Radiometric Temperature Research Articles

Aperture area measurement using two different traceability routes

Given the advances in cryogenic radiometry, area measurement is now one of the limiting factors in the realisation of radiometric and photometric units as well as radiometric temperature scales. An inter-comparison of aperture area measurements using complementary methods at two different national metrology institutes has shown excellent agreement in the values measured, with the measurements agreeing well within the 95% confidence intervals. Importantly, the statistical scatter of the values is consistent with the magnitude of the confidence intervals, implying that the estimates of uncertainty are not overly conservative. This provides increased confidence to both institutes that systematic errors have not been overlooked and that the uncertainty contributions have been realistically assessed.

Variational Bayes and the Principal Component Analysis Coupled With Bayesian Regulation Backpropagation Network to Retrieve Total Precipitable Water (TPW) From GCOM-W1/AMSR2

The Bayes Principal components Backpropagation Network (BPBN) is proposed to retrieve total precipitable water (TPW) from the AMSR2 instrument on-board recently launched GCOM-W1 satellite. The proposed algorithm is a physical inversion method, developed using a radiative transfer model to assure that the geophysical retrieval of the TPW is consistent with the radiative transfer theory. The algorithm is comprised of- a Bayes variational algorithm for bias correction, the principal components transformation of the bias-corrected radiometric brightness temperature, and finally, a Bayesian regulation backpropagation network to translate the principal components to TPW estimate in the geophysical space. The algorithm is applicable over ocean, and in clear and cloudy scenes. However, the rainy and sea ice scenes are excluded in the retrieval. A random forest classifier and NASA sea ice temperature retrieval algorithm are used to detect and suppress the rainy and sea ice scenes, respectively. On the whole, the BPBN is a “comprehensive” algorithm, from discarding the redundant scenes to transforming the radiometric information to TPW estimate, and doesn’t use any auxiliary data. This will make it very useful for assimilating into the numerical weather prediction models. The retrieval accuracy of the BPBN algorithm is around 2 $\hbox{kg/m}^2$ .

Influence of Leaf Area Index on the Radiometric Resistance to Heat Transfer

Sensible heat flux is an important component of the surface energy balance. Land surface models often use the radiative surface temperature instead of the aerodynamic temperature to predict the surface sensible flux, because the former is much easier to observe by remote sensing or to compute from the surface energy balance equation. Here, measurements from 44 FLUXNET sites are used to examine the stability and leaf area index (LAI) dependence of the radiometric resistance, a resistance that should be included in the bulk transfer method if the radiometric temperature is used for the flux calculation. Results show that the radiometric resistance is much higher under stable conditions than under unstable conditions. In unstable conditions, the radiometric resistance is highly sensitive to LAI, decreasing exponentially as LAI increases. Omission of the radiometric resistance from the bulk transfer method causes a large overestimation in the sensible heat flux, especially for low-LAI surfaces and under unstable conditions.

Evaluation of three semi-empirical approaches to estimate the net radiation over a drip-irrigated olive orchard

The use of actual evapotranspiration (ETα) models requires an appropriate parameterization of the available energy, where the net radiation (Rn) is the most important component. Thus, a study was carried out to calibrate and evaluate three semi-empirical approaches to estimate net radiation (Rn) over a drip-irrigated olive (Olea europaea L. 'Arbequina') orchard during 2009/2010 and 2010/2011 seasons. The orchard was planted in 2005 at high density in the Pencahue Valley, Maule Region, Chile. The evaluated models were calculated using the balance between long and short wave radiation. To achieve this objective it was assumed that Ts = Tα for Model 1, Ts = Tv for Model 2 and Ts = Tr for Model 3 (Ts is surface temperature; Tα is air temperature; and Tv is temperature inside of the tree canopy; Tr is radiometric temperature). For the three models, the Brutsaert's empirical coefficient (Φ) was calibrated using incoming long wave radiation equation with the database of 2009/2010 season. Thus, the calibration indicated that Φ was equal to 1.75. Using the database from 2010/2011 season, the validation indicated that the three models were able to predict the Rn at a 30-min interval with errors lower than 6%, root mean square error (RMSE) between 26 and 39 W m-2 and mean absolute error (MAE) between 20 and 31 W m-2. On daily time intervals, validation indicated that models presented errors, RMSE and MAE between 2% and 3%, 1.22-1.54 and 1.04-1.35 MJ m-2 d-1, respectively. The three R„-Models would be evaluated and used in others Mediterranean conditions according to the availability of data to estimate net radiation over a drip-irrigated olive orchard planted at high density.

