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The development of phosphate sensors suitable for long-term in situ deployments in natural waters, is essential to improve our understanding of the distribution, fluxes, and biogeochemical role of this key nutrient in a changing ocean. Here, we describe the optimization of the molybdenum blue method for in situ work using a lab-on-chip (LOC) analyzer and evaluate its performance in the laboratory and at two contrasting field sites. The in situ performance of the LOC sensor is evaluated using hourly time-series data from a 56-day trial in Southampton Water (UK), as well as a month-long deployment in the subtropical oligotrophic waters of Kaneohe Bay (Hawaii, USA). In Kaneohe Bay, where phosphate concentrations were characteristic of the dry season (0.13 ± 0.03 μM, n = 704), the in situ sensor accuracy was 16 ± 12% and a potential diurnal cycle in phosphate concentrations was observed. In Southampton Water, the sensor data (1.02 ± 0.40 μM, n = 1,267) were accurate to ±0.10 μM relative to discrete reference samples. Hourly in situ monitoring revealed striking tidal and storm derived fluctuations in phosphate concentrations in Southampton Water that would not have been captured via discrete sampling. We show the impact of storms on phosphate concentrations in Southampton Water is modulated by the spring-neap tidal cycle and that the 10-fold decline in phosphate concentrations observed during the later stages of the deployment was consistent with the timing of a spring phytoplankton bloom in the English Channel. Under controlled laboratory conditions in a 250 L tank, the sensor demonstrated an accuracy and precision better than 10% irrespective of the salinity (0–30), turbidity (0–100 NTU), colored dissolved organic matter (CDOM) concentration (0–10mg/L), and temperature (5–20◦C) of the water (0.3–13 μM phosphate) being analyzed. This work demonstrates that the LOC technology is mature enough to quantify the influence of stochastic events on nutrient budgets and to elucidate the role of phosphate in regulating phytoplankton productivity and community composition in estuarine and coastal regimes. Refereed 14.A Nutrients TRL 8 Actual system completed and "mission qualified" through test and demonstration in an operational environment (ground or space) Manual (incl. handbook, guide, cookbook etc) Standard Operating Procedure

The dataset contains meteorological observations during a measurement campaign with the drone LUCA (Lightweight high Ceiling Aerial System). The measurements were collected between the 25th and the 29th October 2021 at rather erratic launch times, as operations from the military training area Todendorf (Panker) in Northern Germany within the restricted airspace belonging to the training area depend on air traffic control clearance. As parameters, pressure, temperature, humidity and wind direction/speed were observed along with time and position of the drone. Besides the raw measurements, temperature and humidity readings have been corrected with an estimated inverse sensor transfer function. The data allows intercomparing the drone measurements with collocated radiosonde launches which enables a discussion on the possible use of the drone LUCA and similar systems for operational meteorology.

Changes in marine net primary productivity (PP) and export of particulate organic carbon (EP) are projected over the 21st century with four global coupled carbon cycle-climate models. These include representations of marine ecosystems and the carbon cycle of different structure and complexity. All four models show a decrease in global mean PP and EP between 2 and 20% by 2100 relative to preindustrial conditions, for the SRES A2 emission scenario. Two different regimes for productivity changes are consistently identified in all models. The first chain of mechanisms is dominant in the low- and mid-latitude ocean and in the North Atlantic: reduced input of macro-nutrients into the euphotic zone related to enhanced stratification, reduced mixed layer depth, and slowed circulation causes a decrease in macro-nutrient concentrations and in PP and EP. The second regime is projected for parts of the Southern Ocean: an alleviation of light and/or temperature limitation leads to an increase in PP and EP as productivity is fueled by a sustained nutrient input. A region of disagreement among the models is the Arctic, where three models project an increase in PP while one model projects a decrease. Projected changes in seasonal and interannual variability are modest in most regions. Regional model skill metrics are proposed to generate multi-model mean fields that show an improved skill in representing observation-based estimates compared to a simple multi-model average. Model results are compared to recent productivity projections with three different algorithms, usually applied to infer net primary production from satellite observations.

As part of the Perma-X airborne campaign led by the Alfred Wegener Institute in 2021, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at very high spatial resolution of 20 cm, as well as photogrammetric point clouds in RGB and NIR. This data collection aggregates three data subsets of the southern Baldwin Peninsula, Alaska, covering approximately 80 km². All images were collected on 28 June 2021.

