Review of algorithms estimating export production from satellite derived properties

Whereas the vertical transport of biomass from productive surface waters to the deep ocean (the biological pump) is a critical component of the global carbon cycle, its magnitude and variability is poorly understood. Global-scale estimates of ocean carbon export vary widely, ranging from ∼5 to ∼20 Gt C y – 1 due to uncertainties in methods and unclear definitions. Satellite-derived properties such as phytoplankton biomass, sea surface temperature, and light attenuation at depth provide information about the oceanic ecosystem with unprecedented coverage and resolution in time and space. These products have been the basis of an intense effort over several decades to constrain different biogeochemical production rates and fluxes in the ocean. One critical challenge in this effort has been to estimate the magnitude of the biological pump from satellite-derived properties by establishing how much of the primary production is exported out of the euphotic zone, a flux that is called export production. Here we present a review of existing algorithms for estimating export production from satellite-derived properties, available in-situ datasets that can be used for testing the algorithms, and earlier evaluations of the proposed algorithms. The satellite-derived products used in the algorithm evaluation are all based largely on the Ocean Colour Climate Change Initiative (OC-CCI) products, and carbon products derived from them. The different resources are combined in a meta-analysis

Affine modifications and affine hypersurfaces with a very transitive automorphism group

We study a kind of modification of an affine domain which produces another affine domain. First appeared in passing in the basic paper of O. Zariski (1942), it was further considered by E.D. Davis (1967). The first named author applied its geometric counterpart to construct contractible smooth affine varieties non-isomorphic to Euclidean spaces. Here we provide certain conditions which guarantee preservation of the topology under a modification. As an application, we show that the group of biregular automorphisms of the affine hypersurface $X \subset C^{k+2}$ given by the equation $uv=p(x_1,...,x_k)$ where $p \in C[x_1,...,x_k],$ acts $m-$transitively on the smooth part reg$X$ of $X$ for any $m \in N.$ We present examples of such hypersurfaces diffeomorphic to Euclidean spaces.Comment: 39 Pages, LaTeX; a revised version with minor changes and correction

Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite-derived chlorophyll

Global biogeochemical ocean models are invaluable tools to examine how physical, chemical, and biological processes interact in the ocean. Satellite-derived ocean color properties, on the other hand, provide observations of the surface ocean, with unprecedented coverage and resolution. Advances in our understanding of marine ecosystems and biogeochemistry are strengthened by the combined use of these resources, together with sparse in situ data. Recent modeling advances allow the simulation of the spectral properties of phytoplankton and remote sensing reflectances, bringing model outputs closer to the kind of data that ocean color satellites can provide. However, comparisons between model outputs and analogous satellite products (e.g., chlorophyll a) remain problematic. Most evaluations are based on point-by-point comparisons in space and time, where spuriously large errors can occur from small spatial and temporal mismatches, whereas global statistics provide no information on how well a model resolves processes at regional scales. Here, we employ a unique suite of methodologies, the Probability Density Functions to Evaluate Models (PDFEM), which generate a robust comparison of these resources. The probability density functions of physical and biological properties of Longhurst's provinces are compared to evaluate how well a model resolves related processes. Differences in the distributions of chlorophyll a concentration (mg m−3) provide information on matches and mismatches between models and observations. In particular, mismatches help isolate regional sources of discrepancy, which can lead to improving both simulations and satellite algorithms. Furthermore, the use of radiative transfer in the model to mimic remotely sensed products facilitates model–observation comparisons of optical properties of the ocean.</p

Primary Production, an Index of Climate Change in the Ocean: Satellite-Based Estimates over Two Decades

Primary production by marine phytoplankton is one of the largest fluxes of carbon on our planet. In the past few decades, considerable progress has been made in estimating global primary production at high spatial and temporal scales by combining in situ measurements of primary production with remote-sensing observations of phytoplankton biomass. One of the major challengesinthisapproachliesintheassignmentoftheappropriatemodelparametersthatdefinethe photosynthetic response of phytoplankton to the light field. In the present study, a global database of in situ measurements of photosynthesis versus irradiance (P-I) parameters and a 20-year record of climatequalitysatelliteobservationswereusedtoassessglobalprimaryproductionanditsvariability with seasons and locations as well as between years. In addition, the sensitivity of the computed primaryproductiontopotentialchangesinthephotosyntheticresponseofphytoplanktoncellsunder changing environmental conditions was investigated. Global annual primary production varied from 38.8 to 42.1 Gt C yr−1 over the period of 1998–2018. Inter-annual changes in global primary production did not follow a linear trend, and regional differences in the magnitude and direction of change in primary production were observed. Trends in primary production followed directly from changes in chlorophyll-a and were related to changes in the physico-chemical conditions of the water column due to inter-annual and multidecadal climate oscillations. Moreover, the sensitivity analysis in which P-I parameters were adjusted by±1 standard deviation showed the importance of accurately assigning photosynthetic parameters in global and regional calculations of primary production. TheassimilationnumberoftheP-Icurveshowedstrongrelationshipswithenvironmental variables such as temperature and had a practically one-to-one relationship with the magnitude of change in primary production. In the future, such empirical relationships could potentially be used for a more dynamic assignment of photosynthetic rates in the estimation of global primary production. RelationshipsbetweentheinitialslopeoftheP-Icurveandenvironmentalvariableswere more elusive

