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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]

Anthropogenic climate change is expected to cause an increase in fire danger over south-eastern Australia during the 21st century, primarily driven by increased surface temperature. Studies of future fire weather in Victoria, Australia, have so far mostly utilised direct output from general circulation models, which have inadequate resolution for resolving the dynamics of local fire danger and are prone to substantial biases that may affect the seasonality of dry fuels. In this paper, we assess the ability of the Multivariate Adaptive Constructed Analogs (MACA) method to downscale output from general circulation models over Victoria, and replicate statistical attributes of fire danger indices. We find that climatological descriptors of meteorological variables of wind, temperature and humidity are captured extremely well, and fields on extreme fire days are well captured. We find that the method works very well for statistically downscaling fire weather elements over Victoria and provides a vehicle to assess the regional variation of fire weather projections over Victoria. This paper evaluates the computationally efficient Multivariate Adaptive Constructed Analogs (MACA) method for downscaling a single general circulation model to a fine scale over the state of Victoria, Australia. Comparison with a 4-km fire weather climatology dataset shows the method well reproduces observed statistics of mean and extreme fire weather. Photo showing planned burn in Victoria, Australia, by Tim Brown. [ABSTRACT FROM AUTHOR]

HDO and the D/H ratio are essential to understand Mars past and present climate, in particular with regard to the evolution through ages of the Martian water cycle. We present here new modeling developments of the HDO cycle with the Laboratoire de Météorologie Dynamique Mars Global Climate Model (GCM). The present study aims at exploring the behavior of the D/H ratio cycle and its sensitivity to the modeling of water ice clouds and the formulation of the fractionation by condensation. Our GCM simulations are compared with observations provided by the Atmospheric Chemistry Suite (ACS) on board the ESA/Roscosmos Trace Gas Orbiter (TGO), and reveal that the model quite well reproduces the temperature and water vapor fields, which offers a good basis for representing the D/H ratio cycle. The comparison also emphasizes the importance of modeling the state of supersaturation, resulting from the microphysical processes of water ice clouds, to correctly account for the water vapor and the D/H ratio of the middle‐to‐upper atmosphere. This work comes jointly with a detailed comparison of the measured D/H profiles by TGO/ACS and the model outputs, conducted in the companion paper of Rossi et al. (2022, https://doi.org/10.1029/2022JE007201) (this issue). Plain Language Summary: The D/H ratio observed in a planetary atmosphere is traditionally used as a proxy to estimate the initial water reservoir of the planet. We present here an improved global circulation model including HDO, the main isotope of water on Mars. The updated model takes into account the details of the formation of clouds and their radiative effect. It also includes the effect of photochemistry on HDO and deuterated species. We find that supersaturation is key to the representation of the D/H cycle by making the hygropause more porous, allowing more HDO in the upper atmosphere. It also reduces the efficiency of the isotopic fractionation occurring at condensation. We present here comparisons between observations by the Atmospheric Chemistry Suite spectrometer onboard the orbiter TGO. While the model is globally in agreement with the observations, the inability of the model to reproduce the observed vertical distribution of dust, especially during the Global Dust Storm, causes discrepancies in the representation of water vapor. The model reveals the importance of representing the state of supersaturation to correctly account for the water vapor amount reaching the top of the atmosphere and estimate the D/H ratio at escape. Key Points: The HDO cycle has been implemented in the last version of the Laboratoire de Météorologie Dynamique Mars Global Climate Model including microphysics and radiative effect of water ice cloudsKinetics effect is now included in HDO fractionation during condensation and proves to be significantSupersaturation, the presence of which is regulated by cloud processes, alters significantly the relative abundances of HDO and H2O [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive river discharge analysis to estimate past and future hydrological extremes across Morocco. Hydrological simulations with historical forcing and climate change scenario inputs have been performed to better understand the change in magnitude and frequency of extreme discharge events that cause flooding. Simulations are applied to all major rivers of Morocco, including a total of 16 basins that cover the majority of the country. An ensemble of temperature and precipitation input parameter sets was generated to analyze input uncertainty, an approach that can be extended to other regions of the world, including data-sparse regions. Parameter uncertainty was also included in the analyses. Historical simulations comprise the period 1979–2021, while future simulations (2015–2100) were performed under the Shared Socioeconomic Pathway (SSP) 2–4.5 and SSP5–8.5. Clear patterns of changing flood extremes are projected; these changes are significant when considered as a proportion of the land area of the country. Two types of basins have been identified, based on their different behavior in climate change scenarios. In the Northern/Mediterranean basins we observe a decrease in the frequency and intensity of events by 2050 under both SSPs, whereas for the remaining catchments higher and more frequent high-flow events in the form of flash floods are detected. Our analysis revealed that this is a consequence of the reduction in rainfall accumulation and intensity in both SSPs for the first type of basins, while the opposite applies to the other type. More generally, we propose a methodology that does not rely on observed time series of discharge, so especially for regions where those do not exist or are not available, and that can be applied to undertake future flood projections in the most data-scarce regions. This method allows future hydrological hazards to be estimated for essentially any region of the world. [ABSTRACT FROM AUTHOR]

