Atmospheric correction for the sea surface temperature using NOAA-7 AVHRR and METEOSAT-2 infrared data

The multi-spectral method for atmospheric corrections is investigated. The analysis shows that the non-linear effects of the atmospheric absorption can be accounted for by using three channels. The results clarify and lend theoretical support to previous works. A simple correction procedure is proposed. In the case where channel 3 of the NOAA AVHRR is not available or is contaminated, simultaneous METEOSAT infrared data can be used instead. The result tested with in situ measured temperatures shows a marked improvement when three channels are used. In this procedure, the detailed knowledge of the local atmospheric profiles is not required.     

Aircraft validation of ERS-1 ATSR and NOAA-14 AVHRR sea surface temperature measurements

Infrared brightness temperature (BT) measurements obtained from the UK Meteorological Research Flight C-130 Hercules aircraft, spatially coincident and near contemporaneous with ERS-1 Along Track Scanning Radiometer (ATSR) and NOAA-14 Advanced Very High Resolution Radiometer (AVHRR), are presented. These data have been used to obtain much needed on-going validation of the ERS-1 ATSR prior to the de-commissioning of the ATSR instrument in March 1997. BT comparisons between the ATSR and AVHRR nadir channels show negligible differences of 0.3 deg K, indicating that both radiometers are well calibrated. However, significant differences are found when common sea surface temperature (SST) algorithms are applied to the BT data. The original dual view ERS-1 ATSR skin SST (SSST) algorithm has a 0.6K cool bias relative to the in situ observations, which is consistent with other in situ validation studies. New SSST coefficients derived using the same atmospheric transmission model show that, when the appropriate pixel noise contribution is considered in the algorithm derivation, substantially improved SSST is derived from the ERS-1 ATSR. Comparing the NOAA-14 AVHRR non-linear SST (NLSST) and multi-channel SST (MCSST) algorithms to the aircraft data, the non-linear nature of the NLSST algorithm results in a small bias of 0.3 deg K compared to a substantial cool bias of 1 deg K in the MCSST case. This result highlights deficiencies in the MCSST.     

Improved calibration coefficients for NOAA-14 AVHRR visible and near-infrared channels

An analysis of the calibration coefficients used to describe sensor degradation in channels 1 and 2 of the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-14 spacecraft is presented. The radiometrically stable permanent ice sheet of central Antarctica is used as a calibration target to characterize sensor performance. Published calibration coefficients and the coefficients imbedded in the NOAA Level 1b data stream for the period January 1995 to November 1998 are shown to be deficient in correcting for the degradation of the sensor with time since launch. Calibration formulae constructed from NOAA-9 reflectances are used to derive improved calibration coefficients for the AVHRR visible and near-infrared channels for NOAA-14. Channel 1 reflectances for the Greenland ice sheet derived using the new coefficients are consistent with those derived previously using NOAA-9 AVHRR. In addition, improved reference AVHRR channel 2 reflectances for Greenland are derived from NOAA-14 observations. It is recommended that the coefficients derived in this study be used to calibrate reflectances for NOAA-14 AVHRR channels 1 and 2.     

Updated calibration coefficients for NOAA-14 AVHRR Channels 1 and 2

New calibration coefficients for channels 1 and 2 of NOAA-14 AVHRR are presented. Observations from the radiometrically stable permanent ice sheet of central Antarctica for the period from launch through January 2001 are used to evaluate the accuracy of published calibration coefficients. The rate of sensor degradation in channels 1 and 2 is found to change after January 1998. The new calibration coefficients more accurately characterize sensor performance to date.     

Operational measurement of sea surface temperatures at CMS Lannion from NOAA-7 AVHRR data

Abstract

Data from the NOAA-7 Advanced Very-High-Resolution Radiometer (AVHRR) have been used on a routine basis for sea surface temperature (SST) retrieval at the Centre de Meteorologie Spatiale (CMS) in Lannion (France) since September 1983. Operational SST retrieval is still practised at CMS, using NOAA-9 data. Two methods are used. The first, which is automatic, produces numerical fields (resolution: 15 × 15 nautical miles); the second is manual and produces graphic documents (resolution about 10 km). The corresponding products are published in a monthly bulletin, SATMER. The accuracy of satellite SSTs has been tested by various methods, the results of which are discussed. Some case studies of SST time variability in the Mediterranean are presented. One of the main conclusions is the need for mesoscale (10 km) numerical SST fields produced as often as possible (daily) by interactive methods.     

