Antarctic ice sheet and sea ice regional albedo and temperature change, 1981-2000, from AVHRR Polar Pathfinder data

Spring-summer (November, December, January) ice sheet and sea ice regional surface albedo, surface temperature, sea ice concentration and sea ice extent averages and trends from 1981 to 2000 have been calculated for the Antarctic area. In this research the AVHRR Polar Pathfinder 5-km EASE-Grid Composites and the combined SMMR and SSMI data sets from the National Snow and Ice Data Center (NSIDC), Boulder, Colorado have been employed. A regional analysis has been made for five longitudinal sectors around Antarctica: the Weddell Sea (WS), the Indian Ocean (IO), the Pacific Ocean (PO), the Ross Sea (RS) and the Bellingshausen-Amundsen Sea (BS). The IO and PO sectors show ice sheet albedos of 0.85 and temperatures of − 25 °C. The corresponding values in the RS and BS sectors are 0.80 and − 16 °C respectively. The sea ice albedo is about 0.60 in the RS, BS and WS sectors and 0.55 in the IO and PO sectors. The average sea ice temperature varies around − 12 °C. All the sectors show slight increasing spring-summer albedo trends and decreasing spring-summer temperature trends and similar interannual variability in albedo and surface temperature. The steepest ice sheet albedo trend of 0.0019 ± 0.0009/yr is found in the RS sector. The steepest sea ice albedo trend of 0.0044 ± 0.0017 /yr occurs in the PO sector. The steepest temperature trends for both the ice sheet and sea ice occur in the BS sector, having values of − 0.075 ± 0.040 °C/yr and − 0.107 ± 0.027 °C/yr respectively. The sea ice concentration shows slight increasing trends, the highest being in the PO sector (0.3 ± 0.12%/yr), whereas the sea ice extent trends are near zero with the exception of the RS sector (14,700 ±8600 km²/yr) and the BS sector (− 13,000 ± 6400 km²/yr).     

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.     

Characteristics of atmospheric divergence and convergence in the Indian Ocean inferred from scatterometer winds

Large-scale surface atmospheric convergence and divergence patterns in the Indian Ocean are mapped using high-spatial resolution, merged scatterometer wind vectors during 1991-2000. The convergence zone evolves to north of 15°S as a result of convection promoted by warm (> 28 °C) equatorial sea surface temperature (SST), and it exhibits strong intensity during boreal summer and winter. A divergence zone evolves to the south of 15°S as a result of subdued convection caused by colder SST (< 24 °C) that reduces outgoing long-wave radiation; it exhibits enhanced intensity in the eastern Indian Ocean during boreal winter. The interannual variability shows that the divergence in the eastern Indian Ocean lags its western counterpart by 5-7 months. The convergence in the eastern Indian Ocean is stronger than its western counterpart during boreal summer. Relationship between Southern Oscillation Index and spatially averaged convergence time series indicate that the latter weakened during strong El Niño years 1994 and 1997. Spatially averaged divergence time series show a near-contemporaneous relationship with all-India rainfall, with a temporal lag of 1∼2 months.     

Satellite-based and mesoscale regression modeling of monthly air and soil temperatures over complex terrain in Turkey

Simple regression algorithms were developed to quantify spatio-temporal dynamics of minimum and maximum air temperatures (T_min and T_max, respectively) and soil temperature for a depth of 0-5 cm (T_soil-5cm) across complex terrain in Turkey using Moderate Resolution Imaging Spectroradiometer (MODIS) data at a 500-m resolution. A total of 762 16-day MODIS composites (127 images × 6 bands) between 2000 and 2005 were averaged over a monthly basis to temporally match monthly T_min, T_max, and T_soil-5cm from 83 meteorological stations. A total of 60 (28 temporally averaged plus 32 time series-based) linear regression models of T_min, T_max, and T_soil-5cm were developed using best subsets procedure as a function of a combination of 12 explanatory variables: six MODIS bands of blue, red, near infrared (NIR), middle infrared (MIR), normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI); four geographical variables of latitude, longitude, altitude, and distance to sea (DtS); and two temporal variables of month, and year. The best multiple linear regression models elucidated 65% (RMSE = 5.9 °C), 65% (RMSE = 5.1 °C), and 57% (RMSE = 6.9 °C) of variations in T_min, T_max, and T_soil-5cm, respectively, under a wide range of T_min (−34 to 25 °C), T_max (0.2-47 °C) and T_soil-5cm (−9 to 40 °C) observed at the 83 stations.     

