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The STatistical Analogue Resampling Scheme (STARS) statistical approach was recently used to project changes of climate variables in Germany corresponding to a supposed degree of warming. We show by theoretical and empirical analysis that STARS simply transforms interannual gradients between warmer and cooler seasons into climate trends. According to STARS projections, summers in Germany will inevitably become dryer and winters wetter under global warming. Due to the dominance of negative interannual correlations between precipitation and temperature during the year, STARS has a tendency to generate a net annual decrease in precipitation under mean German conditions. Furthermore, according to STARS, the annual level of global radiation would increase in Germany. STARS can be still used, e.g., for generating scenarios in vulnerability and uncertainty studies. However, it is not suitable as a climate downscaling tool to access risks following from changing climate for a finer than general circulation model (GCM) spatial scale. [ABSTRACT FROM AUTHOR]

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]

I/O is often a performance bottleneck in global ocean circulation models with fine spatial resolution. In this paper, we present an asynchronous parallel I/O framework and demonstrate its efficacy in the Mass Conservation Ocean Model (MaCOM) as a case study. By largely reducing I/O operations in computing processes and overlapping output in I/O processes with computation in computing processes, this framework significantly improves the performance of the MaCOM. Through both reordering output data for maintaining data continuity and combining file access for reducing file operations, the I/O optimizing algorithms are provided to improve output bandwidth. In the case study of the MaCOM, the cost of output in I/O processes can be overlapped by up to 99% with computation in computing processes as decreasing output frequency. The 1D data output bandwidth with these I/O optimizing algorithms is 3.1 times faster than before optimization at 16 I/O worker processes. Compared to the synchronous parallel I/O framework, the overall performance of MaCOM is improved by 38.8% at 1024 computing processes for a 7-day global ocean forecast with 1 output every 2 h through the asynchronous parallel I/O framework presented in this paper. [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]

The atmospheric Green's function method is a technique for modeling the response of the atmosphere to changes in the spatial field of surface temperature. While early studies applied this method to changes in atmospheric circulation, it has also become an important tool to understand changes in radiative feedbacks due to evolving patterns of warming, a phenomenon called the "pattern effect." To better study this method, this paper presents a protocol for creating atmospheric Green's functions to serve as the basis for a model intercomparison project, GFMIP. The protocol has been developed using a series of sensitivity tests performed with the HadAM3 atmosphere‐only general circulation model, along with existing and new simulations from other models. Our preliminary results have uncovered nonlinearities in the response of the atmosphere to surface temperature changes, including an asymmetrical response to warming versus cooling patch perturbations, and a change in the dependence of the response on the magnitude and size of the patches. These nonlinearities suggest that the pattern effect may depend on the heterogeneity of warming as well as its location. These experiments have also revealed tradeoffs in experimental design between patch size, perturbation strength, and the length of control and patch simulations. The protocol chosen on the basis of these experiments balances scientific utility with the simulation time and setup required by the Green's function approach. Running these simulations will further our understanding of many aspects of atmospheric response, from the pattern effect and radiative feedbacks to changes in circulation, cloudiness, and precipitation. Plain Language Summary: Many properties of the atmosphere are affected by the temperature of the ocean surface. Knowing how strong these effects are would help us to better predict global warming. The response to a given surface warming depends on where the warming occurs. To account for this, researchers sometimes simulate the response to individual patches of warming and then assume the response to an arbitrary warming pattern can be summed together from these patch responses. This is sometimes called the atmospheric Green's function method, and it works well at recreating the atmospheric response to historical temperature changes. We are organizing a Green's Function Model Intercomparison Project (GFMIP), in which participants will apply the method consistently for many climate models. This paper presents the GFMIP protocol. In the course of developing this protocol, we found that the atmospheric response to warming is not proportional in all cases: the response to surface warming is not the opposite of the response to surface cooling; warming twice as much doesn't cause twice as much of a response; and making a patch of warming twice as large doesn't cause twice as large a response. GFMIP will help us figure out how to account for this nonlinearity. Key Points: The Green's Function Model Intercomparison Project (GFMIP) explores the atmospheric response to surface temperature patch perturbationsThis paper presents the GFMIP protocol, which was generated using insights from past studies and new sensitivity testsGreen's functions reconstruct the response to historical temperatures, but nonlinearities can affect responses to other warming patterns [ABSTRACT FROM AUTHOR]