The global climate is changing. Predicting the impacts this will have on buildings is the first step in the process of finding suitable building adaptation measures. Future climate adaptation of buildings and infrastructure is a growing field of research, relying on both socio-economical and meteorological research for input values to the simulation models. Models producing hourly future weather data rely on global climate models which are based on emission scenarios made from assumptions of future political, social, and economic developments. Accounting for the uncertainties from these underlying models as much as possible, and communicating the uncertainties in the results, is obviously paramount for reliable conclusions from the building simulation models. This paper is a scoping review, investigating how 132 studies treat and communicate the string of uncertainties from underlying models connected to future weather file generation in the scientific literature on building adaptation research. The findings suggest that climate-model-induced uncertainties are often under-communicated, due to either insufficient analysis or neglect. The studies that included the most comprehensive analyses of the uncertainties frequently concluded that treatment of these is important for the reliability of the results, and neglecting this could lead to misleading conclusions. [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]

In the context of constructing an embedded system to help visually impaired people to interpret text, in this paper, an efficient High-level synthesis (HLS) Hardware/Software (HW/SW) design for text extraction using the Gamma Correction Method (GCM) is proposed. Indeed, the GCM is a common method used to extract text from a complex color image and video. The purpose of this work is to study the complexity of the GCM method on Xilinx ZCU102 FPGA board and to propose a HW implementation as Intellectual Property (IP) block of the critical blocks in this method using HLS flow with taking account the quality of the text extraction. This IP is integrated and connected to the ARM Cortex-A53 as coprocessor in HW/SW codesign context. The experimental results show that the HLS HW/SW implementation of the GCM method on ZCU102 FPGA board allows a reduction in processing time by about 89% compared to the SW implementation. This result is given for the same potency and strength of SW implementation for the text extraction. [ABSTRACT FROM AUTHOR]

A declining trend in Indian summer monsoon precipitation (ISMP) in the latter half of the 20th century is a scientifically challenging and societally relevant research issue. Heavy aerosol loading over India is one of the key factors in modulating the ISMP. Using the state-of-the-state-of-the-art chemistry-climate model, ECHAM6-HAMMOZ, the impacts of South Asian anthropogenic sulfate aerosols on the Indian summer monsoon precipitation were investigated against: (1) 2010 La Niña (excess monsoon), (2) 2015 El Niño (deficit monsoon) in comparison to (3) normal monsoon 2016. Sensitivity simulations were designed with 48% enhancement in South Asian SO 2 emissions based on a trend estimated from Ozone Monitoring Instrument (OMI) satellite observations during 2006–2017. The model simulations showed that sulfate aerosols reduce ISMP by 27.5%–43.3 %, while simulations without sulfate loading enhanced ISMP by 23% in 2010 La Niña and reduction by 35% in 2015 El Niño. This paper reports that sulfate aerosols loading over India reduce precipitation by aerosol-induced direct and indirect effects by inducing atmospheric cooling, weakening in the convection, and reduction in moisture transport to Indian landmass. This paper emphasizes the necessity of alternate use of energy to reduce sulfate aerosol emissions to solve water issues in South Asia. [Display omitted] • Sulfate emission reduces Indian summer monsoon precipitation through aerosol-radiation and aerosol-cloud interactions. • Over 27% of the summer monsoon rainfall deficit in a normal year are linked to Asian anthropogenic sulfate emissions. • Sulfate-induced rainfall reduction is the maximum for La Niña year. • SO 2 loading increases atmospheric stability and weakens moisture transport to India. [ABSTRACT FROM AUTHOR]

