Description: A thorough and reliable assessment of changes in sea surface water temperatures (SSWTs) is essential for understanding the effects of global warming on long-term trends in marine ecosystems and their communities. The first long-term temperature measurements were established almost a century ago, especially in coastal areas, and some of them are still in operation. However, while in earlier times these measurements were done by hand every day, current environmental long-term observation stations (ELTOS) are often fully automated and integrated in cabled underwater observatories (UWOs). With this new technology, year-round measurements became feasible even in remote or difficult to access areas, such as coastal areas of the Arctic Ocean in winter, where measurements were almost impossible just a decade ago. In this context, there is a question over what extent the sampling frequency and accuracy influence results in long-term monitoring approaches. In this paper, we address this with a combination of lab experiments on sensor accuracy and precision and a simulated sampling program with different sampling frequencies based on a continuous water temperature dataset from Svalbard, Arctic, from 2012 to 2017. Our laboratory experiments showed that temperature measurements with 12 different temperature sensor types at different price ranges all provided measurements accurate enough to resolve temperature changes over years on a level discussed in the literature when addressing climate change effects in coastal waters. However, the experiments also revealed that some sensors are more suitable for measuring absolute temperature changes over time, while others are more suitable for determining relative temperature changes. Our simulated sampling program in Svalbard coastal waters over 5 years revealed that the selection of a proper sampling frequency is most relevant for discriminating significant long-term temperature changes from random daily, seasonal, or interannual fluctuations. While hourly and daily sampling could deliver reliable, stable, and comparable results concerning temperature increases over time, weekly sampling was less able to reliably detect overall significant trends. With even lower sampling frequencies (monthly sampling), no significant temperature trend over time could be detected. Although the results were obtained for a specific site, they are transferable to other aquatic research questions and non-polar regions.

Description: The O2A (Observation to Archive) is a data-flow framework for heterogeneous sources, including multiple institutions and scales of Earth observation. In the O2A, once data transmission is set up, processes are executed to automatically ingest (i.e. collect and harmonize) and quality control data in near real-time. We consider a web-based sensor description application to support transmission and harmonization of observational time-series data. We also consider a product-oriented quality control, where a standardized and scalable approach should integrate the diversity of sensors connected to the framework. A review of literature and observation networks of marine and terrestrial environments is under construction to allow us, for example, to characterize quality tests in use for generic and specific applications. In addition, we use a standardized quality flag scheme to support both user and technical levels of information. In our outlook, a quality score should pair the quality flag to indicate the overall plausibility of each individual data value or to measure the flagging uncertainty. In this work, we present concepts under development and give insights into the data ingest and quality control currently operating within the O2A framework.

Description: Climate change is destabilizing permafrost landscapes, affecting infrastructure, ecosystems and human livelihoods. The rate of permafrost thaw is controlled by surface and subsurface properties and processes, all of which are potentially linked with each other. Yet, no standardized protocol exists for measuring permafrost thaw and related processes and properties in a linked manner. The permafrost thaw action group of the Terrestrial Multidisciplinary distributed Observatories for the Study of the Arctic Connections (T-MOSAiC) project has developed a protocol, for use by non-specialist scientists and technicians, citizen scientists and indigenous groups, to collect standardized metadata and data on permafrost thaw.The protocol introduced here addresses the need to jointly measure permafrost thaw and the associated surface and subsurface environmental conditions. The parameters measured along transects are: snow depth, thaw depth, vegetation height, soil texture, and water level. The metadata collection includes data on timing of data collection, geographical coordinates, land surface characteristics (vegetation, ground surface, water conditions), as well as photographs. Our hope is that this openly available dataset will also be highly valuable for validation and parameterization of numerical and conceptual models, thus to the broad community represented by the T-MOSAIC project.

