Evaluation of ASTER and MODIS land surface temperature and emissivity products using long-term surface longwave radiation observations at SURFRAD sites

Land surface temperature (LST) and emissivity are key parameters in estimating the land surface radiation budget, a major controlling factor of global climate and environmental change. In this study, Terra Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) and Aqua MODerate resolution Imaging Spectroradiometer (MODIS) Collection 5 LST and emissivity products are evaluated using long-term ground-based longwave radiation observations collected at six Surface Radiation Budget Network (SURFRAD) sites from 2000 to 2007. LSTs at a spatial resolution of 90 m from 197 ASTER images during 2000-2007 are directly compared to ground observations at the six SURFRAD sites. For nighttime data, ASTER LST has an average bias of 0.1 °C and the average bias is 0.3 °C during daytime. Aqua MODIS LST at 1 km resolution during nighttime retrieved from a split-window algorithm is evaluated from 2002 to 2007. MODIS LST has an average bias of − 0.2 °C. LST heterogeneity (defined as the Standard Deviation, STD, of ASTER LSTs in 1 × 1 km² region, 11 × 11 pixel in total) and instrument calibration error of pyrgeometer are key factors impacting the ASTER and MODIS LST evaluation using ground-based radiation measurements. The heterogeneity of nighttime ASTER LST is 1.2 °C, which accounts for 71% of the STD of the comparison, while the heterogeneity of the daytime LST is 2.4 °C, which accounts for 60% of the STD. Collection 5 broadband emissivity is 0.01 larger than that of MODIS Collection 4 products and ASTER emissivity. It is essential to filter out the abnormal low values of ASTER daily emissivity data in summer time before its application.     

Retrieval of high-resolution sea surface temperature data for Sendai Bay, Japan, using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)

We studied sea surface temperature (SST) retrieval algorithms for Sendai Bay, using output from the thermal-infrared channels of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on board Terra. While the highest resolutions of other satellite SST products are about 1 km, the ASTER thermal-infrared channels provide 90-m spatial resolution. To develop the ASTER algorithm, we employed statistical methods in which SSTs retrieved from the thermal-infrared measurements were tuned against the Moderate Resolution Imaging Spectroradiometer (MODIS) SST product with a 1-km spatial resolution. Terra also carries a MODIS sensor, which observed the same area as the ASTER sensor at the same time. The MODIS SST was validated around Sendai Bay, revealing a bias of −0.15 °C and root mean-square difference (RMSD) of 0.67 °C against in situ SSTs. Taking into account the spatial-resolution difference between ASTER and MODIS, match-up was generated only if the variability of ASTER brightness temperatures (T₁₃) was small in a pixel of MODIS SST (MP). The T₁₃ within one MP was about 121 pixels. The standard deviation (σ₁₃) of T₁₃ was calculated for each cloud-free MP, and the threshold of σ₁₃ for choosing match-up MPs was decided by analyzing the σ₁₃ histogram of one ASTER image. The 15 synchronous pairs of ASTER/MODIS images are separated into two groups of 8 pairs called set (A) and 7 pairs called set (B). Using the common procedure, the match-ups are generated for set (A) and set (B). The former is used for developing the ASTER Multi-Channel SST (MCSST) algorithm, and the latter for validation of the developed ASTER SST. Analysis of the whole 15 pairs indicated that ASTER SST does not depend on the satellite zenith angle. We concluded that, using Akaike's information criterion with set (A) match-ups, the multiple regression formula with all five thermal-infrared channels was adequate for the ASTER SST retrieval. Validation of ASTER SST using match-up set (B) indicated a bias of 0.101 °C and RMSD of 0.455 °C.     