Uttar Pradesh, with a population of 237 million, is the largest agrarian state in India, located in the Indo‐Gangetic plains. Rice cultivation is widespread across all districts of Uttar Pradesh, which have varying climate regimes, irrigation infrastructures, crop management practices, and farm sizes. The state is characterized by different agroecological zones (AEZs) with semi‐arid to sub‐humid climates with significant variability in monsoon rainfall. In this study, the impact of climate change on Kharif‐season rice is estimated using crop‐climate scenarios in Uttar Pradesh. A process‐based Crop Simulation Model, Crop Estimation through Resource and Environment Synthesis‐Rice, was simulated with bias‐corrected and downscaled climate data for historical (1995–2014) and three future periods (the 2030s, 2050s, and 2090s) for two mitigation pathways (SSP2‐4.5 and SSP5‐8.5) from the Coupled Model Intercomparison Project 6. Phenology, irrigation amount, crop evapotranspiration, yield, and water use efficiency were evaluated and assessed for all AEZs. Based on the ensemble of 16 climate models, rainfed rice yield increased in the AEZs of western Uttar Pradesh due to increased rainfall, while in eastern Uttar Pradesh yield decreased, under both shared socioeconomic pathways (SSPs). Irrigated rice yield decreased in all AEZs under both SSPs due to an increase in temperature and a decrease in the length of the growing period, with reductions of up to 20% by the 2090s. Irrigation requirements decreased from the 2030s to the 2090s due to increased rainfall and decreased crop evapotranspiration. Despite the projected increase in rainfed yield, the overall rice yield is expected to decrease in the future under both SSPs. Plain Language Summary: Uttar Pradesh is the most populated state in India, with most of the population working in the agriculture sector and having a low income. The state's vulnerability to climate change is high due to inadequate infrastructure and heavy dependence on agriculture. Rice is a crucial crop for the state, but this study shows that climate change will decrease rice yields in the future, especially for irrigated rice, due to higher temperatures and shorter growing seasons. While rainfed rice yields may increase in some regions due to increased rainfall, rice production is expected to decline overall. Key Points: Rice yield (combining irrigated and rainfed) in Uttar Pradesh, India, is projected to decrease in the future for SSP2‐4.5 and SSP5‐8.5With a projected increase in rainfall, rainfed rice yield increases in rainfall deficit zones, and irrigation decreases under both shared socioeconomic pathwaysPlanting in the early season could reduce the amount of yield loss for irrigated rice [ABSTRACT FROM AUTHOR]

To ensure water use and water resource security along "the Belt and Road", the runoff and hydrological droughts and floods under future climate change conditions in the upper Heihe River Basin were projected in this study, based on the observed meteorological and runoff data from 1987 to 2014, and data from 10 GCMs from 1987 to 2014 and from 2026 to 2100, using the SWAT model, the Standardized Runoff Index, run length theory, and the entropy-weighted TOPSIS method. Both the multi-GCM ensemble (MME) and the optimal model were used to assess future hydrological drought and flood responses to climate change. The results showed that (1) the future multi-year average runoff from the MME was projected to be close to the historical period under the SSP245 scenario and to increase by 2.3% under the SSP585 scenario, and those from the optimal model CMCC-ESM2 were projected to decrease under both scenarios; (2) both the MME and the optimal model showed that drought duration and flood intensity in the future were projected to decrease, while drought intensity, drought peak, flood duration, and flood peak were projected to increase under both scenarios in their multi-year average levels; (3) drought duration was projected to decrease most after 2080, and drought intensity, flood duration, and flood peak were projected to increase most after 2080, according to the MME. The MME and the optimal model reached a consensus on the sign of hydrological extreme characteristic responses to climate change, but showed differences in the magnitude of trends. [ABSTRACT FROM AUTHOR]

The volumetric change in unsaturated loess during loading causes serious damage to the foundation and structure, accompanied by changes in hydraulic conditions. Therefore, quantifying the change in the load effect of loess under hydraulic coupling is of great significance for revealing the mechanism of hydraulic interaction. This study conducts isotropic compression and undrained shear tests on unsaturated compacted loess, simultaneously introducing the strength parameter η to enhance the Glasgow coupled model (GCM). The objective is to elucidate the hydraulic and mechanical coupling mechanism, where saturation increases under mechanical effects lead to strength degradation. The results show that saturation increases under mechanical effects improve the compressibility of the sample, and saturation has a direct impact on the stress–strain relationship. The increase in water content and confining pressure increases the trend of the critical state stress ratio M decreasing, and the strain softening trend increases. The compression of volume during shear tests increases the saturation, changes the hydraulic characteristics of loess, and affects the deformation and strength of loess. The modified GCM improves the applicability and prediction accuracy of unsaturated loess under the same initial state. The research results are of great significance for revealing the hydraulic and mechanical behavior of loess. [ABSTRACT FROM AUTHOR]

Planetary‐scale mountain waves have been observed at the cloud top of Venus and throughout the cloud deck. As they propagate from the surface to the cloud layers, multiple observations and numerical simulations have shown that they grow in size and do not break. However, the fate of mountain waves in the transition region and thermosphere, above the super‐rotating atmosphere, has only been addressed with two‐dimensional models. We conduct for the first time a simulation of mountain waves with a state‐of‐the‐art Venus climate model that includes the thermosphere. We find that mountain waves can propagate up to at least 150 km altitude, well above the transition region. They affect the circulation of the transition region, by reducing winds speeds, and the subsolar‐to‐antisolar circulation. Plain Language Summary: The planet Venus rotates very slowly, with a rotation period of 243 days, while its cloud cover rotates westwards much faster, with a period of 4 days at 70 km altitude, a phenomenon known as superrotation, which is not fully explained yet. Higher up, in the thermosphere, the air flows from the dayside to the nightside, rather than westwards. The thermosphere is difficult to explore by remote sounding due to the low air density, and thus its connection to the surface and the superrotating layer is poorly understood. In 2015, the Venus‐orbiting spacecraft Akatsuki detected a massive standing wave generated at the surface and reaching the superrotating layer, despite the fast zonal winds. Here, we show that this wave also reaches the thermosphere. Key Points: The first simulation of mountain waves with a 3D ground‐to‐thermosphere General Circulation Model is performedMountain waves reach the thermosphere of Venus and change the SS‐AS winds by up to 80 m/s, locally in the afternoonThe vertical wind field above the cloud deck is dominated by the effect of mountain waves [ABSTRACT FROM AUTHOR]

