Search results for "PREDICTION"
showing 10 items of 511 documents
Aviation Contrail Cirrus and Radiative Forcing Over Europe During 6 Months of COVID‐19
2021
Abstract The COVID‐19 pandemic led to a 72% reduction of air traffic over Europe in March–August 2020 compared to 2019. Modeled contrail cover declined similarly, and computed mean instantaneous radiative contrail forcing dropped regionally by up to 0.7 W m−2. Here, model predictions of cirrus optical thickness and the top‐of‐atmosphere outgoing longwave and reflected shortwave irradiances are tested by comparison to Meteosat‐SEVIRI‐derived data. The agreement between observations and modeled data is slightly better when modeled contrail cirrus contributions are included. The spatial distributions and diurnal cycles of the differences in these data between 2019 and 2020 are partially caused…
Gaussian Process Sensitivity Analysis for Oceanic Chlorophyll Estimation
2017
Source at https://doi.org/10.1109/JSTARS.2016.2641583. Gaussian process regression (GPR) has experienced tremendous success in biophysical parameter retrieval in the past years. The GPR provides a full posterior predictive distribution so one can derive mean and variance predictive estimates, i.e., point-wise predictions and associated confidence intervals. GPR typically uses translation invariant covariances that make the prediction function very flexible and nonlinear. This, however, makes the relative relevance of the input features hardly accessible, unlike in linear prediction models. In this paper, we introduce the sensitivity analysis of the GPR predictive mean and variance functions…
Improving RAMS and WRF mesoscale forecasts over two distinct vegetation covers using an appropriate thermal roughness length parameterization
2019
Land Surface Models (LSM) have shown some difficulties to properly simulate day-time 2-m air and surface skin temperatures. This kind of models are coupled to atmospheric models in mesoscale modelling, such as the Regional Atmospheric Modeling System (RAMS) and the Weather Research and Forecasting (WRF) Model. This model coupling is used within Numerical Weather Prediction Systems (NWP) in order to forecast key physical processes for agricultural meteorology and forestry as well as in ecological modelling. The current study first evaluates the surface energy fluxes and temperatures simulated by these two state-of-the-art NWP models over two distinct vegetated covers, one corresponding to a …
Processes governing the amplification of ensemble spread in a medium-range forecast with large forecast uncertainty
2019
This study provides a process-based perspective on the amplification of forecast uncertainty and forecast errors in ensemble forecasts. A case from the North Atlantic Waveguide and Downstream Impact Experiment that exhibits large forecast uncertainty is analysed. Two aspects of the ensemble behaviour are considered: (a) the mean divergence of the ensemble members, indicating the general amplification of forecast uncertainty, and (b) the divergence of the best and worst members, indicating extremes in possible error-growth scenarios. To analyse the amplification of forecast uncertainty, a tendency equation for the ensemble variance of potential vorticity (PV) is derived and partitioned into …
Real-time weather forecasting in the Western Mediterranean Basin: An application of the RAMS model
2014
Abstract A regional forecasting system based on the Regional Atmospheric Modeling System (RAMS) is being run at the CEAM Foundation. The model is started twice daily with a forecast range of 72 h. For the period June 2007 to August 2010 the verification of the model has been done using a series of automatic meteorological stations from the CEAM network and located within the Valencia Region (Western Mediterranean Basin). Air temperature, relative humidity and wind speed and direction of the output of the model have been compared with observations. For these variables, an operational verification has been performed by computing different statistical scores for 18 weather stations. This verif…
Sources of water vapour contributing to the Elbe flood in August 2002-A tagging study in a mesoscale model
2009
In this study we investigate the contribution of various moisture sources to the Elbe flood that occurred in Central Europe during August 2002. An 8-day simulation with the mesoscale numerical weather prediction model CHRM, including newly implemented water vapour tracers, has been performed. According to the simulation, rather than drawing moisture from one single dominant source region, water vapour from widely separated moisture sources contributed to the extreme precipitation in the most affected area, notably at distinct, subsequent periods of time, and each in significant amounts. These moisture sources include the Atlantic and Mediterranean ocean areas inside the model domain, evapot…
Binary logistic regression versus stochastic gradient boosted decision trees in assessing landslide susceptibility for multiple-occurring landslide e…
2015
This study aims to compare binary logistic regression (BLR) and stochastic gradient treeboost (SGT) methods in assessing landslide susceptibility within the Mediterranean region for multiple-occurrence regional landslide events. A test area was selected in the north-eastern sector of Sicily (southern Italy) where thousands of debris flows and debris avalanches triggered on the first October 2009 due to an extreme storm. Exploiting the same set of predictors and the 2009 event landslide archive, BLR- and SGT-based susceptibility models have been obtained for the two catchments separately, adopting a random partition (RP) technique for validation. In addition, the models trained in one catchm…
Current and emerging developments in subseasonal to decadal prediction
2020
Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-…
Both attention and prediction are necessary for adaptive neuronal tuning in sensory processing
2014
International audience; The brain as a proactive system processes sensory information under the top-down influence of attention and prediction. However, the relation between attention and prediction remains undetermined given the conflation of these two mechanisms in the literature. To evaluate whether attention and prediction are dependent of each other, and if so, how these two top-down mechanisms may interact in sensory processing, we orthogonally manipulated attention and prediction in a target detection task. Participants were instructed to pay attention to one of two interleaved stimulus streams of predictable/unpredictable tone frequency. We found that attention and prediction intera…
Prior Precision Modulates the Minimization of Auditory Prediction Error
2019
International audience; The predictive coding model of perception proposes that successful representation of the perceptual world depends upon canceling out the discrepancy between prediction and sensory input (i.e., prediction error). Recent studies further suggest a distinction to be made between prediction error triggered by non-predicted stimuli of different prior precision (i.e., inverse variance). However, it is not fully understood how prediction error with different precision levels is minimized in the predictive process. Here, we conducted a magnetoencephalography (MEG) experiment which orthogonally manipulated prime-probe relation (for contextual precision) and stimulus repetition…