On the Earth's surface energy exchange determination from ERS satellite ATSR data: Part 2. Short-wave radiation

This is the second in a series of papers which discusses determination of the Earth's surface energy exchange from ERS satellite Along-Track Scanning Radiometer (ATSR) data. The paper concentrates on short-wave radiation on sea and land surfaces. In this paper, three methods were used to determine solar irradiance by using ERS ATSR-2 data. We referred to them as 'D scheme', 'T scheme' and 'O scheme'. Intercomparisons of the three schemes were carried out. The schemes were applied to the land and sea areas. The visible and near-infrared reflectances were derived from ERS-2 ATSR-2 spectral bands by using the atmospheric radiative transfer model developed by Xue and Cracknell. The narrowband reflectances are combined into a measure of surface albedo by use of a weighted averaged scheme. The schemes were applied to the land and sea areas in UK and deforestation area in Brazil. The D scheme can give solar spectral irradiance but can not give broadband solar irradiance because of the wavelength limit of sensor visible bands. The T scheme and O scheme can give good broadband solar irradiance but can not give solar spectral irradiance. The O scheme was developed by Oberhuber, which was used to create climatological datasets for GCMs. The O scheme also includes the effects of humidity and surface temperature. The O scheme is better used for daily or monthly averaged solar radiation. The other two schemes can also be developed to determine the hourly or daily solar irradiance. The results show that it is now possible to derive longterm surface solar irradiance from ATSR-2 data which can be useful in climate and hydrological studies. However, our current analysis is restricted to a small range of conditions and needs to be extended to a larger dataset.     

On the Earth's surface energy exchange determination from ERS satellite ATSR data: Part 3. Turbulent heat flux on open sea

This is the third in a series of papers which discusses determination of the Earth's surface energy exchange from ERS satellite Along-Track Scanning Radiometer (ATSR) data. This paper focuses on estimation of turbulence heat flux exchange by using ATSR data in areas of open sea. In this paper, we present results of net longwave radiation, latent heat flux and sensible heat flux. The results of net longwave radiation are from the first paper in the series (Xue et al., 1998, International Journal of Remote Sensing, 19, 2561-2583). We use monthly average tropical-ocean-global-atmosphere (TOGA) data and ATSR sea surface temperature (SST) data to calculate two years' (1992 and 1993) heat fluxes in the TOGA area. A comparison with published results indicates good qualitative agreement. Also, we compared the results of heat flux exchange by using ATSR SST data and by using the TOGA bucket SST data. The ATSR SST dataset has been shown to be useful in helping to estimate the large space scale heat flux exchange.     

Quantifying variability of satellite data in the reflective band for long-term monitoring of the Earth's surface: inference from a multi-temporal relationship between remotely sensed pixels

Reliable long-term monitoring of the Earth's surface is urgently needed for a comprehensive understanding of our environment. However, remotely sensed data is generally affected by a number of temporal factors such as lifetime sensor degradation, Sun–target–satellite geometry and atmospheric conditions. The induced inconsistencies weaken the reliability of satellite-based change studies. A direct method is to remove the inconsistencies through converting the satellite digital number (DN) into a physical quantity using a physically or statistically based model. The associated errors in the conversion are generally hard to trace in the converted quantity, and this leaves questions unanswered. In this study, we propose an alternative approach to quantifying the influences on DN values, based on a multi-temporal relationship in the visible bands. First, we make use of the spectral dependency of aerosol optical thickness on wavelength to expand the validity of the multi-temporal relationship for reflective bands. As an inference of the relationship, a satellite DN value is determined analytically with the temporal influences in terms of a multiplicative and an additive component. In the case of the Landsat-5 Thematic Mapper (TM), we illustrate the variability in DN value in a spatio-temporal context. Lifetime sensor degradation (long-term effect) leads to an increase in the multiplicative effect and a minor change in the additive effect on the DN value. The combined Sun–target–satellite geometry and atmospheric variation induce periodic oscillations in both the multiplicative and additive effects on the DN value. The variation is generally larger for surfaces with a high reflectance than those with a low reflectance. The proposed approach combines sensor calibration and atmospheric correction into one equation, which offers the potential for tracing associated uncertainties propagated into a quantity converted or derived from satellite data, for long-term monitoring of changing surfaces.     