This work shows a 3-year climatology of the horizontal components of the solar diurnal tide, obtained from wind measurements made by a multistatic specular meteor radar (SIMONe) located in Jicamarca, Peru (12 ∘ S, 77 ∘ W). Our observations show that the meridional component is more intense than the zonal component, and that it exhibits its maxima shifted with respect to the equinox times (i.e., the largest peak occurs in August–September, and the second one in April–May). The zonal component only shows a clear maximum in August–September. This observational climatology is compared to a climatology obtained with the Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X). Average comparisons indicate that the model amplitudes are 50% smaller than the observed ones. The WACCM-X results are also used in combination with observed altitude profiles of the tidal phases to understand the relative contributions of migrating and non-migrating components. Based on this, we infer that the migrating diurnal tide (DW1) dominates in general, but that from June until September (November until July) the DE3 (DW2) may have a significant contribution to the zonal (meridional) component. Finally, applying wavelet analysis to the complex amplitude of the total diurnal tide, modulating periods between 5 and 80 days are observed in the SIMONe measurements and the WACCM-X model. These modulations might be associated to planetary waves and intraseasonal oscillations in the lower tropical atmosphere. [ABSTRACT FROM AUTHOR]

This article contributes to discussions that problematize the recent proliferation of soft law instruments in relation to international migration. The Global Compact for Migration has placed soft norm instruments more formally on the agenda of plausible tools with which to regulate people's movement. I am contributing to these discussions by engaging with the question of how the amalgamation of soft and hard law contributes to and impacts on legal effects, using a postcolonial feminist lens. I do so by focusing on the interaction between freedom of movement and the right to leave in the ECOWAS area, drawing on original research material collected mainly in Abuja, Nigeria, but also in Senegal, Guinea, and The Gambia. It is argued that freedom of movement provisions, as they are promoted by the ECOWAS and largely funded by inter-governmental organizations and European donor countries, end up infringing the right to leave. In a first step, existing norms at international, continental, regional, and national level are discussed to prepare the ground to answer the question how such infringing is done. From this step, I conclude that the triple layers of legal instruments, political instruments, and programming are impairing the intent of the right to leave in the way that a politico-legal landscape is constructed within which programs operationalize freedom of movement. The next step then looks at freedom of movement programming at regional, national, and local levels by asking about the subjectivities that are created--for example the "potential migrant"; by shedding light on practices of resistance--for example in how national governments use diplomacy to disengage; and by highlighting how "home patch" talk renders those potential migrants leaving not just implausible but suspect. It is found that, in the legal and political context of West Africa, soft norms thrive. The GCM constitutes an unhelpful list of random contradictory approaches that orient ideas, policy initiatives, programs, and ultimately people, toward being fixed in place, rather than being able to leave and to move freely should they want to. This happens in-country when people have not yet begun to move. [ABSTRACT FROM AUTHOR]

The Western Ghats (WG) in South India is a biological hotspot with a cluster of small river basins and heterogeneous climate and vegetation patterns, and it is categorized under the water stress region by Central Water Commission (CWC). This study aims to evaluate the effects of climate change and land use/land cover (LULC) transformations on water balance components and irrigation water demand (IWD) across different regions of WG for a future period (2020–2050). The variable infiltration capacity model has been calibrated separately for the upper, middle, and lower regions of WG. Further, climate projections from the CMIP6 experiment (SSP2 45/SSP5 85) have been used for future projections of water balance components. The land use change shows an increase in built-up (5.79%) and a decrease in cultivable land (1.24%) by the end of 2030 from 1995. The combined impact due to climate and LULC change shows that the future rainfall/runoff increases in the lower regions of the basin by 100/36.5 mm/year through SSP 4.5. However, the summer months show an increasing water requirement in the future for the Ghats and Nilgiri regions of the basin. The present regional-based study will be useful for future agriculture water management practices in the region for sustainable development and the study can be extended to other similar regions. [ABSTRACT FROM AUTHOR]

