The Study Of Sea Surface Salinity Retrieval Model At L-Band

The sea surface salinity is a key ocean parameter. Study of the distributions and variability of sea surface salinity is very important to understand the characteristics of the oceans and the role of the oceans in the complicated system of the ocean and atmosphere. The remote sensing exploration of the sea surface salinity is the most effective means to obtain the sea surface salinity datum. The paper mainly studies the L band remote sensing mechanism and retrieval model of sea surface salinity. The study takes into full considerations of the complicated condition of ocean and the environmental factors, and discusses the theoretical and experiential sea surface salinity retrieval mode under various sea conditions. The detailed content of the study and creativities are shown in the following.1. Under the quasi-calm sea surface condition, the paper has considered the errors of the brightness temperature respectively because of the effects of Faraday rotation, the atmosphere transmission, ionosphere's absorption of radiation and so on. With the experimental datum of the outer sea of the Zhuang River of Liao-Ning, the paper primarily considered the effects of the environmental factors such as atmosphere propagation, background radiation etc., and established the high precise remote sensing retrieval algorithm. The mean absolute error of the retrieval salinity is 0.39psu, which is more accurate, compared with the present retrieval salinity of the other models. At present time, background radiation is treated as a constant in the retrieval model, but it's a variant about the time and space in fact. Furthermore, the changeable density of the atmosphere components can also result in the error of the retrieval value of the sea surface salinity. The influence of the sea surface roughness for brightness temperature is also an essential factor which can lead to the salinity retrieval error.2. Under the low wind speed condition, the roughness of surface is the key element which influences the sea water brightness temperature. This paper fully considers the effect of the roughness, especially the influence of the wind speed and the ground swell. With the in-site measurements of the sea surface salinity and brightness temperature in the north Yellow Sea, the paper establishes the experimental sea surface salinity retrieval model for the experimental sea area. The mean absolute error of the retrieval salinity is 0.288psu. At present, the highest retrieval precision of the other models reaches 0.52psu. Therefore, the retrieval model in the paper is better than the others in the experimental sea area. The influence is probably to bring the error of the retrieval salinity, such as suspension objects, sand and the difference in temperature between atmosphere and ocean. Thereby, the sea surface salinity retrieval mode is regional restricted.3. Under the white cap covered sea surface condition, sea surface salinity retrieval is always a difficult problem. Nowadays, there is only little study about the sea surface salinity remote sensing theories and experiments about the white cap covered sea surface. This paper specially researches the mechanism of the sea surface salinity remote sensing retrieval about the white cap covered sea surface. On account of the white cap layer of sea surface that is a kind of composite media of water and air, it's necessary to study the effective dielectric response of the composite. Employing the hypergeometric Equations, the paper gets the effective dielectric response analysis formula of graded composite with the graded spherical inclusion that has a complicated dielectric profile. At the same time, the paper verifies the validity of the DEDA (differential effective dipole approximation) method. Based on above results, the paper discusses the influence of the white cap cover rate and the bubble radial distribution for sea surface salinity retrieval under the high sea condition, by using the effective media approximation.In a word, the real ocean and its environment factors are complicated and various. Besides, these ocean physical parameters are relational and restricted each other. For instance, every factor among suspension objects, sand, animalcule, temperature difference can change the effective dielectric constant of seawater as well as influence the precision of sea surface salinity retrieval model. So, it is necessary to make a further study about the influence of these complicated environmental factors to the salinity remote sensing.