**2. Satellite data**

What is satellite data? An electromagnetic (EM) signal with certain characteristics leaves the sea and contains information about the primary observable quantities, which are light, radiation temperature, roughness and sea level. This signal travels through the atmosphere, where it can be distorted, and where noise is added to the signal before it is received by a sensor that registers certain properties of the radiation and converts each measurement into a digital signal to be encoded and sent back to earth. The sensor geometry limits each individual observation to a specific instantaneous field of view.

In order to convert a digital signal received at a ground station into a useful one for scientific measurements with a certain accuracy and quality, the process of obtaining data by the sensor should be numerically transformed using knowledge about signal processing technology, physical and technical properties of the sensor, the physics of the atmosphere, and the interaction of EM radiation with the ocean and near-surface processes in the ocean. The process of extracting data from a unique observation location in space is at the heart of the satellite data feature.

**Table 1** summarizes 5 levels of satellite data processing.

Using the TeraScan software, raw data received from satellites is automatically calibrated and atmospheric correction, as well as georeferencing of data and projection onto a standard map (selection of parameters, projections, etc., is performed


#### **Table 1.**

*A summary of various satellite data processing levels.*

**Figure 2.**

*An example of a ten-day average image with a spatial resolution of 0.25 × 0.25 degrees (left) and 2 × 2 km (right) [2].*

once by the operator, after which it is performed in automatic mode). Then data with different spatial resolution (the maximum resolution for a set of satellites is 2 km, images with a spatial resolution of 250 m can be obtained on separate channels) are entered into the database, where the operator manually corrects each image (eliminates gross errors that most often appear in the case of the presence of semi-transparent clouds). After that, daily data averaging is performed. As the data accumulate, ten-day and monthly averaging is also performed (as shown in **Figure 2** [2]), as well as the calculation of anomalies (deviations from the long-term average value in a specified decade or month, obtained over a number of previous years).

The resulting data set should be carefully analyzed. Determination of the characteristics of unidirectional trends, as well as the amplitudes and phases of cyclic components and the possibility of using them to predict thermal conditions in the next season constituting the content of this study.

#### **3. SST anomalies**

There are two types of SST anomalies as for any parameter distributed in space and time. The first is the sharp deviation of the specified parameter from the mean values in the neighboring areas. Anomalies of this kind can be regular and even present on average long-term maps (**Figure 3** [3]). Typical examples from the point of view of SST are upwelling zones (quasi-stationary), mouths of large rivers, as well as zones of influence of warm and cold currents. Some anomalies of this nature may be unstable and dependent on weather conditions. Such anomalies determine the behavior of aquatic organisms, since each species has its own conditions of existence and development (some species need colder water, and some are more comfortable in warmer water).

The second type of SST anomaly is a deviation from the multiyear average. This type of anomaly depends entirely on the current conditions and reflects the peculiarities of the distribution of the parameter in a given year. From the point of view of SST, this may mean more or less intense heating or cooling than usual. The appearance of such anomalies can lead to a change in the timing of the fish's approach to spawning (**Figure 3** [3]) or to migration to places with more favorable conditions, and in the early stages of development it can lead to death from unfavorable conditions.

Let us consider in more detail the extraordinary conditions that took place in the spring of 2011, when the greatest delay in the release of juveniles from the Sakhalin SFHs was noted. The spatial distributions of sea surface temperature anomalies

#### *Analysis of Spatiotemporal Variability of Surface Temperature of Okhotsk Sea and Adjacent… DOI: http://dx.doi.org/10.5772/intechopen.94918*

observed during the period under consideration, which is strongly characterized by unusual conditions (**Figure 4** [4]), are quite remarkable.