Improving the spatio-temporal distribution of surface solar radiation data by merging ground and satellite measurements

Appropriate information on solar resources is very important for a variety of technological areas, such as: agriculture, meteorology, forestry engineering, water resources and in particular in the designing and sizing of solar energy systems. However, the availability of observed solar radiation measurements has proven to be spatially and temporally inadequate for many applications. In this paper we propose to merge the global solar radiation measurements from the Royal Meteorological Institute of Belgium solar measurements network with the operationally derived surface incoming global short-wave radiation products from Meteosat Second Generation satellites imageries to improve the spatio-temporal resolution of the surface global solar radiation data over Belgium. We evaluate several merging methods with various degrees of complexity (from mean field bias correction to geostatistical merging techniques) together with interpolated ground measurements and satellite-derived values only. The performance of the different methods is assessed by leave-one-out cross-validation.     

Detection of surface soil variation using high-resolution satellite data: results from the U.K. SPOT-simulation investigation

Abstract

A problem in using multispectral scanner(MSS) data for soil and landsystem analysis in north-west Europe is the poor spatial resolution which is insufficient to provide adequate within-field data. The SPOT satellite system will provide MSS data at 20m resolution and panchromatic data at 10m resolution. For any given ground feature the SPOT MSS mode will provide considerably more sample areas than LANDSAT 80m data. The object of this study is to determine how far variation in surface soil parameters can be detected and quantified on the basis of SPOT data.     

Effect of surface wind speed and sensor view zenith angle dependence of emissivity on SST retrieval from thermal infrared data: ATSR

The Along Track Scanning Radiometer (ATSR) data are currently being processed at various places within the European community including the Rutherford Appleton Laboratory (RAL) in the U.K. In generating an atmospherically corrected sea-surface temperature (SST) field, the emissivity of the sea surface is assumed to be independent of the sensor view zenith angle, sea state and wavelength (Ian Barton, RAL, personal communication). The sensor view zenith angle dependence of the emissivity is generally not known because of the complications introduced by the surface wind speed. This paper attempts to evaluate the uncertainties introduced in the SST due to the variation of emissivity with the sensor view zenith angle and surface roughness generated by the wind speed.

Using the Cox and Munk formulation, Takashima and Takayama have simulated the sea water emissivities as a function of wind speed of up to 15ms^-1 and a range of the sensor view zenith angles. Their emissivity data for 11 and 12μm channels corresponding to the viewing geometry of the ATSR have been used in this work. It is shown that, depending on the value of the SST, there can be significant errors due to the sensor view zenith angle and sea surface roughness dependence of the emissivity. For example, if the SST is 10°C and the wind speed is 0ms^-1, then the errors due to the sensor view zenith angle dependence of the emissivity are shown to be 0·77°C and 0·55°C in 11 and 12μm channels, respectively, and at 15 ms^-l the respective errors reach about 1·ldeg K and 0·86 deg K. The errors due to the deviations of the emissivities from unity for nadir view in calm conditions are about 2·1°C and 3·5°C, respectively, in the 11 and 12μm channels. All of these errors are additive, indicating the importance of the calibration and validation.     

Mesoscale surface current fields in the Baltic Sea derived from multi-sensor satellite data

We demonstrate the use of multi-sensor satellite images for the computation of mesoscale surface currents in the Northern and Southern Baltic Proper by enhancing and combining image-processing techniques. The sequential satellite images were acquired by the Thematic Mapper (TM), the ERS-2 Synthetic Aperture Radar (SAR), the Wide-Field Scanner (WiFS) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) during extensive cyanobacterial blooms in July 1997 and in July/August 1999. We also used a pair of Advanced SAR (ASAR) images from May 2005 showing imprints of singular oil spills in the Southern Baltic Proper. Different marine surface films and accumulated algae at the water surface were taken as tracers for the local motion of the sea surface. Data from sensors working at different electromagnetic bands (e.g. TM and SAR) were used to apply high-speed feature-matching (cross-correlation) techniques for motion detection. The sufficiently short time lags between the multiple image acquisitions (from less than 1 h to approximately 1 day) and the high spatial coverage allowed for the calculation of optical flow (i.e. surface motion) fields, which include small-scale turbulent structures that are not resolved by operational numerical models. Our computed surface currents range from 4 to 35 cm s^?1 and are generally larger than those provided by the numerical models for the same dates and areas. We attribute this difference to local wind forcing, causing higher drift velocities at the very sea surface, which is seen from space, but which is not resolved by the numerical models.     