This paper introduces a novel ensemble adjustment Kalman filter (EAKF) that integrates a machine-learning approach. The conventional EAKF adopts linear and Gaussian assumptions, making it difficult to handle cross-component updates in strongly coupled data assimilation (SCDA). The new approach employs nonlinear variable relationships established by a deep neural network (DNN) during the analysis stage of the EAKF, which nonlinearly projects observation increments into the state variable space. It can diminish errors in estimating cross-component error covariance arising from insufficient ensemble members, therefore improving the SCDA analysis. A conceptual coupled model is employed in this paper to conduct twin experiments, validating the DNN–EAKF's capability to outperform conventional EAKF in SCDA. The results reveal that the DNN–EAKF can make SCDA superior to WCDA with a limited ensemble size. The root-mean-squared errors are reduced up to 70% while the anomaly correlation coefficients are increased up to 20% when the atmospheric observations are used to update the ocean variables directly. The other model components can also be improved through SCDA. This approach is anticipated to offer insights for future methodological integrations of machine learning and data assimilation and provide methods for SCDA applications in coupled general circulation models. [ABSTRACT FROM AUTHOR]

The article presents a study which explored the mid-Pliocene and pre-indusrial atmosphere general circulation models (AGCM) simulations, with Norwegian Earth System Model (NorESM-L). The study evaluated he potential uncertainties in the analysis of climate anomalies in the mid-Pliocene period. Results showed that the uncertainties in mid-Pliocene climate anomaly analyses are large in terms of regional scale, but small on a global scale.

In the North West Shelf region of Australia is a surface current (Holloway Current), which flows southwestward along the shelf break. This paper describes a seasonal undercurrent below the Holloway Current. A 5-day climatology is constructed from the output of an eddy-resolving oceanic general circulation model (OGCM). A seasonal northeastward-flowing undercurrent is found on the upper continental slope during the climatological April-May. This undercurrent reverses during February-March. During its annual cycle, the phase of the undercurrent tends to propagate southwestward and upward. The annual frequency dominates, but the positive and negative phases of the undercurrent are not symmetric in the yearly cycle because of the contributions from the semi-annual and 1/3-annual components. We propose a hypothesis that this undercurrent is a beam of coastal trapped wave (CTW). As an initial attempt to assess the plausibility of this hypothesis, we construct an idealized linear coastal-trapped wave (CTW) solution driven by an idealized harmonic meridional winds at the annual frequency. The solution takes the form of a beam originating from the forcing region on the continental shelf and propagating offshore and southward. When it emerges on to the continental slope, it takes the form of an undercurrent. This idealized solution shares several properties with the undercurrent in the OGCM despite several discrepancies. [ABSTRACT FROM AUTHOR]

There is a growing need for proactive planning for natural hazards in a changing climate. Computational modeling of climate hazards provides an opportunity to inform planning, particularly in areas approaching ecosystem state changes, such as Interior Alaska, where future hazards are expected to differ significantly from historical events in frequency and severity. This paper considers improved modeling approaches from a physical process perspective and contextualizes the results within the complexities and limitations of hazard planning efforts and management concerns. Therefore, the aim is not only to improve the understanding of potential climate impacts on streamflow within this region but also to further explore the steps needed to evaluate local-scale hazards from global drivers and the potential challenges that may be present. This study used dynamically downscaled climate forcing data from ERA-Interim reanalysis datasets and projected climate scenarios from two General Circulation Models under a single Representative Concentration Pathway (RCP 8.5) to simulate an observational gage-calibrated WRF-Hydro model to assess shifts in streamflow and flooding potential in three Interior Alaska rivers over a historical period (2008–2017) and two future periods (2038–2047 and 2068–2077). Outputs were assessed for seasonality, streamflow, extreme events, and the comparison between existing flood control infrastructure in the region. The results indicate that streamflow in this region is likely to experience increases in seasonal length and baseflow, while the potential for extreme events and variable short-term streamflow behavior is likely to see greater uncertainty, based on the divergence between the models. [ABSTRACT FROM AUTHOR]

The 1960s was an exciting era for atmospheric predictability research: a finite predictability of the atmosphere was uncovered using Lorenz's models and the well-acknowledged predictability limit of two weeks was estimated using a general circulation model (GCM). Here, we delve into details regarding how a correlation between the two-week predictability limit and a doubling time of five days was established, recognize Lorenz's pioneering work, and suggest non-impossibility for predictability beyond two weeks. We reevaluate the outcomes of three different approaches—dynamical, empirical, and dynamical-empirical—presented in Lorenz's and Charney et al.'s papers from the 1960s. Using the intrinsic characteristics of the irregular solutions found in Lorenz's studies and the dynamical approach, a doubling time of five days was estimated using the Mintz–Arakawa model and extrapolated to propose a predictability limit of approximately two weeks. This limit is now termed "Predictability Limit Hypothesis", drawing a parallel to Moore's Law, to recognize the combined direct and indirect influences of Lorenz, Mintz, and Arakawa under Charney's leadership. The concept serves as a bridge between the hypothetical predictability limit and practical model capabilities, suggesting that long-range simulations are not entirely constrained by the two-week predictability hypothesis. These clarifications provide further support to the exploration of extended-range predictions using both partial differential equation (PDE)-physics-based and Artificial Intelligence (AI)—powered approaches. [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]