Global drought patterns are substantially impacted by climate change, with far-reaching implications for socioeconomic and ecological systems. Existing global climate models (GCMs) are unable to accurately project precipitation and drought characteristics, particularly in countries or regions with complex topography and significant seasonal variability, such as China. Consequently, the purpose of this study is to assess the efficacy of GCMs, and their multi-model ensemble mean, as well as to investigate the seasonal drought characteristics in China using precipitation data from CMIP6 under various "possible future" scenarios. This study selected five GCMs with historical (1961–2014) and future (2015–2100) periods, namely CNRM-CM6-1, GFDL-ESM4, MPI-ESM1-2-HR, MPI-ESM1-2-LR, and NorESM2-MM, as well as their ensemble mean ENS-CGMMN. Based on the China Daily Precipitation Analysis Product (CPAP) as the reference precipitation, the performance of these models is evaluated using the DISO index and the quantile mapping (QM) method for calibration, as well as seasonal-scale drought using the standardized precipitation index (SPI) and spatiotemporal variability analysis methods. In comparison to other climate models and the ensemble mean, the calibrated MPI-ESM1-2-HR model can more precisely describe the actual precipitation conditions at the seasonal scale. Under four scenarios, China's climate will shift from arid to moist in the future period (2015–2100) (SSP126, SSP245, SSP370, and SSP585). Autumn and summer will see a considerable increase in China's moisture levels. During the autumn, winter, and spring, the moisture will generally increase in the northern subregions of China, including the Qinghai-Tibet Plateau (QTP), Xinjiang (XJ), Northwest (NW), Northeast (NE), and North China (NC). Dryness will decrease in southern subregions, such as the Southwest (SW) and South China (SC). In contrast to these three seasons, summer in XJ exhibits a distinct trend of aridity, especially in the SSP245 scenario, whereas the NE, NC, and SC exhibit a distinct trend of moisture. To be more specific, the aridity changes in subregions during various seasons under different future climate scenarios vary significantly. This study's findings can provide significant support for future research on climate change and drought, which can help improve the accuracy of future climate projections and serve as a reference for drought risk management and policy formulation. [ABSTRACT FROM AUTHOR]

In this study, a simple polynomial bias correction method is developed to correct the bias in the forecasted streamflow (runoff) derived from a global circulation model (GCM). First, a set of polynomial correction factors was derived comparing observed and GCM-derived runoff for a hindcast period (1961–2000) for each of the 11 selected GCMs. The correction factors are used to correct the GCM-derived streamflow for projected periods (2046–2065 and 2081–2100) for the Intergovernmental Panel on Climate Change scenarios A2 and B1 (CMIP3) for the Murray-Hotham catchment of Western Australia. The assumption is that the correction factors derived for each GCM for the observed period (1961–2000) are valid for the projected periods. Results show the method reduces biases considerably for the projected runoff at a catchment scale. The method developed here uses CMIP3 data but it may be applicable to any GCM data, such as CMIP5/CMIP6. [ABSTRACT FROM AUTHOR]

Standard quantile mapping (QM) performs well, as a bias adjustment method, in removing historical climate biases, but it can significantly alter a global climate model (GCM) signal. Methods that do incorporate GCM changes commonly consider mean changes only. Quantile delta mapping (QDM) is an exception, as it explicitly preserves relative changes in the quantiles, but it might present biases in preserving GCMs changes in standard deviation. In this work we propose the unbiased quantile mapping (UQM) method, which by construction preserves GCM changes of the mean and the standard deviation. Synthetic experiments and four Chilean locations are used to compare the performance of UQM against QDM, QM, detrended quantile mapping, and scale distribution mapping. All the methods outperform QM, but a tradeoff exists between preserving the GCM relative changes in the quantiles (QDM is recommended in this case), or changes in the GCM moments (UQM is recommended in this case). [ABSTRACT FROM AUTHOR]

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.

[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]

Cirrus clouds play an important role in the Earth's radiative energy budget, thereby affecting the climate state and climate change. Orographic gravity wave (OGW)‐induced sub‐grid scale vertical velocity (i.e., cooling rate) is not resolved by large‐scale models and its impact on ice formation in cirrus clouds is not well quantified. In this study, one sub‐grid scale OGW scheme (e.g., McFarlane) is used in the Community Atmosphere Model version 6 (CAM6) to generate vertical velocity variance (σw) for cirrus formation. Results from the default model and simulations with the OGW‐induced σw are evaluated against the DOE ARM Small Particles in Cirrus (SPARTICUS) campaign observations. The OGW based on the McFarlane scheme increases the sub‐grid scale σw over mountains compared to the default model and improves the model agreement with the SPARTICUS observations. Larger σw due to OGWs can trigger more frequent homogeneous nucleation in orographic cirrus and generates a higher number concentration of ice crystals observed during the SPARTICUS campaign. Moreover, our evaluation of the model simulations against satellite observations indicates that the McFarlane scheme generates high in‐cloud ice number concentrations (>200 L−1) in the upper troposphere over mountains and high plateaus at mid‐ and high‐latitudes of the winter hemisphere as shown in the observations. More ice crystals with smaller sizes absorb more infrared radiation (+0.523 ± 0.125 W m−2). The net radiative cloud forcing change at the top of the atmosphere is +0.330 W m−2 due to the orographic cirrus. Plain Language Summary: Cirrus clouds occurring frequently in the upper troposphere play an important role in the Earth's radiative budget and the global climate. Large mountains in the globe can produce strong gravity waves propagating upward to the upper troposphere. These orographic gravity waves can induce large vertical velocities and form orographic cirrus which can extend hundreds of miles in the atmosphere. This study introduces orographic gravity waves induced by the mountains to cirrus ice formation in a global climate model, the Community Atmosphere Model version 6 (CAM6). We find that a large amount of ice crystals forms in the simulated cirrus over mountains in the winter hemisphere when orographic gravity waves are included in the cirrus formation. The simulation results are improved when comparing with aircraft and satellite observations. Orographic cirrus induces a warming effect on the global climate. Key Points: Vertical velocity variance (σw) generated by orographic gravity waves (OGWs) is introduced to the cirrus formation in CAM6The sub‐grid scale σw is increased by OGW‐induced fluctuations over mountains in orographic cirrus and agrees better with observationsThe large σw induced by OGWs generates high in‐cloud ice number concentrations (>200 L−1) in orographic cirrus as observed [ABSTRACT FROM AUTHOR]

