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Among the most critical issues, climatic abnormalities caused by global warming also affect Taiwan significantly for the past decade. The increasing frequency of extreme rainfall events, in which concentrated and intensive rainfalls generally cause geohazards including landslides and debris flows. The extraordinary Typhoon Morakot hit Southern Taiwan on 8 August 2009 and induced serious flooding and landslides. In this study, the Kao-Ping River watershed was adopted as the study area, and the typical events 2007 Krosa Typhoon and 2009 Morakot Typhoon were adopted to train the susceptibility model. This study employs rainfall frequency analysis together with the atmospheric general circulation model (AGCM) downscaling estimation to understand the temporal rainfall trends, distributions, and intensities in the Kao-Ping River watershed. The rainfall estimates were introduced in the landslide susceptibility model to produce the predictive landslide susceptibility for various rainfall scenarios, including abnormal climate conditions. These results can be used for hazard remediation, miti gation, and prevention plans for the Kao-Ping River watershed. [ABSTRACT FROM AUTHOR]

Almost all climate time series have some degree of nonstationarity due to external driving forces perturbations of the observed system. Therefore, these external driving forces should be taken into account when reconstructing the climate dynamics. This paper presents a new technique of combining the driving force of a time series obtained using the Slow Feature Analysis (SFA) approach, then introducing the driving force into a predictive model to predict non-stationary time series. In essence, the main idea of the technique is to consider the driving forces as state variables and incorporate them into the prediction model. To test the method, experiments using a modified logistic time series and winter ozone data in Arosa, Switzerland, were conducted. The results showed improved and effective prediction skill. [ABSTRACT FROM AUTHOR]

Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multimodel predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre) and an update of the project's results. Although designed to address Arctic predictability, this data set could also be used to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño Southern Oscillation. [ABSTRACT FROM AUTHOR]

Many atmospheric global circulation models have large biases in predicting meridional and vertical winds and fluxes of gas species in remote regions such as the middle and upper atmosphere. In this study, we make sensitivity simulations to recognize the role of vital processes associated with dynamical coupling between different atmospheric layers, namely dynamical and thermal impacts of mesoscale orographic gravity waves (OGWs) generated by the Earth's topography and changes from the easterly to westerly QBO phases in the lower equatorial atmosphere. We improved parameterizations of OGW dynamical and thermal effects and QBO flows and implemented them into a general circulation model of the middle and upper atmosphere used in different countries. With this model, we study the sensitivity of meridional circulation and vertical velocity to stationary OGWs and to changes in QBO phases at altitudes up to 100 km in January. We also considered respective changes in vertical ozone fluxes in the atmosphere. Accounting stationary OGW effects gives changes up to 40% in the meridional velocity and associated ozone fluxes in the stratosphere. Transitions from the easterly to westerly QBO phase in tropics may significantly alter the meridional and vertical circulation of the middle atmosphere at middle and high latitudes: up to 60% from the peak respective values. The improved parameterizations of OGW and QBO effects have impacts on other features of the general circulation model, improving the simulation of general circulation, planetary and tidal wave coupling in the lower, middle and upper atmosphere. [ABSTRACT FROM AUTHOR]

Numerical simulations provide a considerable aid in studying past climates. Out of the various approaches taken in designing numerical climate experiments, transient simulations have been found to be the most optimal when it comes to comparison with proxy data. However, multi-millennial or longer simulations using fully coupled general circulation models are computationally very expensive such that acceleration techniques are frequently applied. In this study, we compare the results from transient simulations of the present and the last interglacial with and without acceleration of the orbital forcing, using the comprehensive coupled climate model CCSM3 (Community Climate System Model 3). Our study shows that in most parts of the world, the simulation of long-term variations in interglacial surface climate is not significantly affected by the use of the acceleration technique (with an acceleration factor 10) and, hence, large-scale model-data comparison of surface variables is not hampered. However, in high-latitude regions where the surface climate has a direct connection to the deep ocean, e.g. in the Southern Ocean or the Nordic Seas, acceleration-induced biases in sea-surface temperature evolution may occur with potential influence on the dynamics of the overlying atmosphere. [ABSTRACT FROM AUTHOR]

The Ent Terrestrial Biosphere Model (Ent TBM) is a mixed-canopy dynamic global vegetation model developed specifically for coupling with land surface hydrology and general circulation models (GCMs). This study describes the leaf phenology submodel implemented in the Ent TBM version 1.0.1.0.0, coupled to the carbon allocation scheme of the Ecosystem Demography (ED) model. The phenology submodel adopts a combination of responses to temperature (growing degree days and frost-hardening), soil moisture (linearity of stress with relative saturation), and radiation (light length). Growth of leaves, sapwood, fine roots, stem wood, and coarse roots is updated on a daily basis. We evaluate the performance in reproducing observed leaf seasonal growth as well as water and carbon fluxes for four plant functional types at five Fluxnet sites, with both observed and prognostic hydrology, and observed and prognostic seasonal leaf area index. The phenology submodel is able to capture the timing and magnitude of leafout and senescence for temperate broadleaf deciduous forest (Harvard Forest and Morgan-Monroe State Forest, US), C3 annual grassland (Vaira Ranch, US), and California oak savanna (Tonzi Ranch, US). For evergreen needleleaf forest (Hyytiäla, Finland), the phenology submodel captures the effect of frost-hardening of photosynthetic capacity on seasonal fluxes and leaf area. We address the importance of customizing parameter sets of vegetation soil moisture stress response to the particular land surface hydrology scheme. We identify model deficiencies that reveal important dynamics and parameter needs. [ABSTRACT FROM AUTHOR]

MATS (Mesospheric Airglow/Aerosol Tomography and Spectroscopy) is a Swedish satellite designed to investigate atmospheric dynamics in the mesosphere and lower thermosphere (MLT). By observing structures in noctilucent clouds over polar regions and oxygen atmospheric-band (A-band) emissions globally, MATS will provide the research community with properties of the MLT atmospheric wave field. Individual A-band images taken by MATS's main instrument, a six-channel limb imager, are transformed through tomography and spectroscopy into three-dimensional temperature fields, within which the wave structures are embedded. To identify wave properties, particularly the gravity wave momentum flux, from the temperature field, smaller-scale perturbations (associated with the targeted waves) must be separated from large-scale background variations using a method of scale separation. This paper investigates the possibilities of employing a simple method based on smoothing polynomials to separate the smaller and larger scales. Using using synthetic tomography data based on the HIAMCM (HIgh Altitude Mechanistic general Circulation Model), we demonstrate that smoothing polynomials can be applied to MLT temperatures to obtain fields corresponding to global-scale separation at zonal wavenumber 18. The simplicity of the method makes it a promising candidate for studying wave dynamics in MATS temperature fields. [ABSTRACT FROM AUTHOR]

In this article we propose two conformal mapping based grid generation algorithms for global ocean general circulation models (OGCMs). Contrary to conventional, analytical forms based dipolar or tripolar grids, the new algorithms are based on Schwarz-Christoffel (SC) conformal mapping with prescribed boundary information. While dealing with the basic grid design problem of pole relocation, these new algorithms also address more advanced issues such as smoothed scaling factor, or the new requirements on OGCM grids arisen from the recent trend of high-resolution and multi-scale modeling. The proposed grid generation algorithm could potentially achieve the alignment of grid lines to coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the generated grids are still orthogonal curvilinear, they can be readily utilized in existing Bryan-Cox-Semtner type ocean models. The proposed methodology can also be applied to the grid generation task for regional ocean modeling where complex land-ocean distribution is present. [ABSTRACT FROM AUTHOR]

