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Developing cost-effective methods for hydrological observations is an identified research objective of the WMO Hydrological Research Strategy 2022-2030. Network settings of hydrological observational networks are central for data collection and monitoring efforts to fulfill observation needs. In this work, we ask the question: Where and how densely (location and time) measurement stations need to be placed to gain sound scientific insights into hydro-meteorological conditions of a region? We address this question through information theory concepts and calculate entropy, joint entropy, and mutual information for an existing large dataset of hydro-meteorological parameters. The dataset spans 36 years (1981-2017) of daily data for Sweden based on the national S-HYPE hydrological model. Hydrological data include runoff, inflow, and streamflow as computed values and meteorological data encompass temperature and precipitation as measured and corrected data. We chose Sweden as a study domain to look at a Nordic region with a large number of water basins and an overall well-sampled region allowing to assess interesting network settings through sub-sampling. Sub-sampling and analysis for potential network settings is done for the seven hydrological clusters across Sweden as they are defined in Girons Lopez et al. (2021). Random sub-sampling (by 10%, 25%, 50%, 75%, and 90%) of each of the seven clusters shows a narrow range of (Shannon) entropy indicating excellent assignment of catchments to the seven clusters. Focusing on three clusters, which span Sweden’s North-South extend and mainly feature forested areas and a cluster covering mostly coastal lakes, we assess how much information remains in the data set if sub-sampled by hydro-geological parameters, such as baseflow and flashiness. Such tests allow us to determine ideal and minimum network settings with respect to observational and computational efforts based on different criteria relevant to scientific investigations and decision-making needs. Girons Lopez, M., Crochemore, L., and Pechlivanidis, I. G.: Benchmarking an operational hydrological model for providing seasonal forecasts in Sweden, Hydrol. Earth Syst. Sci., 25, 1189–1209, https://doi.org/10.5194/hess-25-1189-2021, 2021

The formation of ice particles in Earth's atmosphere strongly influences the dynamics and optical properties of clouds and their impacts on the climate system. Ice formation in clouds is often triggered heterogeneously by ice-nucleating particles (INPs) that represent a very low number of particles in the atmosphere. To date, many sources of INPs, such as mineral and soil dust, have been investigated and identified in the low and mid latitudes. Although less is known about the sources of ice nucleation at high latitudes, efforts have been made to identify the sources of INPs in the Arctic and boreal environments. In this study, we investigate the INP emission potential from high-latitude boreal forests in the mixed-phase cloud regime. We introduce the HyICE-2018 measurement campaign conducted in the boreal forest of Hyytiala, Finland, between February and June 2018. The campaign utilized the infrastructure of the Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II, with additional INP instruments, including the Portable Ice Nucleation Chamber I and II (PINC and PINCii), the SPectrometer for Ice Nuclei (SPIN), the Portable Ice Nucleation Experiment (PINE), the Ice Nucleation SpEctrometer of the Karlsruhe Institute of Technology (INSEKT) and the Microlitre Nucleation by Immersed Particle Instrument (mu L-NIPI), used to quantify the INP concentrations and sources in the boreal environment. In this contribution, we describe the measurement infrastructure and operating procedures during HyICE-2018, and we report results from specific time periods where INP instruments were run in parallel for inter-comparison purposes. Our results show that the suite of instruments deployed during HyICE-2018 reports consistent results and therefore lays the foundation for forthcoming results to be considered holistically. In addition, we compare measured INP concentrations to INP parameterizations, and we observe good agreement with the Tobo et al. (2013) parameterization developed from measurements conducted in a ponderosa pine forest ecosystem in Colorado, USA., Atmospheric Chemistry and Physics, 22 (8), ISSN:1680-7375, ISSN:1680-7367