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RNA interference, or RNAi, refers to a set of biological processes that make use of conserved cellular machinery to silence genes. Although there are several variations in the source and mechanism, they are all triggered by double stranded RNA (dsRNA) which is processed by a protein complex into small, single stranded RNA, referred to as small interfering RNAs (siRNA) with complementarity to sequences in genes targeted for silencing. The use of the RNAi mechanism to develop new traits in plants has fueled a discussion about the environmental safety of the technology for these applications, and this was the subject of a symposium session at the 13th ISBGMO in Cape Town, South Africa. This paper continues that discussion by proposing research areas that may be beneficial for future environmental risk assessments of RNAi-based genetically modified plants, with a particular focus on non-target organism assessment.

The processes responsible for freshwater flux from the Antarctic Ice Sheet (AIS), ice‐shelf basal melting and iceberg calving, are generally poorly represented in current Earth System Models (ESMs). Here we document the cryosphere configuration of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) v1.2. This includes simulating Antarctic ice‐shelf basal melting, which has been implemented through simulating the ocean circulation within static Antarctic ice‐shelf cavities, allowing for the ability to calculate ice‐shelf basal melt rates from the associated heat and freshwater fluxes. In addition, we added the capability to prescribe forcing from iceberg melt, allowing for realistic representation of the other dominant mass loss process from the AIS. In standard resolution simulations (using a noneddying ocean) under preindustrial climate forcing, we find high sensitivity of modeled ocean/ice shelf interactions to the ocean state, which can result in a transition to a high basal melt regime under the Filchner‐Ronne Ice Shelf (FRIS), presenting a significant challenge to representing the ocean/ice shelf system in a coupled ESM. We show that inclusion of a spatially dependent parameterization of eddy‐induced transport reduces biases in water mass properties on the Antarctic continental shelf. With these improvements, E3SM produces realistic ice‐shelf basal melt rates across the continent that are generally within the range inferred from observations. The accurate representation of ice‐shelf basal melting within a coupled ESM is an important step toward reducing uncertainties in projections of the Antarctic response to climate change and Antarctica's contribution to global sea‐level rise. Plain Language Summary The future of the Antarctic Ice Sheet (AIS) has the potential to have broad impacts on global climate, perhaps most notably in contributing to sea‐level rise. The current generation of Earth System Models (ESMs) do not accurately represent the two primary means in which ice is lost from the AIS, through melting at the base of ice shelves floating on the ocean and the calving of icebergs. This limits our ability to make climate projections that incorporate the impacts of the AIS in a changing climate. Here, we demonstrate a novel capability to model one of those processes, ice‐shelf basal melting, in an ESM. We demonstrate the ability to simulate ice‐shelf basal melt rates across many Antarctic ice shelves that are in line with present day observations. We also find that, for certain ice shelves, modeled ice‐shelf basal melting can experience a rapid transition to high melting far above present‐day estimates, and this simulated high melting can be mitigated through improved ocean physics. Key Points Capabilities have been added to an Earth System Model to model realistic Antarctic ice‐shelf basal melt fluxes and prescribe iceberg forcing Simulated basal melt rates have a strong sensitivity to the ocean mesoscale eddy parameterization For one choice of the mesoscale eddy parameterization, the Filchner‐Ronne Ice Shelf transitions to a high melt regime

