For decades, the Svalbard archipelago has been an area of interest for physical, chemical and biological investigations of snow and ice, due to its vulnerable location for climatic interactions and air-mass transport pathways. However, despite the many and demanding field campaigns carried out during the last decades, it has been difficult to link the findings from different projects to obtain the larger picture of snow research in Svalbard, and therefore its importance to the Arctic system is likely underestimated. This is in part related to the heterogeneity of sampling locations and sampling times, which does not promote direct comparisons between the different projects and also to the often mono-disciplinary nature of the research being carried out. Here, we present some of the lessons learned during SnowNet, a collaborative research initiative, developed to foster interdisciplinary Arctic field research. We will discuss key aspects to ensure that the collected data are consistent and comparable, ranging from protocol development, sample collection strategies and data processing and formatting, as well as some of the difficulties encountered. By coordinating our efforts in the field, we can optimize the use of logistics and financial resources, while minimizing our environmental footprint.
Lessons Learned from Interdisciplinary Snow Research in Svalbard
Elena Barbaro;Andrea Spolaor;
2018
Abstract
For decades, the Svalbard archipelago has been an area of interest for physical, chemical and biological investigations of snow and ice, due to its vulnerable location for climatic interactions and air-mass transport pathways. However, despite the many and demanding field campaigns carried out during the last decades, it has been difficult to link the findings from different projects to obtain the larger picture of snow research in Svalbard, and therefore its importance to the Arctic system is likely underestimated. This is in part related to the heterogeneity of sampling locations and sampling times, which does not promote direct comparisons between the different projects and also to the often mono-disciplinary nature of the research being carried out. Here, we present some of the lessons learned during SnowNet, a collaborative research initiative, developed to foster interdisciplinary Arctic field research. We will discuss key aspects to ensure that the collected data are consistent and comparable, ranging from protocol development, sample collection strategies and data processing and formatting, as well as some of the difficulties encountered. By coordinating our efforts in the field, we can optimize the use of logistics and financial resources, while minimizing our environmental footprint.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


