Precipitation comes in various phases, including rainfall, snowfall, sleet, and hail. Shifts of precipitation phases, as well as changes in precipitation amount, intensity, and frequency, have significant impacts on regional climate, hydrology, ecology, and the energy balance of the land-atmosphere system. Over the past century, certain progress has been achieved in aspects such as the observation, discrimination, transformation, and impact of precipitation phases. Mainly including: since the 1980s, studies on the observation, formation mechanism, and prediction of precipitation phases have gradually received greater attention and reached a certain scale. The estimation of different precipitation phases using new detection theories and methods has become a research focus. A variety of discrimination methods or schemes, such as the potential thickness threshold method of the air layer, the temperature threshold method of the characteristic layer, and the near-surface air temperature threshold method, have emerged one after another. Meanwhile, comparative studies on the discrimination accuracy and applicability assessment of multiple methods or schemes have also been carried out simultaneously. In recent years, the shift of precipitation from solid to liquid (SPSL) in the mid-to-high latitudes of the Northern Hemisphere has become more pronounced due to global warming and human activities. It leads to an increase in rain-on-snow (ROS) events and avalanche disasters, affecting the speed, intensity, and duration of spring snow-melting, accelerating sea ice and glacier melting, releasing carbon from permafrost, altering soil moisture, productivity, and phenological characteristics of ecosystems, and thereby affecting their structures, processes, qualities, and service functions. Although some progress has been made in the study of precipitation phases, there remains considerable research potential in terms of completeness of basic data, reliability of discrimination schemes, and the mechanistic understanding of the interaction between SPSL and other elements or systems. The study on shifts of precipitation phases and their impacts will play an increasingly important role in assessing the impacts of global climate change, water cycle processes, water resources management, snow and ice processes, snow and ice-related disasters, carbon emissions from permafrost, and ecosystem safety.

Tibetan Plateau (TP) is known as the water tower of Asia, and glaciers are solid reservoirs that can regulate the amount of water. Black carbon (BC), as one of the important factors accelerating glacier melting, is causing evident environmental effects in snow and ice. However, a systematical summary of the potential sources, analytical methods, distributions, and environmental effects of BC in snow and ice on the TP's glaciers is scarce. Therefore, this study drew upon existing research on snow and ice BC on glaciers of the TP to describe the detection methods and uncertainties associated with them to clarify the concentrations of BC in snow and ice and their climatic effects. The primary detection methods are the optical method, the thermal-optical method, the thermochemical method, and the single-particle soot photometer method. However, few studies have systematically compared the results of BC and this study found that concentrations of BC in different types of snow and ice varied by 1-3 orders of magnitude, which drastically affected the regional hydrologic process by potentially accelerating the ablation of glaciers by approximately 15% and reducing the duration of snow accumulation by 3-4 days. In general, results obtained from the various testing methods differ drastically, which limited the systematical discussion. Accordingly, a universal standard for the sampling and measurement should be considered in the future work, which will be beneficial to facilitate the comparison of the spatiotemporal features and to provide scientific data for the model-simulated climatic effects of BC.

The Tibetan Plateau holds the largest mass of snow and ice outside of the polar regions. The deposition of light-absorbing particles (LAPs) including mineral dust, black carbon and organic carbon and the resulting positive radiative forcing on snow (RFSLAPs) substantially contributes to glacier retreat. Yet how anthropogenic pollutant emissions affect Himalayan RFSLAPs through transboundary transport is currently not well known. The COVID-19 lockdown, resulting in a dramatic decline in human activities, offers a unique test to understand the transboundary mechanisms of RFSLAPs. This study employs multiple satellite data from the moderate resolution imaging spectroradiometer and ozone monitoring instrument, as well as a coupled atmosphere-chemistry-snow model, to reveal the high spatial heterogeneities in anthropogenic emissions-induced RFSLAPs across the Himalaya during the Indian lockdown in 2020. Our results show that the reduced anthropogenic pollutant emissions during the Indian lockdown were responsible for 71.6% of the reduction in RFSLAPs on the Himalaya in April 2020 compared to the same period in 2019. The contributions of the Indian lockdown-induced human emission reduction to the RFSLAPs decrease in the western, central, and eastern Himalayas were 46.8%, 81.1%, and 110.5%, respectively. The reduced RFSLAPs might have led to 27 Mt reduction in ice and snow melt over the Himalaya in April 2020. Our findings allude to the potential for mitigating rapid glacial threats by reducing anthropogenic pollutant emissions from economic activities.