We examine ocean tides in the barotropic version of the Model for Prediction Across Scales (MPAS‐Ocean), the ocean component of the Department of Energy Earth system model. We focus on four factors that affect tidal accuracy: self‐attraction and loading (SAL), model resolution, details of the underlying bathymetry, and parameterized topographic wave drag. The SAL term accounts for the tidal loading of Earth's crust and the self‐gravitation of the ocean and the load‐deformed Earth. A common method for calculating SAL is to decompose mass anomalies into their spherical harmonic constituents. Here, we compare a scalar SAL approximation versus an inline SAL using a fast spherical harmonic transform package. Wave drag accounts for energy lost by breaking internal tides that are produced by barotropic tidal flow over topographic features. We compare a series of successively finer quasi‐uniform resolution meshes (62.9, 31.5, 15.7, and 7.87 km) to a variable resolution (45 to 5 km) configuration. We ran MPAS‐Ocean in a single‐layer barotropic mode forced by five tidal constituents. The 45 to 5 km variable resolution mesh obtained the best total root‐mean‐square error (5.4 cm) for the deep ocean (>$ > $ 1,000 m) M2${\\mathrm{M}}_{2}$tide compared to TPXO8 and ran twice as fast as the quasi‐uniform 8 km mesh, which had an error of 5.8 cm. This error is comparable to those found in other forward (non‐assimilative) ocean tide models. In future work, we plan to use MPAS‐Ocean to study tidal interactions with other Earth system components, and the tidal response to climate change. Plain Language Summary Over the next century, climate change impacts on coastal regions will include floods, droughts, erosion, and severe weather events. The Department of Energy (DoE) is funding the Integrated Coastal Modeling Project to understand these potential risks better. In this paper, we implement tides in the DoE ocean model. Tides themselves respond to climate change, altering coastal flooding risk assessments. We explore the sensitivity of tides to model resolution (the spacing of model gridpoints), ocean‐floor topography, and the so‐called “self‐attraction and loading” (SAL) effect. Self‐attraction and loading occurs as the mass of water in a location fluctuates, causing a deformation of the Earth's crust and changes in the gravitational potential, which must be accounted for when modeling tides. We present a computationally efficient method of calculating the SAL effects and show that it is more accurate than other commonly used approximations. In future work we will examine interactions of tides with other components of the climate system, including sea ice, floating ice shelves, rivers, and current systems. Key Points We calculate the full self‐attraction and loading (SAL) term inline, in a barotropic configuration of Model for Prediction Across Scales (MPAS‐Ocean) Inclusion of the inline SAL and higher resolution meshes yield improved tidal accuracy in stand‐alone barotropic MPAS‐Ocean configurations A 45 to 5‐km variable‐resolution mesh provides reduced tidal errors with better computational performance than a quasi‐uniform 8‐km mesh

Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1‐Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1‐Arctic) historical simulations (1950–2014) with the uniform low‐resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large‐scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high‐resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales. Plain Language Summary Earth system models (ESMs) are essential tools for understanding the climate system and projecting future changes, but standard coarse model resolutions often fail to realistically represent regional processes and topography, particularly in the polar regions, while uniform high‐resolution grids are too computationally expensive. To address this, regionally refined meshes (RRMs) have been developed within ESMs to provide high‐resolution simulations in target areas, improving the accuracy of regional climate simulations while maintaining computational efficiency. This study looks at how well the U.S. DOE's RRM model, E3SMv2.1‐Arctic, performs in simulating Arctic climate. The RRM, which focuses on the Arctic region, is compared to a uniform low‐resolution version, as well as to observations and reanalysis data. The RRM does a better job of simulating important Arctic climate features like precipitation, atmospheric circulation, clouds, sea ice and atmospheric rivers compared to the low‐resolution model. However, it shows some seasonal temperature biases, reducing the cold bias in summer but increasing the warm bias in winter. The RRM also underestimates winter sea ice, consistent with the warm winter bias. While the study demonstrates the advantages of using high‐resolution models to better understand Arctic climate changes, it also notes that some biases remain despite the increased resolution. Key Points Evaluation of atmosphere‐land‐ocean‐ice fully coupled E3SM‐Arctic historical simulations with regionally refined meshes for the Arctic E3SM‐Arctic reduces bias in precipitation, clouds and atmospheric rivers due to better topography compared to its low‐resolution counterpart Higher resolution leads to an increased albedo feedback and more accurate sea ice area, but with faster sea ice melting due to a warm bias

Climate model components utilizing unstructured meshes enable variableresolution, regionally enhanced simulations within global domains. Here we investigate the relationship between mesh quality and simulation statistics using the JIGSAW unstructured meshing library and the Model for Prediction Across ScalesOcean (MPASOcean) with a focus on Gulf Stream dynamics. In the base configuration, the refined region employs 8 km cells that extend 400 km from the coast of North America. This coastal refined region is embedded within a lowresolution global domain, with cell size varying latitudinally between 30 and 60 km. The resolution transition region between the refined region and background mesh is 600 km wide. Three sensitivity tests are conducted: 1) the quality of meshes is intentionally degraded so that horizontal cells are progressively more distorted; 2) the transition region from high to low resolution is steepened; and 3) resolution of the coastal refinement region is varied from 30 km to 8 km. Overall, the ocean simulations are shown to be robust to mesh resolution and quality alterations. Meshes that are substantially degraded still produce realistic currents, with Southern Ocean transports within 0.4% and Gulf Stream transports within 12% of highquality mesh results. The narrowest transition case of 100 km did not produce any spurious effects. Refined regions with high resolution produce eddy kinetic energy and sea surface height variability that are similar to the highresolution reference simulation. These results provide heuristics for the design criteria of variableresolution climate model domains.