In this study we present first results of a new isotope-enabled general circulation model setup. The model consists of a fully coupled atmosphere-ocean model ECHAM5/MPIOM, enhanced by the interactive land surface scheme JSBACH and an explicit hydrological discharge scheme to close the global water budget. Stable water isotopes H182O and HDO have been incorporated into all relevant model components. Results of two equilibrium simulations under pre-industrial and last glacial maximum conditions are analysed and compared to observational data and paleoclimate records for evaluating the model's performance of simulating spatial and temporal variations in the isotopic composition of the Earth's water cycle. For the pre-industrial climate, many aspects of the simulation results of meteoric waters are in good to very good agreement with both observations and earlier atmosphere-only simulations. The model is capable of adequately simulating the large spread in the isotopic composition of precipitation between low and high latitudes. A comparison to available ocean data also shows a good model-data agreement, however a strong bias of too depleted ocean surface waters is detected for the Arctic region. Simulation results under last glacial maximum boundary conditions also fit to the wealth of available isotope records from polar ice cores, speleothems, as well as marine calcite data. Data-model evaluation of the isotopic composition in precipitation reveals a good match of the model results and indicates that the temporal glacial-interglacial isotope-temperature relation was substantially lower than the present spatial gradient for most mid- to high-latitudinal regions. As compared to older atmosphere-only simulations, a remarkable improvement is achieved for the modelling of the deuterium excess signal in Antarctic ice cores. Our simulation results indicate that cool sub-tropical and mid-latitudinal sea surface 25 temperatures are key for this progress. A recently discussed revised interpretation of the deuterium excess record of Antarctic ice cores in terms of marine relative humidity changes on glacial-interglacial timescales is not supported by our model results. [ABSTRACT FROM AUTHOR]

Seasonal and interannual variability in sinking flux of biogenic particles was reported by the multi-year bottom-tethered sediment trap measurements in the Northwind Abyssal Plain (Station NAP: 75°N, 162°W, 1975m water depth) of the western Arctic Chukchi Borderland. Whereas the trapped particle flux had an obvious peak with the dominance of sea ice-related diatom valve in August 2011, the observed particle flux was considerably suppressed throughout the summer season in 2012. In the present study, response of ice algal production and biomass to wind-driven changes in physical environments was addressed using a pan-Arctic sea ice-ocean modeling approach. Sea ice ecosystem with ice algae was newly incorporated into the lower-trophic marine ecosystem model, which was previously coupled with a high-resolution (i.e., horizontal grid size of 5 km) ocean general circulation model. Seasonal experiments covering two year-long mooring periods indicated that primary productivity of ice algae around the Chukchi Borderland depended on basin-scale wind pattern through various processes. Easterly wind in the southern part of distinct Beaufort High supplied high abundance of nutrient for euphotic zones of the NAP region via both surface Ekman transport of Chukchi shelf water and vertical turbulent mixing with underlying nutricline water as in 2011. In contrast, northwesterly wind flowing in the northern part of extended Siberian High transported oligotrophic water within the Beaufort Gyre circulation toward the NAP region as in 2012. The modeled ice algal biomass during the summer season certainly reflected the differences in nutrient distribution. The sinking flux of Particulate Organic Nitrogen (PON) was comparable with the time series obtained from the sediment trap data in summer 2011. On the other hand, lateral advection of shelf-origin ice algal patch during a great cyclone event might have caused a model bias on the PON flux in 2012. The extension of year-long measurements is expected to help the illustration of more general features on the Arctic marine biological pump. [ABSTRACT FROM AUTHOR]

All climate models use parameterizations and tuning in order to be accurate. The different parameterizations and tuning processes are the primary source of difference between models. Because models are tuned with present observations of Earth, they may not accurately simulate climates of other planets or palaeoclimate. A model with no adjustable parameter that happens to fit today's observations is probably more universal and should be more appropriate to model palaeoclimate. However, to our knowledge, such a model does not exist or is yet to be developed. This paper aims to improve a parameter-free radiative–convective model that computes a realistic temperature vertical profile to compute the water cycle, giving a value on average tropical precipitation. Although it is known that the radiative transfer constrains the order of magnitude of precipitation, no parameter-free model has yet been able to compute precipitation. Our model finds a precipitation value closer to observations than similar radiative–convective models or some general circulation models (GCMs). [ABSTRACT FROM AUTHOR]

This paper presents a stochastic approach for the aggregation process rate in the ICOsahedral Nonhydrostatic general circulation model (ICON-AES), which takes subgrid-scale variability into account. This method creates a stochastic parameterization of the process rate by choosing a new specific cloud ice mass at random from a uniform distribution function. This distribution, which is consistent with the model's cloud cover scheme, is evaluated in terms of cloud ice mass variance with a combined satellite retrieval product (DARDAR) from the satellite cloud radar CloudSat and the Cloud–Aerosol Lidar and Infrared Pathfinder Observations (CALIPSO). The global patterns of simulated and observed cloud ice mixing ratio variance are in a good agreement, despite an underestimation in the tropical regions, especially at lower altitudes, and an overestimation in higher latitudes from the modeled variance. Due to this stochastic approach the yearly mean of cloud ice shows an overall decrease. As a result of the nonlinear nature of the aggregation process, the yearly mean of the process rates increases when taking subgrid-scale variability into account. An increased process rate leads to a stronger transformation of cloud ice into snow and therefore to a cloud ice loss. The yearly averaged global mean aggregation rate is more than 20 % higher at selected pressure levels due to the stochastic approach. A strong interaction of aggregation and accretion, however, lowers the effect of cloud ice loss due to a higher aggregation rate. The new stochastic method presented lowers the bias of the aggregation rate. [ABSTRACT FROM AUTHOR]

This paper describes and analyzes the Reed–Jablonowski (RJ) tropical cyclone (TC) test case used in the 2016 Dynamical Core Model Intercomparison Project (DCMIP2016). This intermediate-complexity test case analyzes the evolution of a weak vortex into a TC in an idealized tropical environment. Reference solutions from nine general circulation models (GCMs) with identical simplified physics parameterization packages that participated in DCMIP2016 are analyzed in this study at 50 km horizontal grid spacing, with five of these models also providing solutions at 25 km grid spacing. Evolution of minimum surface pressure (MSP) and maximum 1 km azimuthally averaged wind speed (MWS), the wind–pressure relationship, radial profiles of wind speed and surface pressure, and wind composites are presented for all participating GCMs at both horizontal grid spacings. While all TCs undergo a similar evolution process, some reach significantly higher intensities than others, ultimately impacting their horizontal and vertical structures. TCs simulated at 25 km grid spacings retain these differences but reach higher intensities and are more compact than their 50 km counterparts. These results indicate that dynamical core choice is an essential factor in GCM development, and future work should be conducted to explore how specific differences within the dynamical core affect TC behavior in GCMs. [ABSTRACT FROM AUTHOR]

The development and verification of the convective module of IL-GLOBO, a Lagrangian transport model coupled online with the Eulerian general circulation model GLOBO, is described. The online-coupling promotes the full consistency between the Eulerian and the Lagrangian components of the model. The Lagrangian convective scheme is derived based on the Kain-Fritsch convective parameterisation used in GLOBO. A transition probability matrix is computed using the fluxes provided by the Eulerian KF parameterisation. Then, the convection redistribution of Lagrangian particles is implemented via a Monte Carlo scheme. The formal derivation is described in details and, consistently with the Eulerian module, includes the environmental flux in the transition probability matrix to avoid splitting of the convection and subsidence processes. Consistency of the Lagrangian implementation with its Eulerian counterpart is verified by computing environment fluxes from the transition probability matrix and comparing them to those computed by the Eulerian module. Assessment of the impact of the module is made for different latitudinal belts, showing that the major impact is found in the tropics, as expected. Concerning vertical distribution, the major impact is observed in the boundary layer at every latitude, while in the tropical area, the influence extends to very high levels. [ABSTRACT FROM AUTHOR]