Analyzing the anisotropy of thermal infrared emissivity over arid regions using a new MODIS land surface temperature and emissivity product (MOD21)

Abstract The MOD21 Land Surface Temperature and Emissivity (LST&E) product will be included in forthcoming Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6. Surface temperature and emissivities for thermal bands 29 (8.55 μm), 31 (11 μm) and 32 (12 μm) will be retrieved using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Temperature and Emissivity Separation (TES) method adapted to MODIS at-sensor spectral radiances, previously corrected with the Water Vapor Scaling method (MOD21 algorithm). We simulated MOD21 product estimates over two different sandy deserts (i.e. White Sands and Great Sands) using a series of MODIS scenes from 2010 to 2013. The objective of this study was to evaluate the anisotropy of the thermal infrared emissivity over semiarid regions, since angular variations of thermal infrared emissivity imply important uncertainties in satellite LST retrievals. The obtained LSEs and their dependence on zenith viewing angles were analyzed. Results from the MOD21 simulated algorithm showed that band 29 LSE decreased up to 0.038 from nadir to zenith angle of 60°, while LSEs for bands 31 and 32 did not show significant variation. MOD21 LSE for band 29 also showed mean differences between night and daytime retrievals of + 0.027 for WS and + 0.009 for GS. These differences can be attributed to the water vapor adsorption of the soil from the atmosphere. MOD21 nadir and off-nadir LSEs showed a good agreement with laboratory emissivity measurements, and were used to validate with satellite data a zenithal-dependent emissivity model proposed in a previous study.

Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution

Abstract. This work presents a study on the sensitivity of two satellite cloud height retrievals to cloud vertical distribution. The difference in sensitivity is exploited by relating the difference in the retrieved cloud heights to cloud vertical extent. The two cloud height retrievals, performed within the Freie Universität Berlin AATSR MERIS Cloud (FAME-C) algorithm, are based on independent measurements and different retrieval techniques. First, cloud-top temperature (CTT) is retrieved from Advanced Along Track Scanning Radiometer (AATSR) measurements in the thermal infrared. Second, cloud-top pressure (CTP) is retrieved from Medium Resolution Imaging Spectrometer (MERIS) measurements in the oxygen-A absorption band and a nearby window channel. Both CTT and CTP are converted to cloud-top height (CTH) using atmospheric profiles from a numerical weather prediction model. First, a sensitivity study using radiative transfer simulations in the near-infrared and thermal infrared was performed to demonstrate, in a quantitative manner, the larger impact of the assumed cloud vertical extinction profile, described in terms of shape and vertical extent, on MERIS than on AATSR top-of-atmosphere measurements. Consequently, cloud vertical extinction profiles will have a larger influence on the MERIS than on the AATSR cloud height retrievals for most cloud types. Second, the difference in retrieved CTH (ΔCTH) from AATSR and MERIS are related to cloud vertical extent (CVE), as observed by ground-based lidar and radar at three ARM sites. To increase the impact of the cloud vertical extinction profile on the MERIS-CTP retrievals, single-layer and geometrically thin clouds are assumed in the forward model. Similarly to previous findings, the MERIS-CTP retrievals appear to be close to pressure levels in the middle of the cloud. Assuming a linear relationship, the ΔCTH multiplied by 2.5 gives an estimate on the CVE for single-layer clouds. The relationship is stronger for single-layer clouds than for multi-layer clouds. Due to large variations of cloud vertical extinction profiles occurring in nature, a quantitative estimate of the cloud vertical extent is accompanied with large uncertainties. Yet, estimates of the CVE provide an additional parameter, next to CTH, that can be obtained from passive imager measurements and can be used to further describe cloud vertical distribution, thus contributing to the characterization of a cloudy scene. To further demonstrate the plausibility of the approach, an estimate of the CVE was applied to a case study. In light of the follow-up mission Sentinel-3 with AATSR and MERIS like instruments, Sea and Land Surface Temperature Radiometer (SLSTR) and (Ocean and Land Colour Instrument) OLCI, respectively, for which the FAME-C algorithm can be easily adapted, a more accurate estimate of the CVE can be expected. OLCI will have three channels in the oxygen-A absorption band, possibly providing enhanced information on cloud vertical distributions.

