分类： 地球科学 >> 空间物理学 提交时间： 2017-03-10
摘要： With a standard deviation as large as 2 cm, the sea state bias (SSB) has become the dominant source of error in satellite altimetry. The operational SSB correction models are two-dimensional (2-D) empirical (parametric or nonparametric) models based on the altimeter-measured wind speed (U) and significant wave height (SWH). However, these 2-D SSB models cannot entirely parameterize the range bias variability. The SSB uncertainty may be lowered through improved SSB models including additional measurable or predictable correlatives. This paper presents a method to estimate the SSB from crossover differences by using a three-dimensional (3-D) nonparametric model. The model is based on U, SWH from Jason-2 altimeter ocean observations, and the mean wave period from the European Centre for Medium-Range Weather Forecasts reanalysis project ERA-Interim (The SSB model developed with the method presented in this paper is called “3-D SSB model” and the SSB estimated with the 3-D SSB model is called “3-D SSB estimate”). Simulations indicate that the wave period can greatly affect the SSB. Evaluated by the separate annual datasets from 2009 to 2011, the 3-D SSB estimates can increase the explained variance by 1.32 cm2, or 1.15-cm RMS relative to the traditional 2-D SSB estimates based on U and SWH. Spatial evaluation of improvement shows that the 3-D SSB estimates are better than the traditional 2-D SSB estimates at all latitudes. The enhancement from 2-D to 3-D SSB estimates is of great significance to improve the precision of the altimeter product.[COMP]: Please set math TYPE gin the sentence below (40) as per the authors PDF.
分类： 地球科学 >> 空间物理学 提交时间： 2017-03-10
摘要： In order to satisfy a relatively high resolution for the retrieval of snow water equivalent, an X/Ku-band dual-frequency full-polarized SCATterometer (DFPSCAT) onboard Water Cycle Observation Mission (WCOM) satellite is designed for high-resolution observations. However, given the following situations, the method called “rotating azimuth Doppler discrimination” is proposed, which can satisfy the resolution requirement and real-time processing: 1) the conically rotation rate of antenna is relatively fast; 2) the swath width is larger than 1000 km; and 3) day or night observation capabilities are required. Considering the complexity of the system's design and the improvement of azimuth resolution capability, a burst pulsing scheme is addressed to satisfy the numbers of azimuth sampling. The simulation model is used to analyze the feasibility of azimuth discrimination method based on geometry and system parameters. It is shown that the achievable azimuth resolution is about 2–5 km at far end of the swath and only 5km at near end of the swath. The results show that when the size of a slice is set as 2–5 km, the Kpcis about less than 0.4 as snow depth varies, and the Kpcof combined slices is smaller than a single slice.
分类： 地球科学 >> 空间物理学 提交时间： 2017-03-10
摘要： For Microwave Humidity and Temperature sounder (MWHTS) measurements over ocean, a cloud filtering method is presented to filter out cloud- and precipitation-affected observations by analyzing the sensitivity of the simulated brightness temperatures of MWHTS to cloud liquid water, and using the root mean square error (RMSE) between observation and simulation in clear sky as a reference standard. The atmospheric temperature and humidity profiles are retrieved using MWHTS measurements with and without filtering by multiple linear regression (MLR), artificial neural networks (ANN) and one-dimensional variational (1DVAR) retrieval methods, respectively, and the effects of the filtering method on the retrieval accuracies are analyzed. The numerical results show that the filtering method can improve the retrieval accuracies of the MLR and the 1DVAR retrieval methods, but have little influence on that of the ANN. In addition, the dependencies of the retrieval methods upon the testing samples of brightness temperature are studied, and the results show that the 1DVAR retrieval method has great stability due to that the testing samples have great impact on the retrieval accuracies of the MLR and the ANN, but have little impact on that of the 1DVAR.
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