Using climate-optimized flight trajectories is one essential measure to reduce aviation's climate impact. Detailed knowledge of temporal and spatial climate sensitivity for aviation emissions in the atmosphere is required to realize such a climate mitigation measure. The algorithmic Climate Change Functions (aCCFs) represent the basis for such purposes. This paper presents the first version of the Algorithmic Climate Change Function submodel (ACCF 1.0) within the European Centre HAMburg general circulation model (ECHAM) and Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model framework. In the ACCF 1.0, we implement a set of aCCFs (version 1.0) to estimate the average temperature response over 20 years (ATR20) resulting from aviation CO 2 emissions and non-CO 2 impacts, such as NO x emissions (via ozone production and methane destruction), water vapour emissions, and contrail cirrus. While the aCCF concept has been introduced in previous research, here, we publish a consistent set of aCCF formulas in terms of fuel scenario, metric, and efficacy for the first time. In particular, this paper elaborates on contrail aCCF development, which has not been published before. ACCF 1.0 uses the simulated atmospheric conditions at the emission location as input to calculate the ATR20 per unit of fuel burned, per NO x emitted, or per flown kilometre. In this research, we perform quality checks of the ACCF 1.0 outputs in two aspects. Firstly, we compare climatological values calculated by ACCF 1.0 to previous studies. The comparison confirms that in the Northern Hemisphere between 150–300 hPa altitude (flight corridor), the vertical and latitudinal structure of NO x -induced ozone and H 2 O effects are well represented by the ACCF model output. The NO x -induced methane effects increase towards lower altitudes and higher latitudes, which behaves differently from the existing literature. For contrail cirrus, the climatological pattern of the ACCF model output corresponds with the literature, except that contrail-cirrus aCCF generates values at low altitudes near polar regions, which is caused by the conditions set up for contrail formation. Secondly, we evaluate the reduction of NO x -induced ozone effects through trajectory optimization, employing the tagging chemistry approach (contribution approach to tag species according to their emission categories and to inherit these tags to other species during the subsequent chemical reactions). The simulation results show that climate-optimized trajectories reduce the radiative forcing contribution from aviation NO x -induced ozone compared to cost-optimized trajectories. Finally, we couple the ACCF 1.0 to the air traffic simulation submodel AirTraf version 2.0 and demonstrate the variability of the flight trajectories when the efficacy of individual effects is considered. Based on the 1 d simulation results of a subset of European flights, the total ATR20 of the climate-optimized flights is significantly lower (roughly 50 % less) than that of the cost-optimized flights, with the most considerable contribution from contrail cirrus. The CO 2 contribution observed in this study is low compared with the non-CO 2 effects, which requires further diagnosis. [ABSTRACT FROM AUTHOR]

In this paper we describe the implementation of the carbon isotopes 13 C and 14 C (radiocarbon) into the marine biogeochemistry model REcoM3. The implementation is tested in long-term equilibrium simulations where REcoM3 is coupled with the ocean general circulation model FESOM2.1, applying a low-resolution configuration and idealized climate forcing. Focusing on the carbon-isotopic composition of dissolved inorganic carbon (δ13 C DIC and Δ14 C DIC), our model results are largely consistent with reconstructions for the pre-anthropogenic period. Our simulations also exhibit discrepancies, e.g. in upwelling regions and the interior of the North Pacific. Some of these differences are due to the limitations of our ocean circulation model setup, which results in a rather shallow meridional overturning circulation. We additionally study the accuracy of two simplified modelling approaches for dissolved inorganic 14 C, which are faster (15 % and about a factor of five, respectively) than the complete consideration of the marine radiocarbon cycle. The accuracy of both simplified approaches is better than 5 %, which should be sufficient for most studies of Δ14 C DIC. [ABSTRACT FROM AUTHOR]

In this paper we introduce a new high-resolution (1/10 °) data-driven dataset of 3D ocean currents developed by the National Research Council of Italy in the framework of the European Space Agency World Ocean Circulation project: the WOC-NATL3D dataset. The product domain extends over a wide portion of the North Atlantic Ocean from the surface down to 1500 m depth, and the dataset covers the period between 2010 and 2019. To generate this product, a diabatic quasi-geostrophic diagnostic model is applied to data-driven 3D temperature and salinity fields obtained through a deep learning technique, along with ERA5 fluxes and empirical estimates of the horizontal Ekman currents based on input provided by the European Copernicus Marine Service. The assessment of WOC-NATL3D currents is performed by direct validation of the total horizontal velocities with independent drifter estimates at various depths (0, 15 and 1000 m) and by comparing them with existing reanalyses that are obtained through the assimilation of observations into ocean general circulation numerical models. Our estimates of the ageostrophic components of the flow improve the total horizontal velocity reconstruction, being more accurate and closer to observations than model reanalyses in the upper layers, also providing an indirect proof of the reliability of the resulting vertical velocities. The reconstructed WOC-NATL3D currents are freely available at 10.12770/0aa7daac-43e6-42f3-9f95-ef7da46bc702. [ABSTRACT FROM AUTHOR]

In this paper we develop a novel framework aimed to significantly reduce biases related to marine stratocumulus clouds in general circulation models (GCMs) while circumventing excessive computational cost requirements. Our strategy is to increase the horizontal resolution using a regionally refined mesh (RRM) over our region of interest in addition to using the Framework for Improvement by Vertical Enhancement (FIVE) to increase the vertical resolution only for specific physical processes that are important for stratocumulus. We apply the RRM off the coast of Peru in the southeastern Pacific, a region that climatologically contains the most marine stratocumulus in the subtropics. We find that our new modeling framework is able to replicate the results of our high-resolution benchmark simulation with much fidelity, while reducing the computational cost by several orders of magnitude. In addition, this framework is able to greatly reduce the long-standing biases associated with marine stratocumulus in GCMs when compared to the standard-resolution control simulation. [ABSTRACT FROM AUTHOR]

This paper evaluates barotropic tides simulated by a newly developed multi-layer ocean general circulation, ICON-O, and assesses processes and model configurations that can impact the quality of the simulated tides. Such an investigation is crucial for applications addressing internal tides that are much more difficult to evaluate than the barotropic tides. Although not specially tuned for tides and not constrained by any observations, ICON-O is capable of producing the main features of the open-ocean barotropic tides as described by the geographical distributions of amplitude, phase, and amphidromic points. An error analysis shows, however, that the open-ocean tides simulated by ICON-O are less accurate than those simulated by two other ocean general circulation models (OGCMs), especially when not properly adjusting the time step and the parameters used in the time-stepping scheme. Based on a suite of tidal experiments, we show that an increase in horizontal resolution only improves tides in shallow waters. Relevant for using ICON-O with its telescoping grid capacity, we show that spatial inhomogeneity does not deteriorate the quality of the simulated tides. We further show that implementing a parameterization of topographic wave drag improves the quality of the simulated tides in deep ocean independent of the model configuration used, whereas the implementation of a self-attraction and loading (SAL) parameterization in a low-resolution (40 km) version of ICON-O degrades the quality of tides in shallow ocean. Finally, we show that the quality of tides simulated by ICON-O with low resolution (40 km) can be significantly improved by adjusting the time step or the parameters in the time-stepping scheme used for obtaining the model solution. [ABSTRACT FROM AUTHOR]

In this paper we describe the implementation of the carbon isotopes 13C and 14C (radiocarbon) into the marine biogeochemistry model REcoM3. The implementation is tested in long-term equilibrium simulations where REcoM3 is coupled with the ocean general circulation model FESOM2.1, applying a low-resolution configuration and idealized climate forcing. Focusing on the carbon-isotopic composition of dissolved inorganic carbon (δ13CDIC and Δ14CDIC), our model results are largely consistent with reconstructions for the pre-anthropogenic period. Our simulations also exhibit discrepancies, e.g., in upwelling regions and the interior of the North Pacific. Some of these differences are due to the limitations of our ocean circulation model setup which results in a rather shallow meridional overturning circulation. We additionally study the accuracy of two simplified modelling approaches for dissolved inorganic 14C, which are faster (15 % and about a factor of five, respectively) than the complete consideration of the marine radiocarbon cycle. The accuracy of both simplified approaches is better than 5 % which should be sufficient for most studies of Δ14CDIC. [ABSTRACT FROM AUTHOR]

We introduce ModE-Sim (Modern Era SIMulations), a medium-sized ensemble of simulations with the atmospheric general circulation model ECHAM6 in its LR (low-resolution) version (T63; approx. 1.8 ∘ horizontal grid width with 47 vertical levels). At the lower boundary we use prescribed sea surface temperatures and sea ice that reflect observed values while accounting for uncertainties in these. Furthermore we use radiative forcings that also reflect observed values while accounting for uncertainties in the timing and strength of volcanic eruptions. The simulations cover the period from 1420 to 2009. With 60 ensemble members between 1420 and 1850 and 36 ensemble members from 1850 to 2009, ModE-Sim consists of 31 620 simulated years in total. ModE-Sim is suitable for many applications as its various subsets can be used as initial-condition and boundary-condition ensembles to study climate variability. The main intention of this paper is to give a comprehensive description of the experimental setup of ModE-Sim and to provide an evaluation, mainly focusing on the two key variables, 2 m temperature and precipitation. We demonstrate ModE-Sim's ability to represent their mean state, to produce a reasonable response to external forcings, and to sample internal variability. Through the example of heat waves, we show that the ensemble is even capable of capturing certain types of extreme events. [ABSTRACT FROM AUTHOR]

