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The complexity and isomerization of communication networks have put forth new requirements for cryptographic schemes to ensure the operation of network security protocols. Robust cryptographic schemes have been gradually favored. The robust initialization vector (RIV) instead of the synthetic initialization vector (SIV) was first introduced to support strong security and robust authenticated encryption. This paper first introduces RIV to GCM-SIV1, proposes a robust variant, GCM-RIV1, and proves that it ensures birthday-bound subtle AE (SAE) security and nonce-misuse resistance. Then, to support beyond-birthday-bound (BBB) security with graceful degradation, we introduce another, stronger security variant, GCM-RIV2, and prove that it allows gracefully degrading BBB SAE security in the faulty nonce setting. Finally, the performance of GCM-RIV1 and GCM-RIV2 is discussed and compared. [ABSTRACT FROM AUTHOR]

Though evolutionists routinely assume universal common descent of life, observational evidence militates against this unsubstantiated belief. In contrast, creationists recognize limited common descent where originally created kinds of organisms have reproduced to fill the earth. As they have done so, there has been considerable diversification and adaptation, though not enough to transmute them into a fundamentally different type of organism (e.g., from a rodent to a bat). Organisms that are not related by common descent can be recognized by significant holistic discontinuity between them. In this paper we begin an investigation of ruminants (Ruminantia), members of the order Artiodactyla, to determine if there is significant discontinuity between them and other species within this order. In this first paper, two molecular baraminology techniques were applied to available data to determine the relationship of ruminants to other artiodactyls. The results support the hypothesis that ruminants do not share common ancestry with other artiodactyls. [ABSTRACT FROM AUTHOR]

Modelling rainfall extremes and dry periods over the Southeast Asia (SEA) region is challenging due to the characteristics of the region, which consists of the Maritime Continent and a mountainous region; it also experiences monsoonal conditions, as it is located between the Asian summer monsoon and the Australian summer monsoon. Representing rainfall extremes is important for flood and drought assessments in the region. This paper evaluates extreme rainfall climatic indices from regional climate models from CORDEX Southeast Asia and compares them with the results of high‐resolution global climate models with a comparable spatial resolution from the HighResMIP experiment. Observations indicate a high intensity of rainfall over areas affected by tropical cyclones and long consecutive dry day periods over some areas in Indochina and the southern end of Indonesia. In the model simulations, we find that both coupled and sea surface temperature‐forced HighResMIP model experiments are more similar to the observations than CORDEX model results. However, the models produce a poorer simulation of precipitation intensity‐related indices due to model biases in the rainfall intensity. This bias is higher in CORDEX than in HighResMIP and is evident in both the low‐ and high‐resolution HighResMIP model versions. The comparable performances of HighResSST (atmosphere‐only runs) and Hist‐1950 (coupled ocean–atmosphere runs) demonstrate the accuracy of the ocean model. Comparable performances were also found for the two different resolutions of HighResMIP, suggesting that there is no improvement in the performance of the high‐resolution HighResMIP model compared to the low‐resolution HighResMIP model. [ABSTRACT FROM AUTHOR]

Modelling rainfall extremes and dry periods over the Southeast Asia (SEA) region is challenging due to the characteristics of the region, which consists of the Maritime Continent and a mountainous region; it also experiences monsoonal conditions, as it is located between the Asian summer monsoon and the Australian summer monsoon. Representing rainfall extremes is important for flood and drought assessments in the region. This paper evaluates extreme rainfall climatic indices from regional climate models from CORDEX Southeast Asia and compares them with the results of high‐resolution global climate models with a comparable spatial resolution from the HighResMIP experiment. Observations indicate a high intensity of rainfall over areas affected by tropical cyclones and long consecutive dry day periods over some areas in Indochina and the southern end of Indonesia. In the model simulations, we find that both coupled and sea surface temperature‐forced HighResMIP model experiments are more similar to the observations than CORDEX model results. However, the models produce a poorer simulation of precipitation intensity‐related indices due to model biases in the rainfall intensity. This bias is higher in CORDEX than in HighResMIP and is evident in both the low‐ and high‐resolution HighResMIP model versions. The comparable performances of HighResSST (atmosphere‐only runs) and Hist‐1950 (coupled ocean–atmosphere runs) demonstrate the accuracy of the ocean model. Comparable performances were also found for the two different resolutions of HighResMIP, suggesting that there is no improvement in the performance of the high‐resolution HighResMIP model compared to the low‐resolution HighResMIP model. [ABSTRACT FROM AUTHOR]

Investigating the role of complex dynamical components of a global climate model (GCM) in improving near-surface wind speed (WS) simulation is vital for the climate community in building reliable future WS projections. The relative skill of GCMs in representing WS at diverse climate variable scales (daily, monthly, seasonal, and annual) over land and ocean areas of the South Asian domain is not clear yet. With this in mind, this paper evaluated the skill of 28 Coupled Model Intercomparison Project phase five GCMs in reproducing the WS using a devised relative score approach. It is recommended to use the mean ensemble of MPI-ESM-MR, CSIRO-Mk3.6.0, and GFDL-ESM2G GCMs for understanding future changes in wind–wave climate and offshore wind energy potential. The inter-comparison of GCMs shows that the GCM with high or low atmospheric resolution does not necessarily exhibit the best or worst performance, respectively, whereas the dynamic components in the model configuration play the major role, especially the atmosphere component relative to other dynamical components. The strengthening of annual and seasonal mean WS is observed over coastal plains of the United Republic of Tanzania, Oman, eastern Thailand, eastern Gulf of Thailand and Sumatra, and weakening over the central northern equatorial region of the Indian Ocean in the 21st century for RCP4.5 and RCP8.5 emission scenarios. [ABSTRACT FROM AUTHOR]