On the assessment of multivariable controllers using closed loop data. Part I: Identification of system models

Controller performance assessment of SISO and MIMO systems requires effective and systematic identification of the associated system models based on closed-loop data. In this work, a new methodology for the identification of the process, controller and disturbance models is presented for the purpose of enabling the evaluation of the performance of MIMO control systems. The methodology is based on subspace identification algorithms for the identification of the controller, process and disturbance models from closed-loop data. However, identification of the process model is enhanced by the estimation of the associated interactor matrix via the Variable Regression Estimation technique, the existence of which is mathematically proved. The proposed identification methodology is applied to two 2 × 2 systems utilizing both step-response and PRBS closed-loop data.     

Assessing the information content of multiangle satellite data for mapping biomes: I. Statistical analysis

The insights gained from present land cover classification activities suggest integration of multiangle data into classification attempts for future progress. Land cover types that exhibit distinct signatures in the space of remote sensing data facilitate unambiguous identification of cover types. In this first part, we develop a theme for consistency between cover type definitions, uniqueness of their signatures, and physics of the remote sensing data. The idea of angular signatures in spectral space is proposed to provide a cogent synthesis of information from spectral and angular domains. Three new metrics, angular signature slope (ASSI), length (ASLI), and intercept indices, are introduced to characterize biome signatures. The statistical analyses with these indices confirm the idea that incorporation of the directional variable should improve biome classification result. The consistency principle is tested with the Multiangle Imaging SpectroRadiometer (MISR) leaf area index (LAI) algorithm by examining retrievals when both unique and nonunique signatures are input together with a land cover map. It is shown that this requirement guarantees valid retrievals. Part II provides a theoretical basis for these concepts [Zhang et al., Remote Sens. Environ., in press.].     

Comment on ‘Effect of surface wind speed and sensor view zenith angle dependence of emissivity on SST retrieval from thermal infrared data: ATSR’

Singh, in a recent paper, attempts to describe the effect of sea surface emissivity variations on sea surface temperature (SST) retrieval from satellite borne infrared instruments (specifically the Along Track Scanning Radiometer (ATSR)). It is based, for the most part, on an incorrect premise, draws conclusions about SST retrieval accuracy which are not supported by the necessaryevaluation of atmospheric and retrieval algorithm effects, and contains erroneous calculations. The shortcomings of the paper are discussed.     

Estimating surface temperatures from satellite thermal infrared data—A simple formulation for the atmospheric effect

In recent years the availability of high spatial resolution thermal infrared data from satellites has prompted the use of energy budget models relating satellite-derived surface temperatures to surface moisture, near-surface thermal inertia, energy exchange with the atmosphere, etc. However, correction of the high spatial resolution satellite data for atmospheric water vapor effects can represent a substantial computational burden unless simplifying assumptions are utilized. A simple formulation is developed and its applicability tested by application to standard meteorological soundings at a time near the overpass of an NOAA operational satellite. It appears that reasonable estimates of surface temperature (±2–3°C) are readily obtained for areas of order 100–300 km².     