Predictions of biodiversity trajectories under climate change are crucial in order to act effectively in maintaining the diversity of species. In many ecological applications, future predictions are made under various global warming scenarios, as described by a range of different climate models. We propose a clustering methodology to synthesize and interpret the outputs of these various predictions.We propose an interpretable and flexible two‐step methodology to measure the similarity between predicted species range maps and to cluster the future scenario predictions utilizing a spectral clustering technique. We implement and provide code for this method.We find that clustering based on predicted species range maps is mainly driven by the amount of warming rather than climate model or future scenario. We contrast this with clustering based only on predicted climate variables, which is driven primarily by climate models, that is, scenarios of the same climate model are clustered together, even when the amount of warming input to the models is varied.The differences between species‐based and climate‐based clusterings illustrate that it is crucial to incorporate ecological information to understand the relevant differences between climate models. Our findings can be used to better synthesize forecasts of biodiversity change under the wide spectrum of results that emerge when considering potential future scenarios. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive analysis of extreme events, especially drought and wet events, spanning over the past years, evaluating their trends over time. An investigation of future projections under various scenarios such as SSP-126, SS-245, and SSP-585 for the near (2023–2048), mid (2049–2074), and far future (2075–2100) using the bias-corrected Coupled Model Intercomparisons Project 6 (CMIP6) multi-model ensemble method was also performed. The Standard Precipitation Index (SPI), a simple yet incredibly sensitive tool for measuring changes in drought, is utilized in this study, providing a valuable assessment of drought conditions across multiple timescales. The historical analysis shows that there is a significant increase in drought frequency in subdivisions such as East MP, Chhattisgarh, East UP, East Rajasthan, Tamil Nadu, and Rayalaseema over the past decades. Our findings from a meticulous examination of historical rainfall trends spanning from 1951 to 2022 show a noticeable decline in rainfall across various regions such as Uttar Pradesh, Chhattisgarh, Marathwada, and north-eastern states, with a concurrent increase in rainfall over areas such as Gujarat, adjoining regions of West MP and East Rajasthan, and South Interior Karnataka. The future projection portrays an unpredictable pattern of extreme events, including droughts and wet events, with indications that wet frequency is set to increase under extreme SSP scenarios, particularly over time, while highlighting the susceptibility of the northwest and south peninsula regions to a higher incidence of drought events in the near future. Analyzing the causes of the increase in drought frequency is crucial to mitigate its worst impacts, and recent experiences of drought consequences can help in effective planning and decision-making, requiring appropriate mitigation strategies in the vulnerable subdivisions. [ABSTRACT FROM AUTHOR]

The thermal structure of the upper atmosphere in the Venus polar region is reproduced by the assimilation of horizontal winds in low‐ and mid‐latitudes derived from the Akatsuki ultra‐violet images. The obtained structure is well consistent with infrared and radio occultation measurements. In particular, the unique thermal features in the Venus polar vortex such as the cold collar and the warm polar region in our model are realistic: the level where the cold collar is located and the temperature difference between the cold collar and the warm polar region are consistent with data. The reasons why the thermal structure of the upper atmosphere in the Venus polar region is realistic are that the zonal wind distribution around the cloud top level and the structure of the residual mean meridional circulation induced by the thermal tides are improved with respect to the model without data assimilation. Our results also suggest that the thermal structure in the Venus upper polar region is closely related to the atmospheric dynamics. Plain Language Summary: Data assimilation is one of the powerful techniques to correct an output from a numerical model by comparing with the observations and enables us to obtain the modeling results consistent with the measurements. In this study, by the data assimilation of horizontal winds in low‐ and mid‐latitudes derived by the Akatsuki ultra‐violet images, the thermal structure of the upper atmosphere in the Venus polar region has been reproduced by the General Circulation Model. The zonal wind distribution around the cloud top level in the model is well consistent with the measurements due to the data assimilation, and then the unique thermal structure in the Venus polar vortex such as the cold collar and the warm polar region reproduced by the model is also improved with respect to the model without data assimilation because the structures of the atmospheric circulation and the atmospheric waves are realistic due to the improvement of the zonal wind distribution. Our results also suggest that the thermal structure of the upper atmosphere in the Venus polar region is closely related to the atmospheric dynamics. Key Points: The thermal structure in the Venus upper polar region is reproduced by the assimilation of horizontal winds derived from Akatsuki UVIThe reproduced thermal structure becomes realistic and consistent with the observations due to the data assimilationOur results suggest that the thermal structure in the Venus upper polar region is closely related to the atmospheric dynamics [ABSTRACT FROM AUTHOR]