Nano particulate SnO2 based resistive films as a hydrogen and acetone vapour sensor

SnCl₂ (solution) was spin coated on soda lime glass and Al₂O₃ substrate to obtain nano-particulate tin oxide film, directly by sintering at 550 °C for 40 minutes (min). The surface morphology and crystal structure of the tin oxide films were analyzed using atomic force microscopy (AFM) and X-ray diffraction (XRD). The size of SnO₂ nanostructure was determined from UV-vis and found to be ?3 nm. These films were tested for sensing H₂ concentration of 0.1-1000 ppm at optimized operating temperature of 265 °C. The results showed that sensitivity (R_air/R_gas per ppm) goes on increasing with decreasing concentration of test gas, giving concentration dependent changes. Special studies carried out at low concentration levels (0.1-1 and 1-10 ppm) of H₂, give high sensitivity (200 × 10⁻³/ppm) for lowest concentration (0.1-1 ppm) of H₂. The selectivity for H₂ against relative humidity (RH), CO₂, CO and LPG gases is also good. The sensor, at operating temperature of 200 °C, is showing nearly zero response to 300 ppm of H₂, and offering response to acetone vapour of 11 ppm. Selectivity for acetone against RH% and CO₂ was also studied. These sensors can be used as H₂ sensor at an operating temperature of 265 °C, and as an acetone sensor at the operating temperature of 200 °C.     

Satellite and surface-based remote sensing of Saharan dust aerosols

The spatial and temporal characteristics of dust aerosols and their properties are assessed from satellite and ground-based sensors. The spatial distribution of total column aerosol optical depth at 550 nm (AOD) from the Moderate Resolution Imaging SpectroRadiometer (MODIS) coupled with top of atmosphere Clouds and the Earth's Radiant Energy System (CERES) shortwave fluxes are examined from the Terra satellite over the Atlantic Ocean. These data are then compared with AOD from two Aerosol Robotic Network (AERONET) ground-based sun photometer measurement sites for nearly six years (2000-2005). These two sites include Capo Verde (CV) (16°N, 24°W) near the Saharan dust source region and La Paguera (LP) (18°N, 67°W) that is downwind of the dust source regions. The AOD is two to three times higher during spring and summer months over CV when compared to LP and the surrounding regions. For a unit AOD value, the instantaneous TOA shortwave direct radiative effect (DRE) defined as the change in shortwave flux between clear and aerosol skies for CV and LP are − 53 and − 68 Wm^− 2 respectively. DRE for LP is likely more negative due to fall out of larger particles during transport from CV to LP. However, separating the CERES-derived DRE by MODIS aerosol effective radii was difficult. Satellite and ground-based dust aerosol data sets continue to be useful to understand dust processes related to the surface and the atmosphere.     

A CO2 sensor based upon a continuous-wave thermoelectrically-cooled quantum cascade laser

A CO₂ sensor based upon a continuous-wave thermoelectrically-cooled distributed feedback quantum cascade laser operating between 2305 and 2310 cm⁻¹ and a 54.2 cm long optical cell has been developed. Two approaches for direct absorption spectroscopy have been evaluated and applied for monitoring of the CO₂ concentration in gas lines and ambient laboratory air. In the first approach optical transmittance was derived from the single channel laser intensity, whilst in the second approach a ratio of signal and reference laser intensities (balanced detection) was used. The optimum residual absorption standard deviation was estimated to be 1.9 × 10⁻⁴ for 100 averages of 1 ms duration and 0.1 cm⁻¹ scans over the P(46) CO₂ absorption line of the ν₃ vibrational band at 2306.926 cm⁻¹. A CO₂ detection limit (1 standard deviation) of 36 ppb was estimated for 0.1 s average and balanced detection.     