We demonstrate that both the current (New Dynamics), and next generation (ENDGame) dynamical cores of the UK Met Office global circulation model, the UM, reproduce consistently, the long-term, large-scale flows found in several published ide- alised tests. The cases presented are the Held-Suarez test, a simplified model of Earth (including a stratosphere), and a model of a hypothetical Tidally Locked Earth (TLE). Furthermore, we show that using simplifications to the dynamical equations, which are expected to be justified for the physical domains and flow regimes we have studied, and which are supported by the ENDGame dynamical core, also produces matching long-term, large-scale flows. Finally, we present evidence for differences in the detail of the planetary (meridional) flows and circulations resulting from improvements in the ENDGame formulation over New Dynamics. Specifically, we find greater symmetry in the meridional circulations of the Tidally Locked Earth test case using the ENDGame formulation, which is a better match to our physical expectations of the flow for such a slowly rotating Earth-like system. [ABSTRACT FROM AUTHOR]

I study the Hadley circulation of a completely ice-covered Snowball Earth through simulations with a comprehensive atmosphere general circulation model. Because the Snowball Earth atmosphere is an example of a dry atmosphere, these simulations allow me to test to what extent dry theories and idealized models capture the dynamics of dry Hadley circulations. Perpetual off-equatorial as well as seasonally-varying insolation is used, extending a previous study for perpetual on-equatorial (equinox) insolation. Vertical diffusion of momentum, representing the momentum transport of dry convection, is fundamental to the momentum budgets of both the winter and summer cells. In the zonal budget, it is the primary process balancing the Coriolis force. In the meridional budget, it mixes meridional momentum between the upper and the lower branch and thereby decelerates the circulation. Because of the latter, the circulation intensifies by a factor of three when vertical diffusion of momentum is suppressed. For seasonally-varying insolation, the circulation undergoes rapid transitions from the weak summer into the strong winter regime. Consistent with previous studies in idealized models, these transitions result from a mean-flow feedback, because of which they are insensitive to the treatment of vertical diffusion of momentum. Overall, the results corroborate previous findings for perpetual on-equatorial insolation. They demonstrate that an appropriate description of dry Hadley circulations, in particular their strength, needs to incorporate the vertical momentum transport by dry convection, a process that is neglected in most dry theories and idealized models. An improved estimate of the strength of the Snowball Earth Hadley circulation will also help to better constrain the climate of a possible Neoproterozoic Snowball Earth and its deglaciation threshold. [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]

Understanding historical soil moisture (SM) variations and their relationship with temperature in high‐latitude humid regions is essential for predicting hot droughts under widespread warming. This paper presents the first‐ever annual‐resolution summer surface SM reconstruction (1736–2006 CE) in Sweden, located in northern Europe (NE). The reconstruction utilizes the paleoclimate proxy, tree‐ring δ18O, which exhibits a strong correlation with reanalysis SM data during 1948–2007 CE (r = −0.67, p < 0.001). In contrast to an unprecedented trend suggested by previous studies, our reconstruction exhibits a wetting trend in NE since the 1960s falling within the historical spectrum of trends. Both reanalysis SM data and our reconstruction show significant negative correlations with temperature at interannual timescales. However, Coupled Model Intercomparison Project Phase 6 climate models failed to capture the significant SM‐temperature relationship during the historical (1850–1947 CE) and observation periods (1948–2006 CE). This proxy‐model comparison represents a critical step toward enhancing our understanding of SM dynamics and the reliability of SM projections in high‐latitude humid regions. Plain Language Summary: Soil moisture (SM) refers to water in any form contained in soils, and it plays an important role in sustaining plant growth and influencing climate dynamics. SM deficits can result in ecological/agricultural droughts. However, our understanding of historical SM changes is limited due to the scarcity of long‐term records. Consequently, modeling historical SM changes proves challenging and prone to inaccuracies. In this study, we utilized a tree‐ring record to reconstruct centuries‐long SM changes in Sweden, located in northern Europe. Our analysis revealed a significant negative correlation between SM and temperature in both our reconstruction and SM data sets. However, state‐of‐art models failed to capture the significant relationship observed at our study site. These findings highlight the need to improve climate models to increase the accuracy of climate forecasts and better understand SM dynamics in high‐latitude humid areas. Key Points: This study presents the first 271‐year historical soil moisture (SM) reconstruction in northern Europe (NE) using the tree‐ring δ18O proxySignificant correlations between historical SM and temperature in NE were observed at interannual timescalesOur results implied that Coupled Model Intercomparison Project Phase 6 models might underestimate the SM‐temperature relationship [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]