Horizontal diffusion and resolution are important factors to generate and maintain the super-rotation in the general circulation model (GCM) because waves which transport angular momentum are sensitive to them. Here, we investigated how the super-rotation depends on the magnitude of horizontal hyper diffusion using a Venus atmospheric GCM with medium and high resolutions. In both the runs, we found a parameter range where the structure of fully developed super-rotation is almost independent of the magnitude of horizontal diffusion. Spectral analysis shows that unrealistically strong super-rotation is developed when medium-scale disturbances are dissipated by stronger horizontal diffusion. On the other hand, artificially weak super-rotation is also realized because spurious small-scale disturbances are accumulated when the horizontal diffusion is too weak. [ABSTRACT FROM AUTHOR]

The establishment of Global Compact for Migration (GCM) was considered as the first important step for the international community to comprehensively address the issue of global migration. However, there are certain objectives within the compact that is considered as vague and unfavourable by several states. Previous studies have explored the advantages and disadvantages of GCM but did not address the specific argumentation that creates disagreements between states. This paper uses the theoretical approach from realist perspective to investigate how certain stipulations within the compact are in contrary to certain actors’ interests, specifically the interests of key state actors in global migration governance. Using qualitative methodology, the analysis began by exploring stances of notable states that opposes the compact. The findings discovered that the GCM failed to recognise the core problem of migration itself which is the management of regular and irregular migrants. The result of the study indicates that states’ rejection towards the Global Compact for Migration are mainly driven by the incompatibility of the compact’s goals and objectives with their national interest, particularly concerning sovereignty and national security.

This study aims to assess climate model performance at Wadi El Abid basin (northeastern Tunisia), using Hydrologiska Byråns Vattenbalansavdelning (HBV)-light rainfall-runoff model (RRM). We evaluate time series of daily precipitation and mean daily temperature simulated by eleven couple of regional climate models (RCMs) downscaling five general circulation models (GCMs), provided by the Coordinated Downscaling Experiment–European Domain (EURO-CORDEX), over 1970–2000 historical period. The hydrological performance of regional climate models forced by Global Circulation Models (GCM-RCMs) is achieved using six discharge metrics, evaluating the runoff simulated by RRM forced by climate models' data. Quantile Delta Mapping bias correction technique was used to correct the distribution of precipitation and temperature time series simulated by GCM-RCMs. HBV-light model performed highly over the historical period with Kling-Gupta Efficiency around 0.80 and bias almost null. Quantile Delta Mapping (QDM) reduces greatly the bias in precipitation simulated by GCM-RCMs; nevertheless, disagreement between observed and bias-corrected precipitation is still present at monthly time scale after the application of QDM. This disagreement was transmitted to simulated runoff with further accentuation due to the high elasticity of runoff to precipitation. This finding shows the capacity of the hydrological evaluation of the climate model to highlight the hydrological consequences of certain weaknesses of the GCM-RCM simulations that are not well detectable by the separate evaluation of the climate variables. The hydrological rating of GCM-RCMs shows that IPSL-IPSL-CM5A-MR-IPSL-INERIS-WRF331F was low performing even though it was after bias correction. It is recommended to a modeler, to build their impact studies over the study catchment on the ensemble projection from the remaining ten best-performing GCM-RCMs. [ABSTRACT FROM AUTHOR]

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Bias correction is a vital technique to correct the climate model outputs for regional studies. Prior bias correction methods such as quantile mapping (QM) may be problematic in correcting extreme values. Herein we proposed a novel bias correction method, that is, the piecewise‐quantile mapping (PQM), by combing piecewise mapping with QM, which implements bias corrections on both extreme and nonextreme data. We compared the PQM method and other six commonly used methods in correcting daily precipitation in the Mekong River Basin (MRB) and the Yangtze River Basin (YRB) from two global climate models (GCMs) (i.e., EC‐Earth3 and MPI‐ESM1‐2‐HR) in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Our results show that the PQM perform better in bias correction pertaining to both the precipitation percentiles and most of the extremes indices. For example, the mean absolute error of R20mm (the number of days when precipitation ≥20 mm) is significantly reduced from 21.64 to 9.03 days and from 10.96 to 5.71 days over MRB and YRB, respectively. In addition, the PQM could capture the spatial distributions of extremes indices reasonably well. The PQM developed in this study provides more accurate bias correction of the GCMs outputs, which will reduce the uncertainty in the subsequent analyses, such as climate change impacts on hydrological and biogeochemical cycles, particularly under extreme conditions. [ABSTRACT FROM AUTHOR]

