Related papers: Perturbing parameters to understand cloud contribu…
Experiments on Bose-Einstein condensates at finite temperature typically extract the system parameters, such as temperature, atom number, and condensed fraction from time-of-flight images taken after a free expansion time. This paper…
How will the climate system respond to anthropogenic forcings? One approach to this question relies on climate model projections. Current climate projections are considerably uncertain. Characterizing and, if possible, reducing this…
Climate projections suffer from uncertain equilibrium climate sensitivity. The reason behind this uncertainty is the resolution of global climate models, which is too coarse to resolve key processes such as clouds and convection. These…
In this paper we will prove that GCM-models used in IPCC report AR5 fail to calculate the influences of the low cloud cover changes on the global temperature. That is why those models give a very small natural temperature change leaving a…
Physics parameterizations are often needed for numerical weather prediction (NWP) of precipitation forecast. This is mainly because the resolutions of most computational atmospheric models are not fine enough to explicitly resolve sub-grid…
Mixed-phase clouds, composed of supercooled liquid droplets and ice crystals, play a critical role in weather and climate systems. Their complex microphysical interactions and coupling with turbulence at microscales govern the cloud…
Certain Weather Regimes (WR) are associated with a higher risk of energy shortages, i.e. Blocking regimes for European winters. However, there are many uncertainties tied to the implementation of WRs and associated risks in the energy…
Current cosmological tensions motivate investigating extensions to the standard $\Lambda$CDM model. Additional model parameters are typically varied one or two at a time, in a series of separate tests. The purpose of this paper is to…
A multifactor parameterization is described to permit the efficient calculation of collision efficiency (E) between electrically charged aerosol particles and neutral cloud droplets in numerical cloud and climate models. The four parameter…
When modeling multivariate data, one might have an extra parameter of contextual information that could be used to treat some observations as more similar to others. For example, images of faces can vary by age, and one would expect the…
Accurately representing surface precipitation is crucial for the operational use of weather and climate models. Presently, global numerical weather prediction (NWP) models struggle to accurately generate precipitation due to their…
The increasing availability of data presents an opportunity to calibrate unknown parameters which appear in complex models of phenomena in the biomedical, physical and social sciences. However, model complexity often leads to…
Observed changes such as increasing global temperatures and the intensification of the global water cycle in the 20th century are also robust results of coupled general circulation models. In spite of this success model-to-model variability…
Near-surface extreme winds profoundly affect human society, yet process-based understanding of their changes under climate forcings remains limited. This study systematically investigates the responses of high (HWE) and low (LWE) wind…
This paper aims to perform a phenomenological parametrisation of the standard cosmological model, $\Lambda$CDM, to weigh the different physical processes that define the pattern of the angular power spectra of the Cosmic Microwave…
Regression algorithms are regularly used for improving the accuracy of satellite precipitation products. In this context, satellite precipitation and topography data are the predictor variables, and gauged-measured precipitation data are…
Representing and quantifying uncertainty in physical parameterisations is a central challenge in weather and climate modelling, and approaches are often developed separately for different timescales. Here, we introduce a unified framework…
Atmosphere is one of the most important noise sources for ground-based cosmic microwave background (CMB) experiments. By increasing optical loading on the detectors, it amplifies their effective noise, while its fluctuations introduce…
We conduct a sensitivity analysis of a new type of integrated climate-economic model recently proposed in the literature, where the core economic component is based on the Goodwin-Keen dynamics instead of a neoclassical growth model.…
To analyze climate change mitigation strategies, economists rely on simplified climate models - climate emulators. We propose a generic and transparent calibration and evaluation strategy for these climate emulators that is based on Coupled…