A numerical experiment examining the transient response of climate to a gradual increase in atmospheric CO₂ concentration at a compound annual rate of 1% has been performed with a coupled atmosphere-ocean general circulation model (CGCM) developed at the Meteorological Research Institute (MRI).
Time integration has been performed up to 70 years in the future over which time the CO₂ concentration doubles. This report focuses on the transient climate response at high latitudes in the Northern Hemisphere, especially on the warming over the Okhotsk Sea.
The maximum warming did not occur until the last decade of the 70 year integration near the north pole. This fact and correlation among temporal changes in surface energy fluxes suggests that the negative feedback of lead strongly affects the response in the polar region. Although the sea ice and snow/ice-albedo feedback dominates the CO₂ -induced warming at high latitudes of the Northern Hemisphere, the warming at the southern boundary of sea ice formation is, to some extent, affected by stationary planetary waves in winter, taking a form of zonal wave-number 3 in the decadal time mean. The location of maximum warming at the southern boundaries of the polar region, i.e., the Okhotsk Sea, the Barents Sea and the Hudson Bay, almost agrees with the troughs of the waves. This fact may be applied to detect a CO₂-induced climate-change signal in the real climate system by referring to observed stationary planetary waves, especially to the troughs, in winter. Thus a long term monitoring of the sea ice over there by satellites using remote sensing techniques will provide a strong basis for the detection of the global warming.

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Sea ice has been monitored as its fluctuations are important for climatological studies in the polar regions and also in the Sea of Okhotsk. This study investigates distributions of thin sea ice area in the Sea of Okhotsk. Advection of ice floe from the coastal zone and appearance of thin ice area recur due to out-burst of cold air from Siberia. Successive data of thin ice area was obtained using passive microwave data. Fluctuations of sea ice thickness provide a new data for growth and decay of coastal polynya and productions of frazil ice which affects heat flux and salt rejection. These sea ice processes are fundamental for extent of ice covered area especially in the area of large productivity of sea ice.

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The interannual variability of sea ice extent in the Okhotsk Sea and the sea surface temperature of the eastern equatorial Pacific Ocean suggested the negative correlation between the larger ice extent of the Okhotsk Sea and El Niho, and followed by the smaller ice extent of it after the El Nino events, that is, Anti-El Niho events(occasionally so called La Nina events).
El Nino events could influence the middle latitude anti-cyclone. Namely, the middle latitude westerlies in the region of the North Pacific Ocean become more zonal wind. The stress of intensified westerly winds drive the sea ice to the overall area of the Okhotsk Sea.
In this study, satellite passive microwave data, mainly DMSP-SMM/I data (1987-1994), were used to calculate the interannual variation of sea ice extent in this area. The derived interannual variation graph showed a small peak in each summer under the ice-free condition. In the former analysis, this phenomena was explained as land effect. However, we supported that this phenomena was mainly caused by the high water vapor in the atmosphere over the Okhotsk Sea in summer season. Considering this effect, we have re-evaluated the trend of the sea ice extent in this area and compared with El Nino/La Nina events.
We could result in almost the same interannual trend of sea ice extent, however, the smaller sea ice extent of the Okhotsk Sea, which was obtained by the former algorithm of sea ice concentration.
It also becomes very important for monitoring the interannual variability of sea ice extent in Okhotsk Sea because Noda (1996) pointed out that a notable CO₂-induced warming has firstly appeared around the Okhotsk Sea, although the model resolutions are not enough to resolve the local climate changes and the sea ice model is simple. However, these transient response is plausible because the Okhotsk Sea locates at the southernmost boundary of sea ice formation in the Northern Hemisphere. Therefore, further studies on sea ice extent and El Niho events will be important and continued by satellite microwave data.