Reintroducing radiometric surface temperature into the Penman‐Monteith formulation

AbstractHere we demonstrate a novel method to physically integrate radiometric surface temperature (TR) into the Penman‐Monteith (PM) formulation for estimating the terrestrial sensible and latent heat fluxes (H and λE) in the framework of a modified Surface Temperature Initiated Closure (STIC). It combines TR data with standard energy balance closure models for deriving a hybrid scheme that does not require parameterization of the surface (or stomatal) and aerodynamic conductances (gS and gB). STIC is formed by the simultaneous solution of four state equations and it uses TR as an additional data source for retrieving the “near surface” moisture availability (M) and the Priestley‐Taylor coefficient (α). The performance of STIC is tested using high‐temporal resolution TR observations collected from different international surface energy flux experiments in conjunction with corresponding net radiation (RN), ground heat flux (G), air temperature (TA), and relative humidity (RH) measurements. A comparison of the STIC outputs with the eddy covariance measurements of λE and H revealed RMSDs of 7–16% and 40–74% in half‐hourly λE and H estimates. These statistics were 5–13% and 10–44% in daily λE and H. The errors and uncertainties in both surface fluxes are comparable to the models that typically use land surface parameterizations for determining the unobserved components (gS and gB) of the surface energy balance models. However, the scheme is simpler, has the capabilities for generating spatially explicit surface energy fluxes and independent of submodels for boundary layer developments.

The effect of radiometer placement and view on inferred directional and hemispheric radiometric temperatures of an urban canopy

Abstract. Any radiometer at a fixed location has a biased view when observing a convoluted, three-dimensional surface such as an urban canopy. The goal of this contribution is to determine the bias of various sensors views observing a simple urban residential neighbourhood (nadir, oblique, hemispherical) over a 24 hour cycle under clear weather conditions. The error in measuring a longwave radiation flux density (L) and/or inferring surface temperatures (T0) is quantified for different times over a diurnal cycle. Panoramic time-sequential thermography (PTST) data were recorded by a thermal camera on a hydraulic mast above a residential canyon in Vancouver, BC. The data set resolved sub-facet temperature variability of all representative urban facets in a 360° swath repetitively over a 24-hour cycle. This data set is used along with computer graphics and vision techniques to project measured fields of L for a given time and pixel onto texture sheets of a three-dimensional urban surface model at a resolution of centimetres. The resulting data set attributes L of each pixel on the texture sheets to different urban facets and associates facet location, azimuth, slope, material, and sky view factor. The texture sheets of L are used to calculate the complete surface temperature (T0,C) and to simulate the radiation in the field of view (FOV) of narrow and hemispheric radiometers observing the same urban surface (in absence of emissivity and atmospheric effects). The simulated directional (T0,d) and hemispheric (T0,h) radiometric temperatures inferred from various biased views are compared to T0,C. For a range of simulated off-nadir (φ) and azimuth (Ω) angles, T0,d(φ,Ω) and T0,C differ between −2.6 and +2.9 K over the course of the day. The effects of effective anisotropy are highest in the daytime, particularly around sunrise and sunset when different views can lead to differences in T0,d(φ,Ω) that are as high as 3.5 K. For a sensor with a narrow FOV in the nadir of the urban surface, T0,d(φ=0) differs from T0,C by +1.9 K (day) and by −1.6 K (night). Simulations of the FOV of hemispherical, downward-facing pyrgeometers at 270 positions show considerable variations in the measured L and inferred hemispherical radiometeric temperature T0,h as a function of both horizontal placement and height. The root mean squared error (RMSE) between different horizontal positions in retrieving outgoing longwave emittance L↑ decreased exponentially with height, and was 11.2, 6.3 and 2.0 W m−2 at 2, 3, and 5 times the mean building height zb. Generally, above 3.5zb the horizontal positional error is less than the typical accuracy of common pyrgeometers. The average T0,h over 24 h determined from the hemispherical radiometer sufficiently above an urban surface is in close agreement with the average T0,C. However, over the course of the day, the difference between T0,h and T0,C shows an RMSE of 1.7 K (9.4 W m−2) because the relative contributions of facets within the projected FOV of a pyrgeometer do not correspond to their fractions of the complete urban surface.

