Constance, respectively. While the best two SWAs usually yielded good accuracy, the official SLSTR LST generally had lower accuracy. The SWAs identified and described in this study may serve as alternative algorithms for retrieving LST products from SLSTR data.

Validation of Sentinel-3A SLSTR derived Sea-Surface Skin Temperatures with those of the shipborne M-AERI

The Skin Sea-Surface Temperature (SSTskin) derived from satellite measurements is one of the critical factors for determining ocean-atmosphere interactions in climate prediction and ocean research. Sentinel-3A is a European Earth Observation satellite mission developed to support ocean, land, and atmospheric applications. We compare three years of SSTskin from the Sea and Land Surface Temperature Radiometer (SLSTR) on board the Sentinel-3A satellite from July 2017–March 2019 with independent data from Marine-Atmospheric Emitted Radiance Interferometers (M-AERIs) deployed on research cruises. The comparison results show an average difference of −0.098 K and Robust Standard Deviation of 0.296 K between SLSTR and M-AERI SSTskin values; the average value meets the pre-launch scientific objective of a mean accuracy <0.1 K. Differences between four SSTskin retrieval algorithms have been investigated, the results show that the Dual-view 3 channels night time algorithm (D3) is better than other algorithms. This study involves determining the error and uncertainty characteristics of the SST retrievals in terms of factors that influence the accuracies of the satellite SST's, and we hope this information will be useful to improve the SLSTR atmospheric correction algorithms.

Wideband Epidermal Antenna for Medical Radiometry.

Microwave thermometry is a noninvasive and passive technique for measuring internal body temperature. Wearable compact antennas, matched to the specific body area, are required for this method. We present a new epidermal wideband antenna for medical radiometry. The double asymmetric H-shaped slot antenna was designed to be matched to different parts of the body without fat layers. The slots are fed by a short-circuited microstrip line in order to decrease size and back radiation, thus reducing potential interferences. In this way, contribution to radiometric temperature due to back radiation is lower than 4%, versus the 20% of the volume under investigation, over the whole operating frequency band. The designed prototype was manufactured on a flexible substrate. The antenna is a very small size, to make it comfortable and suitable for being used by patients with different body mass indexes. The double H-shaped antenna shows good wideband matching results from around 1.5 GHz up to 5 GHz, in different body locations such as the neck, foot instep and foot sole.

Harmonization of Space-Borne Infra-Red Sensors Measuring Sea Surface Temperature

Sea surface temperature (SST) is observed by a constellation of sensors, and SST retrievals are commonly combined into gridded SST analyses and climate data records (CDRs). Differential biases between SSTs from different sensors cause errors in such products, including feature artefacts. We introduce a new method for reducing differential biases across the SST constellation, by reconciling the brightness temperature (BT) calibration and SST retrieval parameters between sensors. We use the Advanced Along-Track Scanning Radiometer (AATSR) and the Sea and Land Surface Temperature Radiometer (SLSTR) as reference sensors, and the Advanced Very High Resolution Radiometer (AVHRR) of the MetOp-A mission to bridge the gap between these references. Observations across a range of AVHRR zenith angles are matched with dual-view three-channel skin SST retrievals from the AATSR and SLSTR. These skin SSTs act as the harmonization reference for AVHRR retrievals by optimal estimation (OE). Parameters for the harmonized AVHRR OE are iteratively determined, including BT bias corrections and observation error covariance matrices as functions of water-vapor path. The OE SSTs obtained from AVHRR are shown to be closely consistent with the reference sensor SSTs. Independent validation against drifting buoy SSTs shows that the AVHRR OE retrieval is stable across the reference-sensor gap. We discuss that this method is suitable to improve consistency across the whole constellation of SST sensors. The approach will help stabilize and reduce errors in future SST CDRs, as well as having application to other domains of remote sensing.

