Search

This article evaluates the ability of the Coordinated Regional Downscaling Experiment ( CORDEX) regional climate models ( RCMs) in simulating monthly rainfall variation during the austral summer half year (October to March) over southern Africa, the timing of the rainy season and the relative frequencies of rainfall events of varying intensities. The phasing and amplitude of monthly rainfall evolution and the spatial progression of the wet season onset are well simulated by the models. Notwithstanding some systematic biases in a few models, the simulated onset and end of the rainy season and their interannual variability are highly correlated with those computed from the reference data. The strongest agreements between the reference and modelled precipitation patterns are found north of about 20°S in the vicinity of the Inter Tropical Convergence Zone. A majority of the RCMs adequately capture the reference precipitation probability density functions, with a few showing a bias towards excessive light rainfall events. [ABSTRACT FROM AUTHOR]

Forensic biometrics is the application of forensic science principles to physical and behavioral characteristics. Forensic biometrics is a secondary sub‐system in the forensic science "system of systems," which describes forensic science as a sub‐system in the larger criminal justice, law enforcement, intelligence, and military system. The purpose of this paper is to discuss biometrics in the military domain and integration into the wider forensic science system of systems. The holistic system thinking methodology was applied to the U.S. biometric system to map it to the system of systems framework. The U.S. biometric system is used as a case study to help guide other countries to develop military biometric systems that are integrated and interoperable at the whole‐of‐government level. The aim is to provide the system of systems framework for agencies to consider for proactive design of biometric systems. [ABSTRACT FROM AUTHOR]

ABSTRACT A comprehensive analysis of near surface (10-m and 850 hPa) long-term (1980-2015) austral summer mean wind speed trends over southern Africa and the surrounding oceans (10°-40°S and 10°W-50°E) is carried out. The climate forecast system reanalysis and the climate forecast system reanalysis version 2, the modern era retrospective-analysis for research and applications version 2, and the ERA-Interim products are used for the analysis. Trends are estimated using the Theil-Sen slope estimator and their significance tested with the Mann-Kendall test. Attribution of the wind speed trends to large scale circulation systems is determined from: (1) trends in 850 hPa geopotential height, surface pressure, and surface skin temperatures, (2) changes in the annual frequency of archetypal synoptic states generated by self-organizing maps from geopotential height data, and (3) the correlations of the wind speeds to the southern annular mode ( SAM) and El Niño Southern Oscillations ( ENSO) indices. There is an overall decline in wind speeds evident in all the reanalyses. Wind speeds reduce by an average 0.7 and 1.3 m s−1 at 10 m and 850 hPa, respectively, over the study period. Deceleration in midlatitude westerly and Atlantic south easterly winds are associated with a poleward shift in the subtropical anticyclone, a positive trend in the annual frequency of summer circulation weather types, and the weakening of the subtropical continental heat low. The SAM and ENSO are also found to have a statistically significant linear association with the observed wind speed trends. [ABSTRACT FROM AUTHOR]

ABSTRACT This study evaluates the capability of regional climate models ( RCMs) in simulating extreme rainfall events over Southern Africa, and in reproducing the characteristics of widespread extreme rainfall events ( WERE) in the Western Cape (South Africa). We obtained simulation datasets of nine RCMs from the Co-ordinated Regional Downscaling Experiment ( CORDEX) and compared them with observation datasets from the Global Precipitation Climatology Project ( GPCP) and Tropical Rainfall Measuring Mission ( TRMM) as well as with the reanalysis dataset ( ERAINT) that forced the simulations. A self-organising map was used to classify the WEREs into 12 nodes. The contribution of each RCM to each node was compared with the contributions of GPCP, TRMM and ERAINT. Using ERAINT dataset, we analysed the synoptic-scale atmospheric condition associated with each node. The results show that, in simulating the spatial distribution of the extreme rainfall event over Southern Africa, only four RCMs perform better than the forcing reanalysis ( ERAINT) while two RCMs perform worse than the reanalysis. All the RCMs underestimate the threshold of extreme rainfall over Western Cape, poorly simulate the inter-annual variability of the WEREs ( r ≤ 0.3), but correctly reproduce the maximum frequency of the WEREs in Autumn (March-May). The WEREs in the Western Cape may be broadly grouped into four synoptic rainfall patterns. The first pattern links WEREs with tropical rainfall activities (tropical-temperate troughs); the second pattern shows isolated WEREs; the third and fourth patterns link WEREs with rainfall activities in the mid-latitudes (frontal systems) and over the Agulhas Current, respectively. While most RCMs overestimate the frequency of the first pattern, they all underestimate the frequency of the second pattern but simulate the frequencies of the third and fourth patterns well. The results of this study should help in improving the RCM simulations over Southern Africa and in downscaling impacts of climate change on extreme rainfall events over the region. [ABSTRACT FROM AUTHOR]

We compare ensemble mean daily precipitation and near‐surface temperatures from regional climate model simulations over seven Coordinated Regional Climate Downscaling Experiment domains for the winter and summer seasons. We use Taylor diagrams to show the domain‐wide pattern similarity between the model ensemble and the observational data sets. We use the Climatic Research Unit (CRU) and the University of Delaware gridded observations and ERA‐Interim reanalysis data as an additional observationally based estimate of historical climatology. Taylor diagrams determine the relative skill of the seven sets of simulations and quantify these results in terms of center pattern root‐mean square error and correlation coefficient. Results suggest that there is good agreement between the models and the CRU, in terms of their respective seasonal cycles, as shown in Taylor diagrams and bias plots. There is also good agreement between both gridded observation sets. In addition, downscaled ERA‐Interim precipitation is closer to observations than raw ERA‐Interim precipitation. Domains located in the low latitudes and those having high topography appear to have larger biases, especially precipitation. [ABSTRACT FROM AUTHOR]