Evaluation of LST downscaling algorithms on seasonal thermal data in humid subtropical regions of India

Thermal image downscaling algorithms use a unique relationship between land surface temperature (LST) and vegetation indices (e.g. normalized difference vegetation index (NDVI)). The LST–NDVI correlation and regression parameters vary in different seasons depending on land-use practices. Such relationships are dynamic in humid subtropical regions due to inter-seasonal changes in biophysical parameters. The present study evaluates three downscaling algorithms, namely disaggregation of radiometric surface temperature (DisTrad), sharpening thermal imagery (TsHARP), and local model using seasonal (25 February 2010, 14 April 2010, and 26 October 2011) thermal images. The aggregated Landsat LST of 960 m resolution is downscaled to 480, 360, 240, and 120 m using DisTrad, TsHARP, and the local model and validated with aggregated Landsat LSTs of a similar resolution. The results illustrate that the seasonal variability of the LST–NDVI relationship affects the accuracy of the downscaling model. For example, the accuracy of all algorithms is higher for the growing seasons (February and October) unlike the harvesting season (April). The root mean square error of the downscaled LST increases from 480 to 120 m spatial resolution in all seasons. The models are least suitable in water body and dry-river bed sand areas. However, the downscaling accuracy is higher for NDVI > 0.3. The present study is useful to understand the applicability of the downscaling models in seasonally varied landscapes and different NDVI ranges.

Zeeman effect in atmospheric O<sub>2</sub> measured by ground-based microwave radiometry

Abstract. In this work we study the Zeeman effect on stratospheric O2 using ground-based microwave radiometer measurements. The interaction of the Earth magnetic field with the oxygen dipole leads to a splitting of O2 energy states, which polarizes the emission spectra. A special campaign was carried out in order to measure this effect in the oxygen emission line centered at 53.07 GHz. Both a fixed and a rotating mirror were incorporated into the TEMPERA (TEMPERature RAdiometer) in order to be able to measure under different observational angles. This new configuration allowed us to change the angle between the observational path and the Earth magnetic field direction. Moreover, a high-resolution spectrometer (1 kHz) was used in order to measure for the first time the polarization state of the radiation due to the Zeeman effect in the main isotopologue of oxygen from ground-based microwave measurements. The measured spectra showed a clear polarized signature when the observational angles were changed, evidencing the Zeeman effect in the oxygen molecule. In addition, simulations carried out with the Atmospheric Radiative Transfer Simulator (ARTS) allowed us to verify the microwave measurements showing a very good agreement between model and measurements. The results suggest some interesting new aspects for research of the upper atmosphere.

Monitoring local heating around an interventional MRI antenna with RF radiometry.