Improved land surface emissivities over agricultural areas using ASTER NDVI

Land surface emissivity retrieval over agricultural regions is important for energy balance estimations, land cover assessment and other related environmental studies. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) produces images of sufficient spatial resolution (from 15 m to 90 m) to be of use in agricultural studies, in which fields of crops are too small to be well-resolved by low resolution sensors. The ASTER project generates land surface emissivity images as a Standard Product (AST05) using the Temperature/Emissivity Separation (TES) algorithm. However, the TES algorithm is prone to scaling errors in estimating emissivities for surfaces with low spectral contrast if the atmospheric correction is inaccurate. This paper shows a comparison between the land surface emissivity estimated with the TES algorithm and from a simple approach using the Normalized Difference Vegetation Index (NDVI) for five ASTER images (28 June 2000, 15 August 2000, 31 August 2000, 28 April 2001 and 02 August 2001) of the agricultural area of Barrax (Albacete, Spain). The results indicate that differences are < 1% for ASTER band 13 (10.7 μm) and < 1.5% for band 14 (11.3 μm), but > 2% for bands 10 (8.3 μm), 11 (8.6 μm) and 12 (9.1 μm). The emissivities for the five ASTER bands were tested against in situ measurements carried out with the CIMEL CE 312-2 field radiometer, the NDVI method giving root mean square errors (RMSE) < 0.005 over vegetated areas and RMSE < 0.015 over bare soil, and the TES algorithm giving RMSE ∼ 0.01 for vegetated areas but RMSE > 0.03 over bare soil. The errors and inconsistencies for ASTER bands 13 and 14 are within those anticipated for TES, but the greater errors for bands 10-12 suggest the presence of problems related to atmospheric compensation and model assumptions about soil spectra. The NDVI method uses visible/near-infrared data co-acquired with the thermal images to estimate vegetation cover and, hence, provides an independent constraint on emissivity. The success of this approach suggests that it may be useful for daytime images of agricultural or other heavily vegetated areas, in which the TES algorithm has occasional failures.     

Comparison of satellite-derived and in-situ observations of ice and snow surface temperatures over Greenland

The most practical way to get spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived “clear-sky” LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air temperature observations from Greenland Climate Network (GC-Net) automatic weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from ? 40 to 0 °C. The satellite-derived LSTs agree within a relative RMS uncertainty of ~ 0.5 °C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a “point” while the satellite instruments record data over an area varying in size from: 57 × 57 m (ETM+), 90 × 90 m (ASTER), or to 1 × 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty ~ 2 °C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.     

The effect of transportation suit induced heat stress on helicopter underwater escape preparation and task performance

Although essential in an emergency such as a helicopter ditching, mandatory survival suits worn by civilian personnel may lead to heat strain during a normal flight. To explore the possibility that wearing a helicopter transportation suit impairs emergency performance, 11 individuals completed underwater escape procedures immediately following a pre-recorded emergency announcement (randomly played between 50 and 90 min) in two ambient temperature conditions (Thermoneutral = 21 °C and Hot = 34 °C). Mean skin and rectal temperatures were recorded throughout the trials, while situation awareness and thermal sensation/comfort were recorded on completion of trials. Results indicate that although mean skin and rectal temperatures were significantly higher at the end of both trials, escape procedures were not impaired. It can therefore be concluded that although conditions inside an offshore transport helicopter are perceived as being hot and uncomfortable, no deficits in escape performance should be expected in the first 90 min of flight.     

Temperature and emissivity separation from ASTER data for low spectral contrast surfaces

The performance of Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) thermal infrared (TIR) data product algorithms was evaluated for low spectral contrast surfaces (such as vegetation and water) in a test site close to Valencia, Spain. Concurrent ground measurements of surface temperature, emissivity, and atmospheric radiosonde profiles were collected at the test site, which is a thermally homogeneous area of rice crops with nearly full vegetation cover in summer. Using the ground data and the local radiosonde profiles, at-sensor radiances were simulated for the ASTER TIR channels and compared with L1B data (calibrated at-sensor radiances) showing discrepancies up to 3% in radiance for channel 10 at 8.3 μm (equivalently, 2.5 °C in temperature or 7% in emissivity), whereas channel 13 (10.7 μm) yielded a closer agreement (maximum difference of 0.5% in radiance or 0.4 °C in temperature). We also tested the ASTER standard products of land surface temperature (LST) and spectral emissivity generated with the Temperature-Emissivity Separation (TES) algorithm with standard atmospheric correction from both global data assimilation system profiles and climatology profiles. These products showed anomalous emissivity spectra with lower emissivity values and larger spectral contrast (or maximum-minimum emissivity difference, MMD) than expected, and as a result, overestimated LSTs. In this work, a scene-based procedure is proposed to obtain more accurate MMD estimates for low spectral contrast materials (vegetation and water) and therefore a better retrieval of LST and emissivity with the TES algorithm. The method uses various gray-bodies or near gray-bodies with known emissivities and assumes that the calibration and atmospheric correction performed with local radiosonde data are accurate for channel 13. Taking the channel 13 temperature (atmospherically and emissivity corrected) as the true LST, the radiances for the other channels were simulated and used to derive linear relationships between ASTER digital numbers and at-ground radiances for each channel. The TES algorithm was applied to the adjusted radiances and the resulting products showed a closer agreement with the ground measurements (differences lower than 1% in channel 13 emissivities and within ± 0.3 °C in temperature for rice and sea pixels).     