Description: There is an urgent need for data collection to better understand permafrost thaw and its interaction with vegetation, hydrology, soil and snow. Greater spatial coverage, and improved coordination and consistency of measurements is particularly needed. To enable this, the Permafrost Thaw Action Group of T-MOSAiC have developed a data collection protocol and a user-friendly app (myThaw) aimed at non experts to facilitate collection and synthesis of data from across the Arctic. Recognising the fundamental role of interactions between the different components of the permafrost system, we addressed the need to measure the interconnected parameters of snow, vegetation, hydrology and permafrost in a single protocol so that measurements will be co-located in space and time, allowing relationships between variables to be disentangled. In particular the protocol locates all measurements on 10-30m transects that are revisited throughout the year. The measured variables include snow depth, vegetation height, soil texture and type, water level and permafrost thaw depth. This protocol uses simple measurements so more difficult-to-measure parameters are not collected, but the lack of specialist equipment and skills should enable a much greater participation in data collection and thus an improved coverage of the permafrost region, which is a central goal of this action group. Along with the protocol and the myThaw app, we present here the first results from the data collection which has been live now for several months, and details of how to get involved.

Description: Climate change is destabilizing permafrost landscapes, affecting infrastructure, ecosystems and human livelihoods. The rate of permafrost thaw is affected by surface and subsurface properties and processes, all of which are potentially linked with each other. Yet, no standardized protocol exists for measuring permafrost thaw and related processes and properties in a linked manner. The permafrost thaw action group of the Terrestrial Multidisciplinary distributed Observatories for the Study of the Arctic Connections (T-MOSAiC) project has developed a protocol, for use by non-specialist scientists and technicians, citizen scientists and indigenous groups, to collect standardized metadata and data on permafrost thaw. The protocol introduced here addresses the need to jointly measure permafrost thaw and the associated surface and subsurface environmental conditions. The parameters along transects are: snow depth, thaw depth, and vegetation height, soil texture and water level. The metadata collection includes data on timing of data collection, geographical coordinates, land surface characteristics (vegetation, ground surface, water conditions), as well as photographs. The comprehensive description and management of all data with metadata, central data storage and controlled data access is applied through the Observation to Archives (O2A) dataflow framework. Through this standardized procedure, data can be monitored in near-real time and their spatial distribution visualized. The dedicated user-friendly application (app) myThaw facilitates the data entry of field measurements and provides standardized data collection and documentation. We started our first measurements during March 2021 with snow depth measurements at the Bayelva site along a 10 meter transect. Several INTERACT sites in Svalbard, Alaska, Canada and Siberia have also agreed to start this data collection. This openly available dataset will also be highly valuable for validation and parameterization of numerical and conceptual models, thus to the broad community represented by the T-MOSAIC project.

Description: There is an urgent need for standardized data collection to better understand permafrost thaw and its interaction with vegetation, hydrology, soil and snow. To enable this, the Permafrost Thaw Action Group of T-MOSAiC have developed a protocol for gathering integrated observations of multiple connected components of permafrost landscapes. It is integrated with a user-friendly app aimed at non-experts to facilitate collection and synthesis of data from across the Arctic. Recognizing the fundamental role of interactions between the different components of the permafrost system, we provide measurement guidelines for variables pertaining to snow, vegetation, hydrology, soil and permafrost in a single protocol. The measured variables include snow depth, vegetation height, water level, soil type, and thaw depth. The protocol locates all measurements on transects that are revisited throughout the year. The co-located measurements of multiple variables facilitate quantification of interactions between these variables and model–data integration. The protocol is geared toward non-experts, including citizen scientists. We provide video tutorials and a user-friendly app. The protocol uses simple measurements that do not require specialist equipment or skills. While variables that are more difficult to measure could not be included, we believe that the simplicity of the protocols will enable greater participation in data collection and thus an improved coverage of the permafrost region. Along with the protocol and app, we present the first results from the data collection which has been live now for several months, and details of how to get involved.

Description: Modern digital scientific workflows - often implying Big Data challenges - require data infrastructures and innovative data science methods across disciplines and technologies. Diverse activities within and outside HGF deal with these challenges, on all levels. The series of Data Science Symposia fosters knowledge exchange and collaboration in the Earth and Environment research community. We invited contributions to the overarching topics of data management, data science and data infrastructures. The series of Data Science Symposia is a joint initiative by the three Helmholtz Centers HZG, AWI and GEOMAR Organization: Hela Mehrtens and Daniela Henkel (GEOMAR)