Search results for "Earth System Science"
showing 10 items of 27 documents
Current Wildland Fire Patterns and Challenges in Europe: A Synthesis of National Perspectives
2021
Changes in climate, land use, and land management impact the occurrence and severity of wildland fires in many parts of the world. This is particularly evident in Europe, where ongoing changes in land use have strongly modified fire patterns over the last decades. Although satellite data by the European Forest Fire Information System provide large-scale wildland fire statistics across European countries, there is still a crucial need to collect and summarize in-depth local analysis and understanding of the wildland fire condition and associated challenges across Europe. This article aims to provide a general overview of the current wildland fire patterns and challenges as perceived by natio…
Managing the Historical Agricultural Landscape in the Sicilian Anthropocene Context. The Landscape of the Valley of the Temples as a Time Capsule
2021
The debate over whether we are entering the Anthropocene Epoch focuses on the unequal consumption of the Earth system’s resources at the expense of nature’s regenerative abilities. To find a new point of balance with nature, it is useful to look back in time to understand how the so-called “Great Acceleration”—the surge in the consumption of the planet’s resources—hastened the arrival of the Anthropocene. Some particular places—for various reasons—survived the Great Acceleration and, as time capsules, have preserved more or less intact some landscape features that have disappeared elsewhere. How can we enhance these living archives that have come down to us? Through the analysis of the case…
Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science
2021
Remote sensing methods enable detection of solar-induced chlorophyll a fluorescence. However, to unleash the full potential of this signal, intensive cross-disciplinary work is required to harmonize biophysical and ecophysiological studies. For decades, the dynamic nature of chlorophyll a fluorescence (ChlaF) has provided insight into the biophysics and ecophysiology of the light reactions of photosynthesis from the subcellular to leaf scales. Recent advances in remote sensing methods enable detection of ChlaF induced by sunlight across a range of larger scales, from using instruments mounted on towers above plant canopies to Earth-orbiting satellites. This signal is referred to as solar-in…
Inferring causation from time series in earth system sciences
2019
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.
Earth system data cubes unravel global multivariate dynamics
2020
Understanding Earth system dynamics in light of ongoing human intervention and dependency remains a major scientific challenge. The unprecedented availability of data streams describing different facets of the Earth now offers fundamentally new avenues to address this quest. However, several practical hurdles, especially the lack of data interoperability, limit the joint potential of these data streams. Today, many initiatives within and beyond the Earth system sciences are exploring new approaches to overcome these hurdles and meet the growing interdisciplinary need for data-intensive research; using data cubes is one promising avenue. Here, we introduce the concept of Earth system data cu…
Bioaerosols in the Earth system: Climate, health, and ecosystem interactions
2016
Abstract Aerosols of biological origin play a vital role in the Earth system, particularly in the interactions between atmosphere, biosphere, climate, and public health. Airborne bacteria, fungal spores, pollen, and other bioparticles are essential for the reproduction and spread of organisms across various ecosystems, and they can cause or enhance human, animal, and plant diseases. Moreover, they can serve as nuclei for cloud droplets, ice crystals, and precipitation, thus influencing the hydrological cycle and climate. The sources, abundance, composition, and effects of biological aerosols and the atmospheric microbiome are, however, not yet well characterized and constitute a large gap i…
Evaluation and comparison of satellite precipitation estimates with reference to a local area in the Mediterranean Sea
2014
Precipitation measurement is a key activity for the analysis of storm processes as well as every hydrological process. Satellite retrieval systems, rain-gauge network and radar systems are complement to each other in terms of their coverage and capability of monitoring precipitation. Satellite rainfall estimates systems produce data with global coverage that can provide information in areas for which data from other sources are unavailable. Without referring to ground measurement, satellite-based estimates can be bias. Although some gauged adjusted satellite precipitation products are developed, an effective way of integrating multi-sources of precipitation information is still a challenge.…
Deep learning and process understanding for data-driven Earth system science
2017
Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, rather than amending classical machine learning, we argue that these contextual cues should be used as part of deep learning (an approach that is able to extract spatio-temporal features automatically) to gain further process understanding of Earth system science problems, improving the predictive ability of seasonal forecasting and modelling of long-range spatial connections across multiple timescales, for example. The next step will be a hybri…
A Special Issue on Advances in Machine Learning for Remote Sensing and Geosciences [From the Guest Editors]
2016
Machine learning has become a standard paradigm for the analysis of remote sensing and geoscience data at both local and global scales. In the upcoming years, with the advent of new satellite constellations, machine learning will have a fundamental role in processing large and heterogeneous data sources. Machine learning will move from mere statistical data processing to actual learning, understanding, and knowledge extraction. The ambitious goal is to provide responses to the challenging scientific questions about the earth system. This special issue aims at providing an updated, refreshing view of current developments in the field. For this special issue, we have collected five articles t…
Earth System Chemistry integrated Modelling (ESCiMo) with the Modular Earth Submodel System (MESSy) version 2.51
2016
Abstract. Three types of reference simulations, as recommended by the Chemistry–Climate Model Initiative (CCMI), have been performed with version 2.51 of the European Centre for Medium-Range Weather Forecasts – Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model: hindcast simulations (1950–2011), hindcast simulations with specified dynamics (1979–2013), i.e. nudged towards ERA-Interim reanalysis data, and combined hindcast and projection simulations (1950–2100). The manuscript summarizes the updates of the model system and details the different model set-ups used, including the on-line calculated diagnostics. Simulations have been performed with two diff…