Estimation of storage heat flux in an urban area using ASTER data

The urban heat island phenomenon occurs as a result of the mixed effects of anthropogenic heat discharge, increased use of artificial impervious surface materials, and decreased vegetation cover. These factors modify the heat balance at the land surface and eventually raise the atmospheric temperature. It is important to quantify the surface heat balance in order to estimate the contributions of these factors. The present authors propose the use of storage heat flux to represent the heat flux between the land surface and the inside of the canopy for the heat balance analysis based on satellite remote sensing data. Surface heat fluxes were estimated around the city of Nagoya, Japan using Terra ASTER data and meteorological data. Seasonal and day-night differences in heat balance were compared using ASTER data acquired in the daytime on July 10, 2000, and January 2, 2004 and in the nighttime on September 26, 2003. In the central business and commercial districts, the storage heat flux was higher than those in the surrounding residential areas. In particular, in winter, the storage heat flux in the central urban area was 240 to 290 W m^− 2, which was much larger than the storage heat fluxes in residential areas, which ranged from 180 to 220 W m^− 2. Moreover, the negative storage heat flux in the central urban area was greater at night. This tendency implies that the urban surface stores heat during the daytime and discharges it at night. Extremely large negative storage heat flux occurred primarily in the industrial areas for both daytime and nighttime as a result of the enormous energy consumption by factories.     

Microclimate in ski boots – Temperature,relative humidity,and water absorption

Ski boot quality is determined by mechanical properties and comfort. Comfort is strongly affected by cold feet. The purpose of this study was to determine the microclimate in ski boots. Climate chamber tests with five male subjects and field tests with two male subjects were conducted. Temperature and relative humidity were measured using four sensors placed on the foot and one on the liner. Absorbed water in liners and socks was measured with a precision balance. The subjects gave subjective ratings for comfort. The toe sensor temperature dropped below 20 °C at an ambient temperature of 0 °C, −10 °C, and −20 °C. Relative humidity values at the foot were as high as 78% in the climate chamber and 93% in the field. Water absorption in socks and liners ranged from 4 to 10 g in the climate chamber and 19 to 45.5 g in the field. The results reveal the importance of keeping the feet and in particular the toes warm during skiing. One possible improvement may be to construct the liner so that sweat and melted snow are kept as far away as possible from the foot. Liner material with high water absorption capacity and hydrophobic socks were suggested to prevent wet feet.     

Sub-pixel water temperature estimation from thermal-infrared imagery using vectorized lake features

Water skin temperature derived from thermal infrared satellite data are used in a wide variety of studies. Many of these studies would benefit from frequent, high spatial resolution (100 m pixels) thermal imagery but currently, at any given location, such data are only available every few weeks from spaceborne sensors such as ASTER. Lower spatial resolution (1 km pixels) thermal imagery is available multiple times per day at any given location, from several sensors such as MODIS on board both the AQUA and TERRA satellite platforms. In order to fully exploit lower spatial resolution imagery, a sub-pixel unmixing technique has been developed and tested at Quesnel Lake, British Columbia, Canada. This approach produces accurate, frequent high spatial resolution water skin temperature maps by exploiting a priori knowledge of water boundaries derived from vectorized water features. The pixel water-fraction maps are then input to a gradient descent algorithm to solve the mixed pixel ground leaving radiance equation for sub-pixel water temperature. Ground-leaving radiance is estimated from standard temperature and emissivity data products for pure pixels and a simple regression technique to estimate atmospheric effects. In this test case, MODIS 1 km thermal imagery was used along with 1:50,000 water features to create a high-resolution (100 m) water skin temperature map. This map is compared to a concurrent ASTER temperature image and found to be within 1 °C of the ASTER skin temperature 99% of the time. This is a considerable improvement over the 2.55 °C difference between the original MODIS product and ASTER image due to land temperature contamination. The algorithm is simple, effective, and unlocks a largely untapped resource for limnological and hydrological studies.     

