A perspective on gaussian processes for earth observation

Earth observation (EO) by airborne and satellite remote sensing and in-situ observations play a fundamental role in monitoring our planet. In the last decade, machine learning and Gaussian processes (GPs) in particular has attained outstanding results in the estimation of bio-geo-physical variables from the acquired images at local and global scales in a time-resolved manner. GPs provide not only accurate estimates but also principled uncertainty estimates for the predictions, can easily accommodate multimodal data coming from different sensors and from multitemporal acquisitions, allow the introduction of physical knowledge, and a formal treatment of uncertainty quantification and error propagation. Despite great advances in forward and inverse modelling, GP models still have to face important challenges that are revised in this perspective paper. GP models should evolve towards data-driven physics-aware models that respect signal characteristics, be consistent with elementary laws of physics, and move from pure regression to observational causal inference.Comment: 1 figur

Colorful Luminescent Magnetic Supraparticles: Expanding the Applicability, Information Capacity, and Security of Micrometer‐Scaled Identification Taggants by Dual‐Spectral Encoding

Abstract (Sub)micrometer‐scaled identification (ID) taggants enable direct identification of arbitrary goods, thereby opening up application fields based on the possibility of tracking, tracing, and anti‐counterfeiting. Due to their small dimensions, these taggants can equip in principle even the smallest subcomponents or raw materials with information. To achieve the demanded applicability, the mostly used optically encoded ID taggants must be further improved. Here, micrometer‐scaled supraparticles with spectrally encoded luminescent and magnetically encoded signal characteristics are reported. They are produced in a readily customizable bottom‐up fabrication procedure that enables precise adjustment of luminescent and magnetic properties on multiple hierarchy levels. The incorporation of commonly used magnetic nanoparticles and fluorescent dyes, respectively, into polymer nanocomposite particles, establishes a convenient toolbox of magnetic and luminescent building blocks. The subsequent assembly of selected building blocks in the desired ratios into supraparticles grants for all the flexibility to freely adjust both signal characteristics. The obtained spectrally resolved visible luminescent and invisible magnetic ID signatures are complementary in nature, thus expanding applicability and information security compared to recently reported optical‐ or magnetic‐encoded taggants. Additionally, the introduced ID taggant supraparticles can significantly enhance the coding capacity. Therefore, the introduced supraparticles are considered as next‐generation ID taggants

Have precipitation extremes and annual totals been increasing in the world’s dry regions over the last 60 years?

Daily precipitation extremes and annual totals have increased in large parts of the global land area over the past decades. These observations are consistent with theoretical considerations of a warming climate. However, until recently these trends have not been shown to consistently affect dry regions over land. A recent study, published by Donat et al. (2016), now identified significant increases in annual-maximum daily extreme precipitation (Rx1d) and annual precipitation totals (PRCPTOT) in dry regions. Here, we revisit the applied methods and explore the sensitivity of changes in precipitation extremes and annual totals to alternative choices of defining a dry region (i.e. in terms of aridity as opposed to precipitation characteristics alone). We find that (a) statistical artifacts introduced by data pre-processing based on a time-invariant reference period lead to an overestimation of the reported trends by up to 40 %, and that (b) the reported trends of globally aggregated extremes and annual totals are highly sensitive to the definition of a "dry region of the globe". For example, using the same observational dataset, accounting for the statistical artifacts, and based on different aridity-based dryness definitions, we find a reduction in the positive trend of Rx1d from the originally reported +1.6 % decade−1 to +0.2 to +0.9 % decade−1 (period changes for 1981–2010 averages relative to 1951–1980 are reduced to −1.32 to +0.97 % as opposed to +4.85 % in the original study). If we include additional but less homogenized data to cover larger regions, the global trend increases slightly (Rx1d: +0.4 to +1.1 % decade−1), and in this case we can indeed confirm (partly) significant increases in Rx1d. However, these globally aggregated estimates remain uncertain as considerable gaps in long-term observations in the Earth's arid and semi-arid regions remain. In summary, adequate data pre-processing and accounting for uncertainties regarding the definition of dryness are crucial to the quantification of spatially aggregated trends in precipitation extremes in the world's dry regions. In view of the high relevance of the question to many potentially affected stakeholders, we call for a well-reflected choice of specific data processing methods and the inclusion of alternative dryness definitions to guarantee that communicated results related to climate change be robust.Have precipitation extremes and annual totals been increasing in the world’s dry regions over the last 60 years?publishedVersio

A few extreme events dominate global interannual variability in gross primary production