Radiofrequency (RF) radiometry uses thermal noise detected by an antenna to measure the temperature of objects independent of medical imaging technologies such as magnetic resonance imaging (MRI). Here, an active interventional MRI antenna can be deployed as a RF radiometer to measure local heating, as a possible new method of monitoring device safety and thermal therapy. A 128 MHz radiometer receiver was fabricated to measure the RF noise voltage from an interventional 3 T MRI loopless antenna and calibrated for temperature in a uniformly heated bioanalogous gel phantom. Local heating (ΔT) was induced using the antenna for RF transmission and measured by RF radiometry, fiber-optic thermal sensors, and MRI thermometry. The spatial thermal sensitivity of the antenna radiometer was numerically computed using a method-of-moment electric field analyses. The gel's thermal conductivity was measured by MRI thermometry, and the localized time-dependent ΔT distribution computed from the bioheat transfer equation and compared with radiometry measurements. A "H-factor" relating the 1 g-averaged ΔT to the radiometric temperature was introduced to estimate peak temperature rise in the antenna's sensitive region. The loopless antenna radiometer linearly tracked temperature inside a thermally equilibrated phantom up to 73 °C to within ±0.3 °C at a 2 Hz sample rate. Computed and MRI thermometric measures of peak ΔT agreed within 13%. The peak 1 g-average temperature was H = 1.36 ± 0.02 times higher than the radiometric temperature for any media with a thermal conductivity of 0.15-0.50 (W/m)/K, indicating that the radiometer can measure peak 1 g-averaged ΔT in physiologically relevant tissue within ±0.4 °C. Active internal MRI detectors can serve as RF radiometers at the MRI frequency to provide accurate independent measures of local and peak temperature without the artifacts that can accompany MRI thermometry or the extra space needed to accommodate alternative thermal transducers. A RF radiometer could be integrated in a MRI scanner to permit "self-monitoring" for assuring device safety and/or monitoring delivery of thermal therapy.

Evapotranspiration Estimates over Non-Homogeneous Mediterranean Land Cover by a Calibrated “Critical Resistance” Approach

An approach based on the Penman-Monteith equation was used to estimate the actual evapotranspiration from local meteorological data over non-homogeneous land cover in a Mediterranean site in the south-east of Italy, with two six month data sets from two different years of measurements (2006 and 2009). The “critical resistance” formulation was used in different forms to model the surface resistance, together with some modifications to take into account the soil moisture content. One, two, or three model parameters were estimated, one of them related to the atmospheric resistance and the others to the surface resistance, and the calibration was made by either linear regression or nonlinear minimization of a proper cost function, depending on the applicability. Two kinds of cost functions were tested, the first depending on both the latent heat flux and the difference between screen air temperature and surface radiometric temperature, and the second depending on the temperature difference only. In all cases the calculated fluxes give better results with respect to both a flux-gradient approach and a complementarity based method, that require comparable data inputs. However the calibration by the temperature differences only, that requires no turbulent flux measurements, considerably increases the statistical uncertainty of the calibration parameters. The inclusion of the soil moisture did not significantly improve the model results in the considered site.

Determination of land surface reflectance using the AATSR dual-view capability

Abstract. In this study, a method is presented to retrieve the surface reflectance using the radiances measured at the top of the atmosphere for the two views provided by the Advanced Along-Track Scanning Radiometer (AATSR). In the first step, the aerosol optical depth (AOD) is obtained using the AATSR dual-view algorithm (ADV) by eliminating the effect of the surface on the measured radiances. Hence the AOD is independent of surface properties and can thus be used in the second step to provide the aerosol part of the atmospheric correction which is needed for the surface reflectance retrieval. The method is applied to provide monthly maps of both AOD and surface reflectance at two wavelengths (555 and 659 nm) for the whole year of 2007. The results are validated versus surface reflectance provided by the AERONET-based Surface Reflectance Validation Network (ASRVN). Correlation coefficients are 0.8 and 0.9 for 555 and 659 nm, respectively. The standard deviation is 0.001 for both wavelengths and the absolute error is less than 0.02. Pixel-by-pixel comparison with MODIS (Moderate Resolution Imaging Spectrometer) monthly averaged surface reflectances show a good correlation (0.91 and 0.89 for 555 and 659 nm, respectively) with somewhat higher values (up to 0.05) obtained by ADV over bright surfaces. The difference between the ADV- and MODIS-retrieved surface reflectances is smaller than ±0.025 for 68.3% of the collocated pixels at 555 nm and 79.9% of the collocated pixels at 659 nm. An application of the results over Australia illustrates the variation in the surface reflectances for different land cover types. The validation and comparison results suggest that the algorithm can be successfully used for both the AATSR and ATSR-2 (which has characteristics similar to AATSR) missions, which together cover a 17-year period of measurements (1995–2012), as well as a prototype for the Sea and Land Surface Temperature Radiometer (SLSTR) planned to be launched in the fall of 2015 onboard the Sentinel-3 satellite.