Estimating subpixel fire sizes and temperatures from ASTER using multiple endmember spectral mixture analysis

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) shortwave infrared subsystem can acquire images of active fires during daytime and night-time from a polar orbit, providing useful data on fire properties at a nominal spatial resolution of 30 m. Binary fire/no-fire counts of ASTER pixels have also been useful in evaluating the performance of widely-used fire products from the Moderate-Resolution Imaging Spectroradiometer (MODIS), which have a nominal spatial resolution of 1 km. However, the ASTER fire pixels are actually mixed pixels that can contain flaming, smouldering and non-burning components, and ASTER fire pixel counts provide no information about the sizes or temperatures of these subpixel components. This paper uses multiple endmember spectral mixture analysis (MESMA) to estimate subpixel fire sizes and temperatures from a night-time ASTER image of a fire in California, USA, demonstrating new methods that can provide information on fires not available from other sources. As a fire's size and its temperature exert strong influences on its gas and aerosol emissions, ecological impact and spreading rates, these MESMA estimates from ASTER imagery could contribute valuable new information towards monitoring, forecasting and understanding the behaviour and impacts of many fires worldwide.     

On the relationship between thermodynamic surface temperature and high-frequency (37 GHz) vertically polarized brightness temperature under semi-arid conditions

A method to estimate surface temperature from high-frequency microwave observations is presented. Microwave brightness temperature is a function of the emissivity and the physical temperature of the emitting layer, and therefore possesses a strong physical basis for the estimation of surface temperature. Field observations have shown that maximum and minimum daily air temperatures are strongly related to daytime (1200h) and night-time (2400h) surface temperature. Field measurements of surface temperature are also compared to METEOSAT thermal observations. Long-term daily maximum and minimum air temperatures are then used to derive datasets of daytime and night-time surface temperatures. The results indicate that 37 GHz vertical polarization brightness temperature provides a reasonable estimate of spatially averaged surface temperature. This approach could provide a useful tool for climate modelling, land surface processes investigations, and other energy balance applications by providing consistent and independent long-term estimates of daily global surface temperature.     

Evaluation of thermal and evaporative resistances in cricket helmets using a sweating manikin

The main objective of this study is to establish an approach for measuring the dry and evaporative heat dissipation cricket helmets. A range of cricket helmets has been tested using a sweating manikin within a controlled climatic chamber. The thermal manikin experiments were conducted in two stages, namely the (i) dry test and (ii) wet test. The ambient air temperature for the dry tests was controlled to ∼23 °C, and the mean skin temperatures averaged ∼35 °C. The thermal insulation value measured for the manikin with helmet ensemble ranged from 1.0 to 1.2 clo. The results showed that among the five cricket helmets, the Masuri helmet offered slightly more thermal insulation while the Elite helmet offered the least. However, under the dry laboratory conditions and with minimal air movement (air velocity = 0.08 ± 0.01 ms⁻¹), small differences exist between the thermal resistance values for the tested helmets. The wet tests were conducted in an isothermal condition, with an ambient and skin mean temperatures averaged ∼35 °C, the evaporative resistance, R_et, varied between 36 and 60 m² Pa W⁻¹. These large variations in evaporative heat dissipation values are due to the presence of a thick layer of comfort lining in certain helmet designs. This finding suggests that the type and design of padding may influence the rate of evaporative heat dissipation from the head and face; hence the type of material and thickness of the padding is critical for the effectiveness of evaporative heat loss and comfort of the wearer. Issues for further investigations in field trials are discussed.     

Influence of lake morphology and clarity on water surface temperature as measured by EOS ASTER

Relationships between lake morphometric parameters and nighttime lake surface temperatures were investigated in North American temperate lakes using the ASTER kinetic temperature (AST08) product. Nighttime ASTER kinetic temperature measurements were found to be a good analogue for nighttime surface temperatures. Linear regression between ASTER and buoy-measured temperatures in a test lake were better during the evening (R² = 0.98) than the day (R² = 0.90), presumably due to the greater influence of radiation and latent heat fluxes during daylight hours. Nighttime lake surface temperatures measured in three ASTER scenes were significantly correlated to logarithm of lake area, maximum lake depth, Secchi depth (a measure of lake clarity) and lake order (a measure of lake connection with surface drainage), during October and November. Nighttime lake surface temperatures were significantly correlated only with lake area in July. We hypothesize that morphology was more strongly related to surface temperature in the fall months due to lake turnover during that season. This study suggests that satellite derived thermal data may be useful for calculation of lake heat budgets and evaporation rates, provided surface temperatures are measured in well-mixed lakes.     