Due to the spatial-temporal inadequacy of large-scale general circulation models (GCMs), linking large-scale GCM data with small-scale local climatic data has found great interest. In this paper, in order to downscale minimum and maximum temperatures and precipitation predictands, the performance of three statistical downscaling techniques including Long Ashton Research Station-Weather Generator (LARS-WG), statistical downscaling model (SDSM), and artificial neural network (ANN) was compared based on Intergovernmental Panel on Climate Change-Fifth Assessment Report (IPCC-AR5) in northwest Iran. For this purpose, a nonparametric test named Mann-Whitney test, Spearman correlation coefficient, and the root mean square error (RMSE) were utilized to assess the efficiency of downscaling models. To scrutinize the climate change impacts, periods of 1961–1990 and 1991–2005 were considered as the baseline and verification periods, respectively. The findings revealed the superior performance of the ANN model for minimum and maximum temperatures, while for precipitation predictand, the SDSM represented the best performance among the models. Simulation results for future temperature indicated an ascending trend as 0.1–1.3 °C, 0.3–1.7 °C, and 0.5–2.1 °C for LARS-WG, SDSM, and ANN techniques, respectively. On the other hand, simulation outputs for the precipitation indicated a descending trend of 10–30% in future precipitation of the region according to downscaling models under Representative Concentration Pathway 8.5 (RCP8.5) pessimistic scenario of Hadley Center Coupled Model version 3 (HadCM3) GCM model. [ABSTRACT FROM AUTHOR]

Understanding the reliability of global climate models (GCMs) to reproduce the historical surface wind fields is integral part of building robust projections of surface wind‐climate, and other wind‐dependent geophysical climatic variables. Understanding the skill of atmosphere‐only models (AGCM), coupled atmosphere–ocean models (AOGCM) and fully coupled earth system models (ESM) is likewise paramount to assess any systematic model improvements. In this paper, we systematically assess whether surface wind fields obtained from 28 CMIP5 GCMs can represent large‐scale spatial patterns and temporal variability of historical surface winds. We show that inter‐model uncertainty is typically 2–4 times larger than the uncertainty associated with GCM internal variability, although the latter can be significant within specific regions. We also find that CMIP5 models are typically capable of reliably reproducing large‐scale spatial patterns of historical near‐surface winds, but considerable uncertainty lies within the CMIP5 ensemble with strong latitudinal dependence. CMIP5 models show limitations in their ability to reliably represent inter‐annual and inter‐seasonal variability particularly within tropical‐cyclone‐affected regions. In further analysis, we quantify and intercompare historical wind bias from different types of models with different dynamical cores, based on multiple CMIP5 diagnostic experiments. We find that bias in surface wind fields are largely intrinsic to the atmospheric components of the models, and that the inclusion of carbon‐cycle dynamics has insignificant effect on simulated surface winds (at decadal time‐scales). Inconsistencies between AGCM and AOGCM simulations are largely driven by errors in sea surface temperatures (SST); though such differences are not statistically significant relative to the inter‐model uncertainty within the CMIP5 ensemble. These results show that the dominant source of bias in simulated wind fields lies in the underlying physics of the atmospheric component of the models. [ABSTRACT FROM AUTHOR]

Contributions to climate uncertainty in the modeling of the near surface temperature of the ocean come from several sources: the knowledge of the initial state of the atmosphere, the inadequacy of a model to include or correctly represent all aspects of the dynamics, the uncertain knowledge of the initial state of the ocean and small-scale (or internal, "weather") noise. This paper concentrates on the latter uncertainty, the uncertainty in the knowledge of the initial field, resulting in a map of the uncertainty of the near surface temperature field. To make the full estimate of this uncertainty, the outcomes from a relatively small, 30 member, ensemble were expanded using statistical emulators. The uncertainty varies in space and decreases in time. There are broad areas of similar uncertainty, consistent with uncertainties in the initial conditions and the variability in local processes. After 10 years, the average spatial uncertainty calculated from this expanded data set gives a range of +/− 0.4 ∘ C with 95% of the spatial areas having an uncertainty of less than +/− 0.9 ∘ C. When compared to other estimates of similar metrics, the map represents a lower bound on the uncertainty because this first experiment examines the ocean/ice system in isolation from feedbacks that occur between the atmosphere and the ocean. This uncertainty also does not include any contribution from the lack of knowledge about how a future state of the air/ocean system will be forced by changes in greenhouse gases. [ABSTRACT FROM AUTHOR]