Validation of ASTER Emissivity Retrieval Using the Mako Airborne TIR Imaging Spectrometer at the Algodones Dune Field in Southern California, USA

Validation of emissivity (ε) retrievals from spaceborne thermal infrared (TIR) sensors typically requires spatial extrapolations over several orders of magnitude for a comparison between centimeter-scale laboratory ε measurements and the common decameter and lower resolution of spaceborne TIR data. In the case of NASA’s Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) temperature and ε separation algorithm (TES), this extrapolation becomes especially challenging because TES was originally designed for the geologic surface of Earth, which is typically heterogeneous even at centimeter and decameter scales. Here, we used the airborne TIR hyperspectral Mako sensor with its 2.2 m/pixel resolution, to bridge this scaling issue and robustly link between ASTER TES 90 m/pixel emissivity retrievals and laboratory ε measurements from the Algodones dune field in southern California, USA. The experimental setup included: (i) Laboratory XRD, grain size, and TIR spectral measurements; (ii) radiosonde launches at the time of the two Mako overpasses for atmospheric corrections; (iii) ground-based thermal measurements for calibration, and (iv) analyses of ASTER day and night ε retrievals from 21 different acquisitions. We show that while cavity radiation leads to a 2% to 4% decrease in the effective emissivity contrast of fully resolved scene elements (e.g., slipface slopes and interdune flats), spectral variability of the site when imaged at 90 m/pixel is below 1%, because at this scale the dune field becomes an effectively homogeneous mixture of the different dune elements. We also found that adsorption of atmospheric moisture to grain surfaces during the predawn hours increased the effective ε of the dune surface by up to 0.04. The accuracy of ASTER’s daytime emissivity retrievals using each of the three available atmospheric correction protocols was better than 0.01 and within the target performance of ASTER’s standard emissivity product. Nighttime emissivity retrievals had lower precision (&lt;0.03) likely due to residual atmospheric effects. The water vapor scaling (WVS) atmospheric correction protocol was required to obtain accurate (&lt;0.01) nighttime ASTER emissivity retrievals.

On the retrieval of aerosol optical depth over cryosphere using passive remote sensing

The lack of aerosol information over the cryosphere introduces large uncertainties to our understanding of phenomenon, known as the Arctic Amplification (AA) and its feedback mechanisms. The aerosol optical depth (AOD) describes the optical characteristics of aerosol loading. This paper describes a novel algorithm, which retrieves AOD above snow-covered regions from the measurements of the up-welling radiation at the top of atmosphere, observed by the Advanced Along-Track Scanning Radiometer (AATSR) and the Sea and Land Surface Temperature Radiometer (SLSTR) instruments. The algorithm optimizes the generic eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) approach for longer wavelengths over the cryosphere. The algorithm utilizes the characteristics of solar bidirectional distribution properties of snow and aerosol at wavelength 3.7 μm to derive above-snow-AOD. Since the impact of fine-mode aerosol on 3.7 μm is ignorable, the retrieved AOD in this manuscript represents mainly coarse-mode dominated part. A novel method to extract the solar reflection part at 3.7 μm is presented and used in the surface parameterization. Two aerosol types (sea salt-dominated and dust-dominated) are used and the best-fit type is derived by an iterative procedure, using a Look-Up-Table (LUT) approach. Sensitivity studies of the impact on the retrieved AOD using XBAER algorithm, which investigate the impacts of aerosol type, snow surface emissivity and potential cloud contamination under typical AATSR observation conditions, are presented. The sensitivity studies show that the surface parametrization and aerosol typing are suitable for the retrieval of above-snow-AOD over the Arctic snow-covered region. AOD observations retrieved in this study from AATSR (2002–2012) observation collocated with those from the Aerosol Robotic Network (AERONET) sites over Greenland show good agreement. 72.1% of the match-ups fall into the expected error envelope of (±0.15AOD ± 0.025). The AATSR derived above-snow-AOD at 0.55 μm research product has also been compared with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) aerosol product, the Mineral Aerosols Profiling from Infrared Radiances (MAPIR) derived Infrared Atmospheric Sounding Interferometer (IASI) AOD research product, and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) AOD simulations over Greenland on April 2011. The comparison reveals that all datasets show similar patterns for the AOD above Greenland. The AOD is smaller in central Greenland and larger over the coastline regions. The XBAER derived above-snow-AOD has improved coverage, as compared to that of the existing AATSR aerosol product. The transition between above-snow-AOD and AOD derived over surrounding ocean surfaces does not indicate any systematic errors. Two aerosol transport events have been well-captured by the XBAER derived above-snow-AOD research product. The new algorithm is also applied to the SLSTR onboard Sentinel-3 demonstrating new SLSTR above-snow-AOD data products, and its value for research in the changing AOD during the period of Arctic Amplification.

