Diogo Costa , Andrea Spolaor , Elena Barbaro , Juan I. López-Moreno , John W. Pomeroy
{"title":"通过改善分层雪和雨雪(ROS)事件中液态水运动的表现来改善积雪化学模拟:在挪威斯瓦尔巴群岛的应用","authors":"Diogo Costa , Andrea Spolaor , Elena Barbaro , Juan I. López-Moreno , John W. Pomeroy","doi":"10.1016/j.jhydrol.2024.132573","DOIUrl":null,"url":null,"abstract":"<div><div>Circumpolar and high-elevation cold regions receive a large portion of their annual precipitation as snowfall, which accumulates in snowpacks that can store many contaminants. The discharge of chemical eluent during snowmelt can alter the chemical composition of local streams and have a detrimental effect on aquatic ecosystems.</div><div>Cold regions have been particularly affected by climate change. In the last two decades, the Arctic has been exposed to dramatic atmospheric temperature increases, sea ice decrease, and an increase of air mass transport from lower latitudes bringing warmer and more humid air masses. Instrumental measurements in the Svalbard archipelago, Norway, show that climate warming here is amplified compared to the global average, making its cryospheric environment extremely vulnerable to future climate scenarios.</div><div>In this study, the PULSE model for simulation of snowpack solute dynamics was coupled to two snowpack energy balance models, the Cold Regions Hydrological Model and the SNOWPACK model, to help identify critical processes needed to improve the accuracy of snow chemistry predictions. Focus was given to <figure><img></figure> to represent sea spray sources, <figure><img></figure> to represent terrestrial dust, and <figure><img></figure> to represent various sources including sea salt, biogenic emissions, and long-range atmospheric transport of secondary aerosols. The new coupled models were applied to an experimental site in Svalbard. The hydrological components of each model coupling were validated against snowdepth measurements and the snowpack chemistry components were verified for a selected number of snow ions representative of different sources. Both models were able to predict snowdepths between 1996 and 2018, as well as the stratification of snow chemistry measured during a whole snow accumulation and ablation year. Results show that explicitly representing liquid water movement through layered snow helped improve chemistry predictions. Events such as rain-on-snow (ROS) had a disproportionate effect on the redistribution of ions to deeper snow layers.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"651 ","pages":"Article 132573"},"PeriodicalIF":5.9000,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improving snowpack chemistry simulations through improved representation of liquid water movement through layered snow and rain-on-snow (ROS) episodes: Application to Svalbard, Norway\",\"authors\":\"Diogo Costa , Andrea Spolaor , Elena Barbaro , Juan I. López-Moreno , John W. Pomeroy\",\"doi\":\"10.1016/j.jhydrol.2024.132573\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Circumpolar and high-elevation cold regions receive a large portion of their annual precipitation as snowfall, which accumulates in snowpacks that can store many contaminants. The discharge of chemical eluent during snowmelt can alter the chemical composition of local streams and have a detrimental effect on aquatic ecosystems.</div><div>Cold regions have been particularly affected by climate change. In the last two decades, the Arctic has been exposed to dramatic atmospheric temperature increases, sea ice decrease, and an increase of air mass transport from lower latitudes bringing warmer and more humid air masses. Instrumental measurements in the Svalbard archipelago, Norway, show that climate warming here is amplified compared to the global average, making its cryospheric environment extremely vulnerable to future climate scenarios.</div><div>In this study, the PULSE model for simulation of snowpack solute dynamics was coupled to two snowpack energy balance models, the Cold Regions Hydrological Model and the SNOWPACK model, to help identify critical processes needed to improve the accuracy of snow chemistry predictions. Focus was given to <figure><img></figure> to represent sea spray sources, <figure><img></figure> to represent terrestrial dust, and <figure><img></figure> to represent various sources including sea salt, biogenic emissions, and long-range atmospheric transport of secondary aerosols. The new coupled models were applied to an experimental site in Svalbard. The hydrological components of each model coupling were validated against snowdepth measurements and the snowpack chemistry components were verified for a selected number of snow ions representative of different sources. Both models were able to predict snowdepths between 1996 and 2018, as well as the stratification of snow chemistry measured during a whole snow accumulation and ablation year. Results show that explicitly representing liquid water movement through layered snow helped improve chemistry predictions. Events such as rain-on-snow (ROS) had a disproportionate effect on the redistribution of ions to deeper snow layers.</div></div>\",\"PeriodicalId\":362,\"journal\":{\"name\":\"Journal of Hydrology\",\"volume\":\"651 \",\"pages\":\"Article 132573\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2024-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Hydrology\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0022169424019693\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydrology","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022169424019693","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
Improving snowpack chemistry simulations through improved representation of liquid water movement through layered snow and rain-on-snow (ROS) episodes: Application to Svalbard, Norway
Circumpolar and high-elevation cold regions receive a large portion of their annual precipitation as snowfall, which accumulates in snowpacks that can store many contaminants. The discharge of chemical eluent during snowmelt can alter the chemical composition of local streams and have a detrimental effect on aquatic ecosystems.
Cold regions have been particularly affected by climate change. In the last two decades, the Arctic has been exposed to dramatic atmospheric temperature increases, sea ice decrease, and an increase of air mass transport from lower latitudes bringing warmer and more humid air masses. Instrumental measurements in the Svalbard archipelago, Norway, show that climate warming here is amplified compared to the global average, making its cryospheric environment extremely vulnerable to future climate scenarios.
In this study, the PULSE model for simulation of snowpack solute dynamics was coupled to two snowpack energy balance models, the Cold Regions Hydrological Model and the SNOWPACK model, to help identify critical processes needed to improve the accuracy of snow chemistry predictions. Focus was given to to represent sea spray sources, to represent terrestrial dust, and to represent various sources including sea salt, biogenic emissions, and long-range atmospheric transport of secondary aerosols. The new coupled models were applied to an experimental site in Svalbard. The hydrological components of each model coupling were validated against snowdepth measurements and the snowpack chemistry components were verified for a selected number of snow ions representative of different sources. Both models were able to predict snowdepths between 1996 and 2018, as well as the stratification of snow chemistry measured during a whole snow accumulation and ablation year. Results show that explicitly representing liquid water movement through layered snow helped improve chemistry predictions. Events such as rain-on-snow (ROS) had a disproportionate effect on the redistribution of ions to deeper snow layers.
期刊介绍:
The Journal of Hydrology publishes original research papers and comprehensive reviews in all the subfields of the hydrological sciences including water based management and policy issues that impact on economics and society. These comprise, but are not limited to the physical, chemical, biogeochemical, stochastic and systems aspects of surface and groundwater hydrology, hydrometeorology and hydrogeology. Relevant topics incorporating the insights and methodologies of disciplines such as climatology, water resource systems, hydraulics, agrohydrology, geomorphology, soil science, instrumentation and remote sensing, civil and environmental engineering are included. Social science perspectives on hydrological problems such as resource and ecological economics, environmental sociology, psychology and behavioural science, management and policy analysis are also invited. Multi-and interdisciplinary analyses of hydrological problems are within scope. The science published in the Journal of Hydrology is relevant to catchment scales rather than exclusively to a local scale or site.