The cryosphere is a region most sensitive to the changes in the climate system, such as global warming. Thus, it is necessary to understand relationships that exist among the cryosphere, atmosphere, and oceans as soon as possible. This month's article addresses the cryosphere regions observed from space.
Relationship between Cryosphere and the Earths Environment
Some regions of the Earth are covered with vast expanses of snow and ice. Well-known ice sheets exceeding 3,000 meters in thickness are found in the Antarctic region and in Greenland, for example. We can see blankets of sea ice over the Arctic Ocean. The high latitude region are also covered in deep snow and surrounded by glaciers. These regions are called cryosphere. In particular, the ice sheet regions holds the amount of ice equivalent to about 78% of the fresh water on the Earth, and thus serving as a huge storage for terrestrial water. It has been pointed out that if these ice sheets and glaciers melt as global warming progresses, serious problems such as a rise in sea levels and changes in ocean currents will occur as the melted water flows into the oceans.
Serving as a local storage for terrestrial water in winter is not the only role the high-latitude snow regions in the northern hemisphere plays. Snow in the high latitudes plays an important role in controlling the Earths radiation budget. Since land areas in these regions are covered with snow, solar radiation is not easily absorbed. Also, vast snow surfaces over the ice sheets and sea ice in the both polar regions acts as effective heat exchanger that cool the polar regions through the reflection of solar radiation and the radiation of terrestrial heat into outer space.
Considering that the cryosphere assumes a key role in the Earth system, we must establish future trends of the Earth environment based on a quantitative understanding of the interaction mechanism among the cryosphere, atmosphere, oceans and land. Notably, areas of snow cover on land and distributions of sea ice around the polar circles largely vary every season. These variations have a significant effect on annual rainfall and climate dynamics. It is important to observe these changes closely.
Given the fact that global warming is responsible for changing atmospheric temperature as well as spatial distributions of snowfall profile, the phenomena has been thought to be closely related to changes in the distributions of accumulation and ablation areas of ice sheets and glaciers. For this reason, accumulation and ablation areas of ice sheets and glaciers must be monitored continuously over a long time period. As air pollution has increasingly worsened over recent years, the so-called Arctic Haze - a layer formed from aerosols and other aerial particles has been observed around the North Pole. It has been said that a feed back cycle in degradation of radiative reflectivity may occur should these particles deposit on the surfaces of snow and ice. For instance, as the particle deposits, reflectance of snow decreases, which makes snow and sea ice susceptible to melting, which in turn further degrade radiative reflectivity. Accordingly, it is especially important to obtain data on the quality of snow such as grain size and the degree of snow pollution.
It is most effective to make use of satellites to conduct extensive observations of the cryosphere. Continuous observations from space are required to study the effect of global warming on the cryosphere sub-system, and to detect the sing of climate changes as previously seen during a glacial period.
Extraction of Snow/Ice Areas and Snow Depth from Space
The first satellite-based monitoring of snow and ice was conducted more than thirty years ago. Since 1966 the U.S. National Oceanic and Atmospheric Administration (NOAA) has continuously observed snow covered areas on land in the northern hemisphere using an optical sensor aboard the polar-orbiting meteorological satellite.
NASA launched TERRA in 1999 with the objective of observing the Earths environmental changes. Fig. 1 shows an image taken on June 18, 2000, with the Moderate-Resolution Imaging Spectroradiometer (MODIS) aboard TERRA. It is somewhat difficult to distinguish between clouds and snow/ice. As shown in Fig. 2, however, clouds are identified and the ground surface is classified based on radiances at visible and infrared channels. Since the data in Fig. 2 was obtained during the summer, snow and ice surfaces are distributed only over the ice sheet in Greenland and the sea ice on the Arctic Ocean.
Since optical sensors cannot penetrate clouds, they cannot detect snow on beclouded areas, as illustrated in Fig. 2. Therefore, observations must be conducted over two or more days in order to extract extensive snow and sea ice areas from the data. In addition, forested region in high-latitude, such as Siberia and Alaska, pose another difficulty in detecting snow during the winter because the snow lies so deeply in the forests and is not easily visible from space. A challenge for the future is to improve the accuracy of detecting snow using such information as vegetation density.
Nimbus, which was launched in 1978, has provided us with microwave data useful for understanding the distributions of snow on land and sea ice. Although microwave sensors are inferior to optical sensors in terms of ground resolution, they have a capacity for observing ground surfaces both day and night, regardless of the presence of clouds. These advantages prove microwave sensors efficiency in extracting the distributions of snow and sea ice above which thick clouds linger and polar nights - no sun light during the winter - occur. In recent years techniques were developed to extract the snow depth (volume) from microwave data and have been applied to actual satellite data. From information on snow distributions on land, these techniques enable us to extract not only snow areas, but also snow water. It is expected that the extracted data will be very useful for more accurately estimating the balance of fresh water in rivers and lakes, soil moisture content and amount of evaporation. These data will also contribute to improving the accuracy of meteorological and climate forecasts.
Snow and Ice Monitoring Project with ADEOS-II
Recent improvements in optical sensors of high wavelength resolution and multi-channel observations are expanding the possibility in snow/ice observation. MODIS, mentioned above, and the Global Imager (GLI) onboard ADEOS-II, which is scheduled for launch in 2002, have narrower spectral bandwidths than previous NOAA optical sensors. This feature makes MODIS and GLI insusceptible to the effect of atmospheric absorption. GLI can be operated in thirty-six spectral bands, thereby obtaining more reliable data on the spectral radiance of various observation targets. It is planned to extract physical parameters related to the quality of snow, in addition to conventional information of the existence of snow. Accordingly, GLI is expected to make a significant contribution in identifying ablation and accumulation areas on ice sheets and polluted area as well.
Fig. 3 shows that radiance reflected from snow surfaces correlates to snow grain size and impurity concentration. As seen from Fig. 3, radiance decreases in the visible wavelength region as impurity concentration increases. In contrast, radiance in the near-infrared region is found to decrease in proportion to the growth of snow grain size.
Based on the trends seen in Fig. 3, the snow grain sizes and impurity concentrations are extracted from the image data in Fig. 2 and shown in Fig.4. As it can be seen in Fig. 4, the snow grain size grows on sea ice over the Arctic Ocean while the grain size remains small on ice sheets in Greenland. This is partly due to the fact that Greenland is located in higher altitude than the Arctic Ocean, where the temperatures are higher. In addition, the impurity concentration is higher around lowland coastlines, indicating that anthropogenic aerosols and other windblown dust particles deposit on snow surfaces.
ADEOS-II will accommodate not only GLI, but also Advanced Microwave Scanning Radiometer (AMSR) which has higher spatial resolution than previous microwave sensors. With the use of GLI and AMSR, we can obtain information of the depth and the quality of snow at the same time for a given region. This capability is expected to improve the accuracy of extracting the physical parameters of snow and ice.