## 2 Data and Methods
### Datasets
#### 2.2.1 Soil Moisture Datasets  
CTP-SMTMN is a dense monitoring network composed of 56 stations (indicated by black dots in Figure 1b) primarily located in grasslands at elevations ranging from 4470 to 4950 m. At each station, soil moisture is measured by 5 TM and EC-TM capacitance probes from METER, USA ([[https://www.metergroup.com/](https://www.metergroup.com/)]([https://www.metergroup.com/](https://www.metergroup.com/)), accessed on 11 October 2022), at four depths: 0-5 cm, 10 cm, 20 cm, and 40 cm, and recorded every 30 min [35]. These sensors measure volumetric water content (VWC) based on the relationship between soil dielectric constant and soil liquid water and have been carefully calibrated station by station to take into account the impact of high soil organic carbon (SOC) on soil moisture measurements [35]. All data have been meticulously quality controlled by checking the soil moisture series to eliminate suspected or erroneous data, resulting in more accurate results. Soil moisture ranges from 0.40 to 0.55 at a depth of 0-10 cm [43]. It is usually high due to the higher SOC at the topsoil but decreases with increasing soil depth as SOC decreases [44]. To avoid damage to the wireless transmitter by livestock, the data are downloaded and the network status is checked manually after the deep soil thaw (i.e., early June) and before the soil starts to freeze (i.e., late September) each year. The soil moisture dataset is available from the Central Tibetan Plateau Data Center (TPDC, [[https://www.tpdc.ac.cn/en/](https://www.tpdc.ac.cn/en/)]([https://www.tpdc.ac.cn/en/](https://www.tpdc.ac.cn/en/)), accessed on 11 October 2022), and has been successfully applied in various studies, including soil moisture freeze-thaw monitoring [45; 46], soil moisture scaling [47; 48], and evaluation of soil moisture products [49]. In this study, surface (0-5 cm) soil moisture measurements that are mostly comparable to the SMAP retrievals during 2015-2018 were used. Figure 2 illustrates the temporal evolution of surface soil moisture time series across all 56 stations in the order of completeness in recorded time series, and for each time point, the areal mean is obtained through averaging over all the available soil moisture measurements. However, it is noticed that some stations have missing data at certain time periods. To examine the impact of data missing on the areal mean soil moisture, we compared the time series of average daily in situ soil moisture from stations with good time series completeness (stations numbered 1-35, i.e., those above the red horizontal line in Figure 2) to those of all stations during JJAS 2015-2018. As shown in Figure 3, the two time series show a high level of consistency, indicating the missing data at some stations should have negligible impact on the areal mean soil moisture estimation. The SMAP satellite operates in a sun-synchronous orbit at local solar time of 6:00 A.M. (descending) and 6:00 P.M. (ascending). It makes use of the L-band microwave to detect changes in soil moisture within the topsoil layer of 0-5 cm, which is relatively thicker than previous sensors do, and thereby can provide more information on precipitation. In this study, the recently released SMAP Level 3 radiometer global daily soil moisture (SPL3 SMP) version 8 [50] with spatial resolutions of 36 km \(\times\) 36 km was adopted and fed to SM2 RAIN to estimate precipitation for this region. This retrieval employed the Dual Channel Algorithm (DCA) as the baseline algorithm to retrieve soil moisture, rather than the Single Channel Algorithm-Vertical Polarization (SCA-V) used in its predecessor (i.e., SPL3 SMP version 7). Some studies have demonstrated that the DCA product performed relatively improved or comparable to SCA-V product [51; 52; 53; 54], and it is available at the National Snow and Ice Data Center (NSDIC; [[https://nsidc.org/data](https://nsidc.org/data)]([https://nsidc.org/data](https://nsidc.org/data)), accessed on 10 September 2022).