When anticyclonic conditions persist over mountainous regions in winter, cold-air pools (i.e. thermal inversion layers) develop in valleys and persist from a few days to a few weeks. During these persistent cold-air pool episodes (PCAPs) the atmosphere inside the valley is stable and vertical mixing is prevented, promoting the accumulation of pollutants close to the valley bottom and worsening air quality. It has been shown from reanalysis that the Greater Alpine Region has warmed by three degrees over the last four decades. The purpose of this paper is to address the impact of climate change on PCAPs until the end of this century for the alpine Grenoble valleys. The long-term projections produced with the general circulation model MPI downscaled over the Alps with the regional climate model MAR (Modεave;le Atmosphérique Régional) are used to perform a statistical study of PCAPs over the 21st century. The trends of the main characteristics of PCAPs, namely their duration, frequency, and intensity, are investigated for two future scenarios, SSP2-4.5 and SSP5-8.5. We find that the intensity of PCAPs over the 21st century displays a statistically significant decreasing trend for the SSP5-8.5 scenario only, with a very weak decay rate of 0.058 K km−1 decade−1. The impact of climate change on the detailed structure of PCAPs is next investigated by comparing two such episodes, in the past and around 2050 considering the worst-case scenario (SSP5-8.5). For this purpose, the WRF (Weather Research and Forecasting) model, forced by MAR, is used at a high resolution (111 m). The episodes are carefully selected so that a meaningful comparison can be performed. We find that these episodes present similar atmospheric circulation and heat deficit across the valley depth but different atmospheric stability and (therefore) a different inversion height. The future episode is characterised by stronger atmospheric stability and a lower inversion height and about 4 degrees warmer air both close to the surface and in altitude. Overall, this study shows that the atmosphere in the Grenoble valleys tends to be slightly less stable in the future, under the SSP5-8.5 scenario, but that intense PCAPs can still form. [ABSTRACT FROM AUTHOR]

Precipitation formation and fallout affects atmospheric flows through the release of latent heat and through the removal of mass from the atmosphere, but because the mass of water vapor is only a small fraction of the total mass of Earth's atmosphere, precipitation mass sinks are often neglected in theory and models. However, a small number of modeling studies suggest that water mass sources and sinks can intensify heavily-precipitating weather systems. These studies point to a need to more systematically verify the impact of neglecting precipitation mass sinks, particularly for warmer and moister climates in which precipitation rates can be much higher. In this paper, we add precipitation mass sources and sinks to an idealized general circulation model and examine their effects on steady-state midlatitude storm track statistics across a wide range of climates, including very warm climates. We find that modifying the model to include mass sources and sinks has no detectable effect on midlatitude variability or extremes, even in climates much warmer and moister than the modern. However, we find that a tenfold exaggeration of mass sources and sinks is sufficient to produce more intense midlatitude weather extremes and increase surface pressure variance. This result is consistent with theoretical potential vorticity analysis, which suggests that the dynamical effects of mass sources and sinks are much smaller than the dynamical effects of accompanying latent heating unless mass sinks are artificially amplified by at least a factor of 10. Finally, we use simulations of 'tropical cyclone worlds' to attempt to reconcile our results with earlier work showing stronger deepening in a simulation of a tropical cyclone case study when precipitation mass sinks were included. We demonstrate that abruptly 'turning on' mass sources and sinks can lead to stronger transient deepening in some individual storms (consistent with results of past work) but weaker transient deepening in other storms, without modifying the steady-state statistics of storms in equilibrium with the large-scale environment (consistent with our other results). Our results provide a firmer foundation for using general circulation models that neglect moist mass sources and sinks in climate simulations, even in climates much warmer than today, while leaving open the possibility that their inclusion might lead to short-term improvements in forecast skill. [ABSTRACT FROM AUTHOR]

Radiation schemes are physically important but computationally expensive components of weather and climate models. This has spurred efforts to replace them with a cheap emulator based on neural networks (NNs), obtaining large speed-ups, but at the expense of accuracy, energy conservation and generalization. An alternative approach, which is slower but more robust than full emulation, is to use NNs to predict optical properties but keep the radiative transfer equations. Recently, NNs were developed to replace the RRTMGP (Rapid Radiative Transfer Model for General circulation model applications–Parallel) gas optics scheme and shown to be accurate while improving speed. However, the evaluations were based solely on offline radiation computations. In this paper, we describe the implementation and prognostic evaluation of RRTMGP-NN in the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The new gas optics scheme was incorporated into ecRad, the modular ECMWF radiation scheme. Using two new methods to improve accuracy – a hybrid loss function designed to reduce radiative forcing errors and an early stopping method based on monitoring fluxes and heating rates with respect to a line-by-line benchmark – we train NN models on RRTMGP k distributions with reduced spectral resolutions. Offline evaluation of the new NN gas optics, RRTMGP-NN 2.0, shows a very high level of accuracy for clear-sky fluxes and heating rates. For instance, the RMSE in the shortwave surface downwelling flux is 0.78 W m -2 for RRTMGP and 0.80 W m -2 for RRTMGP-NN in a present-day scenario, while upwelling flux errors are actually smaller for the NN. Because our approach does not affect the treatment of clouds, no additional errors will be introduced for cloudy profiles. RRTMGP-NN closely reproduces radiative forcings for five important greenhouse gases across a wide range of concentrations such as 8×CO2. To assess the impact of different gas optics schemes in the IFS, four 1-year coupled ocean–atmosphere simulations were performed for each configuration. The results show that RRTMGP-NN and RRTMGP produce very similar model climates, with the differences being smaller than those between existing schemes and statistically insignificant for zonal means of single-level quantities such as surface temperature. The use of RRTMGP-NN speeds up ecRad by a factor of 1.5 compared to RRTMGP (the gas optics being almost 3 times faster) and is also faster than the older and less accurate RRTMG, which is used in the current operational cycle of the IFS. [ABSTRACT FROM AUTHOR]

Dansgaard–Oeschger (D–O) events, millennial-scale climate oscillations between stadial and interstadial conditions (of up to 10–15 ∘ C in amplitude at high northern latitudes), occurred throughout the Marine Isotope Stage 3 (MIS3; 27.8–59.4 ka) period. The climate modelling community up to now has not been able to answer the question of whether our climate models are too stable to simulate D–O events. To address this, this paper lays the ground-work for a MIS3 D–O protocol for general circulation models which are used in the International Panel for Climate Change (IPCC) assessments. We review the following: D–O terminology, community progress on simulating D–O events in these IPCC-class models (processes and published examples), and evidence about the boundary conditions under which D–O events occur. We find that no model exhibits D–O-like behaviour under pre-industrial conditions. Some, but not all, models exhibit D–O-like oscillations under MIS3 and/or full glacial conditions. Greenhouse gases and ice sheet configurations are crucial. However most models have not run simulations of long enough duration to be sure which models show D–O-like behaviour, under either MIS3 or full glacial states. We propose a MIS3 baseline protocol at 34 ka, which features low obliquity values, medium to low MIS3 greenhouse gas values, and the intermediate ice sheet configuration, which our review suggests are most conducive to D–O-like behaviour in models. We also provide a protocol for a second freshwater (Heinrich-event-preconditioned) experiment, since previous work suggests that this variant may be helpful in preconditioning a state in models which is conducive to D–O events. This review provides modelling groups investigating MIS3 D–O oscillations with a common framework, which is aimed at (1) maximising the chance of the occurrence of D–O-like events in the simulations, (2) allowing more precise model–data evaluation, and (3) providing an adequate central point for modellers to explore model stability. [ABSTRACT FROM AUTHOR]