Many general circulation models (GCMs) assume some heterogeneity of water amounts in their grid boxes and use probability density functions to parameterize cloud fractions CF and amounts of condensed water qc. Most GCM cloud schemes calculate the CF as the volume of the grid box that contains clouds (CFvol), whereas radiative fluxes primarily depend on the CF by surface (CFsurf), that is, the surface of the grid box covered by clouds when looking from above. This discrepancy matters as previous findings suggest that CFsurf is typically greater than CFvol by about 30%. In this paper we modify the single column model version of the LMDz GCM cloud scheme by introducing the vertical subgrid‐scale heterogeneity of water content. This allows to distinctly compute the two fractions, CFvol and CFsurf, as well as the amount of condensed water qc. This study is one of the first to take into account such vertical subgrid‐scale heterogeneity in a GCM cloud scheme. Three large eddy simulation cases of cumuliform boundary layer clouds are used to test and calibrate two different parameterizations. These new developments increase cloud cover by about 10% for the oceanic cases RICO and Barbados Oceanographic Meteorological Experiment and by up to 50% for the continental case ARM. The change in condensed water reduces the liquid water path by 10–20% and therefore the cloud opacity by 5–50%. These results show the potential of the new scheme to reduce the too few, too bright bias by increasing low‐level CF and decreasing cloud reflectance. Key Points: Most cloud schemes assume vertically homogeneous cloud fractions in GCM grid boxesThis approximation may induce an underestimation of cloud cover and overestimation of reflectanceWe parameterize 3‐D subgrid‐scale heterogeneities for low‐level clouds and reduce these biases [ABSTRACT FROM AUTHOR]

Abstract: A decadal climate prediction system named as IAP‐DecPreS was constructed in the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, based on a fully coupled model FGOALS‐s2 and a newly developed initialization scheme, referred to as EnOI‐IAU. In this paper, we introduce the design of the EnOI‐IAU scheme, assess the accuracies of initialization integrations using the EnOI‐IAU and preliminarily evaluate hindcast skill of the IAP‐DecPreS. The EnOI‐IAU scheme integrates two conventional assimilation approaches, ensemble optimal interpolation (EnOI) and incremental analysis update (IAU). The EnOI and IAU were applied to calculate analysis increments and incorporate them into the model, respectively. Three continuous initialization (INIT) runs were conducted for the period of 1950–2015, in which observational sea surface temperature (SST) from the HadISST1.1 and subsurface ocean temperature profiles from the EN4.1.1 data set were assimilated. Then nine‐member 10 year long hindcast runs initiated from the INIT runs were conducted for each year in the period of 1960–2005. The accuracies of the INIT runs are evaluated from the following three aspects: upper 700 m ocean temperature, temporal evolution of SST anomalies, and dominant interdecadal variability modes, Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO). Finally, preliminary evaluation of the ensemble mean of the hindcast runs suggests that the IAP‐DecPreS has skill in the prediction of the PDO‐related SST anomalies in the midlatitude North Pacific and AMO‐related SST anomalies in the tropical North Atlantic. [ABSTRACT FROM AUTHOR]

[Display omitted] • Establish the quantification of the polarization of hydrogen crossover current. • The current and voltage tendencies are solved out not matter in PSM or GCM. • The PEMFC's hydrogen permeability should be corrected by an internal resistance. Hydrogen crossover in proton exchange membrane fuel cells (PEMFCs) is an effective indicator for evaluating the health condition of PEMFCs. Electrochemical measurement is an indirect but convenient method for assessing the hydrogen crossover; nevertheless, the meaning of the characteristics from the measured signals is not consensus to lack quantitative method. In this paper, we have developed a general expression to quantify the relationship among the measured signals by decomposing the electrochemical processes inside the PEMFCs when measuring the hydrogen crossover current. The theoretical polarization curves were derived from the general equation and confirmed by the experiments on a 25 cm2 single cell. This work clarifies the intrinsic relevancies among these electrochemical methods and would help develop a new evaluation methodology for PEMFCs. [ABSTRACT FROM AUTHOR]

This paper examines the uncertainty in the change in the heat content in the ocean component of a general circulation model. We describe the design and implementation of our statistical methodology. Using an ensemble of model runs and an emulator, we produce an estimate of the full probability distribution function (PDF) for the change in upper ocean heat in an Atmosphere/Ocean General Circulation Model, the Community Climate System Model v. 3, across a multi-dimensional input space. We show how the emulator of the GCM's heat content change and hence, the PDF, can be validated and how implausible outcomes from the emulator can be identified when compared to observational estimates of the metric. In addition, the paper describes how the emulator outcomes and related uncertainty information might inform estimates of the same metric from a multi-model Coupled Model Intercomparison Project phase 3 ensemble. We illustrate how to (1) construct an ensemble based on experiment design methods, (2) construct and evaluate an emulator for a particular metric of a complex model, (3) validate the emulator using observational estimates and explore the input space with respect to implausible outcomes and (4) contribute to the understanding of uncertainties within a multi-model ensemble. Finally, we estimate the most likely value for heat content change and its uncertainty for the model, with respect to both observations and the uncertainty in the value for the input parameters. [ABSTRACT FROM AUTHOR]

The second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II) is designed to improve understanding of the possible roles and feedbacks of sea surface temperature (SST), land use land cover change (LULCC), and aerosols forcings in the Sahel climate system at seasonal to decadal scales. The project's strategy is to apply prescribed observationally based anomaly forcing, i.e., 'idealized but realistic' forcing, in simulations by climate models. The goal is to assess these forcings' effects in producing/amplifying seasonal and decadal climate variability in the Sahel between the 1950s and the 1980s, which is selected to characterize the great drought period of the last century. This is the first multi-model experiment specifically designed to simultaneously evaluate such relative contributions. The WAMME II models have consistently demonstrated that SST forcing is a major contributor to the twentieth century Sahel drought. Under the influence of the maximum possible SST forcing, the ensemble mean of WAMME II models can produce up to 60 % of the precipitation difference during the period. The present paper also addresses the role of SSTs in triggering and maintaining the Sahel drought. In this regard, the consensus of WAMME II models is that both Indian and Pacific Ocean SSTs greatly contributed to the drought, with the former producing an anomalous displacement of the Intertropical Convergence Zone before the WAM onset, and the latter mainly contributes to the summer WAM drought. The WAMME II models also show that the impact of LULCC forcing on the Sahel climate system is weaker than that of SST forcing, but still of first order magnitude. According to the results, under LULCC forcing the ensemble mean of WAMME II models can produces about 40 % of the precipitation difference between the 1980s and the 1950s. The role of land surface processes in responding to and amplifying the drought is also identified. The results suggest that catastrophic consequences are likely to occur in the regional Sahel climate when SST anomalies in individual ocean basins and in land conditions combine synergistically to favor drought. [ABSTRACT FROM AUTHOR]