A first assessment of the SMOS data in southwestern France using in situ and airborne soil moisture estimates: The CAROLS airborne campaign

The Soil Moisture and Ocean Salinity (SMOS) satellite mission, based on an aperture synthesis L-band radiometer was successfully launched in November 2009. In the context of a validation campaign for the SMOS mission, intensive airborne and in situ observations were performed in southwestern France for the SMOS CAL/VAL, from April to May 2009 and from April to July 2010. The CAROLS (Cooperative Airborne Radiometer for Ocean and Land Studies) bi-angular (34°-0°) and dual-polarized (V and H) L-band radiometer was designed, built and installed on board the French ATR-42 research aircraft. During springs of 2009 and 2010, soil moisture observations from the SMOSMANIA (Soil Moisture Observing System-Meteorological Automatic Network Integrated Application) network of Météo-France were complemented by airborne observations of the CAROLS L-band radiometer, following an Atlantic-Mediterranean transect in southwestern France. Additionally to the 12 stations of the SMOSMANIA soil moisture network, in situ measurements were collected in three specific sites within an area representative of a SMOS pixel. Microwave radiometer observations, acquired over southwestern France by the CAROLS instrument were analyzed in order to assess their sensitivity to surface soil moisture (w_g). A combination of microwave brightness temperature (T_b) at either two polarizations or two contrasting incidence angles was used to retrieve w_g through regressed empirical logarithmic equations with good results, depending on the chosen configuration. The regressions derived from the CAROLS measurements were applied to the SMOS T_b and their retrieval performance was evaluated. The retrievals of w_g showed significant correlation (p-value < 0.05) with surface measurements for most of the SMOSMANIA stations (8 of 12 stations) and with additional field measurements at two specific sites, also. Root mean square errors varied from 0.03 to 0.09 m³ m^− 3 (0.06 m³ m^− 3 on average).     

Sea-air flux of CO2 in the Caribbean Sea estimated using in situ and remote sensing data

Empirical relationships between sea surface carbon dioxide fugacity (fCO₂^sw) and sea surface temperature (SST) were applied to datasets of remotely sensed SST to create fCO₂^sw fields in the Caribbean Sea. SST datasets from different sensors were used, as well as the SST fields created by optimum interpolation of bias corrected AVHRR data. Empirical relationships were derived using shipboard fCO₂^sw data, in situ SST data, and SST data from the remote sensing platforms. The results show that the application of a relationship based on shipboard SST data, on fields of remotely sensed SST yields biased fCO₂^sw values. This bias is reduced if the fCO₂^sw-SST relationships are derived using the same SST data that are used to create the SST fields. The fCO₂^sw fields found to best reproduce observed fCO₂^sw are used in combination with wind speed data from QuikSCAT to create weekly maps of the sea-air CO₂ flux in the Caribbean Sea in 2002. The region to the SW of Cuba was a source of CO₂ to the atmosphere throughout 2002, and the region to the NE was a sink during winter and spring and a source during summer and fall. The net uptake of CO₂ in the region was doubled when potential skin layer effects on fCO₂^sw were taken into account.     

AVHRR satellite remote sensing and shipboard measurements of the thermal plume from the Daya Bay, nuclear power station, China

The 1800 MW Daya Bay Nuclear Power Station (DNPS), China's first nuclear power station, is located on the coast of the South China Sea. DNPS discharges 29 10×10⁵ m³ year⁻¹ of warm water from its cooling system into Daya Bay, which could have ecological consequences. This study examines satellite sea surface temperature data and shipboard water column measurements from Daya Bay. Field observations of water temperature, salinity, and chlorophyll a data were conducted four times per year at 12 sampling stations in Daya Bay during January 1997 to January 1999. Sea surface temperatures were derived from the Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites during November 1997 to February 1999. A total of 2905 images with 1.1×1.1 km resolution were examined; among those images, 342 have sufficient quality for quantitative analysis. The results show a seasonal pattern of thermal plumes in Daya Bay. During the winter months (December to March), the thermal plume is localized to an area within a few km of the power plant, and the temperature difference between the plume and non-plume areas is about 1.5 °C. During the summer and fall months (May to November), there is a larger thermal plume extending 8-10 km south along the coast from DNPS, and the temperature change is about 1.0 °C. Monthly variation of SST in the thermal plume is analyzed. AVHRR SST is higher in daytime than in nighttime in the bay during the whole year. The strong seasonal difference in the thermal plume is related to vertical mixing of the water column in winter and to stratification in summer. Further investigations are needed to determine any other ecological effects of the Daya Bay thermal plume.     

