ABSTRACT
Satellite remote sensing can be used to determine the roles of albedo and clouds in the Earth's radiation budget. The objective of this study is to use satellite observations to examine the components of the surface radiation budget, albedo, and cloud forcing at four mid-latitude locations, three at 38N and one at 38S. There are two open ocean sites, one in each hemisphere and two sites at the U. S. east coast, one over land and one over water. The data set is from the ISCCP equal-area grid. Although the percent cloud cover is lower over the land than it is over the adjacent coastal ocean site, the incident surface radiation is also lower over the land site. The observations also show that the shortwave cooling effects are greater over land and the longwave warming is greater over the ocean. This result is consistent with some combination of either higher cloud heights over the coastal ocean which would increase the downward longwave radiation or more clouds during the day over land which would reduce the incident shortwave radiation. Additional analysis of the height and temporal variability of clouds is necessary to clarify these effects. The analysis also shows that there is greater variability in the cloud cover over the. northern open ocean site than over the southern one.
INTRODUCTION
The Sun supplies the energy of the Earth system. The incident solar radiation
(short-wave radiation) is absorbed and reflected by the Earth's surface. In
addition, some of the incident solar radiation interacts with atmospheric gases,
clouds and aerosols. The Earth surface emits radiation out to space and downward
to surface. The atmosphere reemitted longwave radiation ; some of which is absorbed
by atmospheric gases,water vapor and carbon dioxide. The Earth radiation budget
at the top of the atmosphere is a balance between incoming energy from the Sun
and outgoing long-wave and reflected short-wave energy from the Earth. During
the last two decades, satellite remote sensing has been used to measure the
Earth radiation budget.
The reflected rate by the surface is the surface albedo.
The albedo depends on solar solid angle and the character of the surface. The
Earth surface is not homogeneous; it is divided into soil and water (land and
ocean). The character of soil and water is very different from each other. The
albedo of land is higher than that of water because both reflection and refraction
take place on the water surface. Therefore the albedos of land, coast and open
ocean (soil, soil+water, water) are different and this affects on the climate.
In the Earth Radiation Budget, the incoming and outgoing radiation interacts with the atmosphere. Interaction with the clouds is most important because water vapor (cloud) can absorb a wide range radiation and cloud can reflect the radiation. This effect of clouds is called cloud forcing. The total cloud forcing is cooling. This plays an important role in climate. There are some models to predict cloud role.(R.D. Cess et al. 1995, D.A. Randall et al. 1989)
OBJECTIVE
The objective of this study is to use remote sensing data to compare cloud forcing as a part of Earth radiation budget at three mid-latitude sites in the Northern Hemisphere --land, coastal ocean, open ocean. In addition, the comparable latitude in the southern hemisphere open ocean will be examined.
Albedo
Some of incident short-wave radiation reflects the Earth surface. The reflected character of the surface, namely, the reflectivity, is called albedo. This albedo is defined as the ratio of the reflected short-wave radiation to incident short-wave radiation. The average global aldedo is 30%. This value has been determined from satellite measurements. But the albedo is not constant. It varies on the temporal and spatial scale. Seasonal variations in the surface albedo are significant. In the Northern Hemisphere, the albedo is maximum in July and minimum in January. The albedo of surface depends on the following factors -- the type of surface, the solar elevation and the geometry of the surface relative to the Sun, and the spectral distribution of the solar radiation and the spectral reflection. [Table 1] shows that fresh snow has the highest albedo, on natural surfaces. In the ocean surface, both reflection and refraction take place, with radiation penetrating into the water body.
The incident solar radiation interacts with atmospheric gases, clouds and aerosols before it arrives at the earth's surface. The cloud also absorbs some of the radiation and reflects some of the radiation (short-wave). On the other hand, the cloud may absorb the radiation which is emitted by the earth's surface and emit radiation to space and to the earth's surface (long-wave). With this mechanism, the cloud plays a dominant role of earth radiation budget. For example, low, thick clouds reflect incoming solar radiation back to space causing cooling and high clouds trap outgoing infrared radiation producing greenhouse warming.(CERES) In other words, the role of the cloud is to modify the earth's radiation.
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The shortwave cloud forcing is cooling (-50 W/m2) and the longwave cloud forcing is warming (30 W/m2)--it is called the blanket effect. The net cloud forcing is cooling (-20 W/m2).
Usually clouds form when the water vapor in the air parcel is cooled and condensed to liquid form or when an air parcel is saturated with water vapor. There are three ways to cool air : advection of warm air over a cold surface (fog formation), mixing air parcels of different temperatures and moistures and lifting of air to higher levels. A parcel of air is lifted by buoyancy, topographic lifting, and convergence.
Buoyant lifting results from surface heatings. Clouds may form a lot of shapes at various height. The higher clouds are cooler, because temperature decreases with height in the troposphere. [Figure 3]
ISCCP(International Satellite Cloud Climatology Project)
ISCCP was established in 1980 as a part of WCRP(World Climate Research Program). Its objective is to collect and analyze satellite radiance measurements. To obtain global coverage while resolving diurnal variations, the project planned on using data from at least one polar-orbiting and five geostationary weather satellites, although data from a second polar-orbiting satellite was desired. (R.A.Schiffer et al. 1983)
The ISCCP instruments are :
MEOSAT, GMS, GOES-EAST, GOES-WEST, and INSAT refer to geostationary weather satellites; NOAA is used to refer to the polar-orbiting satellite. The Centrede Meteorologie Spatiale at Lannion conducts the radiance normalization and the NASA Goddard Institute for Space Studies produces the final data products. All data products are archived by NOAA NESDIS in Washington D.C.