We introduce ModE-Sim, a medium size ensemble of simulations with the atmospheric general circulation model ECHAM6 in its LR version (T63/approx. 1.8° horizontal with 47 vertical levels) that covers the period from 1420 to 2009. With 60 ensemble members between 1420 and 1850 and 36 ensemble members from 1850 to 2009 ModE-Sim consists of 31620 simulated years in total. The dataset forms the input for a data assimilation procedure that combines historical climate informations with additional constraints from a climate model to produce a novel gridded 3-dimensional dataset of the modern era. Additionally, ModE-Sim on its own is also suitable for many other applications as its various subsets can be used as initial condition and boundary condition ensemble to study climate variability. The main intention of this paper is to give a comprehensive description of the experimental setup of ModE-Sim and to provide an evaluation of the two key variables 2m-temperature and precipitation. We demonstrate ModE-Sims ability to represent their mean state, to produce a reasonable response to external forcings and to sample internal variability. At the example of heat waves we show that the ensemble is even capable of capturing extreme events. [ABSTRACT FROM AUTHOR]

Parameterized boundary layer turbulence and moist convection remain some of the largest sources of uncertainty in general circulation models. High-resolution climate modeling aims to reduce that uncertainty by explicitly attempting to resolve deep moist convective motions. An example of such a model is the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) with a target global resolution of 3.25 km, allowing for a more accurate representation of complex mesoscale deep convective dynamics. Yet, small-scale planetary boundary layer turbulence and shallow convection still need to be parameterized, which in SCREAM is accomplished through the turbulent-kinetic-energy-based (TKE-based) simplified higher-order closure (SHOC) – a simplified version of the assumed-double-Gaussian-PDF (probability density function) higher-order-closure method. In this paper, we implement a stochastic-multiplume mass-flux (MF) parameterization of dry and shallow convection in SCREAM to go beyond the limitations of double-Gaussian-PDF closures and couple it to SHOC (SHOC + MF). The new parameterization implemented in a single-column model type version of SCREAM produces results for two shallow cumulus convection cases (marine and continental shallow convection) that agree well with the reference data from large-eddy simulations, thus improving the general representation of the thermodynamic quantities and their turbulent fluxes as well as cloud macrophysics in the model. Furthermore, SHOC + MF parameterization shows weak sensitivity to the vertical grid resolution and model time step. [ABSTRACT FROM AUTHOR]

Ocean alkalinity enhancement (OAE) has recently gained attention as a potential method for carbon dioxide removal (CDR) at gigatonne (Gt) scale, with near-coast OAE operations being economically favorable due to proximity to mineral and energy sources. In this paper we study critical questions which determine the scale and viability of OAE. Which coastal locations are able to sustain a large flux of alkalinity at minimal pH and ΩArag (aragonite saturation) changes? What is the interference distance between adjacent OAE projects? How much CO2 is absorbed per unit of alkalinity added? How quickly does the induced CO2 deficiency equilibrate with the atmosphere? Choosing relatively conservative constraints on Δ pH or Δ Omega, we examine the limits of OAE using the ECCO LLC270 (0.3 ∘) global circulation model. We find that the sustainable OAE rate varies over 1–2 orders of magnitude between different coasts and exhibits complex patterns and non-local dependencies which vary from region to region. In general, OAE in areas of strong coastal currents enables the largest fluxes and depending on the direction of these currents, neighboring OAE sites can exhibit dependencies as far as 400 km or more. At these steady state fluxes most regional stretches of coastline are able to accommodate on the order of 10s to 100s of megatonnes of negative emissions within 300 km of the coast. We conclude that near-coastal OAE has the potential to scale globally to several Gt CO2 yr -1 of drawdown with conservative pH constraints, if the effort is spread over the majority of available coastlines. Depending on the location, we find a diverse set of equilibration kinetics, determined by the interplay of gas exchange and surface residence time. Most locations reach an uptake efficiency plateau of 0.6–0.8 mol CO2 per mol of alkalinity after 3–4 years, after which there is only slow additional CO2 uptake. Regions of significant downwelling (e.g., around Iceland) should be avoided by OAE deployments, as in such locations up to half of the CDR potential of OAE can be lost to bottom waters. The most ideal locations, reaching a molar uptake ratio of around 0.8, include North Madagascar, California, Brazil, Peru and locations close to the Southern Ocean such as Tasmania, Kerguelen and Patagonia, where the gas exchange appears to occur faster than the surface residence time. However, some locations (e.g., Hawaii) take significantly longer to equilibrate (up to 8–10 years) but can still eventually achieve high uptake ratios. [ABSTRACT FROM AUTHOR]

Wind stress and turbulent heat fluxes are the major driving forces that modify the ocean dynamics and thermodynamics. In the Nucleus for European Modelling of the Ocean (NEMO) ocean general circulation model, these turbulent air–sea fluxes (TASFs) can critically impact the simulated ocean characteristics. This paper investigates how the various bulk parameterizations used to calculate turbulent air-sea fluxes in NEMOv4 can lead to substantial differences in the estimation of sea surface temperatures (SSTs). Specifically, we study the contributions of different aspects and assumptions of the bulk parameterizations in driving the SST differences in the NEMO global model configuration at 1/4 ∘ of horizontal resolution. These aspects include the use of the skin temperature instead of the bulk SST in the computation of turbulent heat flux components and the estimation of wind stress and turbulent heat flux components, which vary in each parameterization due to different bulk transfer coefficients. The analysis of a set of short-term sensitivity experiments where the only change is related to one of the aspects of the bulk parameterizations shows that parameterization-related SST differences are primarily sensitive to wind stress differences and to the implementation of skin temperature in the computation of turbulent heat flux components. In addition, in order to highlight the role of SST–turbulent heat flux negative feedback at play in ocean simulations, we compare the TASF differences obtained using the NEMO ocean model with the estimations by , who compared the different bulk parameterizations using prescribed SSTs. Our estimations of turbulent heat flux differences between bulk parameterizations are weaker than those found by. [ABSTRACT FROM AUTHOR]

The newly developed fast Earth system model CLIMBER-X is presented. The climate component of CLIMBER-X consists of a 2.5-D semi-empirical statistical–dynamical atmosphere model, a 3-D frictional–geostrophic ocean model, a dynamic–thermodynamic sea ice model and a land surface model. All the model components are discretized on a regular lat–long grid with a horizontal resolution of 5∘×5∘. The model has a throughput of ∼ 10 000 simulation years per day on a single node with 16 CPUs on a high-performance computer and is designed to simulate the evolution of the Earth system on temporal scales ranging from decades to >100000 years. A comprehensive evaluation of the model performance for the present day and the historical period shows that CLIMBER-X is capable of realistically reproducing many observed climate characteristics, with results that generally lie within the range of state-of-the-art general circulation models. The analysis of model performance is complemented by a thorough assessment of climate feedbacks and model sensitivities to changes in external forcings and boundary conditions. Limitations and applicability of the model are critically discussed. CLIMBER-X also includes a detailed representation of the global carbon cycle and is coupled to an ice sheet model, which will be described in separate papers. CLIMBER-X is available as open-source code and is expected to be a useful tool for studying past climate changes and for the investigation of the long-term future evolution of the climate. [ABSTRACT FROM AUTHOR]

Mineral dust plays an important role in Earth system models and is linked to many components, including atmospheric wind speed, precipitation and radiation, surface vegetation cover and soil properties and oceanic biogeochemical systems. In this paper, the dust scheme in the first configuration of the United Kingdom Earth System Model UKESM1 is described, and simulations of dust and its radiative effects are presented and compared with results from the parallel coupled atmosphere–ocean general circulation model (GCM) HadGEM3-GC3.1. Not only changes in the driving model fields but also changes in the dust size distribution are shown to lead to considerable differences to the present-day dust simulations and to projected future changes. UKESM1 simulations produce a present-day, top-of-the-atmosphere (ToA) dust direct radiative effect (DRE – defined as the change in downward net flux directly due to the presence of dust) of 0.086 W m -2 from a dust load of 19.5 Tg. Under climate change pathways these values decrease considerably. In the 2081–2100 mean of the Shared Socioeconomic Pathway SSP5–8.45 ToA DRE reaches 0.048 W m -2 from a load of 15.1 Tg. In contrast, in HadGEM3-GC3.1 the present-day values of - 0.296 W m -2 and 15.0 Tg are almost unchanged at - 0.289 W m -2 and 14.5 Tg in the 2081–2100 mean. The primary mechanism causing the differences in future dust projections is shown to be the vegetation response, which dominates over the direct effects of warming in our models. Though there are considerable uncertainties associated with any such estimates, the results presented demonstrate both the importance of the size distribution for dust modelling and also the necessity of including Earth system processes such as interactive vegetation in dust simulations for climate change studies. [ABSTRACT FROM AUTHOR]