Factors influencing user acceptance of public sector big open data

In recent years Government departments and public/private organizations are becoming increasingly transparent with their data to establish the whole new paradigm of big open data. Increasing research interest arises from the claimed usability of big open data in improving public sector reforms, facilitating innovation, improving supplier and distribution networks and creating resilient supply chains that help improve the efficiency of public services. Despite the advantages of big open data for supply chain and operations management, there is severe shortage of empirical analyses in this field, especially with regards to its acceptance. To address this gap, in this paper we use an extended Technology Acceptance Model (TAM) to empirically examine the factors affecting users’ behavioural intentions towards public sector big open data. We outline the importance of our model for operations and supply chain managers, the limitations of the study, and future research directions

Ocean carbon from space: Current status and priorities for the next decade

This is the final version. Available on open access from Elsevier via the DOI in this recordData availability: Data for Fig. 1a were generated from a free Scopus (https://www.scopus.com/) search of the terms "Ocean carbon satellite" (using All fields) in March 2022. Data from Fig. 1b and 1c were generated from the workshop registration and are available within the figure (participation number, geographical representation and gender split).The ocean plays a central role in modulating the Earth’s carbon cycle. Monitoring how the ocean carbon cycle is changing is fundamental to managing climate change. Satellite remote sensing is currently our best tool for viewing the ocean surface globally and systematically, at high spatial and temporal resolutions, and the past few decades have seen an exponential growth in studies utilising satellite data for ocean carbon research. Satellite-based observations must be combined with in-situ observations and models, to obtain a comprehensive view of ocean carbon pools and fluxes. To help prioritise future research in this area, a workshop was organised that assembled leading experts working on the topic, from around the world, including remote-sensing scientists, field scientists and modellers, with the goal to articulate a collective view of the current status of ocean carbon research, identify gaps in knowledge, and formulate a scientific roadmap for the next decade, with an emphasis on evaluating where satellite remote sensing may contribute. A total of 449 scientists and stakeholders participated (with balanced gender representation), from North and South America, Europe, Asia, Africa, and Oceania. Sessions targeted both inorganic and organic pools of carbon in the ocean, in both dissolved and particulate form, as well as major fluxes of carbon between reservoirs (e.g., primary production) and at interfaces (e.g., air-sea and land–ocean). Extreme events, blue carbon and carbon budgeting were also key topics discussed. Emerging priorities identified include: expanding the networks and quality of in-situ observations; improved satellite retrievals; improved uncertainty quantification; improved understanding of vertical distributions; integration with models; improved techniques to bridge spatial and temporal scales of the different data sources; and improved fundamental understanding of the ocean carbon cycle, and of the interactions among pools of carbon and light. We also report on priorities for the specific pools and fluxes studied, and highlight issues and concerns that arose during discussions, such as the need to consider the environmental impact of satellites or space activities; the role satellites can play in monitoring ocean carbon dioxide removal approaches; economic valuation of the satellite based information; to consider how satellites can contribute to monitoring cycles of other important climatically-relevant compounds and elements; to promote diversity and inclusivity in ocean carbon research; to bring together communities working on different aspects of planetary carbon; maximising use of international bodies; to follow an open science approach; to explore new and innovative ways to remotely monitor ocean carbon; and to harness quantum computing. Overall, this paper provides a comprehensive scientific roadmap for the next decade on how satellite remote sensing could help monitor the ocean carbon cycle, and its links to the other domains, such as terrestrial and atmosphere.European Space AgencySimons FoundationUK National Centre for Earth Observation (NCEO)UKRIAtlantic Meridional Transect ProgrammeSwiss National Science Foundatio

Een diverse kijk op culturele verweren

Contains fulltext : 85318.pdf (publisher's version ) (Open Access)M.C Foblets Multicultural Jurisprudence. Comparative Perspectives on the Cultural Defence Oxford:Hart Publishing ,2009 978184113986

Taalanalyse: Schending van Equality of Arms?

Contains fulltext : 65636.pdf ( ) (Open Access