The influence of socioeconomic and topographic factors on nocturnal urban heat islands: a case study in Shenzhen,China

Earlier studies on urban heat islands (UHIs) focused mostly on the phenomenon during the daytime, when temperature peaks could usually be observed. However, for people living and working in tropical and subtropical cities, night-time air temperatures are also important. Several studies have focused primarily on the impact of biophysical and meteorological factors on nocturnal land surface temperatures (LSTs). Less attention has been paid to study of the influence of socioeconomic and topographic factors on nocturnal UHIs within a city. In this study, the integration of remote sensing (RS), geographic information system (GIS) and landscape ecology methods was used to investigate the relationships between nocturnal UHIs and socioeconomic or topographic factors based on a case study of Shenzhen, China. Nocturnal Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and daytime Landsat Thematic Mapper (TM) images were used to derive and analyse night- and daytime LSTs, respectively. Land-use data were generated by onscreen digitizing, and an abundance of impervious surfaces was produced through a normalized spectral mixture analysis (NSMA) method with TM data. Socioeconomic variables were derived from the China 2000 census data. A 30 m digital elevation model (DEM) was used to calculate elevation and slope grids. The relationships between nocturnal UHIs and socioeconomic or topographic factors were analysed using traditional regression analysis. The results show that the nocturnal and daytime LST patterns in different land-use areas were significantly different. Nocturnal LSTs were closely related to socioeconomic and topographic factors. An increase of 5 K on nocturnal LST of sub-districts was associated with an increase of 66.0% on their impervious surface abundance, 39 810 people per km², 1000 Yuan per month on housing rent, 9.5 km per km² on road density or a decline of 217.5 m on elevation and 17.0° on slope.     

Comfort design and optimization of direct expansion multi-connected radiant air conditioning based on 3D flow field simulation

The air conditioning method based on radiation heat exchange has the characteristics of small vertical temperature gradient, high thermal comfort and energy saving, and has become a hot spot of attention. The Fluent numerical simulation, the experiment in this paper studies the direct expansion multi-line radiant air conditioner under the artificially simulated climate environment in winter heating, summer cooling and dehumidification. The temperature difference of the radiation + fresh air mode at the same time indoors under heating conditions is less than 2.5 °C, and the time to reach the indoor set temperature of 24 °C is about 2–3 h. Under cooling conditions, the temperature difference of the radiation + fresh air mode at the same time in the room is about 0.5–2 °C, and the time to reach the indoor set temperature of 26 °C is about 1–3 h. In the fresh air mode, the indoor temperature difference and response time at the same time are slightly larger than the radiation + fresh air mode. The freezing and dehumidification effect of fresh air is obvious, the moisture content of dehumidifying fresh air is between 6.3 and 10.5 g/kg, and the dehumidification efficiency can reach 50%. Under the same artificial simulated climate environment, the consumption of the three modes is not much different. When the outdoor temperature in heating conditions is higher than 9 °C, the fresh air mode can get better, and the radiation + fresh air mode can achieve better comfort when running indoors under various conditions.     

Applying a normalized ratio scale technique to assess influences of urban expansion on land surface temperature of the semi-arid city of Erbil

The difference between surface and air temperature within a city and its surrounding area is a result of variations in surface cover, thermal capacity, and 3-dimensional geometry. This research has examined and quantified the decreasing daytime land surface temperature (LST) in Erbil, Kurdistan region of Iraq, and the influence of rapid urban expansion on urban heat/cool island effect over a 20 year period. Land-use/land-cover change across this time period is also established using pixel samples. The current study proposes the application of the normalized ratio scale (NRS) to adjust the temperature of images acquired at different dates to the same range. Eleven satellite images acquired by Landsat 4, 5, 7, and 8 during the period 1992–2013 are used to retrieve LST. The results indicate that 55.3 km² of city land cover changed from bare soil to urban; consequently, the mean LST of the new urbanized area decreased by 2.28°C. The normalized difference vegetation index (NDVI) of Sami Abdul-Rahman (S.A.) Park increased from 0.09 ± 0.01 to 0.32 ± 0.11, resulting in a decrease of the mean LST by 7.29°C. This study shows that the NRS method is appropriate for detecting temperature trends from urbanization using remote-sensing data. It also highlights that urban expansion may lead to a decrease in daytime LST in drylands.     

