Evaluation of uncertainties in regional climate change simulations

We have run two regional climate models (RCMs) forced by three sets of initial and boundary conditions to form a 2×3 suite of 10-year climate simulations for the continental United States at approximately 50 km horizontal resolution. The three sets of driving boundary conditions are a reanalysis, an atmosphere-ocean coupled general circulation model (GCM) current climate, and a future scenario of transient climate change. Common precipitation climatology features simulated by both models included realistic orographic precipitation, east-west transcontinental gradients, and reasonable annual cycles over different geographic locations. However, both models missed heavy cool-season precipitation in the lower Mississippi River basin, a seemingly common model defect. Various simulation biases (differences) produced by the RCMs are evaluated based on the 2×3 experiment set in addition to comparisons with the GCM simulation. The RCM performance bias is smallest, whereas the GCM-RCM downscaling bias (difference between GCM and RCM) is largest. The boundary forcing bias (difference between GCM current climate driven run and reanalysis-driven run) and intermodel bias are both largest in summer, possibly due to different subgrid scale processes in individual models. The ratio of climate change to biases, which we use as one measure of confidence in projected climate changes, is substantially larger than 1 in several seasons and regions while the ratios are always less than 1 in summer. The largest ratios among all regions are in California. Spatial correlation coefficients of precipitation were computed between simulation pairs in the 2×3 set. The climate change correlation is highest and the RCM performance correlation is lowest while boundary forcing and intermodel correlations are intermediate. The high spatial correlation for climate change suggests that even though future precipitation is projected to increase, its overall continental-scale spatial pattern is expected to remain relatively constant. The low RCM performance correlation shows a modeling challenge to reproduce observed spatial precipitation patterns

Improved SPH simulation of spilled oil contained by flexible floating boom under wave-current coupling condition

A multi-phase Smoothed Particle Hydrodynamics (SPH) method is developed to model the failure process of a flexible oil boom. An algorithm is proposed based on the dynamic boundary particles (DBPs) for preventing the particle disorders during the multi-fluid particle movement around the solid boundary. The improved multi-phase SPH model is firstly validated by the experimental data of a wedge falling into a two-layer oil-water fluid. Then a numerical wave-current flume is established with an active absorbing piston-type wave generator and a circulating current system. The model reliability is validated against the measured vertical profiles of velocity. Simulation of the flexible floating boom movement is implemented by introducing a Rigid Module and Flexible Connector (RMFC) multi-body system. The model is finally applied to the simulation of movement of a flexible floating boom in containing industrial gear oil under the combined waves and currents. Good agreements are obtained between the SPH modeling results and the experimental data in terms of the ambient wave-current field, hydrodynamic responses of the floating body and evolution process of the oil slick for the flexible boom. The hydrodynamic responses and containment performances of the flexible floating boom are also compared with those of the rigid one. It is found from both the experimental and numerical results that two vortices of the water phase exist in the front and rear of the boom skirt and the size of the front vortex decreases with an increase of the current velocity while the wake vortex is reversed. It is also found that the skirt of the flexible boom has a larger magnitude of the swaying and rolling than the rigid one and the maximum quantity of the escaped oil of a flexible boom within one wave cycle is about 5% more than a rigid one under the present test conditions

An Evaluation Method for Tornado Missile Strike Probability with Stochastic Correlation

An efficient evaluation method for the probability of a tornado missile strike without using the Monte Carlo method is proposed in this paper. A major part of the proposed probability evaluation is based on numerical results computed using an in-house code, Tornado-borne missile analysis code, which enables us to evaluate the liftoff and flight behaviors of unconstrained objects on the ground driven by a tornado. Using the Tornado-borne missile analysis code, we can obtain a stochastic correlation between local wind speed and flight distance of each object, and this stochastic correlation is used to evaluate the conditional strike probability, QV(r), of a missile located at position r, where the local wind speed is V. In contrast, the annual exceedance probability of local wind speed, which can be computed using a tornado hazard analysis code, is used to derive the probability density function, p(V). Then, we finally obtain the annual probability of tornado missile strike on a structure with the convolutional integration of product of QV(r) and p(V) over V. The evaluation method is applied to a simple problem to qualitatively confirm the validity, and to quantitatively verify the results for two extreme cases in which an object is located just in the vicinity of or far away from the structure

Performance of RegCM2.5/NCAR-CSM nested system for the simulation of climate change in East Asia caused by global warming

Regional climate in East Asia under 1CO2 and 2CO2 conditions, was simulated for continuous 10-year periods by the RegCM2.5 developed by NCAR, using the output of a CO2 transient run from NCAR-CSM as lateral and surface boundary conditions in order to evaluate the performance of the nested system for the use of climate change simulation caused by global warming for that region. In this study, January and June climates were analyzed. Through the validation of the simulated present climate, it was clarified that the typical precipitation phenomenon which occurs on the northwestern side of Japan during the winter monsoon is relatively well reproduced in the RegCM, but weakly in the CSM. It indicates that the RegCM is essential for the prediction of regional climate change for the East Asia region. Although the present climate reproduced by the RegCM has some marked biases, e.g. the large cold bias in the higher latitude in winter and the missing of the Bai-u front in mainland China, they are mainly due to the overstimation of sea ice area, and the northward shift of the NPH (North Pacific High) in the CSM, respectively. The SST bias in the CSM significantly contributes to the surface air temperature bias on the coast. In the climate change simulations, the large-scale distributions of SLP and temperature in the RegCM bear a resemblance to those of the CSM in both months. On the other hand, the regional scale precipitation change patterns are different between the RegCM and the CSM in June, because the precipitation band near Japan is well reproduced in the RegCM both in the 1CO2 and the 2CO2 climate. In this simulation, some notable climate change features are found, such as the temperature increase at higher latitudes in January, or intensification of the NPH extending to the southwest in June. Although these changes are statistically significant, they are mainly influenced by the bias in the CSM because the changes occur over the bias region, and their magnitudes do not necessarily exceed the bias of the simulated present climate. From these results, it should be stressed that it is of utmost importance that the AOGCM information is of good quality in the prediction of regional climate change