Preprints
Filtering by Subject: Oceanography and Atmospheric Sciences and Meteorology
The Baltic TRANSCOAST approach – investigating shallow coasts as terrestrial-marine interface of water and matter fluxes
Published: 2019-07-16
Subjects: Biogeochemistry, Biology, Earth Sciences, Environmental Monitoring, Environmental Sciences, Hydrology, Life Sciences, Marine Biology, Oceanography and Atmospheric Sciences and Meteorology, Other Oceanography and Atmospheric Sciences and Meteorology, Other Plant Sciences, Physical Sciences and Mathematics, Plant Sciences, Soil Science
In Baltic TRANSCOAST we study the physical, biogeochemical, and biological processes at the land-ocean interface. The coastal zone is heavily impacted by various human activities as well as by geomorphological and climatic processes – on both the land and the sea side. Land-sea interactions at low lying coastal areas that are often dominated by peatlands, and are a common feature along the Baltic [...]
Assessing Climate Model Projections of Anthropogenic Warming Patterns
Published: 2019-07-16
Subjects: Climate, Earth Sciences, Environmental Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
Projections of future anthropogenic climate change and their uncertainties are determined by analyzing large ensembles of numerical climate models. Since the late 1980s, transient climate models have projected a pronounced global warming, with relatively high warming in the Arctic and over land and low warming over the Southern Ocean. In general, confidence in climate model projections is based [...]
Southern Ocean Phytoplankton Blooms Observed by Biogeochemical Floats
Published: 2019-07-16
Subjects: Earth Sciences, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Other Earth Sciences, Physical Sciences and Mathematics
The spring bloom in the Southern Ocean is the rapid-growth phase of the seasonal cycle in phytoplankton. Many previous studies have characterized the spring bloom using chlorophyll estimates from satellite ocean color observations. Assumptions regarding the chlorophyll-to-carbon ratio within phytoplankton and vertical structure of biogeochemical variables lead to uncertainty in satellite-based [...]
Heat distribution in the Southeast Pacific is only weakly sensitive to high-latitude heat flux and wind stress
Published: 2019-07-16
Subjects: Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
The Southern Ocean features regionally-varying ventilation pathways that transport heat and carbon from the surface ocean to the interior thermocline on timescales of decades to centuries, but the factors that control the distribution of heat along these pathways are not well understood. In this study, we use a global ocean state estimate (ECCOv4) to (1) define the recently ventilated interior [...]
The sensitivity of Southeast Pacific heat distribution to local and remote changes in ocean properties
Published: 2019-07-16
Subjects: Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
The Southern Ocean features ventilation pathways that transport surface waters into the subsurface thermocline on timescales of decades to centuries, sequestering anomalies of heat and carbon away from the atmosphere and thereby regulating the rate of surface warming. Despite its importance for climate sensitivity, the factors that control the distribution of heat along these pathways are not [...]
Evidence against a general positive eddy feedback in atmospheric blocking
Published: 2019-07-04
Subjects: Atmospheric Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
The eddy straining mechanism of Shutts (1983; S83) has long been considered a main process for explaining the maintenance of atmospheric blocking. As hypothesized in S83, incoming synoptic eddies experience a meridional straining effect when approaching a split jetstream, and as a result, enhanced PV fluxes reinforce the block. A two-layer QG model is adopted here as a minimal model to conduct [...]
Reducing uncertainties in climate projections with emergent constraints: Concepts, Examples and Prospects
Published: 2019-06-27
Subjects: Atmospheric Sciences, Climate, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
Models disagree on a significant number of responses to climate change, such as climate feedback, regional changes, or the strength of equilibrium climate sensitivity. Emergent constraints aim to reduce these uncertainties by finding links between the inter-model spread in an observable predictor and climate projections. In this paper, the concepts underlying this framework are recalled with an [...]
Is it always Slowdown of the Walker circulation at solar cycle maximum?
Published: 2019-06-27
Subjects: Atmospheric Sciences, Climate, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
It is a commentary following a published paper in PNAS titled, ‘Slowdown of the Walker circulation at solar cycle maximum’, by Stergios Misios, Lesley J. Gray, Mads F. Knudsen, Christoffer Karoff, Hauke Schmidt, and Joanna D. Haigh (2019). The article of Misios et.al.(2019) claims that there is a slowdown of the Walker Circulation during maximum periods of solar cycles. In support, they provided [...]
