**1. Introduction**

24 REMOTE SENSING

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Global changing is a great challenge that affects the nowadays world, even arises and becomes kinds of the political issues. The changing of the snow is not only a sensitive factor act as a driving force but can be influenced much in the global temperature variation, especially for the seasonal snow cover which is vastly distributed over the northern hemisphere. Snow cover influences the atmosphere and ocean, and therefore the climate system, through both direct and indirect effects (Judah, 1991). In the climate regime, the snow cover alters the surface energy and water circle in a global scale in the climate processing (Fg.1). From the IPCC (2001), the recent and anticipated reductions in snow cover due to future greenhouse warming are an important topic for the global change community. Large seasonal variations in snow cover are of importance on continental to hemispheric scales induces to investigate its natural variability in the climate-system forcing of such trends, versus possible anthropogenic influences (Roger, 2002). So, understanding the spatial pattern in the temporal variability of snow cover increase the current understanding of global climate change and provide a mechanism for exploring future trends ( Steve Vavrus, 2007) . As such, snow cover is an appropriate indicator of climate perturbations and may be a suitable surrogate for investigations of climate change (Serreze , 2000; IPCC, 2001; Roger, 2002; Wulder, 2007; IPCC AR4, 2007).

Recent research result over China area revealed that the long time series snow trend is not suit for the whole trend over northern hemisphere and regional northern American (Qin, 2006; Xu, 2007; Wang, 2008;). From Qin's research (2006) of snow cover for the period of 1951

<sup>∗</sup> Corresponding Author

Satellite-Based Snow Cover Analysis and the

snow behaviors over *Tibet Plateau* area in mid-latitude.

area where the atmosphere pressure is less than 700 hPa).

**2.2.1 Snow extent and snow cover fraction products** 

**2.2 Satellite–based snow products and processing method** 

Center, 2008). The key parameters for this type of data are listed below:

**a. IMS Daily Northern Hemisphere Snow and Ice Analysis at 24 km Resolution** 

This data is 24 km daily Northern Hemisphere snow and ice coverage by the NOAA/NESDIS Interactive Multi-sensor Snow and Ice Mapping System (IMS) (National Ice

**2.1 Introduction** 

Snow Water Equivalent Retrieval Perspective over China 49

temperature(Wang, 2008), and positive trend of the snow cover area is connected with the increasing precipitation records (Qin, 2006;) in western China. While over *Tibet Plateau* area, China, it is difficult to analyze the long time series trend for its highly rugged mountain, westeast variation and sparse meteorological stations. The data used in these studies are mostly based on the some single satellite products and meteorological station records which are sparse over the high altitude area of *Tibet Plateau*. Furthermore, the meteorological stations are affected by station location, observing practices and land covers, and are not uniformly distributed. Therefore, it is important to evaluate the gross representative satellite data in a large scale area for more than twenty years and try to deliberate the climate impact on the

According to the importance of the snow and the climate singularity aspects, in this work, we used the available snow cover area (Snow Cover Area), snow depth (Snow Water Equivalent, SWE) products to examine the climatological characteristics and time series analysis over *Tibetan Plateau* area and study the new snow-retrieval algorithm over China area which often experiences the shallow snow situation. This chapter includes two parts, the first is to analyse the snow products, include the near-time optical and passive microwave remote sensing and the blended SCA and SWE products, the second is to analyse the perspective view of the

shallow snow retrieval analysis based on the passive microwave high frequency.

**2. Climatology analyses of the satellite-based snow parameters over China** 

The climatology features for a long time series of snow parameters over land could provide the signature of climate changes across the globe. According to the IPCC AR4 report, the snow extent is sharply decreasing over Northern Hemisphere from the prediction of the nine General Circulation Models since 2000. This part provides a climatology analysis of the SCA and SWE over China area and *Tibetan Plateau* from the satellite observation. The data set includes snow extent and snow water equivalence. Snow extent products are 24 km daily Northern Hemisphere snow and ice coverage from the NOAA/NESDIS Interactive Multisensor Snow and Ice Mapping System (IMS), Near-Real-Time SSM/I-SSMIS EASE-Grid Daily Global Ice Concentration (NISE) and Snow Extent and the Moderate-resolution Imaging Spectroradiometer (MODIS, TERRA/AQUA) snow cover fraction (SCF) products from 1999 to now, and the SWE products include Global Monthly EASE-Grid Snow Water Equivalent Climatology from 1978 to 2007, and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) from 2002 to now. The SCF (MODIS) and SWE (AMSR-E) are employed to analyse the ten years' time series over *Tibetan Plateau* (the area is defined by the

Fig. 1. This conceptual diagram illustrates the connectivity of the positive ice/snow albedo feedback, terrestrial snow and vegetation feedbacks and the negative cloud/radiation feedback. (Source: Chapin III, 2005)

and 1997, the results show that western China did not experience a continual decrease in snow cover during the great warming periods of the 1980s and 1990s. The positive trend of snow cover in western China snow cover is consistent with increasing snowfall, but is in contradiction to regional warming. Xu's result (2007) also show that the SCA of the entire *Tarim* basin in Xinjiang Province revealed a slowly increasing trend from 1958 to 2002, the SCA change in the cold season was positively correlated with the contemporary precipitation change. Wang (2008) reported an inconsistent tend with a reported Northern Hemisphere increasing trend based on limited in situ observations in Xinjiang Province which is a western province in China. While over the area located in the southern parts of the high land of *Tibet Plateau*, China, some investigators explore that annual snow cover has declined by –16% per decade between 1990 and 2001, which is explained due to the contribution of enhanced Indian black carbon (Menon et al., 2010) and the additional absorption of solar radiation by soot on snow cover area (Chand, 2009). Over *Tibetan Plateau* area, Pu's study (2007) indicated that a decreasing trend of snow cover fraction using snow data of 2000–2006 from the Moderate Resolution Imaging Spectroradiometer (MODIS) data is –0.34% per year. In their study, the meteorological station data (Xu, 2007) and the satellite sensor (Scanning Multichannel Microwave Radiometer, SMMR) observed snow depth (SD), NOAA snow cover area data and MODIS snow cover fraction products are used. When concerning the climate change impact on snow cover, the variability of snow cover area is negatively associated with to air temperature(Wang, 2008), and positive trend of the snow cover area is connected with the increasing precipitation records (Qin, 2006;) in western China. While over *Tibet Plateau* area, China, it is difficult to analyze the long time series trend for its highly rugged mountain, westeast variation and sparse meteorological stations. The data used in these studies are mostly based on the some single satellite products and meteorological station records which are sparse over the high altitude area of *Tibet Plateau*. Furthermore, the meteorological stations are affected by station location, observing practices and land covers, and are not uniformly distributed. Therefore, it is important to evaluate the gross representative satellite data in a large scale area for more than twenty years and try to deliberate the climate impact on the snow behaviors over *Tibet Plateau* area in mid-latitude.

According to the importance of the snow and the climate singularity aspects, in this work, we used the available snow cover area (Snow Cover Area), snow depth (Snow Water Equivalent, SWE) products to examine the climatological characteristics and time series analysis over *Tibetan Plateau* area and study the new snow-retrieval algorithm over China area which often experiences the shallow snow situation. This chapter includes two parts, the first is to analyse the snow products, include the near-time optical and passive microwave remote sensing and the blended SCA and SWE products, the second is to analyse the perspective view of the shallow snow retrieval analysis based on the passive microwave high frequency.