Estimation of surface heat fluxes using multi-angular observations of radiative surface temperature

The retrieval of canopy and soil component temperatures for estimating evapotranspiration in the two source energy balance (TSEB) model depends on a relatively accurate partitioning of soil/substrate evaporation and canopy transpiration along with the soil and vegetation temperature components. To avoid the need for a Priestley-Taylor based transpiration formulation, this study applies the TSEB model using radiometric land surface temperature observations at multiple view angles from an airborne sensor for estimating soil and canopy temperatures directly. This direct partitioning between soil and canopy temperatures applied with the TSEB formulation improved the agreement between observed and modeled surface heat fluxes, reducing mean absolute percentage error (MAPE) in latent heat fluxes (LE) with flux tower observations from nearly 20% using the original Priestley-Taylor based TSEB model (TSEB-PT) to 15% using TSEB with thermal infrared observations from two substantially different view angles (TSEB-2AG) to nearly 5% using multiple (~6) view angles (TSEB-6AG). Moreover, TSEB-6AG is shown to compute physically realistic spatially-distributed LE for a range of vegetation cover and environmental conditions over the imaged domain. Values of MAPE for sensible heat (H) tended to be larger for all three models due to the fact that tower measurements tended to be located in well irrigated and densely vegetated sites having relatively low H values. This increased accuracy of soil and vegetation component temperature separation using multiangle radiometric temperature observations is useful for evaluating the utility of single and dual view angle thermal radiometer measurements currently available for applying the TSEB model.

Dielectric and Emissive Properties of Sorghum (Jowar) Vegetation at C-Band Microwave Frequency

Abstract Microwave interaction with earth resources like soil and vegetation provides useful information for remote sensing techniques. Such interaction is mainly governed by a complex dielectric property of target material. This paper reports on laboratory measurements of complex dielectric constant of sorghum vegetation (leaves) at room temperature (30°C), at C-Band microwave frequency. Von Hippel (shorted waveguide) method is used to conduct the measurements. The measurements were performed for freshly cut sorghum leaves as a function of moisture content by using automated C-Band microwave bench set up with movable reflector. The least square fitting technique is used to calculate dielectric constant (e'), dielectric loss (e'') and errors in their measurements. Emissivity and radiometric brightness temperature is estimated from measured dielectric properties at different angle of incidence for dry and moist sorghum leaves using Fresnel equations. This study is useful for interpretation of microwave remote sensing of vegetation and applications specifically in agriculture

Nighttime Cool Skin Effect Observed from Infrared SST Autonomous Radiometer (ISAR) and Depth Temperatures

AbstractThe nighttime ocean cool skin signal ΔT [defined as skin sea surface temperature (SSTskin) minus depth SST (SSTdepth)] is investigated using 103 days of matchups between shipborne Infrared SST Autonomous Radiometer (ISAR) SSTskin and water intake SSTdepth at ~7.1–9.9-m depths, in oceans around Australia. Before data analysis, strict quality control of ISAR SSTskin data is conducted and possible diurnal warming contamination is carefully minimized. The statistical distribution of ΔT, and its dependencies on wind speed, heat flux, etc., are consistent with previous findings. The overall average ΔT value is −0.23 K. It is observed that the magnitude of the cool skin signal increases after midnight and a coolest skin offset (with an average value of −0.36 K) is found at around dawn. The dependency of ΔT on SST conditions is observed. Direct warm skin events are discovered when the net heat flux direction is from the atmosphere to the ocean, which is more likely to occur at high latitudes when the air is very humid and warmer than the SST. In addition, several cool skin models are validated: one widely used physical model performs best and can capture most skin-effect trends and details; the empirical models only reflect the basic features of the observed ΔT values. If the user cannot apply the physical model (due to, e.g., the algorithm complexity or missing inputs), then the empirical parameterization in the form proposed in a 2002 study can be used. However, we recommend using a new set of parameters, calculated in this study, based on much more representative dataset, and with more rigorous quality control.

