Dark microplastics trigger changes on snow metamorphism that depends on the snow initial density.

The Songhua River Basin (SRB) in Northeast China is a high-latitude basin experiencing significant snow cover changes under global warming. This study quantified spatiotemporal changes in snowmelt in the SRB (1961–2020). A specific focus was placed on the changes at event scale, including frequency, magnitude and duration, that have been underexplored in previous work. Correlations between snowmelt and key driving factors were assessed to identify the dominant controls governing the melt process. A significant elevation-dependent decreasing trend in annual snowmelt was found over the decades, with the decrease most pronounced at lower elevations. Relative to the baseline period (1961–1990), the snowmelt dates during 1991–2020 advanced, with the 25%, 50%, and 75% cumulative levels occurring 9, 6, and 2 days earlier, respectively. Seasonally, snowmelt increased significantly in early spring (February to March) but decreased notably in late spring (April to May). Snowmelt events exhibited reduced frequency, total volume, peak value, and mean rate, along with fewer extreme events. The strongest correlation across snowmelt event types was found with mean snow depth for complete depletion and with accumulated sunshine duration for incomplete depletion, while Rain-on-Snow Melt events were most closely associated with sunshine and temperature. This study can provide a crucial reference for sustainable water management and spring agricultural irrigation in the SRB.

ABSTRACT Changes in snowmelt and stream runoff timing due to warming temperatures are a concern for water managers. This study analyzed runoff estimates from 10 Sierra Nevada watersheds upstream of California's San Francisco Estuary (1872–2022) to examine trends and temperature sensitivities. Monthly runoff time series, reconstructed using a multivariate regression model with temperature and precipitation data, revealed high variability with multi‐year wet and dry periods. While no statistically significant annual runoff trends were detected over the entire period, nine of 10 watersheds showed significant decreases in April–July runoff fractions. Breakpoints in the mid‐20th century indicated stationary fractions of April–July runoff followed by declining fractions in six watersheds, with the sharpest reductions occurring in the last decade. Sensitivity analysis linked warming to earlier runoff timing and modest reductions in annual runoff volumes, though interannual precipitation variability masked the impacts. We estimate a 3.7% decrease in total annual flow per o C of warming in the historical record, the effects of which may become more consequential under future warmer periods and during drought conditions. This work confirms previous findings of earlier runoff from snow‐fed watersheds in western North America in recent decades; importantly, it highlights the stationarity in this quantity from the late 19th century to mid‐20th century before significant warming trends emerged.

Abstract Snowmelt and related extreme events can have profound natural and societal impacts. However, the studies on projected changes in snow‐related extremes across the Tianshan Mountains (TS) and Pamir regions have been underexplored. Utilizing regional climate model downscaling and bias‐corrected CMIP6 data, this study examined the changes in snowmelt and water available for runoff (SMROS, rainfall plus snowmelt) during the cold seasons across these regions for historical (1994–2014) and future (2040–2060) periods under shared socioeconomic pathway (SSP) scenarios (SSP245 and SSP585). The results demonstrated that accumulated snowmelt was projected to rise by 17.98% and 20.36%, whereas SMROS could increase by 26.97% and 28.95%, respectively, under SSP245 and SSP585 scenarios. Despite relatively minimal changes in extreme snowmelt, the magnitude of the historical daily maximum extreme SMROS (10‐year return level) was 28.04 mm and was expected to increase by 15.32% and 15.31% under the SSP245 and SSP585 scenarios, respectively, especially in western TS exceeding 26%. Meanwhile, areas with a daily extreme SMROS exceeding 50 mm could rise by over 13.5%. A notable rise in daily extreme SMROS and its area occupation in high intensity highlighted an increased risk of rainfall‐driven extreme snowmelt events. The absolute increase in snowfall and frequent snow‐rain phase transitions during the cold season under climate warming (SSP245: 2.19°C and SSP585: 2.22°C) benefits the increase in high‐intensity rain‐on‐snow events, leading to extreme SMROS augmentation. The findings emphasize the significant role of rainfall‐trigger snowmelt events in exacerbating extreme snowmelt in a warming climate.

Snowmelt decreases light use efficiency in Qinghai-Tibetan plateau between 2000 and 2017

Spatio-temporal variability and trend of blue-green water resources in the Kaidu River Basin, an arid region of China

Snowmelt detection on the Antarctic ice sheet and ice Shelves based on AMSR2 89 GHz channels

Study regionThe Sanjiangyuan, located on the Tibetan Plateau, is the headwater of the three large Asia Rivers－ the Yangtze, Yellow and Lancang (upper Mekong) Rivers. Study focusMountain glacier melt runoff, an important buffer against drought, is enhancing with climate warming. Projection of glacier (especially small glaciers) runoff change is imperative for adapting to climate change and mitigating relevant risks. We aim to provide an up-to-date knowledge of the glacier area and runoff change for 2016–2099 in the Sanjiangyuan. New hydrological insights for the regionProjections based on CMIP6 archive show that 1) glacier area in the Sanjiangyuan for the four SSPs will shrink by 36 ± 12 % (SSP1–2.6), 42 ± 20 % (SSP2–4.5), 49 ± 19 % (SSP3–7.0) and 61 ± 15 % (SSP5–8.5) by the end of the 21st century. Small glacier dominated Lancang River basin is more sensitive to climate change than large glacier abundant Yangtze River basin and Yellow River basin. The Lancang River basin is projected to experience the greatest relative glacier area shrinkage, 10 % of glacier area and 55 % of glacier number will disappear for SSP5–8.5; 2) annual glacier runoff in the Yangtze River and Yellow River will reach peak water around 2080 under SSP3–7.0, while the Lancang River is already in or near peak water timing for all SSPs. Higher emission scenario tends to yield later peak water timing due to the changes in snow melt.

