*********** +++++++++++++++++++++ 031496B.SAT + Source: ONR Asia + *********** +++++++++++++++++++++ Contributory Categories: BIO,ICE Country: Japan From: International Workshop on The Okhotsk Sea and Arctic The Physics and BioGeochemistry implied to the Global Cycles (Influence of Sea Ice on Climate and Marine Ecosystems) 29 Feb. - 1 March 1996, Tokyo, Japan KEYWORDS: Russia, Sea of Okhotsk; AVHRR, Ice cover, Temperature, Ocean Color +++++ Synergistic Satellite Remote Sensing of the Sea of Okhotsk Josefino C. Comiso Laboratory for Hydrospheric Process, NASA/Goddard Space Flight Center Greenbelt, NM, USA The Sea of Okhotsk is one of the most isolated seas on the Earth's surface, yet its role in the climate system is believed to be very profound. To gain insight into the oceanographic, atmospheric, biological, and polar processes that make this sea a very special region, large scale characteristics are studied using multi-sensor satellite observations. In this study, the seasonality and detailed characteristics of the ice cover is evaluated using data from the Special Scanning Microwave Imager (SSM/1). Atmospheric parameters, including wind speed, water vapor and precipitation are also studied using data mainly from the same sensor. Furthermore, spatial and temporal distribution of surface temperature is studied using data from the Advanced Very High Resolution Radiometer (AVHRR). Finally, available ocean color and aerosol data are analyzed in the context of the other parameters to evaluate potential relationships between the different parameters. The ice cover of the Sea of Okhotsk is a seasonal ice cover. This means that during parts of the year the sea is barren. In late autumn, a fraction of the sea starts to be covered by grease and pancake ice. The fraction of ice cover increases with time and reaches a maximum value in February or March. During the period, the ice cover also goes through different transitions (e.g., grease ice to pancake ice to young ice and finally to first year ice with snow cover). The distribution, and extent of the different ice types during theice season are quantified using an unsupervised cluster analysis and a neural network system that makes use of all SSM/I channels to identify the surfaces with distinct radiometric signatures. The results indicate that the ice cover of the Sea of Okhotsk is predominantly pancake and young ice during the ice period. Also, the peak extent is usually reached earlier than inthe Arctic Ocean and other peripheral seas. The aforementioned nature of the ice cover is studied in the context of a generally warmer surface air temperature (than Arctic) as inferred from AVHRR data and relatively strong winds inferred from SSM/I data. A large fraction of the ice cover is close to the ice edge and are vulnerable to breakup due to large wavesand wind forcing while other regions are far enough from the ice edge to be affected by big waves or are protected because of proximity to a land boundary. In the former, ice thickness may increase mainly through rafting or ridging but in the later, thermodynamic growth may be possible because of stability and colder temperatures. The location of the ice edge is examined at various scales. The standard technique is to use ice concentration maps to examine the ice edge but errors in ice concentration may be large at the marginal ice zone because of the predominance of newand pancake ice. These ice types cause special problems because their emissivities are similar to some mixtures of thick ice and open water. Also, the ice concentration algorithm makes use of the 19 GHz channel which has a coarse resolution (about 40 to 50 km). The ice edges inferred from ice concentration maps are compared with those from the 85 GHz and AVHRR GAC data which have resolutions of 12.5 km and 4 km, respectively. The comparative analysis reveals a general consistency in the ice edges inferred from the 85 GHz and AVHRR data while a smearing of the ice edge is observed from the ice concentration maps. Part of the problem may be caused by the mapping of the data, since the antenna pattern is not well known, and side lobe effects that cause the ice edge to have different brightness temperatures when the satellite crosses the ice/water boundaries from different directions. Discrepancies in the location of the 15% ice edge by a few pixel elements are noted in some places. The study also reveals that the 85 GHz and AVHRR data show no ice at some land/ocean boundaries while the ice concentration maps show some ice at these boundaries. A scheme that uses the 85 GHz and AVHRR data are used to mask out data elements at the land/ocean boundaries that apparently have no ice in them thereby improving determination of ice extent and actual ice area from these maps. The advance and retreat of the ice cover cause a redistribution of salt in the sea of Okhotsk. Areas of rapid ice growth are usually areas where salt is deposited and cold dense water are formed while areas of rapid decay are where abundant surface meltwater are introduced. The latter turned out to hav@ a strong effect on the biological productivity since they allow phytoplankton and other micro-organisms to grow rapidly in a vertically stable and light abundant environment. We assume that nutrients and iron are not limiting factors in these regions. The amount of meltwater introduced during ice decay depends on the extent of the ice cover and type of ice which enables estimate of thickness. Both can be derived from the passive i- nicrowave data. The influence of the meltwater, however, also depends on longevity. The longer the layer of meltwater stavs on the surface, the more likelv a phytoplankton bloom materialize, and the higher the biological productivity. The length of this unique environment may be shortened by storms and strong winds which cause the surface meltwater to be incorporated in the deeper layers. These effects are analyzed using wind statistics that are inferred from SSM/I data. Precipitation and river run-off are other sources of fresh water in the region that may stabilize the water column and enhance productivity. Precipitation statistics are also studied using SSM/I data. Climatological ocean color data from the Coastal Zone Color Scanner (CZCS) which provided good data from 1978 through 1986 indeed show that phytoplankton blooms are most intense in spring immediately after ice breakup. In summer and autumn, the blooms are comparable at the Sea of Okhotsk and are usually located adjacent to land areas (e.g., Hokkaido, Sakhalin, Kuril Islands, and Kamchatka). However, the average distribution in neighboring areas are more intense in autumn than in summer. A possible explanation is colder surface temperatures in autumn as inferred from AVHRR data. Detailed analysis is not possible because of many gaps in the ocean color data set. With the expected launch of new ocean color sensors (e.g., SeaWiFS and ADEOS) in 1996, detailed studies of the correlation of ice retreat and other parameters (i.e., temperatures, with precipitation, river runoff, surface temperature, and wind) with phytoplankton blooms will be possible. The synergistic use of several geophysical parameters from satellite data provides a means to gain a deeper understanding of large scale processes in the Sea of Okhotsk than is otherwise possible. However, satellite data should be used concurrently with field data and modeling studies. The latter provide good information about a local area, including subsurface characteristics that may or may not be possible to obtain from satellite data. On the other hand, satellite data provide spatially detailed information of several parameters and enable extrapolation of some local effects to much larger regions. CMR Disclaimer================================================== This document could contain information all or part of which is or may be copyrighted in a number of countries. 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