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During the first half of the Holocene (11 000 to 5000 years ago), the Northern Hemisphere experienced a strengthening of the monsoonal regime, with climate reconstructions robustly suggesting a greening of the Sahara region. Palaeoclimate archives also show that this so-called African humid period (AHP) was accompanied by changes in climate conditions at middle to high latitudes. However, inconsistencies still exist in reconstructions of the mid-Holocene (MH) climate at mid-latitudes, and model simulations provide limited support in reducing these discrepancies. In this paper, a set of simulations performed using a climate model are used to investigate the hitherto unexplored impact of Saharan greening on mid-latitude atmospheric circulation during the MH. Numerical simulations show Saharan greening has a year-round impact on the main circulation features in the Northern Hemisphere, especially during boreal summer (when the African monsoon develops). Key findings include a westward shift in the global Walker Circulation, leading to modifications in the North Atlantic jet stream in summer and the North Pacific jet stream in winter. Furthermore, Saharan greening modifies atmospheric synoptic circulation over the North Atlantic, enhancing the effect of orbital forcing on the transition of the North Atlantic Oscillation phase from predominantly positive to negative in winter and summer. Although the prescription of vegetation in the Sahara does not improve the proxy–model agreement, this study provides the first constraint on the influence of Saharan greening on northern mid-latitudes, opening new opportunities for understanding MH climate anomalies in regions such as North America and Eurasia.

Climate change is considered the most pressing environmental challenge of our time, being transport one of the major contributors. Consequently, transport models are required to test different urban mobility policies that can shift travel to more sustainable transport modes (e.g., active modes). This paper focuses on the development of a validated agent-based model (MATSim) applying a novel open-source methodology to generate the main input datasets, easily transferrable to any region in England. Required input datasets (synthetic population and network) are described with a high level of detail, identifying the datasets and tools used to develop them, with special interest in the simulation of cycling routes. A new attribute (quietness) ranking roads for cycling depending on their built-environment characteristics was incorporated into the MATSim bicycle extension. The results obtained in this paper show the baseline transport model of the Tyne and Wear region (England), where discrepancies up to 3.5% in transport mode shares and minimal differences in vehicle counts in urban areas were obtained, and a realistic representation of the routes chosen by the agents using bicycles is obtained. This provides the basis for the development of similar MATSim implementation in other UK regions.

Despite the wealth of existing climate forecast data, only a small part is effectively exploited for sectoral applications. A major cause of this is the lack of integrated tools that allow the translation of data into useful and skillful climate information. This barrier is addressed through the development of an R package. Climate Services Toolbox (CSTools) is an easy-to-use toolbox designed and built to assess and improve the quality of climate forecasts for seasonal to multi-annual scales. The package contains process-based, state-of-the-art methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination, and multivariate verification, as well as basic and advanced tools to obtain tailored products. Due to the modular design of the toolbox in individual functions, the users can develop their own post-processing chain of functions, as shown in the use cases presented in this paper, including the analysis of an extreme wind speed event, the generation of seasonal forecasts of snow depth based on the SNOWPACK model, and the post-processing of temperature and precipitation data to be used as input in impact models.

Recent advances in modelling capabilities and data processing combined with vastly improved observation tools and networks have resulted in the expansion of available weather and climate information, from historical observations to seasonal climate forecasts, as well as decadal climate predictions and multi-decadal climate change projections. However, it remains a key challenge to ensure this information reaches the intended climate-sensitive sectors (e.g. water, energy, agriculture, health), and is fit-for-purpose to guarantee the usability of climate information for these downstream users. Climate information can be produced on demand via climate resilience information systems which are existing in various forms. To optimise the efficiency and establish better information exchange between these systems, standardisation is necessary. Here, standards and deployment options are described for how scientific methods can be be deployed in climate resilience information systems, respecting the principles of being findable, accessible, interoperable and reusable. Besides the general description of OGC-API Standards and OGC-API Processes based on existing building blocks, ongoing developments in AI-enhanced services for climate services are described.

During austral winter, a compact low cloud deck over the South Atlantic contrasts with clear sky over southern Africa, where forest fires triggered by dry conditions emit large amounts of biomass burning aerosols (BBAs) in the free troposphere. Most of the BBA burden crosses the South Atlantic embedded in the tropical easterly flow. However, midlatitude synoptic disturbances can deflect part of the aerosol from the main transport path towards southern extratropics. In this study, the first objective classification of the synoptic variability controlling the spatial distribution of BBA in southern Africa and the South Atlantic during austral winter (August to October) is presented. By analysing atmospheric circulation data from reanalysis products, a six-class weather regime (WR) classification of the region is constructed. The classification reveals that the synoptic variability is composed of four WRs, representing disturbances travelling at midlatitudes, and two WRs accounting for pressure anomalies in the South Atlantic. The WR classification is then successfully used to characterise the aerosol spatial distribution in the region in the period 2003–2017, in both reanalysis products and station data. Results show that the BBA transport towards southern extratropics is controlled by weather regimes associated with midlatitude synoptic disturbances. In particular, depending on the relative position of the pressure anomalies along the midlatitude westerly flow, the BBA transport is deflected from the main tropical route towards southern Africa or the South Atlantic. Moreover, the WRs accounting for midlatitude disturbances show organised transition sequences, which allow one to illustrate the evolution of the BBA northerly transport across the region in the context of a wave pattern. The skill in characterising the BBA transport shown by the WR classification indicates the potential for using it as a diagnostic/predictive tool for the aerosol dynamics, which is a key component for the full understanding and modelling of the complex radiation–aerosol–cloud interactions controlling the atmospheric radiative budget in the region.

