Spatial and temporal variability of satellite-derived sea surface temperature in the Barents Sea

The Barents Sea (BS) is an important region for studying climate change. This sea is located on the main pathway of the heat transported from low to high latitudes. Since oceanic conditions in the BS may influence vast areas of the Arctic Ocean, it is important to continue to monitor this region and analyse the available oceanographic data sets. One of the important quantities that can be used to track climate change is the sea surface temperature (SST). In this study, we have analysed the 32 years, (1982–2013) National Oceanic and Atmospheric Administration (NOAA) Optimum Interpolation SST Version 2 data for the BS. Our results indicate that the regionally averaged SST trend in the BS (about 0.03°C year^–1) is greater than the global trend. This trend varies spatially with the lowest values north from 76° N and the highest values (about 0.06°C year^–1) in proximity of Svalbard and in coastal regions near the White Sea. The SST and 2 m air temperature (AT) trends are high in winter months in the open BS region located west from Novaya Zemlya. Such trends can be linked to a significant retreat of sea ice in this area in recent years. In this article, we also documented spatial patterns in the annual cycle of SST in the BS. We have shown that the interannual variability of SST is similar in different regions of the BS and well correlated with the interannual patterns in AT variability.     

AVHRR visible-IR detection of diurnal warming events in the western Mediterranean Sea

Abstract

Diurnal warming of the sea surface temperature (SST) is often observed in the spring and summer Advanced Very High Resolution Radiometer (AVHRR) imagery of the Mediterranean Sea. It masks SST features of oceano-graphic interest. Diurnally warmed regions, where low wind conditions prevail, exhibit smooth surface and thus are characterized by low reflected solar radiation except for specular reflection of the visible solar radiation. Utilization of this correlation through clustering of diurnally warmed areas in an infrared-visible histogram permits discrimination from areas where the SST is representative of the underlying bulk temperature.     

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.     

The Adriatic Sea surface temperature historical record from Advanced Very High Resolution Radiometer data (1981–1999)

A long-term time series of Advanced Very High Resolution Radiometer (AVHRR) (1981–1999) data has been used to assess the main physical features in the Adriatic Sea. Individual images were processed to estimate Sea Surface Temperature (SST) values, to create long-term composite fields (weekly, monthly, seasonal scales), and to derive basic statistics for the Northern, Central and Southern regions, each split again into an Eastern and a Western section. At the basin scale, an apparent general warming trend can be recognized in the time series. The linear fit to the seasonal cycles suggests an increase of about 2°C in 20 years, essentially due to a steady rise of summer values. A general north–south gradient can be found during winter, the Northern sections being colder than the Southern ones. An east–west gradient appears during summer, the Western sections being warmer then their Eastern ones. The Northern Adriatic exhibits substantial fluctuations, possibly linked to the cycle of winter cooling and summer warming in the relatively shallow sub-basin. The North Western section shows larger fluctuations than the North Eastern one, with lower winter SST, probably due to the freshwater inflow from the Po River delta. The Southern Adriatic exhibits less variability, possibly influenced by the periodic water exchanges with the Ionian Sea. The South Eastern section shows somewhat larger fluctuations than the South Western one, with higher winter SST, probably due to the inflow of warmer waters from the south. The two Central sections reveal patterns similar to the ones of the whole basin. The observed temperature patterns appear to follow the classical Adriatic cyclonic circulation scheme.     

Diurnal variations in AVHRR SST fields: A strategy for removing warm layer effects from daily images