We describe the model performance of a new global coupled climate model configuration, CM4‐MG2. Beginning with the Geophysical Fluid Dynamics Laboratory's fourth‐generation physical climate model (CM4.0), we incorporate a two‐moment Morrison‐Gettelman bulk stratiform microphysics scheme with prognostic precipitation (MG2), and a mineral dust and temperature‐dependent cloud ice nucleation scheme. We then conduct and analyze a set of fully coupled atmosphere‐ocean‐land‐sea ice simulations, following Coupled Model Intercomparison Project Phase 6 protocols. CM4‐MG2 generally captures CM4.0's baseline simulation characteristics, but with several improvements, including better marine stratocumulus clouds off the west coasts of Africa and North and South America, a reduced bias toward "double" Intertropical Convergence Zones south of the equator, and a stronger Madden‐Julian Oscillation (MJO). Some degraded features are also identified, including excessive Arctic sea ice extent and a stronger‐than‐observed El Nin∼ $\tilde{\mathrm{n}}$o‐Southern Oscillation. Compared to CM4.0, the climate sensitivity is reduced by about 10% in CM4‐MG2. Plain Language Summary: A sophisticated cloud microphysical scheme, along with a mineral dust and temperature‐dependent ice nucleation scheme, have been implemented in a new configuration of the Geophysical Fluid Dynamics Laboratory's most recent climate model (CM4.0). This microphysical scheme predicts both mass and number concentrations of cloud drops, ice crystals, rain, and snow, and treats aerosol‐cloud interactions more consistently. The ice nucleation on mineral dust aerosol in large‐scale clouds is represented more realistically. Centennial‐scale global coupled atmosphere‐ocean‐land‐sea ice simulations from this new configuration compare favorably with observations—with improved subtropical stratocumulus clouds and better tropical intraseasonal variability (i.e., the 30‐ to 90‐day Madden‐Julian Oscillation). The new configuration also reduces the magnitude of future global warming in response to anthropogenic emissions. Key Points: The performance of two‐moment microphysics with prognostic precipitation and an ice nucleation scheme in CM4.0: CM4‐MG2, is documentedThe overall performance of CM4‐MG2 is comparable to or better than CM4.0, based on a set of Model Intercomparison Project Phase 6 Diagnosis, Evaluation, and Characterization of Klima and historical simulationsNotable improvements include enhanced coastal stratocumulus and a stronger Madden‐Julian Oscillation. CM4‐MG2 has a lower climate sensitivity than CM4.0 [ABSTRACT FROM AUTHOR]

Climate change has been affecting agricultural water resources dynamics spatially and temporally. This article presents analysis results of climate change impact on agricultural water availability in Cimanuk Watershed, Indonesia. STREAM was utilized to model agricultural water availability through FAO MOSAICC web application. Climate spatial data time-series were generated using 3 Global Climate Model (GCM), i.e.,: CanESM2, CNRM-CM5, and MPI-ESM-MR following two climate change scenarios of RCP4.5 and 8.5. Model inputs were split into three periods of 1981–2010 (historical), 2010–2039 (near-future), and 2040–2069 (far-future). Historical data model validation showed the efficiency coefficient of the observed and simulated discharge data ratio was 0.68. The results showed a decreasing volumetric water availability from all generated climate data and scenarios, identified by comparing the discharge normal distribution of the historical and future data periods. Whereas, trend analysis of RCP4.5 scenario showed increasing maximum discharge of Cimanuk river using CanESM2 and MPI-ESM-MR GCM's data, with a Mann–Kendall coefficient of 3.23 and 3.57. These results indicate a different agricultural water balance status within the watershed area, particularly a "very critical" water balance in Indramayu and Majalengka, "critical" in Garut, and "close to critical" in Sumedang Regency. [ABSTRACT FROM AUTHOR]

A developing country like Ethiopia suffers immensely from the effects of climate change due to its limited economic capability to build irrigation projects to combat climate change impacts on crop production. This study evaluated the impact of climate change on rainfed maize production in the southern part of Ethiopia. The AquaCrop model was employed to assess potential rainfed maize production in the study area with and without climate change. The latest version of the stochastic weather generator model LARS-WG was used to simulate local-scale level climate variables based on low-resolution GCM outputs. The expected monthly percentage change of rainfall during two-time horizons (2040 and 2060) ranged from -23.18 to 20.23 % (2031-2050) and -14.8 to 36.66% (2051-2070). Moreover, the monthly mean of the minimum and maximum temperature were estimated to increase in the range of 1.296 to 2.192 oC and 0.98 to 1.84 oC for the first time horizon (2031-2050) and from 1.86 to 3.4 oC and 1.56 to 3.18 oC in the second time horizon (2051-2070), respectively. Maize yields were expected to increase with a range of 4.13 to 7 % and 6.36 to 9.32% for the respective time horizons in the study area provided that all other parameters were kept the same. [ABSTRACT FROM AUTHOR]