In climate models, subgrid parameterizations of convection and clouds are one of the main causes of the biases in precipitation and atmospheric circulation simulations. In recent years, due to the rapid development of data science, machine learning (ML) parameterizations for convection and clouds have been demonstrated to have the potential to perform better than conventional parameterizations. Most previous studies were conducted on aqua-planet and idealized models, and the problems of simulation instability and climate drift still exist. Developing an ML parameterization scheme remains a challenging task in realistically configured models. In this paper, a set of residual deep neural networks (ResDNNs) with a strong nonlinear fitting ability is designed to emulate a super-parameterization (SP) with different outputs in a hybrid ML–physical general circulation model (GCM). It can sustain stable simulations for over 10 years under real-world geographical boundary conditions. We explore the relationship between the accuracy and stability by validating multiple deep neural network (DNN) and ResDNN sets in prognostic runs. In addition, there are significant differences in the prognostic results of the stable ResDNN sets. Therefore, trial and error is used to acquire the optimal ResDNN set for both high skill and long-term stability, which we name the neural network (NN) parameterization. In offline validation, the neural network parameterization can emulate the SP in mid- to high-latitude regions with a high accuracy. However, its prediction skill over tropical ocean areas still needs improvement. In the multi-year prognostic test, the hybrid ML–physical GCM simulates the tropical precipitation well over land and significantly improves the frequency of the precipitation extremes, which are vastly underestimated in the Community Atmospheric Model version 5 (CAM5), with a horizontal resolution of 1.9 ∘ × 2.5 ∘. Furthermore, the hybrid ML–physical GCM simulates the robust signal of the Madden–Julian oscillation with a more reasonable propagation speed than CAM5. However, there are still substantial biases with the hybrid ML–physical GCM in the mean states, including the temperature field in the tropopause and at high latitudes and the precipitation over tropical oceanic regions, which are larger than those in CAM5. This study is a pioneer in achieving multi-year stable climate simulations using a hybrid ML–physical GCM under actual land–ocean boundary conditions that become sustained over 30 times faster than the target SP. It demonstrates the emerging potential of using ML parameterizations in climate simulations. [ABSTRACT FROM AUTHOR]

Most radiation schemes in weather and climate models use the "correlated k distribution" (CKD) method to treat gas absorption, which approximates a broadband spectral integration by N pseudo-monochromatic calculations. Larger N means more accuracy and a wider range of gas concentrations can be simulated but at greater computational cost. Unfortunately, the tools to perform this efficiency–accuracy trade-off (e.g. to generate separate CKD models for applications such as short-range weather forecasting to climate modelling) are unavailable to the vast majority of users of radiation schemes. This paper describes the experimental protocol for the Correlated K-Distribution Model Intercomparison Project (CKDMIP), whose purpose is to use benchmark line-by-line calculations: (1) to evaluate the accuracy of existing CKD models, (2) to explore how accuracy varies with N for CKD models submitted by CKDMIP participants, (3) to understand how different choices in the way that CKD models are generated affect their accuracy for the same N , and (4) to generate freely available datasets and software facilitating the development of new gas-optics tools. The datasets consist of the high-resolution longwave and shortwave absorption spectra of nine gases for a range of atmospheric conditions, realistic and idealized. Thirty-four concentration scenarios for the well-mixed greenhouse gases are proposed to test CKD models from palaeo- to future-climate conditions. We demonstrate the strengths of the protocol in this paper by using it to evaluate the widely used Rapid Radiative Transfer Model for General Circulation Models (RRTMG). [ABSTRACT FROM AUTHOR]

Anticipating risks related to climate extremes often relies on the quantification of large return levels (values exceeded with small probability) from climate projection ensembles. Current approaches based on multi-model ensembles (MMEs) usually estimate return levels separately for each climate simulation of the MME. In contrast, using MME obtained with different combinations of general circulation model (GCM) and regional climate model (RCM), our approach estimates return levels together from the past observations and all GCM–RCM pairs, considering both historical and future periods. The proposed methodology seeks to provide estimates of projected return levels accounting for the variability of individual GCM–RCM trajectories, with a robust quantification of uncertainties. To this aim, we introduce a flexible non-stationary generalized extreme value (GEV) distribution that includes (i) piecewise linear functions to model the changes in the three GEV parameters and (ii) adjustment coefficients for the location and scale parameters to adjust the GEV distributions of the GCM–RCM pairs with respect to the GEV distribution of the past observations. Our application focuses on snow load at 1500 m elevation for the 23 massifs of the French Alps. Annual maxima are available for 20 adjusted GCM–RCM pairs from the EURO-CORDEX experiment under the scenario Representative Concentration Pathway (RCP) 8.5. Our results show with a model-as-truth experiment that at least two linear pieces should be considered for the piecewise linear functions. We also show, with a split-sample experiment, that eight massifs should consider adjustment coefficients. These two experiments help us select the GEV parameterizations for each massif. Finally, using these selected parameterizations, we find that the 50-year return level of snow load is projected to decrease in all massifs by -2.9 kN m -2 (-50 %) on average between 1986–2005 and 2080–2099 at 1500 m elevation and RCP8.5. This paper extends the recent idea to constrain climate projection ensembles using past observations to climate extremes. [ABSTRACT FROM AUTHOR]

A critical stage in the development of our ability to model and project climate change occurred in the late 1950s–early 1960s when the first primitive-equation atmospheric general circulation models (AGCMs) were created. A rather idiosyncratic project to develop an AGCM was conducted virtually alone by Cecil E. Leith starting near the end of the 1950s. The Leith atmospheric model (LAM) appears to have been the first primitive-equation AGCM with a hydrological cycle and the first with a vertical resolution extending above the tropopause. It was certainly the first AGCM with a diurnal cycle, the first with prognostic clouds, and the first to be used as the basis for computer animations of the results. The LAM project was abandoned in approximately 1965, and it left almost no trace in the journal literature. Remarkably, the recent internet posting of a half-century-old computer animation of LAM-simulated fields represents the first significant "publication" of results from this model. This paper summarizes what is known about the history of the LAM based on the limited published articles and reports as well as transcripts of interviews with Leith and others conducted in the 1990s and later. [ABSTRACT FROM AUTHOR]

In this paper we introduce a new high-resolution (1/10?) data-driven dataset of 3D ocean currents developed by the National Research Council of Italy in the framework of the European Space Agency World Ocean Circulation project: the WOC-NATL3D dataset. The product domain extends over a wide portion of the North Atlantic Ocean from the surface down to 1500 m depth, and the dataset covers the period between 2010 and 2019. To generate this product, a diabatic quasi-geostrophic diagnostic model is applied to data-driven 3D temperature and salinity fields obtained through a deep learning technique, along with ERA5 fluxes and empirical estimates of the horizontal Ekman currents based on input provided by the European Copernicus Marine Service. The assessment of WOC-NATL3D currents is performed by direct validation of the total horizontal velocities with independent drifter estimates at various depths (0, 15 and 1000 m) and by comparing them with existing reanalyses that are obtained through the assimilation of observations into ocean general circulation numerical models. Our estimates of the ageostrophic components of the flow improve the total horizontal velocity reconstruction, being more accurate and closer-to-observations than model reanalyses in the upper layers, also providing an indirect proof of the reliability of the resulting vertical velocities. The reconstructed WOC-NATL3D currents are freely available at https://www.worldocean circulation.org/Products#/metadata/0aa7daac-43e6-42f3-9f95-ef7da46bc702 (Buongiorno Nardelli, 2022). [ABSTRACT FROM AUTHOR]

In this paper, we show that the projected global temperature change from CMIP5 models is remarkably similar to that obtained using simple regression models relating the global temperature to the atmospheric concentrations of CO2. This result is strengthened when we consider the projections obtained using the CMIP6 models. [ABSTRACT FROM AUTHOR]

