Csc_ADS_2011 - University of Minnesota
... General Circulation Models: Mathematical models with physical equations based on fluid dynamics Cell ...
... General Circulation Models: Mathematical models with physical equations based on fluid dynamics Cell ...
Climate Dynamics and Global Change
... records from areas minimally affected by urbanization, though urban heat island effects mayhave introduced errors on the order of 0.1°C. Ocean data are limited, and such data as are available have been "corrected" substantially (several tenths of a degree). In formingglobal averages, data have been ...
... records from areas minimally affected by urbanization, though urban heat island effects mayhave introduced errors on the order of 0.1°C. Ocean data are limited, and such data as are available have been "corrected" substantially (several tenths of a degree). In formingglobal averages, data have been ...
On the uncertainty of phenological responses to climate change
... structural uncertainty stems from different model assumptions and formulations, with different processes described differently by each model; model driver uncertainty is due to uncertainty in future climate scenarios used for ecological forecasts (Cook et al., 2010). Model-data fusion (e.g. Keenan e ...
... structural uncertainty stems from different model assumptions and formulations, with different processes described differently by each model; model driver uncertainty is due to uncertainty in future climate scenarios used for ecological forecasts (Cook et al., 2010). Model-data fusion (e.g. Keenan e ...
PowerPoint Presentation - Impact of Climate Change on Flow
... Streamflow is over-predicted in this basin by global models because of failure to resolve daily maximum temperatures in summer due to coarse resolution ...
... Streamflow is over-predicted in this basin by global models because of failure to resolve daily maximum temperatures in summer due to coarse resolution ...
Attribution of Weather and Climate-Related Extreme Events
... underlying the event and by asking how external anthropogenic and natural drivers have contributed to the probability of the event occurring, quantitative statements can be made about the role of different factors in contributing to the magnitude of and the probability of occurrence of individual ev ...
... underlying the event and by asking how external anthropogenic and natural drivers have contributed to the probability of the event occurring, quantitative statements can be made about the role of different factors in contributing to the magnitude of and the probability of occurrence of individual ev ...
Brownie, C., King, L. D., and Dube, T. J. (2004Longitudinal and Spatial Analyses Applied to Corn Yield Data from a Long-Term Rotation Trial,"
... variance across years; and C, a control model with iid errors. The models that allowed heterogeneity across years were preferred based on the Akaike Information Criterion (AIC). To select an appropriate analysis for the corn yield data from the long-term, reduced inputs, rotation trial, we consider ...
... variance across years; and C, a control model with iid errors. The models that allowed heterogeneity across years were preferred based on the Akaike Information Criterion (AIC). To select an appropriate analysis for the corn yield data from the long-term, reduced inputs, rotation trial, we consider ...
Impact of weather on commuter cyclist behaviour and implications
... Both Richardson (2000) and Phung and Rose (2007) explored how weather variations affect bicycle ridership in Melbourne, Australia. Rain was identified as the most influential weather parameter which significantly decreased commuting cyclist volumes. Both of these studies found that rainfall has a no ...
... Both Richardson (2000) and Phung and Rose (2007) explored how weather variations affect bicycle ridership in Melbourne, Australia. Rain was identified as the most influential weather parameter which significantly decreased commuting cyclist volumes. Both of these studies found that rainfall has a no ...
Northern African climate at the end of the twenty
... Hagos and Cook 2007) and for capturing land/atmosphere feedbacks (Patricola and Cook 2008). The horizontal resolution is finer than that of typical GCMs and provides information to aid impacts analysis on the regional scale. Integrations run for 231 days from March 15 to October 31 with the first 47 ...
... Hagos and Cook 2007) and for capturing land/atmosphere feedbacks (Patricola and Cook 2008). The horizontal resolution is finer than that of typical GCMs and provides information to aid impacts analysis on the regional scale. Integrations run for 231 days from March 15 to October 31 with the first 47 ...
Author - Princeton ISD
... (10) Expressions, equations, and relationships. The student applies mathematical process standards to use equations and inequalities to solve problems. The student is expected to: (A) model and solve one-variable, one-step equations and inequalities that represent problems, including geometric conce ...
... (10) Expressions, equations, and relationships. The student applies mathematical process standards to use equations and inequalities to solve problems. The student is expected to: (A) model and solve one-variable, one-step equations and inequalities that represent problems, including geometric conce ...
RaysWeather.Com 2016-2017 Winter Fearless Forecast
... While we have hinted at effects of Climate Change in our previous Fearless Forecasts, we have never specifically addressed that issue. First of all, climate change is real. If you are interested in a good source of scientific data and analysis on the subject, see http://climate.nasa.gov/evidence/. B ...
... While we have hinted at effects of Climate Change in our previous Fearless Forecasts, we have never specifically addressed that issue. First of all, climate change is real. If you are interested in a good source of scientific data and analysis on the subject, see http://climate.nasa.gov/evidence/. B ...
Silva2013-ERL-APMortality.pdf
... cancer (7%). These estimates are smaller than ones from previous studies because we use modeled 1850 air pollution rather than a counterfactual low concentration, and because of different emissions. Uncertainty in CRFs contributes more to overall uncertainty than the spread of model results. Mortali ...
... cancer (7%). These estimates are smaller than ones from previous studies because we use modeled 1850 air pollution rather than a counterfactual low concentration, and because of different emissions. Uncertainty in CRFs contributes more to overall uncertainty than the spread of model results. Mortali ...
Hybrid Computing Algorithm in Representing Solid Model
... Muhammad Matondang and Habibollah Haron Department of Modeling and Industrial Computing, Universiti Teknologi Malaysia, Malaysia Abstract: This paper presents an algorithm, which is a hybrid-computing algorithm in representing solid model. The proposed algorithm contains two steps namely reconstruct ...
... Muhammad Matondang and Habibollah Haron Department of Modeling and Industrial Computing, Universiti Teknologi Malaysia, Malaysia Abstract: This paper presents an algorithm, which is a hybrid-computing algorithm in representing solid model. The proposed algorithm contains two steps namely reconstruct ...
numerical methods in computational engineering
... A course in numerical analysis has become accepted as an important ingredient in the undergraduate education of engineers and scientists. Numerical Methods in Engineering and Science reflects experience in teaching such a course for several years. Related work in industry and research has influenced ...
... A course in numerical analysis has become accepted as an important ingredient in the undergraduate education of engineers and scientists. Numerical Methods in Engineering and Science reflects experience in teaching such a course for several years. Related work in industry and research has influenced ...
Here - Hydrol. Earth Syst. Sci.
... The need for downscaling is particularly urgent for mountainous regions. Mountain regions provide important environmental services, such as water supply for adjacent, drier lowlands (Viviroli et al., 2010), but they are also particularly fragile to environmental change. Many of the meteorological, h ...
... The need for downscaling is particularly urgent for mountainous regions. Mountain regions provide important environmental services, such as water supply for adjacent, drier lowlands (Viviroli et al., 2010), but they are also particularly fragile to environmental change. Many of the meteorological, h ...
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.