Understanding the impacts of climate extremes on the carbon cycle is important for quantifying the carbon-cycle climate feedback and highly relevant to climate change assessments. Climate extremes and fires can have severe regional effects, but a spatially explicit global impact assessment is still lacking. Here, we directly quantify spatiotemporal contiguous extreme anomalies in four global data sets of gross primary production (GPP) over the last 30 years. We find that positive and negative GPP extremes occurring on 7% of the spatiotemporal domain explain 78% of the global interannual variation in GPP and a significant fraction of variation in the net carbon flux. The largest thousand negative GPP extremes during 1982–2011 (4.3% of the data) account for a decrease in photosynthetic carbon uptake of about 3.5 Pg C yr−1, with most events being attributable to water scarcity. The results imply that it is essential to understand the nature and causes of extremes to understand current and future GPP variability

Effects of climate extremes on the terrestrial carbon cycle : concepts, processes and potential future impacts

This article is protected by copyright. All rights reserved. Acknowledgements This work emerged from the CARBO-Extreme project, funded by the European Community’s 7th framework programme under grant agreement (FP7-ENV-2008-1-226701). We are grateful to the Reviewers and the Subject Editor for helpful guidance. We thank to Silvana Schott for graphic support. Mirco Miglivacca provided helpful comments on the manuscript. Michael Bahn acknowledges support from the Austrian Science Fund (FWF; P22214-B17). Sara Vicca is a postdoctoral research associate of the Fund for Scientific Research – Flanders. Wolfgang Cramer contributes to the Labex OT-Med (n° ANR-11- LABX-0061) funded by the French government through the A*MIDEX project (n° ANR-11-IDEX-0001-02). Flurin Babst acknowledges support from the Swiss National Science Foundation (P300P2_154543).Peer reviewedPublisher PD

Inferring causation from time series in Earth system sciences

The heart of the scientific enterprise is a rational effort to understand the causes behind the phenomena we observe. In large-scale complex dynamical systems such as the Earth system, real experiments are rarely feasible. However, a rapidly increasing amount of observational and simulated data opens up the use of novel data-driven causal methods beyond the commonly adopted correlation techniques. Here, we give an overview of causal inference frameworks and identify promising generic application cases common in Earth system sciences and beyond. We discuss challenges and initiate the benchmark platform causeme.net to close the gap between method users and developers. © 2019, The Author(s)

Supraparticles for Sustainability

Abstract The indispensable transformation to a (more) sustainable human society on this planet heavily relies on innovative technologies and advanced materials. The merits of nanoparticles (NPs) in this context are demonstrated widely during the last decades. Yet, it is believed that the impact of particle‐based nanomaterials to sustainability can be even further enhanced: taking NPs as building blocks enables the creation of more complex entities, so‐called supraparticles (SPs). Due to their evolving phenomena coupling, emergence, and colocalization, SPs enable completely new material functionalities. These new functionalities in SPs can be utilized to render six fields, essential to human life as it is conceived, more sustainable. These fields, selected based on an entropy‐rate‐related definition of sustainability, are as follows: 1) purification technologies and 2) agricultural delivery systems secure humans “fundamental needs.” 3) Energy storage and conversion, as well as 4) catalysis enable the “basic comfort.” 5) Extending materials lifetime and 6) bringing materials back in use ensure sustaining “modern life comfort.” In this review article, a perspective is provided on why and how the properties of SPs, and not simply properties of individual NPs or conventional bulk materials, may grant attractive alternative pathways in these fields

Supraparticles for Bare‐Eye H2 Indication and Monitoring: Design, Working Principle, and Molecular Mobility

Abstract Indicators for H2 are crucial to ensure safety standards in a green hydrogen economy. Herein, the authors report micron‐scaled indicator supraparticles for real‐time monitoring and irreversible recording of H2 gas via a rapid eye‐readable two‐step color change. They are produced via spray‐drying SiO2 nanoparticles, AuPd nanoparticles, and indicator‐dye resazurin. The resulting gas‐accessible mesoporous supraparticle framework absorbs water from humid atmospheres to create a three‐phase‐system. In the presence of H2, the color of the supraparticle switches first irreversibly from purple to pink and further reversibly to a colorless state. In situ infrared spectroscopy measurements indicate that this color change originates from the (ir)reversible H2‐induced reduction of resazurin to resorufin and hydroresorufin. Further infrared spectroscopic measurements and molecular dynamics simulations elucidate that key to achieve this functionality is an established three‐phase‐system within the supraparticles, granting molecular mobility of resazurin. Water acts as transport medium to carry resazurin molecules towards the catalytically active AuPd nanoparticles. The advantages of the supraparticles are their small dimensions, affordable and scalable production, fast response times, straightforward bare‐eye detection, and the possibility of simultaneously monitoring H2 exposure in real‐time and ex post. Therefore, H2 indicator supraparticles are an attractive safety additive for leakage detection and localization in a H2 economy