Microwave Radiometer Instability Due to Infrequent Calibration

We directly quantify the effect of infrequent calibration on the stability of microwave radiometer temperature measurements (where a power measurement for the unknown source is acquired at a fixed time, but calibration data are acquired at variable earlier times) with robust and nonrobust implementations of a new metric. Based on our new metric, we also determine a component of uncertainty in a single measurement due to infrequent calibration effects. We apply our metric to experimental data acquired from experimental ground-based calibration data acquired from a NASA millimeter-wave imaging radiometer and a NIST radiometer (Noise Figure Radiometer-NFRad). Based on a stochastic model for the NFRad, we determine the random uncertainty of an empirical prediction model of our stability metric by a Monte Carlo method. For comparison purposes, we also present a secondary metric that quantifies stability for the case where calibration data are acquired at a fixed time, but power measurements for the unknown source are acquired at variable later times.

ТЕПЛОВЫЕ ДЕФОРМАЦИИ И РАДИОЯРКОСТНАЯ ТЕМПЕРАТУРА ЛЕДЯНОГО ПОКРОВА ПРЕСНЫХ ВОДОЁМОВ

The paper presents results of experimental studies of the deformation of a freshwater ice cover. The works were carried out on the Lake Arakhley located in the Trans-Baikal Region, where winters are characterized by small amount of snow and sharp daily changes in the air temperature reaching 25 °C. As a result of this, the temperature gradient of the surface layer of the ice cover exceeds 1 °C/cm. This causes formation of the dry cracks in the upper layers of the cover. The authors measured daily variations in the temperature of the ice cover at various depths by its thickness. Results of the experiment made possible to propose the explanation for the formation of dry cracks and the depth of them, which reaches 20 cm in the Trans-Baikal Region. According to studies using a differential strain gauge, it was found that the upper layer of the ice cover is in a stressed state due to changes in its temperature. This is evident from the fact that when the temperature of the upper layer of ice changes, the distance between the reference points slightly changes too. When the air temperature approaches the temperature of the «ice–water» phase transition, the ice cover is unloaded. We assume that the dry cracks can also be formed when the stress state of ice is released at even lower temperatures. Interest in these structural changes had been arisen in connection with possible variations in the electromagnetic properties of the ice cover, which can be detected by non-contact radio wave measurements. These variations result from the presence of a quasiliquid layer on the surfaces of dry cracks (together with hoar-frost and snow in them), which can exist down to a temperature of −90 °C. Its presence increases the complex relative permittivity of a medium consisting of a solid (ice) and a liquid phase (water film). Calculations of the radiometric temperature within the centimeter range in a flat-layer non-isothermal medium have shown that the presence of dry cracks in the ice cover increases radio temperature up to 5 K on both, vertical and horizontal polarizations. This value is recorded during radiometric measurements, and this factor should be taken into account during the remote sensing of freshwater ice covers.

Retrieving Soil and Vegetation Temperatures From Dual-Angle and Multipixel Satellite Observations

