Statistical downscaling of future climate change scenarios onto
... circulation pattern (‘Trade wind’, ’Kona Low’ pattern) ...
... circulation pattern (‘Trade wind’, ’Kona Low’ pattern) ...
20100921144515309-152610
... • For 11 of the 17 atmosphere fully coupled oceanatmosphere runs, use 6-hourly boundary conditions to drive 25km regional climate model for ...
... • For 11 of the 17 atmosphere fully coupled oceanatmosphere runs, use 6-hourly boundary conditions to drive 25km regional climate model for ...
Additional Reading Notes (WORD document)
... c. Feedbacks 3 and 4 in the WORD document are very important. Changes in water vapor and clouds are not well understood and certainly not handled well in climate models. The reason this is so important is that most climate models have an overall positive feedback in response to adding greenhouse gas ...
... c. Feedbacks 3 and 4 in the WORD document are very important. Changes in water vapor and clouds are not well understood and certainly not handled well in climate models. The reason this is so important is that most climate models have an overall positive feedback in response to adding greenhouse gas ...
Guest lecture - Department of Mathematics & Statistics | McMaster
... • “Figure 2 shows such a pattern, obtained in a few hours by a manual computation …” • “The outlines of the black patches are somewhat less irregular than they should be due to an inadequacy in the computation procedure” ...
... • “Figure 2 shows such a pattern, obtained in a few hours by a manual computation …” • “The outlines of the black patches are somewhat less irregular than they should be due to an inadequacy in the computation procedure” ...
Stratospheric and tropospheric SSU/MSU temperature
... years in a “historical” climate simulation will rarely (and only by chance) coincide with years when El Niños have actually occurred. This is because the historical runs are initiated from an arbitrary point of a quasi-equilibrium control run, so internal variations (even if they were perfectly pred ...
... years in a “historical” climate simulation will rarely (and only by chance) coincide with years when El Niños have actually occurred. This is because the historical runs are initiated from an arbitrary point of a quasi-equilibrium control run, so internal variations (even if they were perfectly pred ...
slides - NIMML
... different result, drawn from the joint distribution • Estimating the joint distribution itself is not feasible • Statistics of the joint distribution can be estimated from many samples ...
... different result, drawn from the joint distribution • Estimating the joint distribution itself is not feasible • Statistics of the joint distribution can be estimated from many samples ...
DEB theory
... Originates from physics, where e stands for measurement error Problem: deviations from model are frequently not measurement errors Alternatives: • deterministic systems with stochastic inputs • differences in parameter values between individuals Problem: parameter estimation methods become very comp ...
... Originates from physics, where e stands for measurement error Problem: deviations from model are frequently not measurement errors Alternatives: • deterministic systems with stochastic inputs • differences in parameter values between individuals Problem: parameter estimation methods become very comp ...
biomechanical approach for force analysis of human body
... Models are conceptual constructions which allow formulation and testing of hypothesis. A mathematical model attempts to duplicate the quantitative behavior of the system. Mathematical models are used in today’s scientific and technological world due to the ease with which they can be used to analyze ...
... Models are conceptual constructions which allow formulation and testing of hypothesis. A mathematical model attempts to duplicate the quantitative behavior of the system. Mathematical models are used in today’s scientific and technological world due to the ease with which they can be used to analyze ...
Atmospheric, Oceanic and Planetary Physics
... >300,000 volunteers, >140 countries, >41M model-years ...
... >300,000 volunteers, >140 countries, >41M model-years ...
Global climate models, past, present and future
... Major progress in our understanding of climate processes in past, present and future has been made by the development of numerical models that simulate climate at an increasing level of detail. Recent breakthroughs in spatial coverage and temporal resolutions of systems recording today’s climate (3) ...
... Major progress in our understanding of climate processes in past, present and future has been made by the development of numerical models that simulate climate at an increasing level of detail. Recent breakthroughs in spatial coverage and temporal resolutions of systems recording today’s climate (3) ...
Recent Advances in the Modelling of Renal Function
... complete understanding of hypertonic urine formation. Recent advances in this field include the treatment of a kidney model as an inverse prob lern, the modelling of the three-dimensional Organization of the renal medulla, and dynamic models for the tubuloglomerular feedback mechanism. The latter ma ...
... complete understanding of hypertonic urine formation. Recent advances in this field include the treatment of a kidney model as an inverse prob lern, the modelling of the three-dimensional Organization of the renal medulla, and dynamic models for the tubuloglomerular feedback mechanism. The latter ma ...
NUMERICAL EXPERIMENTS ON THE SPIN UP TIME FOR
... effect of spin-up time on the regional climate simulation results for such an abnormal climate event in summer, a total of 11 experiments were performed with different spin-up time from 10 days to 6 months, respectively. The simulation results show that, for meteorological variables in the atmospher ...
... effect of spin-up time on the regional climate simulation results for such an abnormal climate event in summer, a total of 11 experiments were performed with different spin-up time from 10 days to 6 months, respectively. The simulation results show that, for meteorological variables in the atmospher ...
WGCM Chemistry - Earth, Atmospheric, and Planetary Physics
... • Regression includes terms representing equivalent effective stratospheric chlorine (EESC) and 11-year solar cycle variability. • Extended backwards to 1850 based on the regression fits combined with extended proxy times series of EESC and solar variability. 2. Tropospheric data (3D but decadal ave ...
... • Regression includes terms representing equivalent effective stratospheric chlorine (EESC) and 11-year solar cycle variability. • Extended backwards to 1850 based on the regression fits combined with extended proxy times series of EESC and solar variability. 2. Tropospheric data (3D but decadal ave ...
Numerical weather prediction
Numerical weather prediction uses mathematical models of the atmosphere and oceans to predict the weather based on current weather conditions. Though first attempted in the 1920s, it was not until the advent of computer simulation in the 1950s that numerical weather predictions produced realistic results. A number of global and regional forecast models are run in different countries worldwide, using current weather observations relayed from radiosondes, weather satellites and other observing systems as inputs.Mathematical models based on the same physical principles can be used to generate either short-term weather forecasts or longer-term climate predictions; the latter are widely applied for understanding and projecting climate change. The improvements made to regional models have allowed for significant improvements in tropical cyclone track and air quality forecasts; however, atmospheric models perform poorly at handling processes that occur in a relatively constricted area, such as wildfires.Manipulating the vast datasets and performing the complex calculations necessary to modern numerical weather prediction requires some of the most powerful supercomputers in the world. Even with the increasing power of supercomputers, the forecast skill of numerical weather models extends to about only six days. Factors affecting the accuracy of numerical predictions include the density and quality of observations used as input to the forecasts, along with deficiencies in the numerical models themselves. Post-processing techniques such as model output statistics (MOS) have been developed to improve the handling of errors in numerical predictions.A more fundamental problem lies in the chaotic nature of the partial differential equations that govern the atmosphere. It is impossible to solve these equations exactly, and small errors grow with time (doubling about every five days). Present understanding is that this chaotic behavior limits accurate forecasts to about 14 days even with perfectly accurate input data and a flawless model. In addition, the partial differential equations used in the model need to be supplemented with parameterizations for solar radiation, moist processes (clouds and precipitation), heat exchange, soil, vegetation, surface water, and the effects of terrain. In an effort to quantify the large amount of inherent uncertainty remaining in numerical predictions, ensemble forecasts have been used since the 1990s to help gauge the confidence in the forecast, and to obtain useful results farther into the future than otherwise possible. This approach analyzes multiple forecasts created with an individual forecast model or multiple models.