Results 71 to 80 of about 2,888 (290)
Understanding changes in the hazard component of climate risk is important to inform societal resilience planning in a changing climate. Here, we examine local changes in wind speed, rainfall, and flooding related to tropical cyclones (TCs) and compare ...
Alexander Michalek +2 more
doaj +1 more source
Dynamical and statistical downscaling of a global seasonal hindcast in eastern Africa
Within the FP7 EUPORIAS project we have assessed the utility of dynamical and statistical downscaling to provide seasonal forecast for impact modelling in eastern Africa.
Grigory Nikulin +19 more
doaj +1 more source
Advancing Energy Materials by In Situ Atomic Scale Methods
Progress in in situ atomic scale methods leads to an improved understanding of new and advanced energy materials, where a local understanding of complex, inhomogeneous systems or interfaces down to the atomic scale and quantum level is required. Topics from photovoltaics, dissipation losses, phase transitions, and chemical energy conversion are ...
Christian Jooss +21 more
wiley +1 more source
Improving sea-level projections on the Northwestern European shelf using dynamical downscaling
Changes in ocean properties and circulation lead to a spatially non-uniform pattern of ocean dynamic sea-level change (DSLC). The projections of ocean dynamic sea level presented in the IPCC AR5 were constructed with global climate models (GCMs) from the
Hermans, T.H.J. +5 more
core +2 more sources
Dynamical influences of precipitation assimilation on regional downscaling [PDF]
Precipitation assimilation has previously been found to be useful for improving regional climate model simulations of the surface water and energy cycles. Here we show that upper‐level dynamical features are also better simulated. In particular, noticeable improvements in the intensity and location of the subtropical upper‐level westerly jet and ...
Ana M. B. Nunes, John O. Roads
openaire +1 more source
Enabling Smart Dynamical Downscaling of Extreme Precipitation Events With Machine Learning
The projection of extreme convective precipitation by global climate models (GCM) exhibits significant uncertainty due to coarse resolutions. Direct dynamical downscaling (DDD) of regional climate at kilometer-scale resolutions provides valuable insight ...
Shi, Xiaoming, Xiaoming Shi
core +1 more source
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan +12 more
wiley +1 more source
Climate Change Mitigation in the Dairy Sector: Uncovering Heterogeneity Through Eco‐Efficiency Clubs
ABSTRACT Combining climate change goals with economic targets is crucial for the dairy sector, which is a significant contributor to agricultural greenhouse gas (GHG) emissions worldwide. In this paper, we assess economic and climate change implications of dairy production with panel data of Irish dairy farms from 2013 to 2021.
Doris Läpple +2 more
wiley +1 more source
Harnessing Phase Dynamics Across Diverse Frequencies with Multifrequency Oscillatory Neural Networks
Oscillatory Neural Networks (ONNs) are an emerging computing paradigm that encodes information in the phases of coupled oscillators. Traditionally, ONNs have been investigated using homogeneous frequency oscillators. However, physical hardware implementations are inherently subject to frequency mismatches, device variability, and nonuniformities.
Nil Dinç +2 more
wiley +1 more source
Assessments of local-scale windstorm hazard require highly resolved spatial information on wind speeds and gusts. In this study, maximum (peak) sustained wind speeds on a 3-km horizontal grid over Switzerland are obtained by dynamical downscaling from ...
Peter Stucki +6 more
doaj +1 more source