Land surface component temperatures (LSCTs), i.e., the temperatures of soil and vegetation, are important parameters in many applications, such as estimating evapotranspiration and monitoring droughts. However, the multiangle algorithm is affected due to different spatial resolution between nadir and oblique views. Therefore, we propose a combined retrieval algorithm that uses dual-angle and multipixel observations together. The sea and land surface temperature radiometer onboard ESA's Sentinel-3 satellite allows for quasi-synchronous dual-angle observations, from which LSCTs can be retrieved using dual-angle and multipixel algorithms. The better performance of the combined algorithm is demonstrated using a sensitivity analysis based on a synthetic dataset. The spatial errors in the oblique view due to different spatial resolution can reach 4.5 K and have a large effect on the multiangle algorithm. The introduction of multipixel information in a window can reduce the effect of such spatial errors, and the retrieval results of LSCTs can be further improved by using multiangle information for a pixel. In the validation, the proposed combined algorithm performed better, with LSCT root mean squared errors of 3.09 K and 1.91 K for soil and vegetation at a grass site, respectively, and corresponding values of 3.71 K and 3.42 K at a sparse forest site, respectively. Considering that the temperature differences between components can reach 20 K, the results confirm that, in addition to a pixel-average LST, the combined retrieval algorithm can provide information on LSCTs. This article demonstrates the potential of utilizing additional information sources for better LSCT results, which makes the presented combined strategy a promising option for deriving large-scale LSCT products.

Improvement of Split-Window Algorithm for Land Surface Temperature Retrieval from Sentinel-3A SLSTR Data Over Barren Surfaces Using ASTER GED Product

Land surface temperature (LST) is a key variable influencing the energy balance between the land surface and the atmosphere. In this work, a split-window algorithm was used to calculate LST from Sentinel-3A Sea and Land Surface Temperature Radiometer (SLSTR) thermal infrared data. The National Centers for Environmental Prediction (NCEP) reanalysis atmospheric profiles combined with the radiation transport model MODerate resolution atmospheric TRANsmission version 5.2 (MODTRAN 5.2) were utilized to obtain atmospheric water vapor content (WVC). The ASTER Global Emissivity Database Version 3 (ASTER GED v3) product was utilized to estimate surface emissivity in order to improve the accuracy of LST estimation over barren surfaces. Using a simulation database, the coefficients of the algorithm were fitted and the performance of the algorithm was evaluated. The root-mean-square error (RMSE) values of the differences between the estimated LST and the actual LST of the MODTRAN radiative transfer simulation at each WVC subrange of 0–6.5 g/cm2 were less than 1.0 K. To validate the retrieval accuracy, ground-based LST measurements were collected at two relatively homogeneous desert study sites in Dalad Banner and Wuhai, Inner Mongolia, China. The bias between the retrieved LST and the in situ LST was about 0.2 K and the RMSE was about 1.3 K at the Dalad Banner site, whereas they were approximately -0.4 and 1.0 K at the Wuhai site. As a reference, the retrieved LST was compared with the operational SLSTR LST product in this study. The bias between the SLSTR LST product and the in situ LST was approximately 1 K and the RMSE was approximately 2 K at the Dalad Banner site, whereas they were approximately 1.1 and 1.4 K at the Wuhai site. The results demonstrate that the split-window algorithm combined with improved emissivity estimation based on the ASTER GED product can distinctly obtain better accuracy of LST over barren surfaces.

Mapping and Tracking Forest Burnt Areas in the Indio Maiz Biological Reserve Using Sentinel-3 SLSTR and VIIRS-DNB Imagery.

Wildfires are considered one of the most major hazards and environmental issues worldwide. Recently, Earth observation satellite (EOS) sensors have proven to be effective for wildfire detection, although the quality and usefulness of the data are often hindered by cloud presence. One practical workaround is to combine datasets from multiple sensors. This research presents a methodology that utilizes data of the recently-launched Sentinel-3 sea and land surface temperature radiometer (S3-SLSTR) to reflect its applicability for detecting wildfires. In addition, visible infrared imaging radiometer suite day night band (VIIRS-DNB) imagery was introduced to assure day-night tracking capabilities. The wildfire event in the Indio Maiz Biological Reserve, Nicaragua, during 3–13 April 2018, was the study case. Six S3-SLSTR images were processed to compute spectral indices, such as the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), and the normalized burn ratio (NBR), to perform image segmentation for estimating the burnt area. The results indicate that 5870.7 ha of forest was affected during the wildfire, close to the 5945 ha reported by local authorities. In this study, the fire expansion was delineated and tracked in the Indio Maiz Biological Reserve using a modified fast marching method on nighttime-sensed temporal VIIRS-DNB. This study shows the importance of S3-SLSRT for wildfire monitoring and how it can be complemented with VIIRS-DNB to track burning biomass at daytime and nighttime.