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Among the basic geophysical ocean parameters which can be derived from multichannel passive microwave data are sea ice concentration and ice (or surface) type. Ice concentration can be derived using the Bootstrap algorithm with estimated precision of about 2% to 10% in generally thick consolidated ice areas where the emissivities are relatively stable. In the formalism, the reference brightness temperature of water is assumed to be constant while that of sea ice is allowed to vary according to the location of the input data relative to the multichannel distribution of the consolidated ice data points. Larger uncertainties are expected in marginal ice zones, leads, polynya regions, and meltponded regions where the emissivities of the ice surfaces are considerably more unpredictable. An unsupervised cluster analysis technique, aided by a neural network, has also been developed to provide complementary information about the ice cover. This technique makes use of the observed clustering of radiometrically distinct data points in n-dimensional brightness temperature space, where n represents the number of channels. Atmospheric and surface effects are minimized with the use of a neural network back propagation technique. The technique is shown to provide consistent identification of the various ice regimes in the marginal ice zones, the seasonal ice region, and the perennial ice regions. Observed temporal changes in the ice concentration and classification appear to be realistic and are consistent with known seasonal growth, decay and advection characteristics of the sea ice cover.

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The Sea of Okhotsk is well known as one of the most southern sea ice zones in the Northern Hemisphere where all the sea ice melt in summer season. It is estimated that if the current trend of the global warming continues in the future, the sea ice of the Sea of Okhotsk may not be able to survive even in winter season by the middle of 21 st Century. In order to monitor the interannual validation of sea ice extent in this area, two sea ice concentration algorithms, namely the Comiso algorithm and the NASA Team algorithm, were applied to DMSP SSM/I data for sea ice concentration calculation. The both algorithms were revised in 1994 to reduce weather effects resulting from atmospheric water vapor, cloud-liquid water and others. The effects increase the sea ice concentration over the open water. As the humidity of the Sea of Okhotsk is rather higher than most of the other sea ice zones especially in summer season, the weather effects appear more strongly in this area than the others. The interannual validation graph derived from SSM/I data used to have a small peak in each summer under the sea-ice free conditions. Those small peaks were much reduced with the new weather filters introduced to both algorithms. However, the "false sea ice area" were still observed over the open water in the sea ice concentration images derived with both algorithms. The images also suggested the importance of reducing land effects mainly caused by antenna side lobe and mixed-pixels of SSM/I data. In order to reduce the land effects, the authors have introduced a 3X3 filter here we call as land filter. This filter is a kind of conditioned minimum filter which reduces the land effect by using the land mask information stored in the NSIDC SSM⁄I data set. When at least one out of 3X3 pixels was "land", then the ice concentration of the center pixel will be replaced with the minimum value within the 3 X 3 pixels. The land filter was applied to the ice concentration calculated result of the both algorithms. Almost all the false sea ice area not only in summer but also in other seasons were rejected with this filter for the Comiso algorithm. This result proves the use of the land filter for land effect reduction and the use of the new weather filter of the Comiso algorithm for weather effect reduction for the Sea of Okhotsk. As the land effects occurs not only in summer but also in other seasons, the land filter is applicable to any seasons. On the other hand, the NASA Team algorithm with the land Filter did not show as much improvement as the Comiso algorithm. This result suggests that the new weather filter introduced to the NASA Team algorithm was not fitting so well to the Sea of Okhotsk.

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In order to confirm an effectiveness for synthetic aperture radar (SAR) to monitor sea ice in the Sea of Okhotsk, the ground truth data associated with SAR data onboard the JERS-1 and the ERS-1 were acquired during three consecutive years (1993-1995). Lake Saroma was chosen as a test site for this field observation, because this lake is a salt water lake connected to the Sea of Okhotsk, and the ice cover on this lake is considered to be first-year ice with the same salinity as the sea ice in the open sea. The ice cover on the lake was thick and stable enough to collect ground truth data. The ground truth data from 21 sampling sites, where were chosen to cover various ice thickness with the same surface conditions, have been acquired for three years.
By comparing the backscattering coefficient (σ⁰) derived from SAR data with the ice physical data, the following interesting results were obtained: (1) The ice layer structure, the salinity profiles, and the ice surface conditions of the ice cover on Lake Saroma were found to be similar to those of thin first-year ice observed in the Arctic region; (2) The observed σ⁰ of ERS-1 was about 7 dB higher than that of JERS-1 and the σ⁰ range of ERS-1 was about three times as large as that of J-SAR; (3) The σ⁰ values measured by JERS-1 and ERS-1 were inversely correlated to the ice thickness. It is assumed that the backscatter from the ice cover is mainly dominated by the ice surface scattering.