Global changes in floods and their drivers

Baseflow is the portion of streamflow that comes from groundwater and subsurface sources. Although baseflow is essential for sustaining streams during low flow and drought periods, we have little information about how and why it has changed over large regions of the continental United States. The objective of this study was to evaluate how changes in the climate system have affected observed monthly baseflow records at 3,283 USGS gauges over the last 30 years (1989–2019). We developed a statistical modeling framework to determine the relationship between monthly baseflow and monthly climate predictors (i.e., precipitation, temperature, and antecedent wetness). Overall, we found that baseflow trends and the factors influencing them vary by region and month. In the US Northeast, increases were detected earlier in the year (February and March) and in the summer (May and June), and were likely due to increasing precipitation, warmer temperature, and subsequent changes in snowmelt. Increasing baseflow in the US Pacific Northwest and Midwest were associated with increases in precipitation and antecedent wetness throughout the year. Decreasing trends were located in the US Southeast and Southwest. Baseflow trends in the US Southeast were only detected in March, possibly as a result of decreased precipitation during the spring. On the other hand, decreases in baseflow in the Central Southwestern United States occurred throughout the year. These trends were associated with a lack of precipitation and increases in temperature. Finally, we examined the relationship between monthly baseflow trends and changes in total water storage using monthly Gravity Recovery and Climate Experiment mascon products from the Jet Propulsion Laboratory. In this study, trends in total water storage were strongly associated with baseflow trends across the United States. The spatial and temporal variability in baseflow response to climate reported here can aid water managers in adapting to future climate change.

Abstract. Snowmelt is a major fresh water resource, and quantifying snowmelt and its variability under climate change is necessary for the planning and management of water resources. Spatiotemporal changes in snow properties in China have drawn wide attention in recent decades; however, country-wide assessments of snowmelt are lacking. Using precipitation and temperature data with a high spatial resolution (0.5′; approximately 1 km), this study calculated the monthly snowmelt in China for the 1951–2017 period, using a simple temperature index model, and the model outputs were validated using snowfall, snow depth, snow cover extent and snow water equivalent. Precipitation and temperature scenarios developed from five CMIP5 models were used to predict future snowmelt in China under three different representative concentration pathway (RCP) scenarios (RCP2.6, RCP4.5 and RCP8.5). The results show that the mean annual snowmelt in China from 1951 to 2017 is 2.41×1011 m3 yr−1. The mean annual snowmelt values in Northern Xinjiang, Northeast China and the Tibetan Plateau – China's three main stable snow cover regions – are 0.18×1011, 0.42×1011 and 1.15×1011 m3 yr−1, respectively. From 1951 to 2017, the snowmelt increased significantly in the Tibetan Plateau and decreased significantly in northern, central and southeastern China. In the whole of China, there was a decreasing trend in snowmelt, but this was not statistically significant. The mean annual snowmelt runoff ratios are generally more than 10 % in almost all third-level basins in West China, more than 5 % in third-level basins in North and Northeast China and less than 2 % in third-level basins in South China. From 1951 to 2017, the annual snowmelt runoff ratios decreased in most third-level basins in China. Under RCP2.6, RCP4.5 and RCP8.5, the projected snowmelt in China in the near future (2011–2040; mid-future –2041–2070; far future – 2071–2099) may decrease by 10.4 % (15.8 %; 13.9 %), 12.0 % (17.9 %; 21.1 %) and 11.7 % (24.8 %; 36.5 %) compared to the reference period (1981–2010), respectively. Most of the projected mean annual snowmelt runoff ratios in third-level basins in different future periods are lower than those in the reference period. Low temperature regions can tolerate more warming, and the snowmelt change in these regions is mainly influenced by precipitation; however, the snowmelt change in warm regions is more sensitive to temperature increases. The spatial variability in snowmelt changes may lead to regional differences in the impact of snowmelt on water supply.

To track peaks in resource abundance, temperate-zone animals use predictive environmental cues to rear their offspring when conditions are most favourable. However, climate change threatens the reliability of such cues when an animal and its resource respond differently to a changing environment. This is especially problematic in alpine environments, where climate warming exceeds the Holarctic trend and may thus lead to rapid asynchrony between peaks in resource abundance and periods of increased resource requirements such as reproductive period of high-alpine specialists. We therefore investigated interannual variation and long-term trends in the breeding phenology of a high-alpine specialist, the white-winged snowfinch, Montifringilla nivalis, using a 20-year dataset from Switzerland. We found that two thirds of broods hatched during snowmelt. Hatching dates positively correlated with April and May precipitation, but changes in mean hatching dates did not coincide with earlier snowmelt in recent years. Our results offer a potential explanation for recently observed population declines already recognisable at lower elevations. We discuss non-adaptive phenotypic plasticity as a potential cause for the asynchrony between changes in snowmelt and hatching dates of snowfinches, but the underlying causes are subject to further research.