Different methodologies to estimate the amplitude of the sea surface temperature diurnal variation (DV) and remove it from remotely sensed SST images have been proposed in the last years. Among these, the parameterization proposed by [Stuart-Menteth et al., 2004a] and [Stuart-Menteth et al., 2004b] [Stuart-Menteth, A.C., Robinson, I.S., & Weller, R.A. (2004a). Sensitivity of the diurnal warm layer to meteorological fluctuations Part 1: observations, submitted to Journal of Atmospheric and Ocean Science; Stuart-Menteth, A.C., Robinson, I. S., & Donlon, C.J. (2004b). Sensitivity of the diurnal warm layer to meteorological fluctuations Part 2: a new parameterisation for diurnal warming, submitted to Journal of Atmospheric and Ocean Science] and adopted by the GHRSST-PP (Donlon, 2004) [Donlon, C.J., ad the GHRSST-PP Science Team, 2004: The GHRSST-PP data processing specification v1.0 (GDS v1.0, revision 1.5), GHRSST-PP Report N. 17, Published by the International GHRSST-PP Project Office, pp. 241] appeared as the most promising. In fact, it takes into account wind and insolation variations during the day, that effectively drive the SST diurnal cycle.This parameterization has been tested on 6 months of NOAA-16 AVHRR images acquired and processed at CNR with Pathfinder algorithm. The tests evidenced some limits for a correct estimation of the DV in low-wind regimes for any insolation condition, and in high insolation regimes (>600 W/m²) when the wind intensity increases or decreases of more than 2 m/s during the morning. The limits of applicability of the DV correction to NOAA-16 AVHRR data (at least for the Mediterranean area) were thus identified, and data outside these limits were flagged. However, some anomalous heating were not corrected even with these constraints, due to the lack of accuracy in the wind field used for the correction. As a result, a strategy to flag residual outliers in the corrected daily images has been developed, based on the comparison to an optimally interpolated night SST field of the previous day.     

Relationship between AVHRR surface temperature and NDVI in Arctic tundra ecosystems

A negative, linear relationship between thermal emissions and a spectral vegetation index has been demonstrated for numerous mid‐latitude ecosystems. In this study, it is hypothesized that the relationship between surface temperature and the normalized difference vegetation index (NDVI) will be linear, but positive in Arctic tundra ecosystems due to the contrast between warm vegetation and the cold soil/moss background. This hypothesis is tested using Advanced Very High Resolution Radiometer (AVHRR) data collected over the North Slope of Alaska on three days during the summer of 1999. Results of the study generally provide support for this hypothesis. However, a consistent relationship observed across two contrasting physiographic provinces on one study day was shown to change the following day and could not be readily explained by differences in satellite zenith angle or observed air temperature. Surface temperatures are shown to respond directly to spatial and temporal variations in air temperature.     

Multisatellite observations and numerical simulation of an along‐coast cumulus cloud line induced by sea‐breeze circulation

A coastal cumulus cloud‐line formation along the east coast of the USA was observed on a National Oceanic and Atmospheric Administration (NOAA) Polar Orbiting Environmental Satellite (POES) Advanced Very High Resolution Radiometer (AVHRR) satellite image from 17 August 2001. The cloud line starts to form at about 16:00 UTC (local 12:00 noon) and follows the coastline from Florida to North Carolina. The length and width of the cloud line are about 850 km and 8.5 km, respectively. A 15‐min interval sequence of NOAA Geostationary Operational Environmental Satellite (GOES) images shows that the cloud line maintains the shape of the coastline and penetrates inland for more than 20 km over the next 6‐h timespan. Model simulation with actual atmospheric conditions as inputs shows that the cloud line is formed near the land–sea surface temperature (SST) gradient. The synoptic flow at all model levels is in the offshore direction prior to 16:00 UTC whereas low‐level winds (below 980 hPa) reverse direction to blow inland after 16:00 UTC. This reversal is due to the fact that local diurnal heating over the land takes place on shorter time‐scales than over the ocean. The vertical wind at these levels becomes stronger as the land–SST increases during the summer afternoon, and the leading edge of the head of the inland wind ascends from 920 hPa to about 850 hPa in the 3 h after 16:00 UTC. Model simulation and satellite observations show that the cloud line becomes very weak after 21:00 UTC when the diurnal heating decreases.     