Electrical conductivity dependence of Ni doped Sm0.95Ce0.05FeO3−δ on surface morphology and composition

Sm_0.95Ce_0.05Fe_1−xNi_xO_3−δ materials are considered as candidates for sensing reducing gases. The total electrical conductivity of Ni doped Sm_0.95Ce_0.05FeO_3−δ perovskite materials is discussed in terms of Ni concentration, surface morphology and relative surface atomic ratios. Powders of formula Sm_0.95Ce_0.05Fe_1−xNi_xO_3−δ (x = 0-0.10) were prepared from citrate precursors by using a sol gel method and were then pressed uniaxially and sintered at 1350 °C for 4 h to form pellets. In fresh pellets the relative surface atomic ratios of Sm and Ni increased while that of Fe and Ce decreased as a function of nickel concentration, showing the segregation of samarium species. In contrast, the chemically reduced pellets show Fe rich surfaces. The electrical conductivity of fresh, partially reduced (700 °C under 5% (v/v) H₂/N₂ for 1 h) and fully reduced (1000 °C under 5% (v/v) H₂/N₂ for 1 h) pellets was measured by the four probe DC method.Under air, x = 0.07 and x = 0.10 showed the highest electrical conductivity in the series. Interestingly the x = 0.01-0.05 materials were n-type conductors while x = 0.07-0.10 exhibited p-type behaviour. The reduction treatment at 1000 °C enhanced electrical conductivities up to ∼5000 fold due to changes associated with surface morphology and surface elemental composition. While phase separations are usually detrimental, in this case the reduced sensors are more sensitive without sacrificing reproducibility.     

Electrical and CO gas sensing properties of nanostructured La1−xCexCoO3 perovskite prepared by activated reactive synthesis

A series of nanostructred La_1−xCe_xCoO₃ perovskite-type (x ranging from 0 to 0.2), with a crystallite size of around 10 nm and a specific surface area of up to 55 m²/g were prepared using the activated reactive grinding method. XRD results showed that Ce segregates as CeO₂ when the addition level exceeds 10 at%. CO was chosen as a typical reducing gas and its interaction with surface oxygen was investigated. TPD-O₂ was used to investigate the effect of Ce-doping on total surface oxygen. The experimental results confirmed a positive effect of Ce-doping of up to 10 at% on total surface oxygen (α-O₂). TPD-CO and XPS analyses were performed to find the total carbon adsorption (i.e. related to the adsorption of CO) on the surface of the synthesized samples. Both methods confirmed that more carbon adsorbs on the surface of doped formulations compared to the pure LaCoO₃. Ce-doping increases the surface oxygen, thereby facilitating the adsorption and oxidation processes. CO gas sensing properties of thick La_1−xCe_xCoO₃ films were performed. La_0.9Ce_0.1CoO₃ showed the highest conductivity and the lowest activation energy. The optimum CO sensing temperature for doped formulation was found to be 100 °C compared to 130 °C for pure perovskite. Ce-doped samples showed a maximum response ratio of 240% with respect to 100 ppm CO in air compared to 60% obtained with pure LaCoO₃.     

An interferometric biosensor composed of a prism-chamber assembly and a composite waveguide with a Ta2O5 nanometric layer

A highly sensitive integrated polarimetric interferometer biosensor with improved long-time stability and simple operation was prepared by using a novel prism-chamber assembly and an inexpensive waveguide made by sputtering a tapered nanometric layer of Ta₂O₅ on a single-mode glass waveguide. By comparing the measured refractive-index (RI) sensitivities with those simulated based on a four-layer homogeneous waveguide, both the equivalent thicknesses (T_eq) for the tapered Ta₂O₅ layers and a severe dependence of RI sensitivity on T_eq were obtained. Addition of 1 g of water in 100 g of a Chinese liquor (alcohol concentration = 46% (v/v)) was easily detected by the sensor. Monitoring of anti-human IgG adsorption with a waveguide of T_eq = 31.99 nm indicates that the antibody coverage required for inducing a phase-different change of Δ? = π is less than 0.012 monolayer. The same waveguide presents a quasi-linear dependence of Δ? on water temperature with the slope of d(Δ?)/dT = −28.50°/°C to which the contribution by the thermo-optical effect of the waveguide is 4.24°/°C, equivalent to a liquid RI change of Δn_c = 1.41 × 10⁻⁵. The interferometer exhibits the promising potential for chemical and biological analyses because of its outstanding characteristics.     