High-resolution downscaling is vital to project climate extremes and their future changes by resolving fine topography reasonably well, which is a key to represent local climatology and impacts of weather extremes. A direct dynamical downscaling with a regional climate model (RCM) embedded within an atmosphere-ocean coupled general circulation model (AOGCM) is commonly used but is subject to systematic biases in their present-day simulations of AOGCM, which may cause unexpected effects on future projections and lead to difficult interpretation of climate change. In a high-resolution atmospheric general circulation model (AGCM)-RCM system, the present-day climate in AGCM is forced by observed sea surface temperature (SST) and sea-ice distribution. Then, the future climate is calculated with the "future" boundary conditions (SST and sea-ice), which are created by adding their future changes projected by AOGCM to the observed present-day values, besides the future radiative forcing. This system is one of methods to minimize the effects of such biases. A Meteorological Research Institute AGCM with 20-km grids is successfully applied to project future changes in weather extremes such as tropical cyclones and rain systems that cause heavy rainfall and strong winds. Regional downscaling with 5-km mesh RCM is then performed over certain area to investigate local extreme rainfall events and their future changes. In this paper, we review various downscaling methods and try to rationalize a use of high-resolution AGCM-RCM system. [ABSTRACT FROM AUTHOR]

This paper establishes a comprehensive assessment model to measure the regional impact of climate change on Taiwan's water resources. Working from future rainfall data simulated by Japan's high-resolution GCM model JMA/MRI TL959L60 in a SRES-A1B scenario, we first apply climate change to an assessment model of renewable water resources to estimate the volume of renewable water resources on a regional basis. We then conduct a water resources system simulation based on estimates of future water needs, regional reservoir effective capacity and renewable water resource volume. This paper uses three water resource assessment indicators: the annual water utilization ratio indicator, the water shortage indicator and the extreme event occurrence indicator. Through fuzzy comprehensive assessment, we divide the evaluation set into five levels: very good (L1), good (L2), fair (L3), poor (L4) and very poor (L5). Results indicate that, given the effects of future climate change (2080 - 2099) and the increase in water demand, future water resources conditions in northern and eastern Taiwan will not be significantly different from historical levels (1979 - 1998) and will maintain a "good" level (L2), while the conditions in southern Taiwan will visibly deteriorate from its historical "fair" level (L3) to "poor" (L4); and the future conditions for central Taiwan will be "poor" (L4). The initiation of adaptation options for water management in southern and central Taiwan would be needed by increasing reservoir capacity and reducing overall water use. [ABSTRACT FROM AUTHOR]

Abstract: The Pliocene Epoch, 5.33–2.58million years ago (Ma), was a generally warmer and wetter interval with atmospheric CO2-concentrations at or slightly above modern levels. This paper provides an overview of Pliocene vegetation, sea surface temperatures and climate modelling outcomes. Most prominent changes in Pliocene biome distribution compared to today include a northwards shift of temperate and boreal vegetation zones in response to a warmer and wetter climate as well as an expansion of tropical savannas and forests at the expense of deserts. Faunal analysis techniques and modelling experiments using the Hadley Centre climate model identified significantly higher Pliocene sea surface temperatures at mid and high latitudes of the northern hemisphere with cooling or unchanged sea surface temperatures at low latitudes. Global mean annual surface temperatures (MAT) are estimated to have been 2 to 3°C higher during the Piacenzian (3.6–2.58Ma) than today with a reduced equator to pole gradient. The marine realm during the Pliocene was characterised by a reconfiguration of ocean gateways, particularly the narrowing of the Indonesian Seaway and closure of the Central American Isthmus, which produced essentially a modern pattern of ocean circulation. In the Southern Ocean a warm early Pliocene gave way to late Piacenzian cooling. Proxy data indicate a reduced east to west sea surface temperature gradient in the tropical Pacific during the Pliocene warmth. The Pliocene is one of the most intensively studied geological intervals of the pre-Quaternary. No other warm period in the geological past yields such a unique combination of near modern atmospheric CO2-concentrations, palaeogeography and palaeobiology. However, this paper also identifies data gaps and shortcomings in the reconstruction of Pliocene environments using proxy data and climate models on which future research should focus. [Copyright &y& Elsevier]