Revealing the impacts of climate change on mountainous catchments through high-resolution modelling

Abstract Hydrological processes in mountain headwater basins are changing as climate and vegetation change. Interactions between hydrological processes and subalpine forest ecological function are important to mountain water supplies due to their control on evapotranspiration (ET). Improved understanding of the sensitivity of these interactions to seasonal and interannual changes in snowmelt and summer rainfall is needed as these interactions can impact forest growth, succession, health, and susceptibility to wildfire. To better understand this sensitivity, this research examined ET for a sub‐alpine forest in the Canadian Rockies over two contrasting growing seasons and quantified the contribution of transpiration (T) from the younger tree population to overall stand ET. The younger population was focused on to permit examination of trees that have grown under the effect of recent climate change and will contribute to treeline migration, and subalpine forest densification and succession. Research sites were located at Fortress Mountain Research Basin, Kananaskis, Alberta, where the subalpine forest examined is composed of Abies lasiocarpa (Subalpine fir) and Picea engelmannii (Engelmann spruce). Seasonal changes in water availability from snowmelt, precipitation, soil moisture reserves yielded stark differences in T and ET between 2016 and 2017. ET was higher in the drier year (2017), which had late snowmelt and lower summer rainfall than in the wetter year (2016) that had lower snowmelt and a rainy summer, highlighting the importance of spring snowmelt recharge of soil moisture. However, stand T of the younger trees (73% of forest population) was greater (64 mm) in 2016 (275 mm summer rainfall) than 2017 (39 mm T, 147 mm summer rainfall), and appears to be sensitive to soil moisture decreases in fall, which are largely a function of summer period rainfall. Relationships between subalpine forest water use and different growing season and antecedent (snowmelt period) hydrological conditions clarify the interactions between forest water use and alpine hydrology, which can lead to better anticipation of the hydrological response of subalpine forest‐dominated basins to climate variability and change.

Transient merging of two Rhine flow regimes from climate change

In many mountainous regions, winter precipitation accumulates as snow that melts in spring and summer, providing water to one billion people globally. Climate warming and earlier snowmelt compromises this natural water storage. While snowpack trend analyses commonly focus on snow water equivalent (SWE), we propose that trends in accumulation season snowmelt serve as a critical indicator of hydrologic change. Here we compare long-term changes in snowmelt and SWE from snow monitoring stations in western North America and find 34% of stations exhibit increasing winter snowmelt trends (p < 0.05), a factor of three larger than the 11% showing SWE declines (p < 0.05). Snowmelt trends are highly sensitive to temperature and an underlying warming signal, while SWE trends are more sensitive to precipitation variability. Thus, continental-scale snow water resources are in steeper decline than inferred from SWE trends alone. More winter snowmelt will complicate future water resource planning and management.

Effects of shifting snowmelt regimes on the hydrology of non-alpine temperate landscapes

ABSTRACT Big Earth Data—big data associated with Earth sciences—can potentially revolutionize research on climate change, sustainable development, and other issues of global concern. For example, analyzing massive amounts of satellite imagery of polar environments, which are sensitive to the effects of climate change, provides insights into global climate trends. This study proposes a method to use Big Earth Data to explore changes in snowmelt over the Antarctic ice sheet from 1979 to 2016. The method uses Zernike moments to observe melt area in Antarctica and uses the Mann-Kendall test to detect temporal changes and abnormal information about the continent's melt area. The melting trend in the time-series data matched the changes in temperature and seasonal transitions. The results do not demonstrate significant change in the area of surface melt; however, abrupt changes in melt conditions linked to temperature changes over the Antarctic ice sheet were observed within the time series. The experiment results demonstrate that the proposed method is robust, adaptive, and capable of extracting the core features of melting snow.

Impacts of climate change on snow accumulation and melting processes over mountainous regions in Northern California during the 21st century

The hydrological response of mountainous catchments particularly dependent on melting runoff is very vulnerable to climatic variability. This study is an attempt to assess hydrological response towards climatic variability of the Hunza catchment located in the mountainous chain of greater Hindu Kush-Himalaya (HKH) region. The hydrological response is analyzed through changes in snowmelt, ice melt and total runoff simulated through the application of the hydrological modeling system PREVAH under hypothetically developed climate change scenarios. The developed scenarios are based on changes in precipitation (Prp) and temperature (Tmp) and their combination. Under all the warmer scenarios, the increase in temperature systematically decreases the mean annual snow melt and increases significantly glacier melt volume. Temperature changes from 1°C to 4°C produce a large increase in spring and summer runoff, while no major variation was observed in the winter and autumn runoff. The maximum seasonal changes recorded under the Tmp+4°C, Prp+10% scenario.