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Abstract In recent decades, the Barents Sea has warmed more than twice as fast as the rest of the Arctic in winter, but the exact causes behind this amplified warming remain unclear. In this study, we quantify the wintertime Barents Sea warming (BSW, for near-surface air temperature) with an average linear trend of 1.74 °C decade −1 and an interdecadal change around 2003 based on a surface energy budget analysis using the ERA5 reanalysis dataset from 1979–2019. Our analysis suggests that the interdecadal change in the wintertime near-surface air temperature is dominated by enhanced clear-sky downward longwave radiation (CDLW) associated with increased total column water vapor. Furthermore, it is found that a mode of atmospheric variability over the North Atlantic region known as the Barents oscillation (BO) strongly contributed to the BSW with a stepwise jump in 2003. Since 2003, the BO turned into a strengthened and positive phase, characteristic of anomalous high pressure over the North Atlantic and South of the Barents Sea, which promoted two branches of heat and moisture transport from southern Greenland along the Norwegian Sea and from the Eurasian continent to the Barents Sea. This enhanced the water vapor convergence over the Barents Sea, resulting in BSW through enhanced CDLW. Our results highlight the atmospheric circulation related to the BO as an emerging driver of the wintertime BSW through enhanced meridional atmospheric heat and moisture transport over the North Atlantic Ocean. 

Abstract. As an important atmosphere constituent, sulfate aerosols exert profound impacts on climate, the ecological environment, and human health. The Tibetan Plateau (TP), identified as the “Third Pole”, contains the largest land ice masses outside the poles and has attracted widespread attention for its environment and climatic change. However, the mechanisms of sulfate formation in this specific region still remain poorly characterized. An oxygen-17 anomaly (Δ17O) has been used as a probe to constrain the relative importance of different pathways leading to sulfate formation. Here, we report the Δ17O values in atmospheric sulfate collected at a remote site in the Mt. Everest region to decipher the possible formation mechanisms of sulfate in such a pristine environment. Throughout the sampling campaign (April–September 2018), the Δ17O in non-dust sulfate show an average of 1.7 ‰±0.5 ‰, which is higher than most existing data on modern atmospheric sulfate. The seasonality of Δ17O in non-dust sulfate exhibits high values in the pre-monsoon and low values in the monsoon, opposite to the seasonality in Δ17O for both sulfate and nitrate (i.e., minima in the warm season and maxima in the cold season) observed from diverse geographic sites. This high Δ17O in non-dust sulfate found in this region clearly indicates the important role of the S(IV)+O3 pathway in atmospheric sulfate formation promoted by conditions of high cloud water pH. Overall, our study provides an observational constraint on atmospheric acidity in altering sulfate formation pathways, particularly in dust-rich environments, and such identification of key processes provides an important basis for a better understanding of the sulfur cycle in the TP. 

Abstract. Recent studies have revealed a significant influx of anthropogenic aerosol from South Asia to the Himalayas and Tibetan Plateau (TP) during pre-monsoon period. In order to characterize the chemical composition, sources, and transport processes of aerosol in this area, we carried out a field study during June 2015 by deploying a suite of online instruments including an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-AMS) and a multi-angle absorption photometer (MAAP) at Nam Co station (90°57′E, 30°46′N; 4730ma.s.l.) at the central of the TP. The measurements were made at a period when the transition from pre-monsoon to monsoon occurred. The average ambient mass concentration of submicron particulate matter (PM₁) over the whole campaign was  ∼ 2.0µgm⁻³, with organics accounting for 68%, followed by sulfate (15%), black carbon (8%), ammonium (7%), and nitrate (2%). Relatively higher aerosol mass concentration episodes were observed during the pre-monsoon period, whereas persistently low aerosol concentrations were observed during the monsoon period. However, the chemical composition of aerosol during the higher aerosol concentration episodes in the pre-monsoon season was on a case-by-case basis, depending on the prevailing meteorological conditions and air mass transport routes. Most of the chemical species exhibited significant diurnal variations with higher values occurring during afternoon and lower values during early morning, whereas nitrate peaked during early morning in association with higher relative humidity and lower air temperature. Organic aerosol (OA), with an oxygen-to-carbon ratio (O∕C) of 0.94, was more oxidized during the pre-monsoon period than during monsoon (average O∕C ratio of 0.72), and an average O∕C was 0.88 over the entire campaign period, suggesting overall highly oxygenated aerosol in the central TP. Positive matrix factorization of the high-resolution mass spectra of OA identified two oxygenated organic aerosol (OOA) factors: a less oxidized OOA (LO-OOA) and a more oxidized OOA (MO-OOA). The MO-OOA dominated during the pre-monsoon period, whereas LO-OOA dominated during monsoon. The sensitivity of air mass transport during pre-monsoon with synoptic process was also evaluated with a 3-D chemical transport model.

 

Abstract. Subseasonal-to-seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging, but also has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges(GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiativecalled “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction” (LS4P) as the first international grass-roots effort to introduce spring land surface temperature(LST)/subsurface temperature (SUBT) anomalies over high mountain areas as acrucial factor that can lead to significant improvement in precipitationprediction through the remote effects of land–atmosphere interactions. LS4P focuses on process understanding and predictability, and hence it is differentfrom, and complements, other international projects that focus on theoperational S2S prediction. More than 40 groups worldwide have participated in this effort, including 21 Earth system models, 9 regionalclimate models, and 7 data groups. This paper provides an overview of the history and objectives of LS4P, provides the first-phase experimental protocol (LS4P-I) which focuses on the remote effect ofthe Tibetan Plateau, discusses the LST/SUBT initialization, and presents thepreliminary results. Multi-model ensemble experiments and analyses ofobservational data have revealed that the hydroclimatic effect of the springLST on the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation beyond EastAsia and its S2S prediction. Preliminary studies and analysis have alsoshown that LS4P models are unable to preserve the initialized LST anomaliesin producing the observed anomalies largely for two main reasons: (i) inadequacies in the land models arising from total soil depths which are tooshallow and the use of simplified parameterizations, which both tend to limit the soil memory; (ii) reanalysis data, which are used for initial conditions, have large discrepancies from the observed mean state andanomalies of LST over the Tibetan Plateau. Innovative approaches have beendeveloped to largely overcome these problems.