Projected river discharge in the Euphrates Tigris Basin
... runoff outputs of 2 global climate models (GCMs) (the SRES A1B scenario simulation of ECHAM5/MPIOM and the RCP 4.5 scenario simulation of MPI-ESM-LR) and the dynamically downscaled outputs of ECHAM5/MPIOM and NCAR-CCSM3 scenario (SRES A1FI, A2 and B1) simulations. The suite of simulations enables a ...
... runoff outputs of 2 global climate models (GCMs) (the SRES A1B scenario simulation of ECHAM5/MPIOM and the RCP 4.5 scenario simulation of MPI-ESM-LR) and the dynamically downscaled outputs of ECHAM5/MPIOM and NCAR-CCSM3 scenario (SRES A1FI, A2 and B1) simulations. The suite of simulations enables a ...
Future Emissions and Concentrations of Carbon Dioxide
... Model Q in ‘Release 1’ were an earlier ‘ocean-only’ case, and the ocean differed slightly from the form used for later versions; and Model R denoted the version of IMAGE-2 with CO2 -climate feedback (subsequently denoted R ). Draft release 2. This was released to IPCC lead authors for comment and a ...
... Model Q in ‘Release 1’ were an earlier ‘ocean-only’ case, and the ocean differed slightly from the form used for later versions; and Model R denoted the version of IMAGE-2 with CO2 -climate feedback (subsequently denoted R ). Draft release 2. This was released to IPCC lead authors for comment and a ...
Improving Societal Outcomes of Extreme Weather in a Changing
... Closely related hazards include landslides and wildfires. Some of these are extremes in weather variables, such as precipitation amount and high and low temperature, measured for a specified period of time and location. Others, such as tornados, tropical cyclones, and droughts, are phenomena that exte ...
... Closely related hazards include landslides and wildfires. Some of these are extremes in weather variables, such as precipitation amount and high and low temperature, measured for a specified period of time and location. Others, such as tornados, tropical cyclones, and droughts, are phenomena that exte ...
How much do precipitation extremes change in a warming
... [8] Besides the well-known model deficiencies in simulating convection that could lead to models’ underestimation of heavy precipitation changes under global warming conditions, there are other aspects that could contribute to the large difference between the results of Sun et al. [2007] and Liu et ...
... [8] Besides the well-known model deficiencies in simulating convection that could lead to models’ underestimation of heavy precipitation changes under global warming conditions, there are other aspects that could contribute to the large difference between the results of Sun et al. [2007] and Liu et ...
draft for USGS Review - UAF SNAP
... of climate change on landscape structure and function. There are two different methods used to couple the models in the IEM, linear and cyclical (Figure 2-3). The first method, referred to as linear or asynchronous coupling, allows for the exchange of information between models to occur in series. F ...
... of climate change on landscape structure and function. There are two different methods used to couple the models in the IEM, linear and cyclical (Figure 2-3). The first method, referred to as linear or asynchronous coupling, allows for the exchange of information between models to occur in series. F ...
Climate change in Australia | Monsoonal North cluster report
... scenario and also show the range of natural variability for a given climate. Greenhouse gas concentrations are similar amongst different RCPs for the near future, and for some variables, such as rainfall, the largest range in that period stems from natural variability. Later in the century, the diff ...
... scenario and also show the range of natural variability for a given climate. Greenhouse gas concentrations are similar amongst different RCPs for the near future, and for some variables, such as rainfall, the largest range in that period stems from natural variability. Later in the century, the diff ...
Adapting to the Weather: Lessons from U.S. History Hoyt Bleakley
... global warming on U.S. agriculture than did the traditional production-function approach. Although the newly-developed method and findings have influenced later researches on climate change, the study does not actually observe the adaptation to climate or dynamic adjustment because of cross-sectiona ...
... global warming on U.S. agriculture than did the traditional production-function approach. Although the newly-developed method and findings have influenced later researches on climate change, the study does not actually observe the adaptation to climate or dynamic adjustment because of cross-sectiona ...
JDEP384hLecture18.pdf
... Now iterate on x Notation: spectral radius of matrix G is ρ (G ), the maximum absolute value of any eigenvalue of G . Key Theorem: If ρ (G ) < 1, or ρ (G ) = 1 with exactly one First write ...
... Now iterate on x Notation: spectral radius of matrix G is ρ (G ), the maximum absolute value of any eigenvalue of G . Key Theorem: If ρ (G ) < 1, or ρ (G ) = 1 with exactly one First write ...
Weather, Traffic Accidents, and Climate Change
... our predictions. While we do not find any evidence of adaptation between climate zones or over time, there is the possibility that adaptation or migration may reduce these magnitudes. Nevertheless, because accident costs have a large external component, it is likely that optimal response will requir ...
... our predictions. While we do not find any evidence of adaptation between climate zones or over time, there is the possibility that adaptation or migration may reduce these magnitudes. Nevertheless, because accident costs have a large external component, it is likely that optimal response will requir ...
The coupled atmosphere–chemistry–ocean model SOCOL
... S. Muthers et al.: SOCOL-MPIOM pressure, humidity and cloud water as prognostic variables (Roeckner et al., 2003, 2006; Manzini et al., 2006). In the vertical dimension a hybrid sigma-pressure coordinate system is used. The short-wave (SW) radiation code originates from the European Centre of Mediu ...
... S. Muthers et al.: SOCOL-MPIOM pressure, humidity and cloud water as prognostic variables (Roeckner et al., 2003, 2006; Manzini et al., 2006). In the vertical dimension a hybrid sigma-pressure coordinate system is used. The short-wave (SW) radiation code originates from the European Centre of Mediu ...
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.