Electric sector investments under technological and policy-related uncertainties: a stochastic programming approach

Although emerging technologies like carbon capture and storage and advanced nuclear are expected to play leading roles in greenhouse gas mitigation efforts, many engineering and policy-related uncertainties will influence their deployment. Capital-intensive infrastructure decisions depend on understanding the likelihoods and impacts of uncertainties such as the timing and stringency of climate policy as well as the technological availability of carbon capture systems. This paper demonstrates the utility of stochastic programming approaches to uncertainty analysis within a practical policy setting, using uncertainties in the US electric sector as motivating examples. We describe the potential utility of this framework for energy-environmental decision making and use a modeling example to reinforce these points and to stress the need for new tools to better exploit the full range of benefits the stochastic programming approach can provide. Model results illustrate how this framework can give important insights about hedging strategies to reduce risks associated with high compliance costs for tight CO₂ caps and low CCS availability. Metrics for evaluating uncertainties like the expected value of perfect information and the value of the stochastic solution quantify the importance of including uncertainties in capacity planning, of making precautionary low-carbon investments, and of conducting research and gathering information to reduce risk.     

On calculation of wind speed in tornado

A formula is obtained for calculation of wind speed in tornado, as proportional to the speed of convective updraft. Results are presented of wind speed calculation using the formula for 57 tornadoes observed at different time and in different regions of the world. Possibilities are shown of tornado wind speed forecasting taking into account criteria of tornado danger of the Cb clouds.     

Stability functions based upon shear functions

The stability functions for momentum and heat under a Richardson number formulation are derived from the nondimensional shear functions under a Monin-Obukhov formulation. The Prandtl number is also derived as a function of the Richardson number. Previously, this has been done only in a limited sense. Because the Richardson number formulation is expressed in closed form, iterative techniques are no longer needed in numerical models that use Monin-Obukhov similarity theory. This time-saving approach is made possible by deriving expressions for the friction velocity and temperature in terms of the Richardson-number-dependent stability functions. In addition, the Richardson number approximation in the lowest layer is made to depend explicitly upon the surface roughness.     

Airborne radar and in-situ observations of a shallow stratus with drizzle

Observations were made of a shallow stratus of upslope origin using an aircraft equipped with insitu probes and with a vertically-pointing radar of 3-mm wavelength. A cloud layer of 300 m thickness was found below the inversion; an additional layer of 100 m thickness was located within the inversion. The coldest temperature within the cloud was -2°C and the cloud contained no ice particles. Drizzle drops up to 180 Am were present in both cloud layers.The observations reveal precipitation and air motion structures of approximately 1 km horizontal dimensions. The origin of this organization appears to be weak convection. In addition, mixing played an important role in forming the cloud droplet and drizzle drop size distributions.