Dynamical Systems Theory Sheds New Light on Compound Climate Extremes in Europe and Eastern North America
Published: 2019-06-27
Subjects: Applied Mathematics, Atmospheric Sciences, Climate, Dynamic Systems, Earth Sciences, Meteorology, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Physics, Statistical, Nonlinear, and Soft Matter Physics
We propose a novel approach to the study of compound extremes, grounded in dynamical systems theory. Specifically, we present the co-recurrence ratio (α), which elucidates the dependence structure between variables by quantifying their joint recurrences. This approach is applied to daily climate extremes, derived from the ERA-Interim reanalysis over the 1979-2018 period. The analysis focuses on [...]
Systems of intensive vertical vortices in turbulent atmosphere
Published: 2019-06-22
Subjects: Atmospheric Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
At certain conditions a system of well-separated quasi-point vortices can appear in two-dimensional turbulence. Such system contains main part (almost entire) of the flow enstrophy (mean squared vorticity). Spectral properties of the two-dimensional turbulence in the presence of the system of the quasi-point vortices have been studied using notion of the distributed chaos. Results of direct [...]
Large uncertainty in volcanic aerosol radiative forcing derived from ice cores
Published: 2019-06-20
Subjects: Atmospheric Sciences, Climate, Earth Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Volcanology
Reconstructions of volcanic aerosol radiative forcing are required to understand past climate variability. Currently, reconstructions of pre-20th century volcanic forcing are derived from sulfate concentrations measured in polar ice cores, predominantly using a relationship between average ice sheet sulfate deposition and stratospheric sulfate aerosol based on a single explosive eruption - the [...]
Data-driven prediction of a multi-scale Lorenz 96 chaotic system using deep learning methods: Reservoir computing, ANN, and RNN-LSTM
Published: 2019-06-20
Subjects: Applied Mathematics, Artificial Intelligence and Robotics, Atmospheric Sciences, Climate, Computer Sciences, Dynamic Systems, Earth Sciences, Fluid Dynamics, Non-linear Dynamics, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Physics
In this paper, the performance of three deep learning methods for predicting short-term evolution and for reproducing the long-term statistics of a multi-scale spatio-temporal Lorenz 96 system is examined. The methods are: echo state network (a type of reservoir computing, RC-ESN), deep feed-forward artificial neural network (ANN), and recurrent neural network with long short-term memory [...]
Optimizing Regional Climate Model Output for Hydro-Climate Applications in the Eastern Nile Basin
Published: 2019-06-18
Subjects: Civil and Environmental Engineering, Climate, Earth Sciences, Engineering, Hydrology, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
This study focuses on the Eastern Nile (EN) Basin, most of whose water flows into the High Aswan Dam (HAD), Egypt. It is, therefore, crucial to have an accurate hydrological assessment overtime to plan water resource management in the area. With complex topography, it is important to capture most of the physics captured with the least bias in meteorological information. Weather Research and [...]
Probing the chemical transformation of seawater-soluble crude oil components during microbial oxidation
Published: 2019-06-18
Subjects: Biogeochemistry, Chemistry, Earth Sciences, Environmental Chemistry, Environmental Sciences, Life Sciences, Microbiology, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Oil, Gas, and Energy, Physical Sciences and Mathematics
Studies assessing the environmental impacts of oil spills focus primarily on the non-water-soluble components, leaving the fate of the water-soluble fraction (WSF) largely unexplored. We employed untargeted chemical analysis along with biological information to probe the transformation of crude oil WSF in seawater, in the absence of light, in a laboratory experiment. Over a 14-day incubation, [...]
Understanding Low Cloud Mesoscale Morphology with an Information Maximizing Generative Adversarial Network
Published: 2019-06-05
Subjects: Artificial Intelligence and Robotics, Atmospheric Sciences, Computer Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
Generative adversarial networks (GANs) are a class of machine learning algorithms with two neural networks, one generator and one discriminator, playing adversarial games with each other. Information maximizing GANs (InfoGANs) is a particular GAN type that tries to maximize mutual information between a subset of latent variables and generated samples, thereby establishing a mapping between the [...]