The Eastern Mediterranean surface circulation is highly energetic, composed of structures interacting stochastically. However, some main features are still debated, and the behavior of some fine-scale dynamics and their role in shaping the general circulation is yet unknown. In the following paper, we use an unsupervised neural network clustering method to analyze the long-term variability of the different mesoscale structures. We decompose 26 years of altimetric data into clusters reflecting different circulation patterns of weak and strong flows with either strain or vortex-dominated velocities. The vortex-dominated cluster is more persistent in the western part of the basin, which is more active than the eastern part due to the strong flow along the coast, interacting with the extended bathymetry and engendering continuous instabilities. The cluster that reflects a weak flow dominated the middle of the basin, including the Mid-Mediterranean Jet (MMJ) pathway. However, the temporal analysis shows a frequent and intermittent occurrence of a strong flow in the middle of the basin, which could explain the previous contradictory assessment of MMJ existence using in-situ observations. Moreover, we prove that the Levantine Sea is becoming more and more energetic as the activity of the main mesoscale features is showing a positive trend. [ABSTRACT FROM AUTHOR]

In the southern winter polar stratosphere, the distribution of gravity wave momentum flux in many state-of-the-art climate simulations is inconsistent with long-time satellite and superpressure balloon observations around 60 ∘ S. Recent studies hint that a lateral shift between prominent gravity wave sources in the tropospheric mid-latitudes and the location where gravity wave activity is present in the stratosphere causes at least part of the discrepancy. This lateral shift cannot be represented by the column-based gravity wave drag parameterisations used in most general circulation models. However, recent high-resolution analysis and re-analysis products of the European Centre for Medium-Range Weather Forecasts Integrated Forecast System (ECMWF-IFS) show good agreement with the observations and allow for a detailed investigation of resolved gravity waves, their sources, and propagation paths. In this paper, we identify resolved gravity waves in the ECMWF-IFS analyses for a case of high gravity wave activity in the lower stratosphere using small-volume sinusoidal fits to characterise these gravity waves. The 3D wave vector together with perturbation amplitudes, wave frequency, and a fully described background atmosphere are then used to initialise the Gravity Wave Regional or Global Ray Tracer (GROGRAT) gravity wave ray tracer and follow the gravity waves backwards from the stratosphere. Finally, we check for the indication of source processes on the path of each ray and, thus, quantitatively attribute gravity waves to sources that are represented within the model. We find that stratospheric gravity waves are indeed subject to far (>1000 km) lateral displacement from their sources, which already take place at low altitudes (<20 km). Various source processes can be linked to waves within stratospheric gravity wave (GW) patterns, such as the orography equatorward of 50 ∘ S and non-orographic sources above the Southern Ocean. These findings may explain why superpressure balloons observe enhanced gravity wave momentum fluxes in the lower stratosphere over the Southern Ocean despite an apparent lack of sources at this latitude. Our results also support the need to improve gravity wave parameterisations to account for meridional propagation. [ABSTRACT FROM AUTHOR]

General circulation models (GCMs) are routinely run under Atmospheric Modelling Intercomparison Project (AMIP) conditions with prescribed sea surface temperatures (SSTs) and sea ice concentrations (SICs) from observations. These AMIP simulations are often used to evaluate the role of the land and/or atmosphere in causing the development of systematic errors in such GCMs. Extensions to the original AMIP experiment have also been developed to evaluate the response of the global climate to increased SSTs (prescribed) and carbon dioxide (CO2) as part of the Cloud Feedback Model Intercomparison Project (CFMIP). None of these international modelling initiatives has undertaken a set of experiments where the land conditions are also prescribed, which is the focus of the work presented in this paper. Experiments are performed initially with freely varying land conditions (surface temperature, and soil temperature and moisture) under five different configurations (AMIP, AMIP with uniform 4K added to SSTs, AMIP SST with quadrupled CO2, AMIP SST and quadrupled CO2 without the plant stomata response, and increasing the solar constant by 3.3%). Then, the land surface temperatures from the free land experiments are used to perform a set of "AMIP prescribed land" (PL) simulations, which are evaluated against their free land counterparts. The PL simulations agree well with the free land experiments, which indicates that the land surface is prescribed in a way that is consistent with the original free land configuration. Further experiments are also performed with different combinations of SSTs, CO2 concentrations, solar constant and land conditions. For example, SST and land conditions are used from the AMIP simulation with quadrupled CO2 in order to simulate the atmospheric response to increased CO2 concentrations without the surface temperature changing. The results of all these experiments have been made publicly available for further analysis. The main aims of this paper are to provide a description of the method used and an initial validation of these AMIP prescribed land experiments. [ABSTRACT FROM AUTHOR]

This paper describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the pre-industrial era and the recent past. In addition, meteorology is available for the near future and end of the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport, and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) product and with observational constraints. [ABSTRACT FROM AUTHOR]

This paper investigates the potential of a Wasserstein generative adversarial network to produce realistic weather situations when trained from the climate of a general circulation model (GCM). To do so, a convolutional neural network architecture is proposed for the generator and trained on a synthetic climate database, computed using a simple three dimensional climate model: PLASIM. The generator transforms a "latent space", defined by a 64-dimensional Gaussian distribution, into spatially defined anomalies on the same output grid as PLASIM. The analysis of the statistics in the leading empirical orthogonal functions shows that the generator is able to reproduce many aspects of the multivariate distribution of the synthetic climate. Moreover, generated states reproduce the leading geostrophic balance present in the atmosphere. The ability to represent the climate state in a compact, dense and potentially nonlinear latent space opens new perspectives in the analysis and handling of the climate. This contribution discusses the exploration of the extremes close to a given state and how to connect two realistic weather situations with this approach. [ABSTRACT FROM AUTHOR]

Lockdowns to avoid the spread of COVID-19 have created an unprecedented reduction in human emissions. While the country-level scale of emissions changes can be estimated in near real time, the more detailed, gridded emissions estimates that are required to run general circulation models (GCMs) of the climate will take longer to collect. In this paper we use recorded and projected country-and-sector activity levels to modify gridded predictions from the MESSAGE-GLOBIOM SSP2-4.5 scenario. We provide updated projections for concentrations of greenhouse gases, emissions fields for aerosols, and precursors and the ozone and optical properties that result from this. The code base to perform similar modifications to other scenarios is also provided. We outline the means by which these results may be used in a model intercomparison project (CovidMIP) to investigate the impact of national lockdown measures on climate, including regional temperature, precipitation, and circulation changes. This includes three strands: an assessment of short-term effects (5-year period) and of longer-term effects (30 years) and an investigation into the separate effects of changes in emissions of greenhouse gases and aerosols. This last strand supports the possible attribution of observed changes in the climate system; hence these simulations will also form part of the Detection and Attribution Model Intercomparison Project (DAMIP). [ABSTRACT FROM AUTHOR]

Weather forecasts rely heavily on general circulation models of the atmosphere and other components of the Earth system. National meteorological and hydrological services and intergovernmental organizations, such as the European Centre for Medium-Range Weather Forecasts (ECMWF), provide routine operational forecasts on a range of spatio-temporal scales by running these models at high resolution on state-of-the-art high-performance computing systems. Such operational forecasts are very demanding in terms of computing resources. To facilitate the use of a weather forecast model for research and training purposes outside the operational environment, ECMWF provides a portable version of its numerical weather forecast model, OpenIFS, for use by universities and other research institutes on their own computing systems. In this paper, we describe a new project (OpenIFS@home) that combines OpenIFS with a citizen science approach to involve the general public in helping conduct scientific experiments. Volunteers from across the world can run OpenIFS@home on their computers at home, and the results of these simulations can be combined into large forecast ensembles. The infrastructure of such distributed computing experiments is based on our experience and expertise with the climate prediction.net (https://www.climateprediction.net/ , last access: 1 June 2021) and weather@home systems. In order to validate this first use of OpenIFS in a volunteer computing framework, we present results from ensembles of forecast simulations of Tropical Cyclone Karl from September 2016 studied during the NAWDEX field campaign. This cyclone underwent extratropical transition and intensified in mid-latitudes to give rise to an intense jet streak near Scotland and heavy rainfall over Norway. For the validation we use a 2000-member ensemble of OpenIFS run on the OpenIFS@home volunteer framework and a smaller ensemble of the size of operational forecasts using ECMWF's forecast model in 2016 run on the ECMWF supercomputer with the same horizontal resolution as OpenIFS@home. We present ensemble statistics that illustrate the reliability and accuracy of the OpenIFS@home forecasts and discuss the use of large ensembles in the context of forecasting extreme events. [ABSTRACT FROM AUTHOR]