The coverage provided by five geostationary satellites and one polar-orbiting satellite is defined arbitrarily to be 100%, representing eight observations per day at each location (the actual observation frequency is somewhat smaller, near 50-60' latitude. The initial complement of satellites was NOAA-7, METEOSAT-2, GMS-2, GOES-5 and GOES-6. Failures and replacements of satellites are indicated. Time is given in quarter years.
The procedure of ISCCP analysis is divided into three parts : cloud detection, radiative model analysis, and statistical analysis. Cloud detection is to seperate the pixels into cloudy and clear images. (This is sometimes called cloud algorithm.) The effects of the atmosphere on the radiances are accounted for by using the TOVS (Tiros Operational Vertical Sounder) of NOAA satellite for each location and time. The data is drawn by statistics(mean, standard deviation, and frequency distributions) of spatial variability of the surface and clouds.
METHODOLOGY
The data set is from SRB homepage. The data for the following areas ([Figure 5]; red points) are given on the ISCCP equal-area grid : (1) Virginia state (38.75N,78.75W) (2) Coast of Atlantic city (38.75N,72.32W) (3) Northern Atlantic Open Ocean (38.75N,30.54W) (4) Southern Atlantic Open Ocean (38.75S,30.54W). (The mentioned points are the central points in each pixel) The average data for 4 years (from January 1987 to December 1990) is used to compare albedo flux and cloud forcing. The plot to compare is made by Microsoft Excel.
The data has a spatial resolution of about 280km. Pixel level data are collected into an equal-area map grid which has constant 2.5' latitude increments and variable longitude increments, ranging from 2.5' at the equator to 120' at the pole. Further it represents a monthly summary (stage C2 data) of data set for each of the 3h periods (stage C1 data).
RESULTS [Figure 6] shows the seasonal variations of surface albedo. The land has a higher variation than the ocean all year round. On the water surface, both reflection and refraction take place. In summer, various vegetation grows on land. This is why the land has a higher value and more deviation in the summer. Moreover Virginia state has a strong fluctuation during the summer and maximum albedo in September and minimum albedo in January. The surface albedo depends on the type of surface, so there is no difference between coastal ocean and open ocean. The Southern Hemisphere has opposite curve from the Northern Hemisphere. In the Northern Ocean, surface albedo is maximum in December and minimum in June. Finally, the seasonal variation of land and ocean in the same latitude is opposite.
[Figure 7] shows the annual variation of cloud percent of Southern open ocean and Northern open ocean. In Northern hemisphere, the minimum value is 50.99% in July and the maximum value is 85.53% in January, the difference being 34.53%. In Southern Hemisphere, the minimum value is 69.63% in January, the maximum value is 84.21% in July, the difference being only 14.58%. The Northern Hemisphere has a stronger annual variation than Southern hemisphere because it contains more land, which creates stronger air-heat exchange.(R.Cheney et al. 1994) (even for sea surface height, the Northern Hemisphere has a greater overall change than the Southern Hemisphere. Go to seasonal changes in the ocean)
[Figure 8] shows the annual variation of cloud percent of ocean (coastal ocean of Atlantic City) and land (Virginia State). The coastal ocean has more cloud than the land all year round. However both have the minimum in October and the maximum in December. The formation of clouds reauires the saturation of water vapor cooling of the air parcel. Because the atmosphere over the coastal ocean has more humidity, it is easier to form clouds.
The measurement of the incoming solar radiation of the greater number of clouds is greater than that of the fewer number of clouds. [Figure 9]. Therefore in the Northern Hemisphere, the cloud percent is minimum but the shortwave cloud forcing is maximum in July.
In the case of longwave cloud forcing, the open ocean has a higher value than coastal ocean and land. [Figure 10] Here are two different explainations regarding this phenomena. First, the longwave cloud forcing has both cloud-base warming effect (to the earth surface) and cloud-top cooling effect (to space) (W.K.Tao et al. 1996) The net cloud forcing is warming. The cloud of high latitude has less cooling effect than of lower latitude. Because of the vertical temperature profile, the temperature of high cloud is cooler than low cloud. Thus high clouds emist less radiation to space.[Figure 11] More high cloud can be formed over the ocean than land, because over the land, the conditions for high cloud formation peaks during a particular time of the day. (S.A.Barr-Kumarakulasinghe et al. 1997) On the other hand, over the ocean, there are more clouds than the land.[Figure 12] which means that there is more emission of longwave radiation by clouds into the ocean than over the land. This is true especially at night, because there is no reflection of shortwave radiation; therefore so more clouds have more warming effects.
The total net flux in the Northern Hemisphere is maximum in July and minimum in December and in the Southern Hemisphere is maximum in January and minimum in June. [Figure 13] This explains why the Northern Hemisphere has different seasons from the Southern Hemisphere.
CONCLUSIONS
FUTURE WORKS
ACKNOWLEDGEMENT
I thank James Miller, Jennifer A. Francis, and Scott Glenn for their guidance and the time.
REFERENCE
APPENDIX
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If you have any comments or questions; contact to
Last updated Apr. 30, 1998
Remote Sensing/Environmental Science/Rutgers,The University of New Jersey
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