On the net surface water exchange rate estimated from remote-sensing observation and reanalysis

This study compares the net surface water exchange rates, or surface precipitation (P) minus evapotranspiration (ET), and atmospheric water vapour sinks calculated from various observations and reanalyses, and investigates whether they are physically consistent. We use the observed precipitation from the Global Precipitation Climatology Project (GPCP) and the Tropical Rainfall Measuring Mission (TRMM) 3B43, ocean evaporation from Goddard Satellite-based Surface Turbulent Fluxes Version 2c (GSSTF2c), and land ET from the Moderate Resolution Imaging Spectroradiometer (MODIS) global ET project (MOD16) and PT-JPL products to calculate observed P minus observed ET. P–ET is also obtained from atmospheric water vapour sink calculated using Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit observation specific humidity observation and wind fields from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and ERA-interim, denoted as AIRS_M and AIRS_E, respectively. MERRA and ERA-interim water vapour budgets are also calculated for cross-comparison and consistency check. The period of study is between 2003 and 2006 based on the availability of all of the data sets. Averaged water vapour sinks from AIRS and reanalysis are consistent over the global ocean and are close to zero (range: 0.02–0.06 mm day^?1), but range between 0.14 and 0.23 mm day^?1 when land is included. Over ocean within 50^oS--50^oN, averaged observed P minus observed evaporation shows a much larger negative number than that obtained from AIRS and reanalysis. The differences mainly occur over subtropical oceans, especially in the southern hemisphere in summer and the northern hemisphere in winter. Over land, generally higher agreement between observed P minus observed ET and atmospheric water vapour sinks (calculated from AIRS and reanalysis) is found. However, large regional differences, often with strong seasonal dependence, are also observed over land. Estimates of atmospheric water vapour sinks are influenced by both winds and biases in water vapour data, especially over tropics and subtropical oceans, thereby calling for the need for further investigations and consistency checks of satellite-based and reanalysis water vapour, reanalysis winds, P observations, and surface evaporation estimates. In higher latitudes, atmospheric water vapour sinks calculated from AIRS_M, AIRS_E, MERRA, and ERA-interim are more consistent with each other.     

Reduction of excessive energy in the four-noded membrane quadrilateral element. Part I: Linear theory-compressible materials

The objective of the paper is to set forth, in a consistent manner, reasons for the appearance of excessive energy in the four-noded membrane quadrilateral element and to propose a formulation leading to simple and reliable elements that are less sensitive to distortions of the geometrical shape. By presenting the differential geometry, emphasis is placed upon those geometrical attributes which are inherently related to the quadrilateral. A modified version of the functional of Hu-Washizu is employed for the discretization. Appropriate approximations for the displacements/rotations are chosen and the physical meaning of the various parameters is identified. A systematic procedure is followed for the approximation of stress and strain. The convergence of the formulation is investigated by examining the inf–sup condition and applying the patch test. Also, results of numerical examples and comparisons with other elemental formulations are presented.     

Development of a model for the estimation of photosynthetically active radiation from geostationary satellite data in a tropical environment

This paper presents a model for the estimation of photosynthetically active radiation (PAR) from geostationary satellite data. The model is aimed to estimate the monthly average hourly PAR in a tropical environment. This model represents a physical relation of PAR incident on the earth's surface and satellite-derived earth-atmospheric albedo together with the absorption and scattering coefficients of various atmospheric constituents. The earth-atmospheric albedo was obtained from the Multifunctional Transport Satellite-1R (MTSAT-1R). The absorption of PAR by water vapor, an important process for the tropics, was computed from the ambient temperature and relative humidity. The absorption of PAR by aerosols was estimated by using the visibility data and aerosol optical properties obtained from the Aerosol Robotic Network (AERONET) of NASA in this region. The total column ozone from the Ozone Monitoring Instrument onboard of AURA satellite (OMI/AURA) was used for the estimation of the absorption of PAR by ozone. The model was validated against the monthly average hourly PAR from measurements at four solar radiation measuring stations situated in the tropical environment of Thailand. The values of the monthly average hourly PAR estimated from the model and those obtained from the measurement were in good agreement, with the root mean square error (RMSE) and mean bias error (MBE) of 9.8% and 0.6%, respectively. After the validation, the model was employed to estimate the monthly average hourly PAR over Thailand using a 4-year period of data from MTSAT-1R and other ancillary surface data. Values of the monthly average hourly PAR were presented as maps showing the geographical distribution of PAR. These maps reveal the diurnal and seasonal variation of PAR over the country.     