Remote observation of the sea surface and atmosphere The oceanic skin effect

Abstract

A comparison is made between the measurements of sea surface temperature (SST), obtained using an infrared radiometer mounted on a vessel of the British Antarctic Survey, and from a conventional Meteorological Office rubber bucket with mercury thermometer. These measurements are used to investigate the size and variability of the oceanic skin effect from the tropical Atlantic to the waters of Antarctica. The implication of the skin effect on the validation of satellite-borne infrared sensors of the sea surface temperature is also investigated. In terms of the overall average for the complete Atlantic Ocean data set, the skin of the sea is about 0-30 deg K cooler than the bulk at about 10cm below the surface. There are only a few cases of the skin being warmer than the bulk temperature, on the other hand there are some occasions when the skin can be of the order of 1 -0 deg K cooler than the bulk. There is a suggestion that the skin effect at night-time is smaller than it is during the day-time, and a possible explanation of this is given in terms of the complication of the diurnal thermocline. The skin effect can be an important source of error in the validation of space-borne sensors of SST, particularly with the requirement for high accuracy of SST measurement for climate studies. In terms of the retrieval of SST from satellite infrared sensors the skin effect is only one of several physical effects that create uncertainty in the value of SST.     

An assessment of chlorophyll-a algorithms available for SeaWiFS in coastal and open areas of the Bay of Bengal and Arabian Sea

Three ocean colour algorithms, OC4v6, Carder and OC5 were tested for retrieving Chlorophyll-a (Chla) in coastal areas of the Bay of Bengal and open ocean areas of the Arabian Sea. Firstly, the algorithms were run using ~ 80 in situ Remote Sensing Reflectance, (R_rs(λ)) data collected from coastal areas during eight cruises from January 2000 to March 2002 and the output was compared to in situ Chla. Secondly, the algorithms were run with ~ 20 SeaWiFS R_rs(λ) and the results were compared with coincident in situ Chla. In both cases, OC5 exhibited the lowest log₁₀-RMS, bias, had a slope close to 1 and this algorithm appears to be the most accurate for both coastal and open ocean areas. Thirdly the error in the algorithms was regressed against Total Suspended Material (TSM) and Coloured Dissolved Organic Material (CDOM) data to assess the co-variance with these parameters. The OC5 error did not co-vary with TSM and CDOM. OC4v6 tended to over-estimate Chla > 2 mg m⁻³ and the error in OC4v6 co-varied with TSM. OC4v6 was more accurate than the Carder algorithm, which over-estimated Chla at concentrations > 1 mg m⁻³ and under-estimated Chla at values < 0.5 mg m⁻³. The error in Carder Chla also co-varied with TSM. The algorithms were inter-compared using > 5500 SeaWiFS R_rs(λ) data from coastal to offshore transects in the Northern Bay of Bengal. There was good agreement between OC4v6 and OC5 in open ocean waters and in coastal areas up to 2 mg m⁻³. There was a strong divergence between Carder and OC5 in open ocean and coastal waters. OC4v6 and Carder tended to over-estimate Chla in coastal areas by a factor of 2 to 3 when TSM > 25 g m⁻³. We strongly recommend the use of OC5 for coastal and open ocean waters of the Bay of Bengal and Arabian Sea. A Chla time series was generated using OC5 from 2000 to 2003, which showed that concentrations at the mouths of the Ganges reach a maxima (~ 5 mg m⁻³) in October and November and were 0.08 mg m⁻³ further offshore increasing to 0.2 mg m⁻³ during December. Similarly in early spring from February to March, Chla was 0.08 to 0.2 mg m⁻³ on the east coast of the Bay.     