Air-sea interacting effects to the sea surface temperature observation by NOAA/AVHRR

Abstract

Abstract. By combining the brightness temperatures by NOAA-9/AVHRR and the sea surface temperature by Mutsu Bay automatic marine monitoring buoy system, the total number of 390 match-ups was set up. The temporal and spatial coincidence in each match-up is within 30 minutes and one pixel resolution. Following to the split-window method, a regression function for the sea surface temperature estimation was calculated and its standard deviation of estimation errors was 0-59°C. The residues were carefully examined with respect to the sensor calibration data and the meteorological data at match-up collections. Then it was found that large errors appeared when differences between the air temperature and the buoy temperature were large. Those were estimated to be caused by the air-sea interacting effects. By removing the match-ups with larger errors, a selected data set with 334 match-ups was prepared and the SST estimation function was recalculated. The standard deviation of errors reduced to 0-34 °C.     

Development of a daily long term record of NOAA-14 AVHRR land surface temperature over Africa

We developed a new 6-year daily, daytime and nighttime, NOAA-14 AVHRR based land surface temperature (LST) dataset over continental Africa for the period 1995 through 2000. The processing chain was developed within the Global Inventory Modeling and Mapping System (GIMMS) at NASA's Goddard Space Flight Center. This paper describes the processing methodology used to convert the Global Area Coverage Level-1b data into LST and collateral data layers, such as sun and view geometries, cloud mask, local time of observation, and latitude and longitude. We used the Ulivieri et al. [Ulivieri, C., M.M. Castronuovo, R. Francioni, and A. Cardillo (1994), A split window algorithm for estimating land surface temperature from satellites, Adv. Space Research, 14(3):59-65.] split window algorithm to determine LST values. This algorithm requires as input values of surface emissivity in AVHRR channels 4 and 5. Thus, we developed continental maps of emissivity using an ensemble approach that combines laboratory emissivity spectra, MODIS-derived maps of herbaceous and woody fractional cover, and the UNESCO FAO soil map. A preliminary evaluation of the resulting LST product over a savanna woodland in South Africa showed a bias of < 0.3 K and an uncertainty of < 1.3 K for daytime retrievals (< 2.5 K for night). More extensive validation is required before statistically significant uncertainties can be determined. The LST production chain described here could be adapted for any wide field of view sensor (e.g., MODIS, VIIRS), and the LST product may be suitable for monitoring spatial and temporal temperature trends, or as input to many process models (e.g., hydrological, ecosystem).     

Estimation of sea surface temperature from SEVIRI data: algorithm testing and comparison with AVHRR products

Three surface temperature (ST) algorithms for Spinning Enhanced Visible and InfraRed Imager (SEVIRI) data are developed and tested. A general split window algorithm for ST estimation, a sea surface temperature (SST) algorithm and a nonlinear algorithm (NLSST) developed for SEVIRI data. The test was carried out by comparing SEVIRI data with two types of data: (a) in situ and (b) obtained with the NLSST algorithm applied to Advanced Very High Resolution Radiometer (AVHRR). The field campaign was carried out over sea using a thermal radiometer. The algorithms were applied to SEVIRI images in coincidence with the field campaign and the results show an rms error lower than 0.7 K. The comparison with AVHRR data was carried out in six test regions and provided an rms error lower than 1.3 K. The best results were obtained for the SST algorithm proposed.     

Time series analysis of NOAA-4 sea surface temperature (SST) data

Through time series analysis of GOSSTCOMP satellite data, time differences in the occurrence of maximum and minimum mean monthly SST's off the coast of Brazil were observed in the region of 20–28° S by 34–47° W and showed the maximum surface water temperature to lag the coastal land station (Cananeia) by two months and the minimum by one month. For annual components of SST, maximum amplitudes were observed at Cabo Frio (influenced by upwelling) and Cananeia (influenced by Malvinas current) and minimum amplitudes at coastal and oceanic area between Ubatuba and Santos, a more thermally stable area.     

Size estimates of the factors controlling sea surface temperature with AVHRR data

NOAA AVHRR thermal infrared images, meteorological measurements and model calculations have been used to estimate the magnitude of the processes controlling the sea surface temperature variability in the Bay of Biscay. The estimates are based on the equation of temperature conservation and the equation for the total derivative. The results show that local time change, advection, horizontal diffusion and vertical turbulent flux vary with time and space. The sea surface temperature variability is mainly controlled by vertical turbulent flux and advection. For an average of five-day estimates, the order of the relative importance of the processes is vertical turbulence (38 per cent), advection (32 per cent), local time change (22 per cent) and horizontal diffusion (8 per cent).     