Regression Kriging-Based Upscaling of Soil Moisture Measurements From a Wireless Sensor Network and Multiresource Remote Sensing Information Over Heterogeneous Cropland

The ground truth estimated by in situ measurements is important for accurately evaluating retrieved remote sensing products, particularly over heterogeneous land surfaces. This letter analyzes the role of multisource remote sensing observations on the upscaling of soil moisture observed by a wireless sensor network at the pixel scale via the regression kriging (RK) method. Three types of auxiliary remote sensing information are employed, including Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Temperature Vegetation Dryness Index (TVDI; 90 m), Polarimetric L-band Multiband Radiometer brightness temperature (700 m), and Moderate Resolution Image Spectroradiometer TVDI (1000 m). Moreover, a comparison with the ordinary kriging method is analyzed. The spatial inferences show that the RK method is more accurate and that its spatial pattern is more consistent with the auxiliary data when the trend is successfully removed, particularly when spatial continuity is destroyed by irrigation. The ASTER TVDI has a higher resolution and stronger correlation with soil moisture and yields more accurate interpolation results than the other types of remote sensing information. Although medium-resolution data do not substantially contribute to capture the spatial patterns of soil moisture, such data may still improve the prediction accuracy.

Variability of the martian seasonal CO2 cap extent over eight Mars Years

We present eight Mars Years of nearly continuous tracking of the CO2 seasonal cap edges from Mars Year (MY) 24 to 31 using Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) and Mars Reconnaissance Orbiter (MRO) Mars Climate Sounder (MCS) thermal infrared data. Spatial and temporal resolutions are 1 pixel per degree and 10°Ls (aerocentric longitude of the Sun). The seasonal caps are defined as the regions where the diurnal radiometric temperature variations at ∼32μm wavelength do not exceed 5K. With this definition, terrains with small areal fraction of defrosted regolith able to experience measurable diurnal temperature cycles are not mapped as part of the cap. This technique is adequate to distinguish CO2 from H2O ices, and effective during the polar night or under low illumination conditions. The present analysis answers outstanding questions stemming from fragmented observations at visible wavelengths: (1) the previously sparsely documented growth of the North seasonal caps (160°<Ls<270°) is shown to be repeatable within 1–2° equivalent latitude, and monotonic over the MY 24–31 time period; high repeatability is observed during the retreat of the caps in non-dusty years (∼1° or less equivalent latitude); (2) the MY 25 storm does not seem to have impacted the growth rate, maximal extents, or recession rate of the North seasonal caps, whereas the MY 28 dust storm clearly sped up the recession of the cap (∼2° smaller on average after the storm, during the recession, compared to other years); (3) during non-dusty years, the growth of the South seasonal cap (350°<Ls<100°) presents noticeable variability (up to ∼4° equivalent latitude near Ls=20°) with a maximum extent reached near Ls=90°; (4) the retreat of the Southern seasonal cap (100°<Ls<310°) exhibits large inter-annual variability, especially near 190°<Ls<220°; (5) the recession of the MY 25 South seasonal cap is significantly accelerated during the equinox global dust storm, with surface temperatures suggesting increased patchiness or enhanced dust mantling on the CO2 ice. These results suggest that atmospheric temperatures and dust loading are the primary source of variability in an otherwise remarkably repeatable cycle of seasonal cap growth and recession.