In the third decade of May (**Figure 4A**), significant negative deviations from the norm were noted along the entire eastern coast of Sakhalin Island and in the Aniva Gulf; they were the largest (up to 3°C) in the basin of the Mordvinova Gulf. Judging by the zone of negative anomalies stretching from the Terpeniya Peninsula along the line of the depth increase, which corresponds to the core of the East Sakhalin Current [5], they were caused by the outflow of cold water and ice-cover remains from the northeastern shelf. This opinion is confirmed by a satellite image on June 2, 2011 (**Figure 3** [3]), which clearly shows the transport of drifting ice from the north to the Terpeniya Peninsula and further towards the Mordvinova Gulf. Such a situation is observed relatively rarely: usually, under the influence of the southern winds characteristic of this period of the year, the ice that is transported from the Sakhalin Gulf is blocked at the northeastern tip of the island and does not move south of 52° N. A similar ice removal was observed in spring 2005 [6]. Then, due to the unusual distribution of the surface atmospheric pressure, the northeastern

#### **Figure 3.**

*An example of the long-term average distribution of SST, the actual temperature in the second decade of July 2018 and the 2018 anomaly relative to the multi-year average (these conditions led to a two-week delay in the approach of pink salmon to spawning rivers) [3].*

#### **Figure 4.**

*Distribution of surface temperature anomalies (°С) in the third decade of may (A) and in the second decade of June (B) 2011. Ice conditions off the east coast of Sakhalin Island (right) on June 2, 2011 (snapshot of the aqua satellite). The strait of Tatary is closed by heavy clouds [4].*

winds prevailed in the study region, which just contribute to the transport of drifting ice to the southeastern coast of Sakhalin Island, as well as to the estuarine regions of the Naiba and Ai rivers and to the Mordvinova Gulf.

In spring 2011, the distribution of surface atmospheric pressure also significantly differed from the characteristic one in the given period of the year. For example, in the third decade of May, the high-pressure region was located in the southern part of the Sea of Okhotsk, above the Kuril Basin (**Figure 5A** [7]). Usually this area is located in the eastern part of the sea, and air flows directed to the north are formed above this basin. When the pressure distribution has this structure, the atmospheric circulation typical for the summer monsoon is not formed; in principle, it was weakly expressed, since the pressure gradients were small and cold waters with low salinity moved freely to the south, transporting drifting ice.

Subsequently, the high-pressure region shifted from the sea to the Pacific Ocean. In particular, in the second decade of June, zonal, northeast-oriented air flows prevailed, which is not typical for the warm season (**Figure 5B** [7]).

However, it is unlikely that only the peculiarities of the synoptic conditions can explain the significant negative temperature anomalies of the sea surface in the northern part of the Sea of Japan, primarily in the main zone of the Tsushima Current influence, off the west coast of Hokkaido Island (up to 5–6°C). Another zone with approximately the same negative anomalies was noted in the zone of the influence of the Amur River runoff in the region of its mouth, in the western part of the Amur Estuary, and in a significant part of the Sakhalin Gulf, as well as on the northeastern shelf of Sakhalin Island (up to about 52° N). Pronounced negative anomalies were observed both on the southwestern and southeastern coasts of Sakhalin Island, as well as in the Aniva Gulf. It is difficult to explain the cause of such a heat deficit in the surface waters of a very wide basin: one of them could be a decrease in the intensity of the Tsushima Current, whose quasi-periodic fluctuations (a cycle with a period of 5–6 years is especially distinguished) have a significant influence on the climate of the Sakhalin-Kuril region [8]. It is also difficult to assess how often such situations can be observed which have led to a delay in the release of juveniles from Sakhalin SFHs lasting from 3 weeks to a month. Probably, due to the low temperature of coastal waters observed for a long time, there could be a mass death of juveniles of natural origin which rolled along the spawning rivers of the island.

#### **Figure 5.**

*Distribution of surface pressure (hPa) over the Sea of Okhotsk in the third decade of may (A) and the second decade of June (B) 2011 [7].*

*Analysis of Spatiotemporal Variability of Surface Temperature of Okhotsk Sea and Adjacent… DOI: http://dx.doi.org/10.5772/intechopen.94918*