An update on the dynamically induced episodes of extreme low ozone values over the northern middle latitudes

Over the middle latitudes of the Northern Hemisphere (NH), especially during the months of October–December, a number of episodes are observed when the total ozone for more than 2–3 days falls below 220 DU. This value has been introduced as the threshold for the Antarctic ozone hole but also represents ozone deviations of about one-third from the pre-1976 October–November–December monthly mean for the middle latitudes of the NH. Earlier studies have shown that the most common pattern of these events indicates transport of subtropical air from the Atlantic to the northeast frequently reaching Scandinavia and Northern Russia, sometimes combined with upward motions above a tropospheric anticyclone lifting low ozone mixing ratios to higher altitudes. In this study we report on the frequency and spatial extend of such extreme events using the newly available Multi Sensor Reanalysis (MSR) satellite total ozone data set for the period 1978–2008. During the autumn months considered in this study these events result to an ozone mass deficiency (O₃MD) of 5 tonnes km^?2 and their areal extend on a daily basis often exceeds 1.5 million km². More and larger in area events were observed during the 1990s and were possibly influenced by changes in the meridional circulation triggered by the maximum ozone depletion observed then over the middle latitudes of the NH.     

Bimodal variation of SST and related physical processes over the North Indian Ocean: special emphasis on satellite observations

Using sea surface temperature (SST) and wind speed retrieved by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), for the period of 1998–2003, we have studied the annual cycle of SST and confirmed the bimodal distribution of SST over the north Indian Ocean. Detailed analysis of SST revealed that the summer monsoon cooling (winter cooling) over the eastern Arabian Sea (Bay of Bengal) is more prominent than winter cooling (summer monsoon cooling). A sudden drop in surface short wave radiation by 57 W m^?2 (74 W m^?2) and rise in kinetic energy per unit mass by 24 J kg^?1 (26 J kg^?1) over the eastern Arabian Sea (Bay of Bengal) is observed in summer monsoon cooling period. The subsurface profiles of temperature and density for the spring warming and summer monsoon cooling phases are studied using the Arabian Sea Monsoon Experiment (ARMEX) data. These data indicate a shallow mixed layer during the spring warming and a deeper mixed layer during the summer monsoon cooling. Deepening of the mixed layer by 30 to 40 m with corresponding cooling of 2°C is found from warming to summer monsoon cooling in the eastern Arabian Sea. The depth of the 28°C isotherm in the eastern Arabian Sea during the spring warming is 80 m and during summer monsoon cooling it is about 60 m, while over the Bay of Bengal the 28°C isotherm is very shallow (35 m), even during the summer monsoon cooling. The time series of the isothermal layer depth and mixed layer depth during the warming phase revealed that the formation of the barrier layer in the spring warming phase and the absence of such layers during the summer cooling over the Arabian Sea. However, the barrier layer does exist over the Bay of Bengal with significant magnitude (20–25 m). The drop in the heat content with in first 50 m of the ocean from warming to the cooling phase is about 2.15 × 10⁸ J m^?2 over the Arabian Sea.     

Validation and application of MODIS-derived SST in the South China Sea

Using a variety of in situ sea surface temperature (SST) data sets in the South China Sea, we validate the satellite-derived SST from the Moderate Resolution Imaging Spectroradiometer (MODIS). Analysis of a large number of match-up samples during 2008–2012 shows that the MODIS SSTs have biases ranging from –0.19°C to –0.34°C and standard deviation (STD) errors ranging from 0.58°C to 0.68°C. Specifically, mean biases are all negative but there are smaller cool biases in daytime than those in night-time. The monthly validation analysis shows that the biases exhibit apparent seasonal variations. The biases in daytime have relatively small magnitudes in spring and summer, while the negative biases in night-time are most apparent in summer. On the other hand, the time series of MODIS SSTs may exhibit an evident diurnal variation for some months, which roughly agrees with the in situ SST measurements. This study also highlights that the MODIS SSTs under cloud-free conditions are effective at detecting the high-frequency and small-scale oceanic features, such as the localized diurnal variation, oceanic front, and coastal upwelling.     