The concept of Data Transportability (DT) of Confined Field Testing (CFT) to support the Environmental Risk Assessment (ERA) of Genetically Modified (GM) plants was first introduced in the literature by Garcia-Alonso et al., in 2014. Since then, DT has been discussed in many countries and regions as a concept to prevent duplication of regulatory studies without compromising quality of the ERA. However, despite its usefulness and scientific justification, DT is not well adopted at this time and many regulatory agencies around the world require additional in-country CFT be conducted before approving GM plants. Based on the current circumstances, the authors organized a parallel session entitled “ Introduction and Scientific Justification of DT for CFT for the ERA of GM plants ” at 16th ISBR (the International Society for Biosafety Research). This session mainly consisted of the following three parts. The first two speakers, Andrew Roberts and Abigail Simmons provided an overview of DT and examples of conditions for the transportability of field data/conclusions advocated in the peer-reviewed scientific journals. Next, the current status of DT adoption in some countries/regions such as Japan and Africa, and a theoretical case study for Argentina were introduced by Kazuyuki Hiratsuka, Douglas Miano, and Facundo Vesprini, respectively. Lastly, a risk hypothesis-based approach for DT which was developed in advance by the five speakers of this parallel session, was introduced. During the discussion, there was a common understanding that transition to the risk hypothesis-based approach for DT was scientifically appropriate, considering the accumulated evidences that several countries have conducted confirmatory local CFT for more than 20 years but they have not detected any differences related to the ERA assessment endpoints in GM crops. The risk hypothesis-based approach for DT introduced here is expected to play an important role in discussions on the implementation of DT in various parts of the world in the future.

Background Bone morphogenetic proteins (BMPs) are members of the conserved transforming growth factor β (TGFβ superfamily, and play many developmental and homeostatic roles. In C. elegans , a BMP-like pathway, the DBL-1 pathway, controls body size and is involved in innate immunity. How these functions are carried out, though, and what most of the downstream targets of this pathway are, remain unknown. Results We performed a microarray analysis and compared expression profiles of animals lacking the SMA-6 DBL-1 receptor, which decreases pathway signaling, with animals that overexpress DBL-1 ligand, which increases pathway signaling. Consistent with a role for DBL-1 in control of body size, we find positive regulation by DBL-1 of genes involved in physical structure, protein synthesis and degradation, and metabolism. However, cell cycle genes were mostly absent from our results. We also identified genes in a hedgehog -related pathway, which may comprise a secondary signaling pathway downstream of DBL-1 that controls body size. In addition, DBL-1 signaling up-regulates pro-innate immunity genes. We identified a reporter for DBL-1 signaling, which is normally repressed but is up-regulated when DBL-1 signaling is reduced. Conclusions Our results indicate that body size in C. elegans is controlled in part by regulation of metabolic processes as well as protein synthesis and degradation. This supports the growing body of evidence that suggests cell size is linked to metabolism. Furthermore, this study discovered a possible role for hedgehog -related pathways in transmitting the BMP-like signal from the hypodermis, where the core DBL-1 pathway components are required, to other tissues in the animal. We also identified the up-regulation of genes involved in innate immunity, clarifying the role of DBL-1 in innate immunity. One of the highly regulated genes is expressed at very low levels in wild-type animals, but is strongly up-regulated in Sma/Mab mutants, making it a useful reporter for DBL-1/BMP-like signaling in C. elegans .