Retrieval of land surface albedo and temperature using data from the Indian geostationary satellite: a case study for the winter months

The shortwave and longwave radiation budget at land surfaces is largely dependent on two fundamental quantities, the albedo and the land surface temperature (LST). A time series (November 2005 to March 2006) of daily data from the Indian geostationary satellite Kalpana‐1 Very High Resolution Radiometer (K1VHRR) sensor in the visible (VIS), water vapour (WV) and thermal infrared (TIR) bands from noontime (0900 GMT) observations were processed to retrieve these quantities in clear skies for five winter months. Cloud detection was carried out using bispectral threshold tests (in both VIS and TIR bands) in a dekadal time series. Surface albedo was retrieved using a simple atmospheric transmission model. K1VHRR albedo was compared with Moderate Resolution Imaging Spectroradiometer (MODIS) AQUA noontime albedo over different land targets (agriculture, forest, desert, scrub and snow) that showed minimum differences over agriculture and forest. The comparison of spatial albedo over different landscapes yielded a root mean square deviation (RMSD) of 0.021 in VHRR albedo (9% of MODIS albedo). A mono‐window algorithm was implemented with a single TIR band to retrieve the LST. Its accuracy was also verified over different land targets by comparison with aggregated MODIS AQUA LST. The maximum RMSD was obtained over agriculture. Spatial comparison of VHRR and AQUA LSTs over homogeneous and heterogeneous landscape cutouts revealed an overall RMSD of 2.3 K. An improvement in the retrieval accuracy is expected to be achieved with atmospheric products from the sounder and split thermal bands in the imager of future INSAT 3D missions.     

On the relation between HCMM satellite data and temperatures from standard meteorological sites in complex terrain

Data from the Heat Capacity Mapping Mission Experiment Satellite (HCMM) are used to plot lines of constant temperature at 1° intervals for the city of Melbourne and surrounding country. Using four individual scenes, the relationship between uncalibrated, i.e. relative, surface temperature and screen daily minimum air temperature at some 26 standard meteorological stations in the greater Melbourne region was studied. It was found that the relation between the two data sources is poor for the sites taken separately but that means of daily minimum temperatures for appropriately grouped meteorological sites show a consistent linear relationship with night-time HCMM data. The HCMM data also show significant variation in surface temperatures within short distances from meteorological sites and it is concluded that surface temperatures in such an area vary on a spatial scale that is large compared with the area sampled by a standard meteorological site but small compared with an HCMM pixel. The implications are that a number of sites arc needed to characterize a region independently of site-specific effects (i.e. that appropriately grouped sites can under some circumstances be used for calibrating satellite thermal data) and that thermal imagery could provide criteria for the selection of new standard meteorological sites.     

Estimation of absorbed PAR across Scandinavia from satellite measurements: Part I: Incident PAR

The primary productivity of a plant community can be modeled as the product of the amount of photosynthetically active radiation (PAR) absorbed by the canopy and a light use efficiency factor, where the amount of absorbed PAR (APAR) is the product of the fractional absorption and the amount of incident PAR. By implementing a method, PARcalc, using atmospheric data from the Moderate Resolution Imaging Spectroradiometer (MODIS), incident PAR is estimated in this study. In addition, since many PAR datasets are generated by converting shortwave radiation into PAR, the ratio of PAR to shortwave radiation was also investigated. PARcalc models the photosynthetic photon flux density (PPFD) as a product of atmospheric transmittance, the cosine of the Sun zenith angle, and the solar constant. The atmospheric transmittance includes the attenuation of radiation by Rayleigh and aerosol scattering, and absorption by water and ozone. A cloud transmittance factor which is primarily a function of the cloud optical thickness is added in order to cope with cloudy conditions. The model was implemented at two sites in Sweden, Asa and Norunda, where in situ measurements of PPFD were made during the spring and summer of 2004. Modeled time-series were evaluated against the measurements, and daily sums of PPFD were calculated by fitting of a sine function in combination with linear interpolation of the instantaneous estimates from sunrise to sunset. This gave correlation coefficients at Norunda and Asa of 0.80 and 0.77, respectively, when comparing modeled and measured daily insolation. The average relative errors were 24% and 25%. Corresponding figures for five day averages were 0.91 and 0.86; and 9.3% and 11.9%. Instantaneous estimates of PPFD were modeled with correlation coefficients of 0 88-0 93 and average relative errors from 17.0%. These numbers were acquired when using measured values for determining cloudiness; the corresponding figures when the method is fully implemented using satellite data are 0.84 to 0.71 and 24.9%, respectively. The ratio of PAR to shortwave radiation was measured at Norunda 1 Jan to 31 Oct 2004 and was found to vary between 0.27 and 0.48 on a daily basis with an average of 0.43 for the whole period.     