Can phytoplankton community structure be inferred from satellite-derived sea surface temperature anomalies calculated relative to nitrate depletion temperatures?

Hydrographic data collected in the upper 50 m off La Jolla, CA, USA (31°N, 117°W) between 1970 and 1972 were reanalyzed to examine temporal variability in the local temperature-nitrate relationship and to document how chlorophyll a concentration and phytoplankton community structure covary with the temperature-nitrate relationship. Based on the linear expression y=mx+b, the y-intercepts (b), slopes (m), and x-intercepts (−b/m or nitrate depletion temperature, NDT) of four seasonal (January-March, April-June, July-September, and October-December) temperature-nitrate relationships, obtained from the combined multiyear data set, were statistically different from each other and varied around overall multiyear values of b=72.73 μM, m=−5.33 μM °C⁻¹, and NDT=13.65 °C. Three interannual temperature-nitrate relationships from February to April 1970, 1971, and 1972 also had y-intercepts, slopes, and x-intercepts that were statistically different from each other. Nevertheless, limited variability in direct comparisons among seasonal or interannual regression lines and a 1 °C La Jolla NDT range compared to a 25 °C global NDT range supported the general utility of NDT-based comparisons. A nitrate-normalized temperature axis (T−NDT) was created for the La Jolla data set by subtracting NDT from the recorded water column temperatures (T). Chlorophyll a reached a maximum between 0 and 2 °C on this T-NDT axis that ranged from −4 to 10 °C. Microscope-based determinations of La Jolla centric diatom, pennate diatom and dinoflagellate abundances, and La Jolla chlorophyll a, partitioned in proportion to the numerical abundance of the three groups, both peaked in logical progression along the T-NDT axis. In a separate analysis of high-performance liquid chromatography (HPLC) data from three Atlantic Meridional Transect (AMT) cruises (50°N to 52°S), chlorophyll a peaked below 0 °C and three different phytoplankton classes, nanoflagellates, large eukaryotes and prokaryotes, distributed in logical progression along a sea surface temperature (SST) minus NDT axis. To further generalize these results, a previously reported 1° latitude×1° longitude grid of NDTs for the world ocean was applied to satellite-derived grids of SST for March 1999 through June 2000. The SST−NDT calculation provided a standard nitrate-normalized axis simultaneously applicable to all locations in the world ocean. Sixteen plots of satellite-derived chlorophyll a versus SST−NDT for March 1999 through June 2000 demonstrated the opposing seasonal movements of northern and southern hemisphere chlorophyll a along the SST-NDT axis. Based on the phytoplankton community patterns along the temperature minus NDT in the La Jolla and AMT data sets, this chlorophyll a movement along the SST-NDT axis can be associated with phytoplankton community changes related to location around SST−NDT=0 °C. The SST−NDT index appears to provide a useful tool for interpreting the character of the phytoplankton community structure contributing to satellite-derived chlorophyll a in the world ocean.     

Impact of sea ice on the retrieval of water-leaving reflectance, chlorophyll a concentration and inherent optical properties from satellite ocean color data

Two physical phenomena by which satellite remotely sensed ocean color data are contaminated by sea ice at high latitudes are described through simulations and observations: (1) the adjacency effect that occurs along sea ice margins and (2) the sub-pixel contamination by a small amount of sea ice within an ocean pixel. The signal at the top of the atmosphere (TOA) was simulated using the 6S radiative transfer code that allows modeling of the adjacency effect for various types of sea ice surrounding an open water area. In situ sea ice reflectance spectra used in the simulations were measured prior to and during the melt period as part of the 2004 Canadian Arctic Shelf Exchange Study (CASES). For sub-pixel contamination, the TOA signal was simulated for various surface reflectances obtained by linear mixture of both sea ice and water-leaving reflectances (ρ_w). The standard atmospheric correction algorithm was then applied to the simulated TOA spectra to retrieve ρ_w spectra from which chlorophyll a concentrations (CHL) and inherent optical properties (IOPs) were derived. The adjacency effect was associated with large errors (> 0.002) in the retrieval of ρ_w as far as 24 km from an ice edge in the blue part of the spectrum (443 nm). Therefore, for moderate to high CHL (> 0.5 mg m^− 3), any pixel located within a distance of ∼ 10-20 km from the ice edge were unreliable. It was also found necessary to consider the adjacency effect when the total absorption coefficient (a_t) was to be retrieved using a semi-analytical algorithm. a_t(443) was underestimated by more than 35% at a distance of 20 km from an ice edge for CHL > 0.5 mg m^− 3. The effect on the retrieval of the particle backscattering coefficient (b_bp) was important only for clear waters (CHL ∼ 0.05 mg m^− 3). In contrast, sub-pixel contamination by a small amount of sea ice produced systematic underestimation of ρ_w in the blue because of incorrect interpretation of enhanced reflectance in the near infrared that is attributed to higher concentrations of atmospheric aerosols. In general, sub-pixel contamination was found to result in overestimations of CHL and a_t, and underestimations of b_bp. A simple method was proposed to flag pixels contaminated by adjacency effect.     