1. Plant–soil interactions play a central role in the biogeochemical carbon (C), nitrogen (N) and hydrological cycles. In the context of global environmental change, they are important both in modulating the impact of climate change and in regulating the feedback of greenhouse gas emissions (CO2, CH4 and N2O) to the climate system. 2. Dynamic global vegetation models (DGVMs) represent the most advanced tools available to predict the impacts of global change on terrestrial ecosystem functions and to examine their feedbacks to climate change. The accurate representation of plant–soil interactions in these models is crucial to improving predictions of the effects of climate change on a global scale. 3. In this paper, we describe the general structure of DGVMs that use plant functional types (PFTs) classifications as a means to integrate plant–soil interactions and illustrate how models have been developed to improve the simulation of: (a) soil carbon dynamics, (b) nitrogen cycling, (c) drought impacts and (d) vegetation dynamics. For each of these, we discuss some recent advances and identify knowledge gaps. 4. We identify three ongoing challenges, requiring collaboration between the global modelling community and process ecologists. First, the need for a critical evaluation of the representation of plant–soil processes in global models; second, the need to supply and integrate knowledge into global models; third, the testing of global model simulations against large-scale multifactor experiments and data from observatory gradients. 5. Synthesis. This paper reviews how plant–soil interactions are represented in DGVMs that use PFTs and illustrates some model developments. We also identify areas of ecological understanding and experimentation needed to reduce uncertainty in future carbon coupled climate change predictions. [ABSTRACT FROM AUTHOR]

The terrestrial biosphere is an important global carbon (C) sink, with the potential to drive large positive climate feedbacks. Thus a better understanding of interactions between land use change, climate change and the terrestrial biosphere is crucial in planning future land management options. Climate change has the potential to alter terrestrial C storage since changes in temperature, precipitation and carbon dioxide (CO2) concentrations could affect net primary production (NPP), C inputs to soil, and soil C decomposition rates. Climate change could also act as a driver for land use change, thus further altering terrestrial C fluxes. The net balance of these different effects varies considerably between regions and hence the case studies presented in this paper (the GEFSOC project countries Kenya, Jordan, Brazil, and India) provide a unique opportunity to study climate impacts on terrestrial C storage. This paper first presents predicted changes in climate for the four case study countries from a coupled climate-C cycle Global Circulation Model (HadCM3LC), followed by predicted changes in vegetation type, NPP and soil C storage. These very coarse assessments provide an initial estimate of large-scale effects. A more detailed study of climate impacts on soil C storage in the Brazilian Amazon is provided as an example application of the GEFSOC system. Interestingly in the four cases studied here precipitation seems to control the sign of the soil C changes under climate change with wetter conditions resulting in higher soil C stocks and drier conditions in lower soil C stocks, presumably because increased NPP in wetter conditions here will override any increase in respiration. In contrast, globally, it seems to be temperature that controls changes in C stocks under climate change. Even if there is a slight increase in precipitation globally, a decrease in C stocks is predicted—in other words, the regional response to precipitation differs from the global response. The reason for this may be that whilst temperature increases under climate change were predicted everywhere, the nature of precipitation changes varies greatly between regions. [Copyright &y& Elsevier]

Watershed-scale hydrologic simulation models generally require climate data inputs including precipitation and temperature. These climate inputs can be derived from downscaled global climate simulations which have the potential to drive runoff forecasts at the scale of local watersheds. While a simulation designed to drive a local watershed model would ideally be constructed at an appropriate scale, global climate simulations are, by definition, arbitrarily determined large rectangular spatial grids. This paper addresses the technical challenge of making climate simulation model results readily available in the form of downscaled datasets that can be used for watershed scale models. Specifically, we present the development and deployment of a new Coupled Model Intercomparison Project phase 5 ( CMIP5) based database which has been prepared through a scaling and weighted averaging process for use at the level of U.S. Geological Survey (USGS) Hydrologic Unit Code (HUC)-8 watersheds. The resulting dataset includes 2,106 virtual observation sites (watershed centroids) each with 698 associated time series datasets representing average monthly temperature and precipitation between 1950 and 2099 based on 234 unique climate model simulations. The new dataset is deployed on a HydroServer and distributed using WaterOneFlow web services in the WaterML format. These methods can be adapted for downscaled General Circulation Model (GCM) results for specific drainage areas smaller than HUC-8. Two example use cases for the dataset also are presented. [ABSTRACT FROM AUTHOR]

Communication performance in the color-independent visual-multiple input multiple output (visual-MIMO) technique is deteriorated by light emitting array (LEA) detection and tracking errors in the received image because the image sensor included in the camera must be used as the receiver in the visual-MIMO system. In this paper, in order to improve detection reliability, we first set up the color-space-based region of interest (ROI) in which an LEA is likely to be placed, and then use the Harris corner detection method. Next, we use Kalman filtering for robust tracking by predicting the most probable location of the LEA when the relative position between the camera and the LEA varies. In the last step of our proposed method, the perspective projection is used to correct the distorted image, which can improve the symbol decision accuracy. Finally, through numerical simulation, we show the possibility of robust detection and tracking of the LEA, which results in a symbol error rate (SER) performance improvement. [ABSTRACT FROM AUTHOR]

