Reply: For physical models, like global and regional climate models, the grid spacing used for the simulation can affect the total precipitation volume over a region. This results mainly from terrain effects. With finer grid spacing, the mountain ranges are better resolved, which produces more intense precipitation over the domain. This is a reason why regional models, especially those run at r...

This paper values the option of a firm to downscale production in recessionary times. The regulator allows downscaling as long as the recession lasts. The end of the recession is modelled via a Poisson process. We show that the disinvestment timing is affected by two contrary effects. First, when the probability increases that the recession will be over soon, the firm will disinvest sooner, bec...

This work aims at introducing model methodology and numerical studies related to a Lagrangian stochastic approach applied to the computation of the wind circulation around mills. We adapt the Lagrangian stochastic downscaling method that we have introduced in [3] and [4] to the atmospheric boundary layer and we introduce here a Lagrangian version of the actuator disc methods to take account of ...

This paper1 reports on two experiments with a Talking Head that explore the ability of eyebrow movements to cue focus. The first experiment tests how listeners react to synthetic stimuli in which the eyebrow movements coincide with pitch accents versus those in which these two occur on different words. Results show that subjects prefer those utterances in which pitch and eyebrow movements are a...

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The 46km Livingstone Creek Catchment in south-eastern Australia was flown with a passive microwave airborne remote sensor (Polarimetric L-band Multibeam Radiometer, PLMR) as part of the National Airborne Field Experiment in 2006 with a spatial resolution of ~ 200m. The catchment was experiencing extreme drought conditions leading up to the experiment and as a result ground cover in the catchmen...

We investigated the usability of the method of local linear models (LLM), multilayer perceptron neural network (MLP NN) and radial basis function neural network (RBF NN) for the construction of temporal and spatial transfer functions between different meteorological quantities, and compared the obtained results both mutually and to the results of multiple linear regression (MLR). The tested met...

Local studies aimed at assessing the impact of climate variability on crop yield at the individual farm level require the use of weather and climate data. These are often collected at points known as meteorological stations. In West Africa, meteorological stations are sparsely distributed and as a result, are often unable to satisfy the data requirements for such studies. One major problem aris...

Accurate precipitation data at a high spatial resolution are essential for hydrological, meteorological, and ecological research at regional scales. This study presented a geostatistical downscaling-calibration procedure to derive the high spatial resolution maps of precipitation over a mountainous watershed affected by a monsoon climate. Based on the relationships between precipitation and oth...

25 Sixteen global general circulation models were used to develop probabilistic projections of 26 temperature (T) and precipitation (P) changes over California by the 2060s. The global models 27 were downscaled with two statistical techniques and three nested dynamical regional climate 28 models, although not all global models were downscaled with all techniques. Both monthly and 29 daily times...