During the first half of the Holocene (11 000 to 5000 years ago), the Northern Hemisphere experienced a strengthening of the monsoonal regime, with climate reconstructions robustly suggesting a greening of the Sahara region. Palaeoclimate archives also show that this so-called African humid period (AHP) was accompanied by changes in climate conditions at middle to high latitudes. However, inconsistencies still exist in reconstructions of the mid-Holocene (MH) climate at mid-latitudes, and model simulations provide limited support in reducing these discrepancies. In this paper, a set of simulations performed using a climate model are used to investigate the hitherto unexplored impact of Saharan greening on mid-latitude atmospheric circulation during the MH. Numerical simulations show Saharan greening has a year-round impact on the main circulation features in the Northern Hemisphere, especially during boreal summer (when the African monsoon develops). Key findings include a westward shift in the global Walker Circulation, leading to modifications in the North Atlantic jet stream in summer and the North Pacific jet stream in winter. Furthermore, Saharan greening modifies atmospheric synoptic circulation over the North Atlantic, enhancing the effect of orbital forcing on the transition of the North Atlantic Oscillation phase from predominantly positive to negative in winter and summer. Although the prescription of vegetation in the Sahara does not improve the proxy–model agreement, this study provides the first constraint on the influence of Saharan greening on northern mid-latitudes, opening new opportunities for understanding MH climate anomalies in regions such as North America and Eurasia. [ABSTRACT FROM AUTHOR]

Diploid organisms have two copies of each gene, called alleles, that can be separately transcribed. The RNA abundance associated to any particular allele is known as allele-specific expression (ASE). When two alleles have polymorphisms in transcribed regions, ASE can be studied using RNA-seq read count data. ASE has characteristics different from the regular RNA-seq expression: ASE cannot be assessed for every gene, measures of ASE can be biased towards one of the alleles (reference allele), and ASE provides two measures of expression for a single gene for each biological samples with leads to additional complications for single-gene models. We present statistical methods for modeling ASE and detecting genes with differential allelic expression. We propose a hierarchical, overdispersed, count regression model to deal with ASE counts. The model accommodates gene-specific overdispersion, has an internal measure of the reference allele bias, and uses random effects to model the gene-specific regression parameters. Fully Bayesian inference is obtained using the fbseq package that implements a parallel strategy to make the computational times reasonable. Simulation and real data analysis suggest the proposed model is a practical and powerful tool for the study of differential ASE.

There is little knowledge on how the difficulty of forecasting weather may be affected by climate change. Here, the authors find that the atmosphere’s predictability may increase in the future due to warmer oceans.

In the last 15 years, crustacean fisheries have experienced billions of dollars in economic losses, primarily due to viral diseases caused by such pathogens as white spot syndrome virus (WSSV) in the Pacific white shrimp Litopenaeus vannamei and Asian tiger shrimp Penaeus monodon. To date, no effective measures are available to prevent or control disease outbreaks in these animals, despite their economic importance. Recently, double-stranded RNA-based vaccines have been shown to provide specific and robust protection against WSSV infection in cultured shrimp. However, the limited stability of double-stranded RNA is the most significant hurdle for the field application of these vaccines with respect to delivery within an aquatic system. Polyanhydride nanoparticles have been successfully used for the encapsulation and release of vaccine antigens. We have developed a double-stranded RNA-based nanovaccine for use in shrimp disease control with emphasis on the Pacific white shrimp L. vannamei. Nanoparticles based on copolymers of sebacic acid, 1,6-bis(p-carboxyphenoxy)hexane, and 1,8-bis(p-carboxyphenoxy)-3,6-dioxaoctane exhibited excellent safety profiles, as measured by shrimp survival and histological evaluation. Furthermore, the nanoparticles localized to tissue target replication sites for WSSV and persisted through 28 days postadministration. Finally, the nanovaccine provided ~80% protection in a lethal WSSV challenge model. This study demonstrates the exciting potential of a safe, effective, and field-applicable RNA nanovaccine that can be rationally designed against infectious diseases affecting aquaculture.