Recent years have been witnessing an increasing interest on global climate change and, although we are only at the first stage of the projected trends, some signals of climate alteration are already visible. Climate change encompasses modifications in the characteristics of several interrelated climate variables, and unavoidably produces relevant effects on almost all the natural processes related to the hydrological cycle. This study focuses on potential impacts of climate variations on the streamflow regime of small river basins in Mediterranean, seasonally dry, regions. The paper provides a quantitative evaluation of potential modifications in the flow duration curves (FDCs) and in the partitioning between surface and subsurface contributions to streamflow, induced by climate changes projected over the next century in different basins, also exploring the role exerted by different soil–vegetation compositions. To this aim, it is used a recent hydrological model, which is calibrated at five Sicilian (Italy) basins using a past period with available streamflow observations. The model is then forced by daily precipitation and reference evapotranspiration series representative of the current climatic conditions and two future temporal horizons, referring to the time windows 2045–2065 and 2081–2100. Future climatic series are generated by a weather generator, based on a stochastic downscaling of an ensemble of General Circulation Models. The results show how the projected climatic modifications are differently reflected in the hydrological response of the selected basins, implying, in general, a sensible downshift of the FDCs, with a significant reduction in the mean annual streamflow, and substantial alterations in streamflow seasonality and in the relative importance of the surface and subsurface components. The projected climate change impact on the hydrological regime of ephemeral rivers could have important implications for the water resource management and for the sustainability of many riparian Mediterranean ecosystems. [ABSTRACT FROM AUTHOR]

High-resolution downscaling is vital to project climate extremes and their future changes by resolving fine topography reasonably well, which is a key to represent local climatology and impacts of weather extremes. A direct dynamical downscaling with a regional climate model (RCM) embedded within an atmosphere-ocean coupled general circulation model (AOGCM) is commonly used but is subject to systematic biases in their present-day simulations of AOGCM, which may cause unexpected effects on future projections and lead to difficult interpretation of climate change. In a high-resolution atmospheric general circulation model (AGCM)-RCM system, the present-day climate in AGCM is forced by observed sea surface temperature (SST) and sea-ice distribution. Then, the future climate is calculated with the "future" boundary conditions (SST and sea-ice), which are created by adding their future changes projected by AOGCM to the observed present-day values, besides the future radiative forcing. This system is one of methods to minimize the effects of such biases. A Meteorological Research Institute AGCM with 20-km grids is successfully applied to project future changes in weather extremes such as tropical cyclones and rain systems that cause heavy rainfall and strong winds. Regional downscaling with 5-km mesh RCM is then performed over certain area to investigate local extreme rainfall events and their future changes. In this paper, we review various downscaling methods and try to rationalize a use of high-resolution AGCM-RCM system. [ABSTRACT FROM AUTHOR]

Network on Chip (NoC) is an emerging solution to the existing scalability problems with System on Chip (SoC). However, it is exposed to security threats like extraction of secret information from IP cores. In this paper we present an Authenticated Encryption (AE)-based security framework for NoC based systems. The security framework resides in Network Interface (NI) of every IP core allowing secure communication among such IP cores. The secure cores can communicate using permanent keys whereas temporary session keys are used for communication between secure and non-secure cores. A traffic limiting counter is used to prevent bandwidth denial and access rights table avoids unauthorized memory accesses. We simulated and implemented our framework using Verilog/VHDL modules on top of NoCem emulator. The results showed tolerable area overhead and did not affect the network performance apart from some initial latency. [ABSTRACT FROM AUTHOR]

One way in which global climate model (GCM) output can be utilized to infer local impacts is through the use of synoptic climatology: creating a set of atmospheric patterns that capture the variability in the climate system, and then analyzing trends and variability in the frequency of these patterns moving into the future. In this paper, we demonstrate a new synoptic climatological technique for classifying atmospheric patterns that can be used in conjunction with GCM output data (in this case, the Community Climate System Model 3). We apply this method to 850-hPa temperature patterns over the contiguous United States to derive daily categorizations. A total of 15 clusters are created from the data set; once the mean GCM bias is removed, historical cluster frequencies in the GCM data set are not statistically different from those of the reanalysis data set. In the future, significant changes in frequency are observed across most of the transition season clusters, as they broaden in seasonality at the expense of winter clusters, some of which nearly entirely disappear. Changes are greater moving further into the future, and greater for the more carbon-intensive special report on emissions scenarios (SRES) scenarios (A1FI, A2) than the less-intensive scenario tested (B1). Diagnostics test how well the mean patterns of the reanalysis data set, GCM historical data set and the future GCM data sets resemble each other. For some clusters, mean bias between the historical and future data sets grows substantially by the end of the 21st century under the more carbon-intensive scenarios. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

This paper explores the evolution of idealized tropical cyclones in the Community Atmosphere Model CAM 5 with the spectral element (SE) dynamical core at grid spacings of 111, 55 and 28 km. Over 10 simulation days the storms become increasingly intense and compact with increasing resolution. The experiments reveal unrealistically strong tropical cyclone intensities of minimum surface pressures ranging from 845 to 865 hPa and absolute maximum wind speeds greater than 100 m s−1 at the highest resolution, especially when small physics time steps are used. This unphysical behavior is related to the manner in which the physics time step is applied in CAM 5. The analysis indicates that the behavior of the physics parameterizations, namely the partitioning between convective and large-scale precipitation, at small time steps contributes to this intensity. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Abstract: Twenty years ago, the discovery of the blood oxygen level dependent (BOLD) contrast and invention of functional magnetic resonance imaging (MRI) not only allowed for enhanced analyses of regional brain activity, but also laid the foundation for novel approaches to studying effective connectivity, which is essential for mechanistically interpretable accounts of neuronal systems. Dynamic causal modeling (DCM) and Granger causality (G-causality) modeling have since become the most frequently used techniques for inferring effective connectivity from fMRI data. In this paper, we provide a short historical overview of these approaches, describing milestones of their development from our subjective perspectives. [Copyright &y& Elsevier]