Soot deposition from wildfires decreases snow and ice albedo and increases the absorption of shortwave radiation, which advances and accelerates melt. Soot deposition also induces algal growth, which further decreases snow and ice albedo. In recent years, increasingly severe and widespread wildfire activity has occurred in western Canada in association with climate change. In the summers of 2017 and 2018, westerly winds transported smoke from extensive record-breaking wildfires in British Columbia eastward to the Canadian Rockies, where substantial amounts of soot were deposited on high mountain glaciers, snowfields, and icefields. Several studies have addressed the problem of soot deposition on snow and ice, but the spatiotemporal resolution applied has not been compatible with studying mountain icefields that are extensive but contain substantial internal variability and have dynamical albedos. This study evaluates spatial patterns in the albedo decrease and net shortwave radiation (K*) increase caused by soot from intense wildfires in Western Canada deposited on the Columbia Icefield (151 km(2)), Canadian Rockies, during 2017 and 2018. Twelve Sentinel-2 images were used to generate high spatial resolution albedo retrievals during four summers (2017 to 2020) using a MODIS bidirectional reflectance distribution function (BRDF) model, which was employed to model the snow and ice reflectance anisotropy. Remote sensing estimates were evaluated using site-measured albedo on the icefield's Athabasca Glacier tongue, resulting in a R-2, mean bias, and root mean square error (RMSE) of 0.68, 0.019, and 0.026, respectively. The biggest inter-annual spatially averaged soot-induced albedo declines were of 0.148 and 0.050 (2018 to 2020) for southeast-facing glaciers and the snow plateau, respectively. The highest inter-annual spatially-averaged soot-induced shortwave radiative forcing was 203 W/m(2) for southeast-facing glaciers (2018 to 2020) and 106 W/m(2) for the snow plateau (2017 to 2020). These findings indicate that snow albedo responded rapidly to and recovered rapidly from soot deposition. However, ice albedo remained low the year after fire, and this was likely related to a bio-albedo feedback involving microorganisms. Snow and ice K* were highest during low albedo years, especially for south-facing glaciers. These large-scale effects accelerated melt of the Columbia Icefield. The findings highlight the importance of using large-area high spatial resolution albedo estimates to analyze the effect of wildfire soot deposition on snow and ice albedo and K* on icefields, which is not possible using other approaches.

Absolute-age dating horizons play a pillar role in the reconstruction of an ice core chronology. In the modern era, these have included the global fallout from massive volcanic eruptions, atmospheric and marine thermonuclear weapons testing and nuclear accidents. After the occurrence of the Fukushima Daiichi nuclear accident (FDNA) on March 11 2011, the simulation of the radioactivity from the FDNA by a dispersion model (HYSPLIT) shows that the nuclides reached the study area in late March, consistent with the ground measurements in Xi'an, Lanzhou and Urumqi. To investigate the deposition of radioactivity resulting from the FDNA, we collected snowpack samples from four glaciers (i.e. Glacier No. 1, Glacier No. 72, Qiyi and Shiyi glaciers, respectively) in northwestern China and analysed them for total beta activity (TBA). The measured TBA in the FDNA layers were increased by two to four times, compared with the averages in the non-FDNA layers. We revisited Glacier No. 1 in 2018 and studied a much deeper snow-pit profile for the TBA, seven years after the first-time investigation into a relatively shallow snow pit in 2011. The TBA concentrated in a dust layer and became more significant in 2018 compared to that in 2011. We compared the TBA in Glacier No. 1 with that in the Muztagata glacier from the Chernobyl accident in 1986, and the depositions of radioactivity in the two High-Asian glaciers were comparable. We conclude that the FDNA formed a distinctly new lasting reference in the snow, which could help date the snow and ice in the Northern Hemisphere.

Deposition of light-absorbing particles on glacier surfaces poses a series of adverse impacts on the cryospheric environment, climate and human health. Broad attention of the scientific community has been paid on insoluble light-absorbing impurities (ILAIs) in snow and ice on glaciers over the Tibetan Plateau (TP). However, systematic investigation of ILAIs in snowpack of glaciers on the TP is scarce. In this study, the properties and darkening effect of ILAIs in snowpack on glaciers are extensively investigated in the southeast of TP. Results show that ILAIs concentrations in multiple types of snow and ice samples were significantly different. Snowpit depths varied substantially from one profile to another during May and June 2016. The average concentrations of ILAls in snowpits increase as snow melting progresses. Black carbon (BC) and dust cause snow albedo reduction more in snow with larger grain size Re. Based on a radiative transfer model calculation, the average albedo reduction induced by BC in the snowpack was 0.141 +/- 0.02, and associated daily maximum radiative forcing (RF) was 72.97 +/- 12.7 W m(-2). BC is a controlling light-absorbing factor in snowpack and causes substantial albedo reduction and thus the associated daily maximum RF. The maximum reduction of snow cover duration was 4.56 +/- 0.71 days caused by BC and dust in snowpack in southeastern TP. The average mass absorption cross- (MAC) of BC from multiple snowpits was 3.26 +/- 0.46 m(2) g(-1), which represents a typical value of MAC in snow on glaciers, but it is type-dependent of snow/ice samples. Tropospheric aerosols vertically extended up to 8 km over the TP and its surrounding areas, which indicates the transport of aerosols from remote sources through elevated pathways. A large amount of carbon stored in the brittle glaciers can be potentially released with meltwater runoff under a warming climate. This study provides a new insight for investigating carbonaceous and light-absorbing particles in glacierization areas. (C) 2019 Elsevier Ltd. All rights reserved.

We have developed an approach which examines ecosystem function and the potential effects of climatic shifts. The Lake McDonald watershed of Glacier National Park was the focus for two linked research activities: acquisition of baseline data on hydrologic, chemical and aquatic organism attributes that characterize this pristine northern rocky mountain watershed, and further developing the Regional Hydro-Ecosystem Simulation System (RHESSys), a collection of integrated models which collectively provide spatially explicit, mechanistically-derived outputs of ecosystem processes, including hydrologic outflow, soil moisture, and snowpack water equivalence. In this unique setting field validation of RHESSys, outputs demonstrated that reasonable estimates of SWE and streamflow are being produced. RHESSys was used to predict annual stream discharge and temperature. The predictions, in conjunction with the field data, indicated that aquatic resources of the park may be significantly affected. Utilizing RHESSys to predict potential climate scenarios and response of other key ecosystem components can provide scientific insights as well as proactive guidelines for national park management.