Interannual variations in global SST deviations through SMMR from 1978 to 1987

We study variability of global sea surface temperature (SST) utilizing the data of scanning multichannel microwave radiometer (SMMR) on board the NASA Nimbus 7 satellite from 1978 to 1987. First, we model, and then remove from the SMMR SST data, the seasonal cycle by using an intercept, a trend and first five harmonics of the annual cycle to fit the data at each grid point by the method of least squares. A general negative nine‐year trend was observed. In order to analyse the deviations in the global SSTs, we calculate and remove zonally averaged temperatures. We then show Hoffmueller diagrams for the deviations along paths in different oceanic regions over the globe. These paths include a quadrangle in the south Pacific and paths in the north Pacific, Atlantic and along the equatorial Pacific. Both 1983 and 1987 El Niño events as well as the 1984–85 La Niña event are clearly depicted. During these events, the SSTs in the equatorial Pacific and Atlantic are completely out of phase. We also demonstrate spatial propagation of SST waves over interannual scales. In particular, a wave of a period of about 3–4 years following the North Pacific Current will be shown.     

Seasonal variation of sea surface temperature in the Bay of Bengal during 1992 as derived from NOAA-AVHRR SST data

Monthly maps of sea surface temperature (SST) derived from NOAA (National Oceanic and Atmospheric Administration)-AVHRR (Advanced Very High Resolution Radiometer) data during 1992 for the Bay of Bengal are analysed and compared with the available/compiled monthly seatruth (bucket thermometer) data of this region. It was noticed that the computed SST bias (AVHRR SST minus Seatruth SST), in general, varied between 2.0 and 2.5 C with smaller bias values (1.5 to 1.5 C) during January-June and December. Larger bias values were noticed in the south-eastern Bay in July and in the Andaman Sea in October. The large SST biases suggested the necessity for improvement of SST algorithms by properly removing the clouds. The spatial variation of Standard Deviation of SST bias was particularly high (0.7) in the western Bay when compared to other parts of the Bay of Bengal. The monthly maps of AVHRR SST clearly depicted the seasonal cycle of SST showing the well known bi-modal SST distribution of the study region with winter cooling, summer heating, monsoonal cooling and post-monsoon warming phases. The seasonal cycle of SST further revealed the persistence of Warm Pool (SST 28 C) in the Bay of Bengal from March through October.     

Geostrophic surface currents as derived from satellite SST images and measured by a land-based HF radar

Sea-surface temperatures (SST), as observed from a space-borne radiometer (AVHRR), are related to surface currents as measured by the high-frequency coastal radar (CODAR) in Norwegian coastal waters. Both systems yield about the same spatial resolution of the order of 1 km. Introducing a number of simplifying assumptions, the geostrophic portion of surface currents is derived from the SST distribution and compared with the CODAR measurements. In areas, characterised by strong temperature gradients, good agreement is found for current velocity and also for relative vorticity.     

Identification of upwelling areas on sea surface temperature images using fuzzy clustering

Sixteen sea surface temperature (SST) images obtained over the coastal ocean of Portugal during the period September 1992-September 2003 were used aiming to identify automatically the areas covered by upwelling waters. Suitable high resolution colour scales were applied to the SST images in order to enhance the thermal patterns and easily identify the waters with a coastal upwelling origin. The automatic identification of the areas covered by upwelling waters was developed by the authors in a previous work, through the application of fuzzy clustering and validation indexes, and here is explored as an oceanographic application to the Portuguese coastal upwelling. The fuzzy c-means (FCM) algorithm showed to be able to find partitions that closely defined the upwelling areas and the visualization of the fuzzy c-partitions was achieved through the application of a colour scale. The Xie-Beni validation index was used to select the c-partition that best represented the stage of the upwelling event and showed an agreement with the oceanographic interpretation in 10 of the 14 SST segmented images used in this work. Two SST images without upwelling were also used in order to check the response of the algorithm to the absence of the phenomena. The computation of the matching rate between a c-partition and the two areas split by the hand-contoured upwelling boundary also allowed the evaluation of how closely the obtained segmentation reproduced the shape of the areas covered by upwelling waters. This method successfully identified the upwelling boundary regions in 10 of the 14 SST images. The values obtained for the matching rate were higher than 0.77, thus indicating the good quality of the fuzzy partitions. The segmented images with 3 or 4 clusters were the most suitable ones to reproduce the areas covered by upwelling waters, but it was also shown that, for some cases, the upwelling areas could be reasonably well reproduced by the FCM 2-partition images. While in the latter, the area covered with upwelling waters was coincident with the first cluster, in the former, the segmented image showed two clusters within the upwelling area: the first cluster coincided with the area occupied by the most recently upwelled waters near the coast, while the second cluster was coincident with the area occupied by the “older” upwelling waters with its extensions offshore, the so-called cold filaments. The FCM algorithm revealed to be a promising technique in the automatic identification of upwelling areas on SST images.     