Validation of coastal sea and lake surface temperature measurements derived from NOAA/AVHRR data

An interactive validation monitoring system is being used at the NOAA/NESDIS to validate the sea surface temperature (SST) derived from the NOAA-12 and NOAA-14 polar orbiting satellite AVHRR sensors for the NOAA CoastWatch program. In 1997, we validated the SST in coastal regions of the Gulf of Mexico, Southeast US and Northeast US and the lake surface temperatures in the Great Lakes every other month. The in situ     

The effect of orbit drift on the calibration of the 3.7 µm channel of the AVHRR onboard NOAA-14 and its impact on night-time sea surface temperature retrievals

The orbit drift of National Oceanic & Atmospheric Administration (NOAA)-14 towards the terminator has caused the deterioration of the radiometric calibration of the Advanced Very High Resolution Radiometer (AVHRR) 3.7?µm channel at night. This deterioration is a result of solar contamination of the radiometric calibration system when the sun strikes the instrument from the spacecraft horizon. The long-term trend and seasonal variation of the contamination are analysed in this study based on trending data from 1995 to 2000. The calibration bias is evaluated and its effect on the sea surface temperature retrievals is quantified. The solar contamination in late 2000 affected as much as 25% of an orbit of data, compared to an average of 7% in 1995. The NOAA/NESDIS operational calibration algorithm partially corrects for the bias but residual effects can still contribute bias on the order of 0.5?K in scene brightness temperature.     

Movements of migrating green turtles in relation to AVHRR derived sea surface temperature

Previous studies have shown that for some populations of marine turtle, individuals move along narrow migration corridors in the open ocean. It has been suggested that these migration corridors may correspond with nearsurface oceanographic features that can be detected by remote sensing. This idea is examined by superimposing the tracks of green turtles (Chelonia mydas) migrating from Ascension Island to Brazil, on sea surface temperature (SST) data derived from Advanced Very High Resolution Radiometer (AVHRR) images. The turtles did not follow specific isotherms during migration nor make turns en-route where specific thermal cues were encountered. These results suggest that for this population, SST plays a minimal role in influencing the exact route that individuals follow.     

An algorithm for sea surface temperature estimation from ERS-1 ATSR using moisture dependent coefficients: a simulation study

A new algorithm for estimating sea surface temperature (SST) from ERS-1 ATSR data using moisture dependent coefficients has been proposed. The clear-column water vapour (WV) information required for selecting the appropriate coefficients has also been derived from ERS-1 ATSR data. The method has been tested with the simulated ATSR data by comparing the estimated SST with the true SST used for simulating the data. The comparison of SST estimation errors by present and standard methods, under different noise conditions, has indicated improvements by the present method over the standard method. The small errors anticipated in SST estimation due to the errors in WV estimation causing erroneous selection of coefficients have also been taken care of by making use of overlapping ranges of WV for moisture dependent SST estimation coefficients. The method could be used for operational SST from ATSR data.     

Comparisons of regional satellite sea surface temperature gradients derived from MODIS and AVHRR sensors

Regional sea surface temperature (SST) gradients were examined for a 6-year (2003–2008) period using data from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua and the Advanced Very High Resolution Radiometer (AVHRR) on two NOAA satellite platforms. Two regions, one in the California Current System and the other in the Gulf Stream, representing an eastern boundary upwelling region and strong western boundary current, respectively, were chosen to investigate the seasonal variability, statistical differences and similarities, and correlations with respect to the two sets of SST gradients. Results indicated higher gradient magnitudes using MODIS SST in relative comparison to those derived from AVHRR that are attributed to instrument and algorithm differences. These observed differences are important for any studies that employ SST gradients, such as fisheries investigations that have traditionally relied on AVHRR SST gradients only.     

Deriving some expansion theorems for nonlinear functional equations by an algorithm

In this paper we define the class of quasi-bilinear forms which covers the most important part of classes of nonlinear forms in functional programming. We give an algorithm for expanding such forms by equivalent transformations. We prove the corresponding theorem which guarantees that the output of the algorithm is an expansion of the input equation. And we give some examples to illustrate how to apply the algorithm to prove expansion theorems for some nonlinear equations.     

Deriving an inter-sensor consistent calibration for the AVHRR solar reflectance data record

A new set of reflectance calibration coefficients has been derived for channel 1 (0.63 μm) and channel 2 (0.86 μm) of the Advanced Very High Resolution Radiometer (AVHRR) flown on the National Oceanic and Atmospheric Administration (NOAA) and European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar orbiting meteorological satellites. This paper uses several approaches that are radiometrically tied to the observations from National Aeronautics and Space Administration's (NASA's) Moderate Resolution Imaging Spectroradiometer (MODIS) imager to make the first consistent set of AVHRR reflectance calibration coefficients for every AVHRR that has ever flown. Our results indicate that the calibration coefficients presented here provide an accuracy of approximately 2% for channel 1 and 3% for channel 2 relative to that from the MODIS sensor.     

Estimation of sea surface temperature from AVHRR data: reply to some comments by J. R. Eyre

Abstract

This paper refers to a previous comment by J. R. Eyre on an earlier paper of ours in which we tried to make the best possible use of 4-channel AVHRR/1 data for the determination of sea surface temperatures in situations where data from the 5-channel AVHRR/2 were not available. Here we clarify certain points regarding the philosophy of our earlier paper and also respond to some specific points made by Eyre.