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Satellite Radar Interferometry (SRI) based on SAR imagery from the European Remote Sensing Satellite (ERS-1) can detect differential changes in surface elevation on the order of centimeters (Massonnet, et al., 1993, 1994). These changes are embedded in an intermediate fringe map that depicts the pixel by pixel phase difference of the SAR beam from two repeat orbits. The phase difference results from the path length difference viewed by a stereo-pair of coherent complex SAR images, and the movement of surface and near surface active scatterers in the time interval bracketed by the repeat images. After the effect of curvature of the earth ellipsoid is removed, the residual phase difference reflects the surface deformation provided that the spatial separation between the orbits is on the order of meters, or the surface is flat. Otherwise, a terrain correction is necessary. Additional corrections bring the accuracy of orbit separation from ±3 meters, as determined by the accuracy of the restituted state vector measurements, to at least ±0.5 meters, and remove errors caused by variations in the along track elevation. The final interferogram reflects one or more of several components in surface deformation. Examples of the fast ice near Prudhoe Bay in January 1992 shown here display a dense, colorful fringe pattern indicating deformation. Discontinuities in the pattern which are up to tens of kilometers long reflect cracks that separate the fast ice into discrete segments which underwent either compression or tilting between satellite passes. Areas where the fast ice remained stationary and was probably grounded can also be identified.

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TOPEX/POSEIDON data obtained at about three day intervals prepare its an aspect of sea state variation. Choosing four parameters of sea state; sea surface height, wind speed, significant wave height, and humidity, the authors plotted those data transitions in 1994 at four test points on the Sea of Okhotsk. Humidity curve shows a typical feature of the annual variation. Sea surface height corresponds to the low pressure on weather maps under certain circumstances.

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The purpose of this study is to use coastal zone color scanner chlorophyll imagery (CZCS-Chl) to determine annual cycles in phytoplankton chlorophyll (biomass) averaged over 8 areas of the Okhotsk Sea and adjacent sea. In Kuril Basin region, relatively low concentration of chlorophyll was observed in comparison with other region through the year. In Kashevarova Bank region, high concentration of chlorophyll area occurred in August although there was no high concentration area around this region.

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NASDA (National Space Development Agency of Japan) has been updating the long term Earth observation scenario.
In the latest scenario, it was classified into the following; global observation, regional land observation, diurnal cycle observation, geostationary observation and experimental flight for newly developed sensors. ADEOS, ADEOS-II for global observation, ALOS for regional land observation and TRMM for diurnal cycle observation have been carried forward actually.
ADEOS-II (ADVANCED EARTH OBSERVATION SATELLITE-II) is a post-ADEOS polar orbiting satellite, major objectives of which are to observe the global environment change by international cooperation and to develop satellite remote-sensing technology.
The mission of ADEOS-II is to obtain earth science data regarding global water and energy cycling and carbon cycling. In order to achieve this mission, in addition to two instruments, AMSR and GLI, developed by NASDA, three instruments, ILAS-Il, SeaWinds and POLDER, are to be developed and delivered to ADEOS-II by Environment Agency of Japan, NASA/JPL, CNES, respectively.
The primary objectives of the AMSR(Advanced Microwave Scanning Radiometer) are to obtain the physical content concerning water cycling. AMSR has the capability of measuring dual polarized microwave radiation from the earth's atmosphere and surface at 8 frequencies in the region from 6.9 GHz to 89 GHz with 1600 km of swath width and 5 to 50 km spatial resolution.
AMSR scans the surface with the mechanical rotation of 2 m aperture antenna to achieve the constant incident angle and the wide swath width.
The primary objectives of the GLI (GLobal Imager) are to obtain the physical content concerning carbon and water cycling and primary ocean production.
GLI measures the reflectance and radiation from land and sea surfaces and atmosphere with 36 channels in the spectrum range from 375 nm to 12.5, um, 1600 km of swath width and 1 km and 250 m spatial resolution.
GLI scans the surface in the direction of cross-track by the mechanical rotation of mirror both side of which will be used. In the direction of along-track GLI has 12 detectors arrays, therefore rotation velocity of the mirror will be reduced. Because of this the integration time will be made long and accuracy will be improved. Now these instruments are in the phase of manufacturing and test of engineering model, to validate the flight design. And the RA (Research Announcement) were issued.

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