Detection method of the Kuroshio front using the satellite-derived chlorophyll-a images

Satellite-derived sea surface temperature (SST) has been providing high-resolution information of the oceanic front. However, in summer, increasing surface heating effects make SSTs uniform and the SST front disappears. The purpose of the present study is to examine applicability of satellite-derived surface chlorophyll-a (Chl-a) for detection of the Kuroshio front in the ocean south of Japan during the summer season.The Kuroshio surface front is formed between the Kuroshio water (KW) and the coastal water (CW) in the study area. Investigating accumulated in situ observations of SST and Chl-a, it is shown that the difference of Chl-a between KW and CW is increased in summer though that of SST becomes small. Using 76 pairs of cloud-free satellite-derived SST and Chl-a images with 0.01° spatial resolution, their seasonal variations are investigated through two-dimensional (2-D) histograms of Chl-a and SST. In summer, SST ranges from 25 to 30 °C and Chl-a ranges 0.03 to 0.4 mg/m³. Two peaks in the summer 2-D histogram correspond to wider KW and CW areas with rather uniform Chl-a and SST distributions. The peak values are extracted from the 2-D histograms and used to determine a threshold value dividing the KW and CW surface Chl-a during summer. It is found that the Chl-a concentration of 0.17 mg/m³ divides the extracted peaks into two groups, i.e., CW and KW except for a few peaks.The proposed Kuroshio-front detection method using the Chl-a images and the threshold value is examined using the satellite images and in situ data. The threshold contour superimposed in the summer Chl-a image distinctly separates the two representative waters in the ocean south of Japan. The front positions determined by the satellite-derived Chl-a, in situ SST, and in situ surface salinity transects along observation lines crossing the Kuroshio front agree with each other. Applying a traditional Kuroshio front index of temperature at 200 m depth, the capability of new Chl-a threshold in dividing two waters around the near-front area is quantitatively examined. Producing 74 match-ups of the satellite-derived Chl-a and 200-m temperature in the frontal zone, the dividing capability is evaluated quantitatively using the traditional Kuroshio-axis index. The detection capability of the proposed method is 82%, which can be considered high enough for practical applications.     

Relationship between satellite-derived land surface temperatures, arctic vegetation types, and NDVI

Arctic vegetation distribution is largely controlled by climate, particularly summer temperatures. Summer temperatures have been increasing in the Arctic and this trend is expected to continue. Arctic vegetation has been shown to change in response to increases in summer temperatures, which in turn affects arctic fauna, human communities and industries. An understanding of the relationship of existing plant communities to temperature is important in order to monitor change effectively. In addition, variation along existing climate gradients can help predict where and how vegetation changes may occur as climate warming continues. In this study we described the spatial relationship between satellite-derived land surface temperature (LST), circumpolar arctic vegetation, and normalized difference vegetation index (NDVI). LST, mapped as summer warmth index (SWI), accurately portrayed temperature gradients due to latitude, elevation and distance from the coast. The SWI maps also reflected NDVI patterns, though NDVI patterns were more complex due to the effects of lakes, different substrates and different-aged glacial surfaces. We found that for the whole Arctic, a 5 °C increase in SWI along the climate gradient corresponded to an increase in NDVI of approximately 0.07. This result supports and is of similar magnitude as temporal studies showing increases of arctic NDVI corresponding to increases in growing season temperatures over the length of the satellite record. The strongest positive relationship between NDVI and SWI occurred in partially vegetated and graminoid vegetation types. Recently deglaciated areas, areas with many water bodies, carbonate soil areas, and high mountains had lower NDVI values than predicted by SWI. Plant growth in these areas was limited by substrate factors as well as temperature, and thus is likely to respond less to climate warming than other areas.     