Flood is one of the most calamitous natural disasters that causes extensive property and life damages across the world. It however, could be a blessing due to its special natural water resources recharging value. By simulating the magnitude of probable floods considering the anthropogenic and natural effects and implementing contingency plans, their damages could be reduced. In this paper, the General Circulation Model (GCM) climate change scenarios are employed to simulate future floods. The GCM scenarios include simulation of climatic signals of the future considering green house gas emission forces. In this study a statistical downscaling model (SDSM) has been applied for rainfall downscaling to provide regional results from GCM outputs. Then, a rainfall-runoff model called HEC-HMS has been employed to estimate runoff in the region. The maximum simulated rainfall for each year that is of high enough potential to cause flood, is introduced into the rainfall-runoff model to simulate the plausible hydrograph of the flood. The proposed procedure is applied to the Kajoo River basin in South Baloochestan region, south-east of Iran. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we examine the nature of the Pliocene Antarctic Peninsula Ice Sheet by comparing the terrestrial and marine geological records of the Antarctic Peninsula and surrounding sea floor with estimated net snow accumulation in the region derived from numerical palaeoclimate model experiments. Pliocene geological data and our new modelling results are consistent and mutually supportive in suggesting that an ice sheet was present even during the warmest episodes of the Pliocene. The combined results suggest that the ice sheet in the Antarctic Peninsula is more robust to globally warmer conditions than is generally assumed, at least up to the climatic limits examined in our study. [Copyright &y& Elsevier]

The natural resources of the Okavango Delta, a large wetland in semi-arid Botswana, form the basis of livelihoods of the local population and support economically important high-end tourism. The hydro-ecological system is dynamic at various time scales, responding to climate variability, and both flood and drought conditions have in the past put pressure on the system's users. Human-induced climate change can potentially exacerbate the effects of existing climate variability. In this paper, we present simulated future hydro-ecological conditions in the Okavango Delta generated by a step-wise modelling procedure. The outputs of three different global climate models are used to drive a suite of hydrological models. Lastly, a rule-based dynamic model relates hydroperiod conditions to vegetation assemblages. The simulated future conditions vary from much drier to much wetter than those recorded in the past. Models indicate that climatic change would result in change in both extent and distribution of the major ecotopes of the Okavango Delta. Importantly, the different ecotopes will be affected to varying degrees. The projected changes will have consequences for the wildlife-based management of the system. They will affect, for example, available grazing and migration/movement patterns of large herbivores, as well as fish. Such consequences can have rapid up-trophic level effects, ultimately leading to potentially substantial impacts on the economy. The main conclusion to be drawn is that management planning and land-use systems should be as flexible as possible. [ABSTRACT FROM AUTHOR]

Abstract: When planning the acquisition of new palaeo proxy data for reconstructing past climates, many factors influence the decision of where the proxies are to be collected. One such influence is the likelihood of recording a significant climate change relative to the modern. Another consideration, which is less often considered, is the desire to target regions in which there is significant uncertainty in numerical model predictions of past climate change. New proxy data in these regions enables a more rigorous test of model simulations, and results in better constraints on the various boundary conditions used to force the models. In this paper we present a methodology for targeting new palaeo proxy data, based on model simulations. We use the terrestrial late Miocene (11.6 to 5.3 Ma) as a case study. The late Miocene climate provides insights into future climate behavior, as it is believed to have been considerably warmer than the modern. We carry out a suite of late Miocene atmosphere-only General Circulation Model simulations, which we initially evaluate relative to an example dataset of terrestrial temperature and precipitation. In terms of targeting future data acquisition, we locate those regions in the model which exhibit the largest change in temperature and/or precipitation relative to the pre-industrial. We also locate those regions which display the largest variability between the model simulations, because new data in these regions are most likely to provide a strict test of the reliability of the model results. Among other regions, the Amazon basin, the Chad basin, central Canada, and northern India are identified as potentially useful areas to collect data. [Copyright &y& Elsevier]

The aim of this paper is to review recent trends in the appli cation of ground based radon observations to atmospheric research. In spite of over four decades of atmospheric radon monitoring, only in the past decade has the potential of this passive tracer been realised through a series of atmospheric model evaluation studies. Firstly, the key operational requirements for baseline radon detectors are briefly discussed, including lower limit of detection and response time. Then, current radon-related benchmarks for the evaluation of regional and global models are reviewed, with particular consideration given to the implications of data availability, resolution, site location and model spatial/temporal resolution. An 8-year subset of radon observations from the Cape Grim Baseline Air Pollution Station is used to suggest new benchmarks that exploit long-term data sets. Lastly an overview is presented of a technique that uses radon to estimate regional fluxes of climatically sensitive gases, with specific examples for CO2, CH4 and N2O. [Copyright &y& Elsevier]

Renewable energy resources will play a key role in meeting the world''s energy demand over the coming decades. Unfortunately, these resources are all susceptible to variations in climate, and hence vulnerable to climate change. Recent findings in the atmospheric science literature suggest that the impacts of greenhouse gas induced warming are likely to significantly alter climate patterns in the future. In this paper we investigate the potential impacts of climate change on wind speeds and hence on wind power, across the continental US. General Circulation Model output from the Canadian Climate Center and the Hadley Center were used to provide a range of possible variations in seasonal mean wind magnitude. These projections were used to investigate the vulnerability of current and potential wind power generation regions. The models were generally consistent in predicting that the US will see reduced wind speeds of 1.0 to 3.2% in the next 50 years, and 1.4 to 4.5% over the next 100 years. In both cases the Canadian model predicted larger decreases in wind speeds. At regional scales the two models showed some similarities in early years of simulations (e.g. 2050), but diverged significantly in their predictions for 2100. Hence, there is still a great deal of uncertainty regarding how wind fields will change in the future. Nevertheless, the two models investigated here are used as possible scenarios for use in investigating regional wind power vulnerabilities, and point to the need to consider climate variability and long term climate change in citing wind power facilities. [Copyright &y& Elsevier]