Evaluating land surface models (LSMs) using available observations is important for understanding the potential and limitations of current Earth system models in simulating water- and carbon-related variables. To reveal the error sources of a LSM, five essential climate variables have been evaluated in this paper (i.e., surface soil moisture, evapotranspiration, leaf area index, surface albedo, and precipitation) via simulations with the IPSL (Institute Pierre Simon Laplace) LSM ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) model, particularly focusing on the difference between (i) forced simulations with atmospheric forcing data (WATCH Forcing Data ERA-Interim – WFDEI) and (ii) coupled simulations with the IPSL atmospheric general circulation model. Results from statistical evaluation, using satellite- and ground-based reference data, show that ORCHIDEE is well equipped to represent spatiotemporal patterns of all variables in general. However, further analysis against various landscape and meteorological factors (e.g., plant functional type, slope, precipitation, and irrigation) suggests potential uncertainty relating to freezing and/or snowmelt, temperate plant phenology, irrigation, and contrasted responses between forced and coupled mode simulations. The biases in the simulated variables are amplified in the coupled mode via surface–atmosphere interactions, indicating a strong link between irrigation–precipitation and a relatively complex link between precipitation–evapotranspiration that reflects the hydrometeorological regime of the region (energy limited or water limited) and snow albedo feedback in mountainous and boreal regions. The different results between forced and coupled modes imply the importance of model evaluation under both modes to isolate potential sources of uncertainty in the model. [ABSTRACT FROM AUTHOR]

This paper describes and analyzes the Reed-Jablonowski (RJ) tropical cyclone (TC) test case used in the 2016 Dynamical Core Model Intercomparison Project (DCMIP2016). The intermediate complexity test case analyzes the evolution of a weak vortex into a TC in an idealized tropical environment. Simulations from general circulation models (GCMs) that participated in DCMIP2016 are analyzed in this study at 50 km horizontal grid spacing, with 5 of these models also providing simulations at 25 5 km grid spacing for an analysis on the impact of finer grid spacing. Evolution of minimum surface pressure (MSP) and maximum 1 km azimuthally averaged wind speed (MWS), the wind-pressure relationship, radial profiles of wind speed and surface pressure, and wind composites are documented for all participating GCMs at both horizontal grid spacings. While results are generally similar between all models, some GCMs reach significantly higher storm intensities than others, ultimately impacting specific characteristics of their horizontal and vertical structure. TCs simulated at 25 km grid spacings retained these differences, but reach higher intensities and are more compact than their 50 km counterparts. These results indicate dynamical core choice is an essential factor in GCM development, and future work should be conducted to explore how specific differences within the dynamical core affect TC behavior in GCMs. [ABSTRACT FROM AUTHOR]

When solving hydrodynamic equations in spherical or cylindrical geometry using explicit finite-difference schemes, a major difficulty is that the time step is greatly restricted by the clustering of azimuthal cells near the pole due to the Courant–Friedrichs–Lewy condition. This paper adapts the azimuthal averaging–reconstruction (ring average) technique to finite-difference schemes in order to mitigate the time step constraint in spherical and cylindrical coordinates. The finite-difference ring average technique averages physical quantities based on an effective grid and then reconstructs the solution back to the original grid in a piecewise, monotonic way. The algorithm is implemented in a community upper-atmospheric model, the Thermosphere–Ionosphere Electrodynamics General Circulation Model (TIEGCM), with a horizontal resolution up to 0.625∘×0.625∘ in geographic longitude–latitude coordinates, which enables the capability of resolving critical mesoscale structures within the TIEGCM. Numerical experiments have shown that the ring average technique introduces minimal artifacts in the polar region of general circulation model (GCM) solutions, which is a significant improvement compared to commonly used low-pass filtering techniques such as the fast Fourier transform method. Since the finite-difference adaption of the ring average technique is a post-solver type of algorithm, which requires no changes to the original computational grid and numerical algorithms, it has also been implemented in much more complicated models with extended physical–chemical modules such as the Coupled Magnetosphere–Ionosphere–Thermosphere (CMIT) model and the Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension (WACCM-X). The implementation of ring average techniques in both models enables CMIT and WACCM-X to perform global simulations with a much higher resolution than that used in the community versions. The new technique is not only a significant improvement in space weather modeling capability, but it can also be adapted to more general finite-difference solvers for hyperbolic equations in spherical and polar geometries. Highlights. The ring average technique is adapted to solve the issue of clustered grid cells in polar and spherical coordinates with a finite-difference method. The ring average technique is applied to develop a 0.625∘×0.625∘ high-resolution TIEGCM and more complicated geoscientific models with polar and spherical coordinates as well as finite-difference numerical schemes. The high-resolution TIEGCM shows good capability in resolving mesoscale structures in the ionosphere–thermosphere (I–T) system. [ABSTRACT FROM AUTHOR]

The Arctic regional coupled sea-ice–ocean–atmosphere model (ArcIOAM) has been developed to provide reliable Arctic sea ice prediction on seasonal timescales. The description and implementation of ArcIOAM and its preliminary results for the year of 2012 are presented in this paper. In the ArcIOAM configuration, the Community Coupler 2 (C-Coupler2) is used to couple the Arctic sea-ice–oceanic configuration of the MITgcm (Massachusetts Institute of Technology general circulation model) with the Arctic atmospheric configuration of the Polar WRF (Weather Research and Forecasting) model. A scalability test is performed to investigate the parallelization of the coupled model. As the first step toward reliable Arctic seasonal sea ice prediction, ArcIOAM, implemented with two-way coupling strategy along with one-way coupling strategy, is evaluated with respect to available observational data and reanalysis products for the year of 2012. A stand-alone MITgcm run with prescribed atmospheric forcing is performed for reference. From the comparison, all the experiments simulate reasonable evolution of sea ice and ocean states in the Arctic region over a 1-year simulation period. The two-way coupling has better performance in terms of sea ice extent, concentration, thickness and sea surface temperature (SST), especially in summer. This result indicates that sea-ice–ocean–atmosphere interaction plays a crucial role in controlling Arctic summertime sea ice distribution. [ABSTRACT FROM AUTHOR]

A simplified model of the atmospheric boundary layer (ABL) of intermediate complexity between a bulk parameterization and a three-dimensional atmospheric model is developed and integrated to the Nucleus for European Modelling of the Ocean (NEMO) general circulation model. An objective in the derivation of such a simplified model, called ABL1d, is to reach an apt representation in ocean-only numerical simulations of some of the key processes associated with air–sea interactions at the characteristic scales of the oceanic mesoscale. In this paper we describe the formulation of the ABL1d model and the strategy to constrain this model with large-scale atmospheric data available from reanalysis or real-time forecasts. A particular emphasis is on the appropriate choice and calibration of a turbulent closure scheme for the atmospheric boundary layer. This is a key ingredient to properly represent the air–sea interaction processes of interest. We also provide a detailed description of the NEMO-ABL1d coupling infrastructure and its computational efficiency. The resulting simplified model is then tested for several boundary-layer regimes relevant to either ocean–atmosphere or sea-ice–atmosphere coupling. The coupled system is also tested with a realistic 0.25∘ resolution global configuration. The numerical results are evaluated using standard metrics from the literature to quantify the wind–sea-surface-temperature (a.k.a. thermal feedback effect), wind–current (a.k.a. current feedback effect), and ABL–sea-ice couplings. With respect to these metrics, our results show very good agreement with observations and fully coupled ocean–atmosphere models for a computational overhead of about 9 % in terms of elapsed time compared to standard uncoupled simulations. This moderate overhead, largely due to I/O operations, leaves room for further improvement to relax the assumption of horizontal homogeneity behind ABL1d and thus to further improve the realism of the coupling while keeping the flexibility of ocean-only modeling. [ABSTRACT FROM AUTHOR]