Accuracy and uncertainty of thermal-infrared remote sensing of stream temperatures at multiple spatial scales

Stream temperature is an important indicator of water quality, particularly in regions where endangered fish populations are sensitive to elevated water temperature. Regional assessment of stream temperatures from the ground is limited by sparse sampling in both space and time. Remotely sensed thermal-infrared (TIR) images are able to make spatially distributed measurements of the radiant skin temperature of streams. We quantify and discuss the accuracy and uncertainty limits to recovering stream temperatures in the Pacific Northwest for a range of stream widths (10-500 m), and TIR pixel sizes (5-1000 m) from remotely sensed airborne and satellite TIR images. Among locations with more than three pixels across the stream, the image temperature overestimated the in-stream temperature on average by 1.2 °C, which is 7% of the in-stream temperature (standard error (SE) of 0.2 °C, n = 21). The corresponding uncertainty (band weighted standard deviation in image temperature) for these locations averaged ± 0.3 °C (SE < 0.1 °C, n = 21) which is 2% of in-stream temperatures. This overestimation by the image temperatures is likely to be due to thermal stratification between the stream surface and the location of the in-stream temperature measurements deeper in the water column. For streams with one to three pixels across, mixing with bank elements increased the overestimation by image temperatures to 2.2 °C (SE = 0.3 °C, n = 23) on average (13% of in-stream temperatures), and the uncertainty increased to ± 0.4 °C (SE = 0.1 °C, n = 23) which is 2% of in-stream temperatures. For a fraction of a pixel across the stream the overestimation by image temperatures was 7.6 °C (SE = 1.2 °C, n = 23) on average (45% of in-stream temperatures), and the uncertainty was ± 0.5 °C (SE = 0.1 °C, n = 23) which is 3% of in-stream temperatures. These results show that reliable satellite TIR measurement of stream temperatures is limited to large rivers (∼180-m across for Landsat ETM+), unless novel unmixing algorithms are used effectively.     

Estimating average daytime and daily temperature profiles within Europe

We present a methodology for estimating the average profiles of daytime and daily ambient temperature from a spatially-continuous database for any location within Europe. The primary database with 1-km grid resolution was developed by interpolation of monthly averages of 7 daily values of temperature: minimum and maximum and 5 measurements at 3-h intervals from 6:00 to 18:00 hours Greenwich Mean Time. With a little over 800 meteorological stations available, we obtained a cross-validation root mean square error of 1.0–1.2 °C, while the interpolation error is lower, at 0.5–0.7 °C.A polynomial fit was applied to estimate the daytime temperature profile (assuming only time from sunrise to sunset) from the interpolated 3-h measurements for each month. The curve fit coefficients make it possible to calculate a number of derived data, such as average daytime temperature, maximum daytime temperature and time of its occurrence within the region. An example demonstrates the coupling of the simulated daytime temperature profile with a model for assessing the relative efficiency of electricity generation by crystalline silicon photovoltaic modules.As an alternative to the polynomial fitting, a double-cosine method was applied to enable calculation of daily (24-h) temperature profiles for each month using interpolated minimum and maximum temperatures. Compared to the polynomial curve-fitting, this method does not offer lower errors, but it provides data which are more suitable for estimation of solar thermal heating or calculation of degree days for building heating/cooling.     

Accuracy of ASTER Level-2 thermal-infrared Standard Products of an agricultural area in Spain

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) collects five-channel thermal-infrared images that are calibrated, corrected for atmospheric effects, and then converted to land surface temperature and emissivity products by the ASTER Temperature/Emissivity Separation (TES) algorithm. TES scales low- and high-contrast surfaces differently, and has been validated over water (low contrast) and rock (high contrast). Performance of TES over agricultural areas, however, has not been evaluated specifically. To address this issue, field measurements of “ground truth” were made over bare soil in addition to green grass, alfalfa and corn, at an agricultural research site in Spain during two coincident campaigns (SPectrA Barrax Campaign, or SPARC, and Exploitation of AnGular effects in Land surface, or EAGLE) during an ASTER overflight. Comparison of the ASTER Standard Products for land surface temperature (AST-08) and emissivity (AST-05) with ground measurements for the crops (corn and barley, plus grass) showed that accuracies of ± 1.5 K and ± 0.01, respectively, were achieved there. However, bare soil was assessed incorrectly by TES as having high emissivity contrast, leading to inaccurate scaling and low apparent emissivities.