Radiometric measurements of the sea-surface skin temperature: the competing roles of the diurnal thermocline and the cool skin

It has long been recognized that satellite-borne infrared radiometers measure radiance that is more closely related to the temperature of the skin of the ocean than the sub-surface bulk temperature, but, historically, atmospheric correction algorithm derivation and validation exercises have been conducted using bulk temperatures measured at a depth of a metre or more. A recent validation of sea-surface temperature (SST) fields derived from the Advanced Very High Resolution Radiometer (AVHRR) with skin temperature measurements of the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) revealed a very low mean bias error, much smaller than was expected, given the thermal skin effect which acts to cool the surface with respect to sub-surface values by several tenths of a degree. This result does not imply the skin effect is unimportant-its effect is now well documented in many datasets-but that its effect is being partially compensated by diurnal heating effects. The evidence for this is presented and the consequences in terms of validating satellite-derived SSTs and of merging data from sensors with different satellite overpass times are discussed.     

Mean seasonal cycle and evolution of the sea surface temperature from satellite and in situ data in the English Channel for the period 1986–2006

A night-time series of sea surface temperature (SST) of the advanced very high-resolution radiometer (AVHRR) sensors provided by the AVHRR/Pathfinder was analysed over the period 1986–2006 in the English Channel. The studied area is characterized by a strong influence of the bathymetry on the mixing of the water column, mostly through the action of the tide and waves, leading to regional patterns in the SST fields. Another specific aspect of the area is the relatively large number of in situ measurements available from coastal stations. The remotely sensed SST data with fine spatial resolution and high-frequency measurements made at coastal stations have been analysed using a common model. The long-term evolution of SST has been defined in this study through a linear trend while the seasonal evolution has been described through two harmonic functions. The daily satellite SST fields have been estimated over the period 1986–2006 by applying the kriging method to the anomalies calculated from the model. These interpolated temperatures were compared with in situ data, including many coastal stations unreachable at the sensor resolution. To use those coastal stations for comparison and to complement the satellite-derived data set, we defined transfer functions established from fine analysis of the in situ gradients along cross shore transects. The study showed the existence of a long-term warming and that this trend was not homogeneous in the area studied. The central part of the English Channel and the Western part of Brittany show an increase in temperature of about 0.6°C and the Northern part of the Irish and Baltic Sea, included in the studied area, show a maximum increase in the temperature of 1.6°C over the period 1986–2006.     

Synergistic analysis of SeaWiFS chlorophyll concentration and NOAA-AVHRR SST features for exploring marine living resources

Near-synchronous Sea-viewing Wide Field-of-View Sensor (SeaWiFS) derived chlorophyll concentration and National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) derived sea surface temperature (SST) images were used to understand patterns, persistence and inter-relationship between ocean colour and thermal features. Different types of oceanic features were observed on chlorophyll concentration and SST images. An inverse relationship between chlorophyll concentration and SST features was observed. The features observed in the chlorophyll concentration images were well defined and appeared to contained more information than those on the SST images. The frontal zone positions on the chlorophyll concentration images coincided with temperature boundaries at some locations. This coincidence indicates that the physical and bio-chemical processes are closely coupled at these locations. High fish catch points were found in the vicinity of these features. A synergistic analysis of chlorophyll concentration and SST may increase our understanding of the inter-relationship between environmental variables for locating potential fishing grounds.