| The earth is covered with a large amount of snow,and glaciers,which provide valuable freshwater resources for human beings and affect the regional climate and ecological environment of the earth.As the global temperature rising,climate warming has had a large scale and significant impact on both natural and human systems,such as the reduction of freshwater resources,species migration,changes in agricultural production conditions,melting of glaciers,rapid Arctic warming and sea ice melting,increasing frequency and intensity of extreme weather and climate events such as high temperature,torrential rains,floods and droughts.Due to its high albedo characteristics,the small changes of snow can form a positive feedback effect on the energy budget of the earth-atmosphere system,and further strengthen the global warming.Changes of snow temporal and spatial distribution and remote sensing monitoring of various key parameters such as snow grain size and albedo have always been the focus of snow research.The increasing frequency of human activities produces a large number of aerosols.These aerosols,including many light-absorbing impurities,are transported over long distances and deposited into the snow,which has a major impact on the snow albedo and the radiation budget of earth-atmosphere system.Clouds play an important role in the earth-atmosphere system.The high albedo of snow and the clouds in the Arctic make the accurate calculation of the radiation budget in the Arctic particularly important.Firstly,the thesis introduces research background and research significance,and investigates the research progress,problems and challenges in snow research at home and abroad.Then the radiative transfer models commonly used in remote sensing retrieval are introduced.Lastly,we propose a new method to retrieve snow spectral albedo from infrared to ultraviolet,and calculate clouds radiative forcing using snow albedo retrieved in the Arctic.The main contents are as follows:1.A method combining the asymptotic radiative transfer theory and discrete ordinate radiative transfer method is proposed to retrieve the snow spectral albedo.The snow grain size is retrieved using the asymptotic radiative transfer theory,and snow spectral albedo is calculated using discrete ordinate radiative transfer method.The snow optical parameters are calculated by the MIE scattering program.The differences of snow grain size retrieved from different satellite data are analyzed,and the snow albedo reduction caused by light absorption impurities is corrected.2.Using C++language,a system for querying snow grain size and snow albedo has been written.Enter the latitude,longitude and time to query the presence or absence of snow and snow grain size in the research area.At the same time,the snow spectral albedo in the area and the spatial distribution of snow grain size in the Arctic can be downloaded and saved.3.Based on MODIS data,the temporal and spatial distribution characteristics of cloud parameters from 2003 to 2019 are analyzed.The cloud types are mainly ice clouds,liquid clouds and undetermined clouds.Cloud parameters mainly include cloud top height,cloud optical thickness,cloud effective grain size and cloud phase probability.4.The SBDART model has been improved.The solar spectrum and the absorption spectrum of common gases have been replacedby 10 cm-1 in MODTRAN4 to 1 cm-1 in MODTRAN5.The snow albedo in the model replaces the original snow albedo with the retrieved snow albedo.5.The SBDART model is used to calculate the radiative forcing of different types of clouds and the mean cloud radiative forcing.The effects of different incident angles on the snow albedo and the cloud radiative forcing are compared,and the effects of cloud radiative forcing on clouds assumed as ice clouds and liquid clouds with uncertain phase states are analyzed.The differences of cloud radiative forcing when the undetermined cloud is assumed to be ice cloud and liquid cloud respectively are analyzed. |
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