Estimates of sea surface nitrate concentrations from sea surface temperature and chlorophyll concentration in upwelling areas: A case study for the Benguela system

The knowledge of nitrate fields at global or regional scales in the ocean is fundamental for the study of oceanic biogeochemical processes, particularly those linked to new primary production. The estimate of nitrate concentrations from space is generally based on empirical inverse relationships between sea surface temperature (SST) and nitrate concentrations. These relationships, however, are often highly variable spatially and temporally, and hardly applicable to large areas (i.e., larger than a few degrees in latitude). In this paper we propose a new approach specifically developed for areas influenced by upwelling processes. It relates the nitrate concentration to the difference between SST and the estimated temperature of the upwelled water (variable with latitude and season), δT, which is an indicator of the time elapsed since upwelling. This approach is tested for the Benguela upwelling system, and algorithms are developed using in situ data provided by the World Ocean Database 2005 of the NOAA-NESDIS-National Oceanographic Data Center. The results reveal a significant improvement compared to the NO₃-SST relationships, and a single algorithm can be applied to the whole upwelling area (15 to 35°S). Further improvement is gained by coupling this approach with a method that derives sea surface nitrate concentrations from SST and surface chlorophyll a concentration using multiple regression analyses, as proposed by Goes et al. [Goes, Saino, Oaku, Jiang, (1999). Method for estimating sea surface nitrate concentrations from remotely sensed SST and chlorophyll a: A case study for the North Pacific Ocean using OCTS/ADEOS data. IEEE Transactions on Geoscience and Remote Sensing, 37, no. 3 II, 1633-1644].     

Multi-sensor satellite and in situ measurements of a warm core ocean eddy south of the Brazil-Malvinas Confluence region

A warm core eddy was detected south of the Brazil-Malvinas (Falkland) Confluence (BMC) region in satellite images of the southwestern Atlantic Ocean in late 2002. The structure was also sampled by in situ instruments deployed by a ship in 2 days of November 2002. An analysis of satellite data was performed to account for the lifecycle, dimension, surface temperature, surface chlorophyll concentration, surface height anomaly and displacement of the eddy since it was detached from the Brazil Current in September 2002. Satellite data were derived from several sources such as the AMSR-E, MODIS and radar altimeter. The structure lasted 64 days at south of the Brazil-Malvinas Confluence region later being re-assimilated by the Brazil Current return flow. In situ data collected during 2 days showed that the eddy was about 150 m deep, 5.5 °C warmer and 1 practical salinity unit saltier than adjacent waters. The salt anomaly associated to the eddy was estimated as 1.37 × 10¹² kg while its heat content was 4.24 × 10¹⁸ J. These are typical estimates for eddies present at the BMC region. Sea surface temperature (SST), chlorophyll concentration, and sea surface height anomaly time series were analyzed for the eddy's center along its trajectory path throughout its lifetime. Mean translational velocities for the eddy during its lifetime were computed from visual interpretation and by using an adaptation of the Maximum Cross-Correlation (MCC) method on AMSR-E SST images. The overall deviation between the two methods was 26%. This suggests that the MCC method has a potential to be applied in monitoring programs to automatically account for the translational velocities of eddies in the BMC region.