In the field of ocean observing, the term of “observatory” is often used without a unique meaning. A clear and unified definition of observatory is needed in order to facilitate the communication in a multidisciplinary community, to capitalize on future technological innovations and to support the observatory design based on societal needs. In this paper, we present a general framework to define the next generation Marine OBservatory (MOB), its capabilities and functionalities in an operational context. The MOB consists of four interconnected components or “gears” (observation infrastructure, cyberinfrastructure, support capacity, and knowledge generation engine) that are constantly and adaptively interacting with each other. Therefore, a MOB is a complex infrastructure focused on a specific geographic area with the primary scope to generate knowledge via data synthesis and thereby addressing scientific, societal, or economic challenges. Long-term sustainability is a key MOB feature that should be guaranteed through an appropriate governance. MOBs should be open to innovations and good practices to reduce operational costs and to allow their development in quality and quantity. A deeper biological understanding of the marine ecosystem should be reached with the proliferation of MOBs, thus contributing to effective conservation of ecosystems and management of human activities in the oceans. We provide an actionable model for the upgrade and development of sustained marine observatories producing knowledge to support science-based economic and societal decisions. Refereed 14.A Manual (incl. handbook, guide, cookbook etc) 2018-09-07

A critical challenge in paleoclimate data analysis is the fact that the proxy data are heterogeneously distributed in space, which affects statistical methods that rely on spatial embedding of data. In the paleoclimate network approach nodes represent paleoclimate proxy time series, and links in the network are given by statistically significant similarities between them. Their location in space, proxy and archive type is coded in the node attributes. We develop a semi-empirical model for Spatio-Temporally AutocoRrelated Time series, inspired by the interplay of different Asian Summer Monsoon (ASM) systems. We use an ensemble of transition runs of this START model to test whether and how spatio–temporal climate transitions could be detectable from (paleo)climate networks. We sample model time series both on a grid and at locations at which paleoclimate data are available to investigate the effect of the spatially heterogeneous availability of data. Node betweenness centrality, averaged over the transition region, does not respond to the transition displayed by the START model, neither in the grid-based nor in the scattered sampling arrangement. The regionally defined measures of regional node degree and cross link ratio, however, are indicative of the changes in both scenarios, although the magnitude of the changes differs according to the sampling. We find that the START model is particularly suitable for pseudo-proxy experiments to test the technical reconstruction limits of paleoclimate data based on their location, and we conclude that (paleo)climate networks are suitable for investigating spatio–temporal transitions in the dependence structure of underlying climatic fields.

As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at very high spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR. This data collection aggregates two data subsets of the Imuruk volcanic field on the northern Seward Peninsula, Alaska, covering approximately 50 km². All images were collected on 10 July 2021.

For years, the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI), together with the international MOSAiC partners, had been planning and developing the scientific, logistical and financial concept for the implementation of the MOSAiC expedition. The planning and organization of this endeavor was an enormous e˙ort, involving more than 80 institutions from 20 countries. The number of groups and individuals that significantly contributed to the success of the drift observatory goes far beyond the scope of usual polar expeditions.

Strong earthquakes cause large changes in the station positions and velocities of the geodetic reference stations; i.e., the global ITRF (International Terrestrial Reference Frame) and its regional densifications like SIRGAS (Sistema de Referencia Geocéntrico para Las Américas) in Latin America and the Caribbean. To ensure the long-term stability of the geodetic reference frames, the transformation of station positions between different epochs requires the computation of reliable continuous surface deformation (or velocity) models. This data set contains the new continental continuous crustal deformation model VEMOS2015 (Velocity Model for SIRGAS 2015) for Latin America and the Caribbean inferred from GNSS (GPS+GLONASS) measurements gained after the strong earthquakes occurred in 2010 in Chile and Mexico. It is based on a multi-year velocity solution for a network of 456 continuously operating GNSS stations covering a five years period from March 14, 2010 to April 11, 2015. VEMOS2015 is computed using the least square collocation (LSC) approach with empirically determined covariance functions.

Water/ice velocity data and instrument status from a Nortek Aquadopp Profiler 2MHz acoustic doppler current profiler (ADCP) attached to a remotely operated vehicle (ROV) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition between November 2019 and September 2020. The Aquadopp System Integrator Manual by Nortek AS can be found here: https://sensor.awi.de/rest/sensors/onlineResources/getOnlineResourcesFile/1764/system-integrator-manual_Mar2016.pdf