This study provides an overview of the coupled high‐resolution Version 1 of the Energy Exascale Earth System Model (E3SMv1) and documents the characteristics of a 50‐year‐long high‐resolution control simulation with time‐invariant 1950 forcings following the HighResMIP protocol. In terms of global root‐mean‐squared error metrics, this high‐resolution simulation is generally superior to results from the low‐resolution configuration of E3SMv1 (due to resolution, tuning changes, and possibly initialization procedure) and compares favorably to models in the CMIP5 ensemble. Ocean and sea ice simulation is particularly improved, due to better resolution of bathymetry, the ability to capture more variability and extremes in winds and currents, and the ability to resolve mesoscale ocean eddies. The largest improvement in this regard is an ice‐free Labrador Sea, which is a major problem at low resolution. Interestingly, several features found to improve with resolution in previous studies are insensitive to resolution or even degrade in E3SMv1. Most notable in this regard are warm bias and associated stratocumulus deficiency in eastern subtropical oceans and lack of improvement in El Niño. Another major finding of this study is that resolution increase had negligible impact on climate sensitivity (measured by net feedback determined through uniform +4K prescribed sea surface temperature increase) and aerosol sensitivity. Cloud response to resolution increase consisted of very minor decrease at all levels. Large‐scale patterns of precipitation bias were also relatively unaffected by grid spacing. Plain Language Summary The Energy Exascale Earth System Model (E3SM) is a relatively new fully coupled Earth system and climate model used in major international model simulation projects and mission‐defined efforts for the U.S. Department of Energy. This paper describes the first simulation of the model in its high‐resolution configuration. This higher‐resolution version is able to capture the most energetic motions in the ocean, which are poorly represented in standard resolution coupled climate models, as well as the largest of storms in the atmosphere. Evaluation of this simulation confirms the benefits of high resolution found by other models with a few notable exceptions. These discrepancies with other studies are interesting because they provide a richer understanding of how and why resolution affects model bias. Another key finding is that climate and aerosol sensitivity in E3SM is unaffected by resolution change. This affirms the usefulness of coarser‐resolution models for understanding global‐scale climate change. This study also confirms the benefits of increased resolution for studying fine‐scale features such as hurricanes and orographic precipitation. Finally, the high‐resolution version of E3SM is shown to compare favorably to its low‐resolution counterpart and to the models participating in Phase 5 of the Coupled Model Intercomparison Project. Key Points The high‐resolution E3SMv1 model was run for 50 years using 1950 forcing data according to the HighResMIP protocol Higher resolution and associated retuning improved bias relative to coarser versions of E3SMv1, particularly in ocean and sea ice metrics Aerosol and climate sensitivity were relatively unaffected by resolution change; resolution‐related tuning had a larger impact

Oceanic tides are seldom represented in Earth system models (ESMs) owing to the need for high horizontal resolution to accurately represent the associated barotropic waves close to coasts. This paper presents results of tides implemented in the Model for Prediction Across Scales–Ocean or MPAS-Ocean, which is the ocean component within the U.S. Department of Energy developed Energy Exascale Earth System Model (E3SM). MPAS-Ocean circumvents the limitation of low resolution using unstructured global meshing. We are at this stage simulating the largest semidiurnal (M2, S2, N2) and diurnal (K1, O1) tidal constituents in a single-layer version of MPAS-O. First, we show that the tidal constituents calculated using MPAS-Ocean closely agree with the results of the global tidal prediction model TPXO8 when suitably tuned topographic wave drag and bottom drag coefficients are employed. Thereafter, we present the sensitivity of global tidal evolution due to the presence of Antarctic ice shelf cavities. The effect of ice shelves on the amplitude and phase of tidal constituents are presented. Lower values of complex errors (with respect to TPXO8 results) for the M2 tidal constituents are observed when the ice shelf is added in the simulations, with particularly strong improvement in the Southern Ocean. Our work points towards future research with varying Antarctic ice shelf geometries and sea ice coupling that might lead to better comparison and prediction of tides and thus better prediction of sea-level rise and also the future climate variability.

A new collaborative organization for sea-ice model development, the CICE Consortium, has devised quality control procedures to maintain the integrity of its numerical codes’ physical representations, enabling broad participation from the scientific community in the Consortium’s open software development environment. Using output from five coupled and uncoupled configurations of the Los Alamos Sea Ice Model, CICE, we formulate quality control methods that exploit common statistical properties of sea-ice thickness, and test for significant changes in model results in a computationally efficient manner. New additions and changes to CICE are graded into four categories, ranging from bit-for-bit amendments to significant, answer-changing upgrades. These modifications are assessed using criteria that account for the high level of autocorrelation in sea-ice time series, along with a quadratic skill metric that searches for hemispheric changes in model answers across an array of different CICE configurations. These metrics also provide objective guidance for assessing new physical representations and code functionality. This article is part of the theme issue ‘Modelling of sea-ice phenomena’.