Diurnal Dynamics of Wheat Evapotranspiration Derived from Ground-Based Thermal Imagery

The latent heat flux, one of the key components of the surface energy balance, can be inferred from remotely sensed thermal infrared data. However, discrepancies between modeled and observed evapotranspiration are large. Thermal cameras might provide a suitable tool for model evaluation under variable atmospheric conditions. Here, we evaluate the results from the Penman-Monteith, surface energy balance and Bowen ratio approaches, which estimate the diurnal course of latent heat fluxes at a ripe winter wheat stand using measured and modeled temperatures. Under overcast conditions, the models perform similarly, and radiometric image temperatures are linearly correlated with the inverted aerodynamic temperature. During clear sky conditions, the temperature of the wheat ear layer could be used to predict daytime turbulent fluxes (root mean squared error and mean absolute error: 20–35 W∙m−2, r2: 0.76–0.88), whereas spatially-averaged temperatures caused underestimation of pre-noon and overestimation of afternoon fluxes. Errors are dependent on the models’ ability to simulate diurnal hysteresis effects and are largest during intermittent clouds, due to the discrepancy between the timing of image capture and the time needed for the leaf-air-temperature gradient to adapt to changes in solar radiation. During such periods, we suggest using modeled surface temperatures for temporal upscaling and the validation of image data.

Combining the bulk transfer formulation and surface renewal analysis for estimating the sensible heat flux without involving the parameter

AbstractThe single‐source bulk transfer formulation (based on the Monin‐Obukhov Similarity Theory, MOST) has been used to estimate the sensible heat flux, H, in the framework of remote sensing over homogeneous surfaces (HMOST). The latter involves the canopy parameter, , which is difficult to parameterize. Over short and dense grass at a site influenced by regional advection of sensible heat flux, HMOST with = 2 (i.e., the value recommended) correlated strongly with the H measured using the Eddy Covariance, EC, method, HEC. However, it overestimated HEC by 50% under stable conditions for samples showing a local air temperature gradient larger than the measurement error, 0.4 km−1. Combining MOST and Surface Renewal analysis, three methods of estimating H that avoid dependency have been derived. These new expressions explain the variability of H versus , where is the friction velocity, is the radiometric surface temperature, and is the air temperature at height, z. At two measurement heights, the three methods performed excellently. One of the methods developed required the same readily/commonly available inputs as HMOST due to the fact that the ratio between and the ramp amplitude was found fairly constant under stable and unstable cases. Over homogeneous canopies, at a site influenced by regional advection of sensible heat flux, the methods proposed are an alternative to the traditional bulk transfer method because they are reliable, exempt of calibration against the EC method, and are comparable or identical in cost of application. It is suggested that the methodology may be useful over bare soil and sparse vegetation.

Radiometric temperature measurement with Si and InGaAs single-photon avalanche photodiode.

We experimentally demonstrate the use of single-photon avalanche photodiode (SPAD) for radiometric temperature measurement. The low dark count rate CMOS SPAD and a commercial InGaAs/InP SPAD can detect the thermal radiation from a blackbody down to the temperatures of 510 and 405 K, respectively. Our work shows that current SPADs are cost-effective thermal sensors for various applications.

Investigation of very high cycle fatigue by thermographyc method

Nowadays, many components and structures are subjected to fatigue loading with a number of cycles higher than 107. In this scientific work, the behaviour of two kinds of tool steel was investigated in very high cycle fatigue regime. The fatigue tests were carried out at the frequency of 20 kHz and in fully reversed tensioncompression mode (R = -1) by means of an ultrasonic fatigue testing equipment. The radiometric surface temperature was detected during all the test by means of an IR camera in order to extend the Thermographic Method and the Energetic Approach in very high cycle fatigue regime. The failure mechanism of the investigated steels was evaluated by means of several experimental techniques (scanning electron microscopy, Energy Dispersive X-ray spectroscopy and Optical Microscopy).

Development of the mechanical cryocooler system for the Sea Land Surface Temperature Radiometer

The Sea Land Surface Temperature Radiometer is a dual view Earth observing instrument developed as part of the European Global Monitoring for Environment and Security programme. It is scheduled for launch on two satellites, Sentinel 3A and 3B in 2014. The instrument detectors are cooled to below 85K by two split Stirling Cryocoolers running in hot redundancy. These coolers form part of a cryocooler system that includes a support structure and drive electronics. Aspects of the system design, including control and reduction of exported vibration are discussed; and results, including thermal performance and exported vibration from the Engineering Model Cryooler System test campaign are presented.