Ground-based method for measuring thermal infrared effective emissivities: Implications and perspectives on the measurement of land surface temperature from satellite data

Thermal infrared emissivity is an important parameter for surface characterization and for determining surface temperature. The field-based measurements for ground and vegetation emissivities in 8-14 w m waveband were performed with an emissivity box. A theoretical analysis was carried out using the box and a correcting factor has been determined. The average value for thermal band emissivity of the exposed bare soil was found to be around 0.909; the average value measured for most of the varieties of vegetation present were in the range of 0.980-0.985. A theoretical model is used for obtaining effective emissivity in the 8-14 w m region from Advanced Very High Resolution Radiometer (AVHRR) data considering the proportion of vegetation cover in a pixel and the field-measured emissivity values. The error of the methodology is found to be within 1.5%. Narrow band emissivities for AVHRR channels 4 and 5 have been derived from the emissivity values in the 8-14 w m waveband. The surface temperature has been derived from AVHRR data using a split-window algorithm as a function of emissivities derived in narrow bands. The split-window algorithm accounted for absorption effects of the atmosphere by incorporating the water vapour concentration measured in the campaign. A good agreement was obtained between the satellite-derived surface temperature and the in situ observations. The result suggest that the methodology allows us to derive land surface temperature with an accuracy better than 1.5° C provided the surface emissivity is known. The paper describes the field-based emissivity measurement and approach for deriving surface temperature over land surface.     

Estimation of absorbed PAR across Scandinavia from satellite measurements. Part II: Modeling and evaluating the fractional absorption

The aim of this study is to generate a quality-controlled sub-kilometer dataset of the fraction of absorbed photosynthetically active radiation (FAPAR) across Scandinavia from satellite. FAPAR is required for estimating the amount of PAR absorbed (APAR) by vegetation, which in turn allows for estimation of carbon uptake. In this study, FAPAR was modeled from normalized difference vegetation index (NDVI) which was obtained from the MODIS VI product (MOD13Q1) at 250 m spatial resolution. Modeled FAPAR was evaluated against in-situ measurements of fractional interception of PAR (FIPAR) and FAPAR at nine plots in six forested sites across Sweden and Denmark from 2001 to 2005. High resolution remote sensing data were used to investigate the representativeness of the measurement areas. Furthermore, FAPAR from the MODIS LAI/FPAR product at 1 km spatial resolution (MOD15A2) was investigated and compared the measured and modeled FAPAR. There was good agreement between modeled and measured FAPAR (6.9% average RMSE of the means). A linear relationship between daily values of NDVI and FAPAR was found (R² = 0.82), and it is concluded that seasonally adjusted NDVI can be used for accurate FAPAR estimations over forested areas in Scandinavia. However, it was found that the error was correlated with average FAPAR and that it is important to take the understory vegetation into account when measuring FAPAR in open canopies. The observed difference between FIPAR and FAPAR was 2.3 and 1.4 percentage units for coniferous and deciduous stands, respectively. MODIS FAPAR performed well although a few unrealistic values were present, highlighting the necessity to filter out low quality values using the quality-control datasets.     

The EQUALANT99 experiment: in situ and satellite data for surface circulation in the tropical Atlantic

In summer 1999, an extensive survey of the tropical Atlantic ocean was operated during the EQUALANT99 cruise. Several experiments were carried out on board including, for the first time in that area, eXpendable Conductivity–Temperature–Depth (XCTD) launches. The aim of this experiment was first to evaluate XCTD temperature and salinity profiles, and secondly to check how XCTD could be used together with altimetric satellite missions in order to capture a good picture of the tropical Atlantic surface circulation.