A semi-empirical method for estimating complete surface temperature from radiometric surface temperature, a study in Hong Kong city

The complete surface temperature (Tc) in urban areas, defined as the mean temperature of the total active surface area, is an important variable in urban micro-climate research, specifically for assessment of the urban surface energy balance. Since most vertically-oriented building facets are not observed by a nadir-viewing remote imaging radiometer, the radiometric surface temperature (Tr) measured at a specific view angle cannot be used with existing heat transfer equations to estimate radiative and convective fluxes in the urban environment. Thus, it is necessary to derive Tc for city neighborhoods. This study develops a simple method to estimate Tc from Tr with the aid of the Temperatures of Urban Facets in 3D (TUF-3D) numerical model, which calculates 3-D sub-facet scale urban surface temperatures for a variety of surface geometries and properties, weather conditions and solar angles. The effects of geometric and meteorological characteristics – e.g., building planar area index (λp), wall facet area index (F), solar irradiance – on the difference between Tc and Tr were evaluated using the TUF-3D model. Results showed the effects of geometric and meteorological characteristics on the difference between Tc and Tr differ between daytime and nighttime. The study then sought to predict the relationship between Tr and Tc, using λp, F, and solar irradiance for daytime and only using λp and F for nighttime. Based on the simulated data from TUF-3D, the resulting relationships achieve a coefficient of determination (r2) of 0.97 and a RMSE of 1.5 K during daytime, with corresponding nighttime values of r2 = 0.98 and RMSE = 0.69 K. The relationships between Tr and Tc are evaluated using high resolution airborne thermal images of daytime urban scenes: r2 = 0.75 and RMSE = 1.09 K on August 6, 2013 at 12:40 pm; and r2 = 0.86 and RMSE = 1.86K on October 24, 2017 at 11:30 am. The new relationships were also applied to estimate Tc from Tr in Hong Kong retrieved from Landsat 5 Thematic Mapper (TM) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). In the present climatic context, the difference between Tc and Tr can reach 10 K during daytime in summer, and 6 K during daytime in winter, with seasonal variation attributable to the variations in shortwave irradiance. The nighttime difference between Tc and Tr can also reach 2 K in both summer and spring seasons.

Tropical Cyclone Surface Pressure Field Estimation Using Satellite Passive Microwave Observations over the Oceans

AbstractThe real time and accurate estimation of tropical cyclone (TC) surface pressure fields is highly desired in TC forecasting and analysis. Using satellite passive microwave observations over the oceans, the retrieval of TC surface pressure fields was investigated in this study, and a new retrieval algorithm was developed. This algorithm uses brightness temperatures (TBs) and TB anomalies together to accurately estimate TC surface pressure fields. Considering the relative superiority of 118‐GHz radiometers in spatial resolution, this study not only used the measurements of 60‐GHz radiometer Advanced Technology Microwave Sounder (ATMS) but also the 118‐GHz radiometer Microwave Humidity and Temperature Sounder (MWHTS). The TC measurements from July 2015 to September 2018 and the corresponding Global Data Assimilation System (GDAS) Final (FNL) analysis data were used to develop and test the retrieval algorithm. The testing results show that the proposed method can estimate the surface pressure fields of a TC's core area (within a 2° radius from the center) with an accuracy of better than 4.0, 5.0, and 8.0 hPa for tropical depressions and tropical storms, typhoons or hurricanes, and severe typhoons or major hurricanes, respectively. In addition, an in situ comparison demonstrates that the accuracy of the retrieved central pressure is better than 6.0, 8.0, and 10.0 hPa for tropical depressions and tropical storms, typhoons or hurricanes, and severe typhoons or major hurricanes, respectively.