Evaluation of TIGGE Ensemble Forecasts of Precipitation in Distinct Climate Regions in Iran

The application of numerical weather prediction(NWP) products is increasing dramatically. Existing reports indicate that ensemble predictions have better skill than deterministic forecasts. In this study, numerical ensemble precipitation forecasts in the TIGGE database were evaluated using deterministic, dichotomous(yes/no), and probabilistic techniques over Iran for the period 2008–16. Thirteen rain gauges spread over eight homogeneous precipitation regimes were selected for evaluation.The Inverse Distance Weighting and Kriging methods were adopted for interpolation of the prediction values, downscaled to the stations at lead times of one to three days. To enhance the forecast quality, NWP values were post-processed via Bayesian Model Averaging. The results showed that ECMWF had better scores than other products. However, products of all centers underestimated precipitation in high precipitation regions while overestimating precipitation in other regions. This points to a systematic bias in forecasts and demands application of bias correction techniques. Based on dichotomous evaluation,NCEP did better at most stations, although all centers overpredicted the number of precipitation events. Compared to those of ECMWF and NCEP, UKMO yielded higher scores in mountainous regions, but performed poorly at other selected stations.Furthermore, the evaluations showed that all centers had better skill in wet than in dry seasons. The quality of post-processed predictions was better than those of the raw predictions. In conclusion, the accuracy of the NWP predictions made by the selected centers could be classified as medium over Iran, while post-processing of predictions is recommended to improve the quality.     

A continuum‐discrete model using Darcy's law: formulation and verification

This paper presents a numerical scheme for fluid‐particle coupled discrete element method (DEM), which is based on poro‐elasticity. The motion of the particles is resolved by means of DEM. While within the proposition of Darcian regime, the fluid is assumed as a continuum phase on a Eulerian mesh, and the continuity equation on the fluid mesh for a compressible fluid is solved using the FEM. Analytical solutions of traditional soil mechanics examples, such as the isotropic compression and one‐dimensional upward seepage flow, were used to validate the proposed algorithm quantitatively. The numerical results showed very good agreement with the analytical solutions, which show the correctness of this algorithm. Sensitivity studies on the effect of some influential factors of the coupling scheme such as pore fluid bulk modulus, volumetric strain calculation, and fluid mesh size were performed to display the accuracy, efficiency, and robustness of the numerical algorithm. It is revealed that the pore fluid bulk modulus is a critical parameter that can affect the accuracy of the results. Because of the iterative coupling scheme of these algorithms, high value of fluid bulk modulus can result in instability and consequently reduction in the maximum possible time‐step. Furthermore, the increase of the fluid mesh size reduces the accuracy of the calculated pore pressure. This study enhances our current understanding of the capacity of fluid‐particle coupled DEM to simulate the mechanical behavior of saturated granular materials. Copyright © 2014 John Wiley & Sons, Ltd.     

Event in the case of a single reservoir: the Ghèzala dam in Northern Tunisia

The paper focuses on the development of reservoir operating rules for dry and rainfall events, and their implementation in the case of the Ghézala dam located in northern Tunisia (characterized by Mediterranean climate). Rainfall events are defined in terms of depth and duration that are correlated to each other. A depth analysis per event is performed, conditioned on the event duration. The gamma distribution provides a good fit to depth per event, especially for events lasting at least 6 days. The event duration fits a geometric distribution, whereas the dry events during the rainy season fit a negative binomial distribution. The climatic cycle length is fitted to a gamma distribution. On this basis, many 50-year synthetic event series were generated. Every synthetic streamflow sequence obtained from synthetic rainfall sequences as well as the one derived from the historic rainfall events time series were optimized and optimal decisions were formulated. These decisions were assessed by means of multiple regression analysis to estimate the relation between the optimal decision to every stage (dry or rainfall event) and other system variables. Optimal rules, which have a linear form, were derived by predetermined useful storage interval and depend on storage, inflows and downstream demand at dry or rainfall event t. The range of t is 1–13 days (rainfall event) and 1–57 days (dry event). The rules were satisfactory for every predetermined useful storage interval. The simulated dam performance generated by the operation rules was compared with the deterministic optimum operation and the historical operation. Also included is the comparison of the implicit stochastic optimization-based operation policy per event during the water years 1985–2002.

Discovery of antler from a new site in the Pinjor Formation (Pleistocene) of Pakistan

Partially complete right antler from the Pinjor Formation (Pleistocene) of the Upper Siwalik Subgroup is identified, described and its phylogenetic relationship is discussed. The fossil antler is compared with other known fossil records of family Cervidae as well as with the extant species, on the basis of which it can be attributed to Axis punjabiensis. This species has not been reported previously from this fossil site.