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The surface soil moisture over the Qinghai–Tibet Plateau (QTP) has an important impact on the weather and climate of East Asia. Under climate warming, the imbalance of solid–liquid water of QTP has become a research hotspot, but the surface soil moisture dynamics over QTP are not clear owing to the lack of precise measurements over a large scale. In this paper, the quality of gridded surface soil moisture products including CSSPv2 high-resolution (6 km) simulation, ESA CCI satellite retrieval, ERA5 land-atmosphere coupled reanalysis, and GLDAS2.1 land reanalysis products (Noah, Catchment, VIC) is analyzed over QTP by comparison with the in situ measurements at 140 stations during 2009–2017. We find that the CSSPv2 product shows a higher correlation than the global satellite and reanalysis products, with correlation increased by 7.7%–115.6%. The root mean squared error of the CSSPv2 product is lower than that of other products, with the error decreased by 13.4%–46.3%. The triple collocation analysis using high-resolution simulation, global reanalysis, and satellite retrieval products over the entire plateau shows that the error of CSSPv2 is the lowest, followed by ESA CCI, while ERA5 is the highest. The soil moisture products of ESA CCI, ERA5, and CSSPv2 all show an increasing trend from April to September of 2009 to 2017, with wetting in the west and drying in the east. This study indicates that the CSSPv2 high-resolution surface soil moisture product has better performance over QTP than other global products, and the global satellite and reanalysis products may overestimate the surface soil moisture dynamics. [ABSTRACT FROM AUTHOR]

In this paper, we investigated the possible impact of snow darkening effect (SDE) by light-absorbing aerosols on the regional changes of the hydrological cycle over Eurasia using the NASA GEOS-5 Model with aerosol tracers and a state-of-the-art snow darkening module, the Goddard SnoW Impurity Module (GOSWIM) for the land surface. Two sets of ten-member ensemble experiments for 10 years were carried out forced by prescribed sea surface temperature (2002–2011) with different atmospheric initial conditions, with and without SDE, respectively. Results show that SDE can exert a significant regional influence in partitioning the contributions of evaporative and advective processes on the hydrological cycle, during spring and summer season. Over western Eurasia, SDE-induced rainfall increase during early spring can be largely explained by the increased evaporation from snowmelt. Rainfall, however, decreases in early summer due to the reduced evaporation as well as moisture divergence and atmospheric subsidence associated with the development of an anomalous mid- to upper-tropospheric anticyclonic circulation. On the other hand, in the East Asian monsoon region, moisture advection from the adjacent ocean is a main contributor to rainfall increase in the melting season. A warmer land-surface caused by earlier snowmelt and subsequent drying further increases moisture transport and convergence significantly enhancing rainfall over the region. Our findings suggest that the SDE may play an important role in leading to hotter and drier summers over western Eurasia, through coupled land-atmosphere interaction, while enhancing East Asian summer monsoonal precipitation via enhanced land-ocean thermal contrast and moisture transport due to the SDE-induced warmer Eurasian continent. [ABSTRACT FROM AUTHOR]

Accurate initial soil moisture conditions are essential for numerical weather prediction models, because they play a major role in land–atmosphere interactions. This study constructed a soil moisture data assimilation system and evaluated its impacts on the Global Data Assimilation and Prediction System based on the Korea Integrated Model (GDAPS-KIM) to improve its weather forecast skill. Soil moisture data retrieved from the Advanced Scatterometer (ASCAT) onboard the Meteorological Operational Satellite was assimilated into GDAPS-KIM using the ensemble Kalman filter method, and its impacts were evaluated for the 2019 boreal summer period. Our results indicated that the soil moisture data assimilation improved the agreement of the observations with the initial conditions of GDAPS-KIM. This led to a statistically significant improvement in the accuracy of the initial fields. A comparison of a five-day forecast against an ERA5 reanalysis and in situ observations revealed a reduction in the dry and warm biases of GDAPS-KIM over the surface and in the lower- and mid-level atmospheres. The temperature bias correction through the initialization of the soil moisture estimates from the data assimilation system was shown in the five-day weather forecast (root mean squared errors reduction of the temperature at 850 hPa by approximately 5% in East Asia). [ABSTRACT FROM AUTHOR]

This study examined the surface-wetness effects in calculating dust generation in source regions, using Asian dust aerosol model version 3 (ADAM3; the control run; CNTL). Model sensitivity experiment was conducted in such a way that the dust generation in CNTL is compared against three ADAM3 versions with various surface-wetness effect schemes. The dust-generation algorithm in ADAM_RAIN utilizes precipitation, while the scheme in ADAM3_SM1 and ADAM3_SM2 employs soil water content to account for the surface-wetness effects on dust generation. Each run was evaluated for the spring (March–May) of 2020. ADAM3_SM1 shows the best performance for the dust source region in East Asia based on the root-mean-square error and the skill score, followed by ADAM3_SM2 and ADAM3_RAIN. Particularly, incorporation of the surface-wetness effects improves dust generation mostly in wet cases rather than dry cases. The three surface-wetness-effect runs reduce dust generation in the source regions compared to CNTL; hence, the inclusion of surface-wetness effects improves dust generation in the regions where CNTL overestimates dust generation. [ABSTRACT FROM AUTHOR]