The persistence of the weather is a well-known phenomenon. If, for example, one day is sunny and warm, there is a high tendency that the next day remains similar. In this paper, we review recent results showing that the long-term persistence, characterized by the correlation C(s) of temperature variations separated by s days, decays for large s as a power law. For continental stations, the exponent is always close to 0.7, while for stations on islands as well as for sea surface temperatures, the exponent is close to 0.4. In contrast to the temperature fluctuations, the fluctuations of the rainfall usually are not characterized by long-term power-law correlations but rather by short-term correlations. The universal persistence law for the temperature fluctuations on continental stations represents an ideal (and uncomfortable) test bed for the state-of-the-art global climate models and allows to evaluate their performance. [Copyright &y& Elsevier]

• Hydrological responses to land use and climate change are simulated using integrated modelling. • Scoring method is applied to select representative climate models. • Mean temperature is likely to increase by 1.79 °C (3.57 °C) under mid (high) emission scenarios. • Annual and monsoon flow is likely to increase during the 2050s and 2080s. • Hydrological sensitivity of the basin is analysed against changes in climatic variables. Accurate spatial and temporal measurement of water budget play a crucial role in achieving the sustainable planning and management of water resources. This paper presents a comprehensive integrated approach to simulate hydrological responses under dynamics of land use land cover (LULC) and climate change scenarios over Upper Narmada Basin, India. In order to select the representative climate models, scoring method was applied at regional scale. Best five performing climate models (MIROC5, CNRM-CM5, MPI-ESM-LR, GFDL-ESM2G and IPSL-CM5A-MR) were coupled with semi-distributed hydrological model to simulate the hydrological responses. Considering the heterogeneity of the large basin, multi-site calibration and parameters sensitivity analysis were performed using Sequential Uncertainty Fitting (SUFI-2) algorithm. To compute the hydrological sensitivity against land use change, calibrated model was coupled with historical and futuristic land use scenarios (1990, 2000, 2010 and 2030). The results indicate intensified precipitation towards the late 21st century, whereas annual mean temperature could be raised by 1.79 °C and 3.57 °C under mid and high emission scenarios respectively, at the end of century. Annual and monsoon flow in the basin likely to increase during the 2050 s (2041–2070) and 2080 s (2071–2100). Moreover, the relation between climate variables and water budget components were identified to analyse the hydrological sensitivity of the basin under changing climate. [ABSTRACT FROM AUTHOR]

With each passing day, Internet of Things (IoT), has the potential to transform our society to a more digital way. In this paper, a cryptographic system is proposed, which has been designed and implemented, following the IoT optimized technologies. As the benefits of IoT are numerous, the need for a privacy platform is more than necessary to be developed. This work aims to demonstrate this by, firstly, implementing efficient and flexible, the fundamentals primitives of cryptography and privacy. Secondly, this is achieved, by introducing applied cryptography, in a more interactive and flexible approach. The proposed system and the incorporation of this platform is scrutinized. In the context of this work, an application of symmetric cryptography is introduced, based on the Advanced Encryption Standard (AES) in Electronic Code Book (ECB), Cipher Block Chaining (CBC) and Counter (CTR) modes of operation, for both encryption and decryption of texts, images and electronic data applications. In addition two other security schemes are supported by the proposed system: AES Galois/Counter Mode (GCM) and AES Galois Message Authentication Code (GMAC). The GCM proposed integration, in an authentication scheme, designed to provide authenticity and confidentiality, at the same time. On the other hand, GMAC, can be applied as message authentication code. Both operations, are optimized in sense of implementation resources, since the major cost is targeted to AES core. In addition, based on the integrated hardware modules, user registration and validation is proposed and implemented, with no additional cost, and with no performance penalty. Furthermore, two factor authentication has been designed and proposed, based on One Time Passwords (OTP), which can been produced with a random procedure. After these, a reference to the security levels, as regards to the communication between the IoT layers of the architecture, is presented. IoT hardware platforms are facing lack of security level and this brings the opportunity to use advanced security mechanisms. Implementation comparison results emphasize the importance of testing and measuring the performance of the alternative encryption algorithms, supported by hardware platforms. [ABSTRACT FROM AUTHOR]

The level of interest in Galois Counter Mode (GCM) Authenticated Encryption rose significantly within the last few years. GCM is interesting because it is the only authenticated encryption standard that can be implemented in a fully pipelined or parallelized way and it is the most appropriate for encrypting packetized data. McGrew and Viega [CHECK END OF SENTENCE] described (but did not detail) how GHASH can be implemented with more than one multiplier operating in parallel. This paper details how that can be done and shows that, when N multipliers are used, and the multipliers use the approach of multiplying polynomials then applying a modular reduction, a single modular reduction can be used instead on N separate operations. This optimization can be used even when there is a single multiplier, which makes this implementation strategy have a broader appeal. Recently Intel has introduced new ISA instructions into the next generation CPU core, namely: AES family and PCLMULQDQ operating in XMM registers domain. In this paper, we discuss the example implementation of proposed GHASH modifications using above instructions. [ABSTRACT FROM AUTHOR]