Radionuclide impact of the Fukushima Dai-ichi nuclear power plant accident on the distribution of radionuclides in seawater of the NW Pacific Ocean is compared with global fallout from atmospheric tests of nuclear weapons. Surface and water column seawater samples collected during the international expedition in June 2011 were analyzed for 134Cs, 137Cs, 129I and ³H. The 137Cs, 129I and 3H levels in surface seawater offshore Fukushima varied between 0.002--3.5 Bq L-1, 0.01--0.8 µ Bq L-1, and 0.05--0.15 Bq L-1, respectively. At the sampling site about 40 km from the coast, where all three radionuclides were analyzed, the Fukushima impact on the levels of these three radionuclides represent an increase above the global fallout background by factors of about 1000, 30 and 3, respectively. The water column data indicate that the transport of Fukushimaderived radionuclides downward to the depth of 300 m has already occurred. The observed 137Cs levels in surface waters and in the water column are in reasonable agreement with predictions obtained from the Ocean General Circulation Model, which indicates that the radionuclides have been transported from the Fukushima coast eastward. The 137Cs inventory in the water column (the area from 34 to 37° N, and from 142 to 147° E) due to the Fukushima accident is estimated to be about 2.2 PBq. The amount of 129I and ³H released and deposited on the NW Pacific Ocean after the Fukushima accident was estimated to be about 7 GBq and 0.1 PBq, respectively. Due to a suitable residence time in the ocean, Fukushima-derived radionuclides will provide useful tracers for isotope oceanography studies on the transport of water masses in the NW Pacific Ocean. [ABSTRACT FROM AUTHOR]

The Arctic Ocean is a region that is particularly vulnerable to the impact of ocean acidification driven by rising atmospheric CO2, negatively impacting calcifying organisms such as coccolithophorids and foraminiferans. In this study, we use an ocean general circulation model, with embedded biogeochemistry and a full description of the carbon cycle, to study the response of pH and saturation states of calcite and aragonite to changing climate in the Arctic Ocean. Particular attention is paid to the strong regional variability within the Arctic and, for comparison, simulation results are contrasted with those for the global ocean. Simulations were run to year 2099 using the RCP 8.5 (the highest IPCC AR5 CO2 emission scenario). The separate impacts of the direct increase in atmospheric CO2 and indirect effects via climate feedbacks (changing temperature, stratification, primary production and fresh water fluxes) were examined by undertak- ing two simulations, one with the full system and the other in which ocean-atmosphera exchange of CO2 was prevented from increasing beyond the flux calculated for year 2000. Results indicate that climate feedbacks, and spatial heterogeneity thereof, play a strong role in the declines in pH and carbonate saturation (Ω) seen in the Arctic. The central Arctic, Canadian Arctic Archipelago and Baffin Bay show greatest rates of acidification and Ω decline as a result of melting sea ice. In contrast, areas affected by Atlantic inflow including the Greenland Sea and outer shelves of the Barents, Kara and Laptev seas, had minimal decreases in pH and Ω because weakening stratification associated with diminishing ice cover led to greater mixing and primary production. As a consequence, the predicted onset of undersaturation is highly variable regionally within the Arctic, occurring during the decade of 2000-2010 in the Siberian shelves and Canadian Arctic Archipelago, but as late as the 2080s in the Barents and Norwegian Seas. We conclude that, in order to make future projections of acidification and carbon saturation state in the Arctic, regional variability needs to be adequately resolved, with particular emphasis on reliable predictions of the rates of retreat of the sea-ice which are a major source of uncertainty. [ABSTRACT FROM AUTHOR]

The article presents a study which developed a parameterization of black carbon (BC) aging to be used in general circulation models (GCMs). The BC aging rate is expressed as the rate of conversion from hydrophobic to hydrophilic BC modes. It notes that the use of the developed parameterization in GCMs will lead to more reliable estimates of BC spatial distribution.

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]

A general circulation model of intermediate complexity with an idealized earthlike aquaplanet setup is used to study the impact of changes in the oceanic heat transport on the global atmospheric circulation. Focus is put on the Lorenz energy cycle and the atmospheric mean meridional circulation. The latter is analysed by means of the Kuo-Eliassen equation. The atmospheric heat transport compensates the imposed oceanic heat transport changes to a large extent in conjunction with significant modification of the general circulation. Up to a maximum about 3PW, an increase of the oceanic heat transport leads to an increase of the global mean near-surface temperature and a decrease of its equator-to-pole gradient. For larger transports, the gradient is reduced further but the global mean remains approximately constant. This is linked to a cooling and a reversal of the temperature gradient in the tropics. A larger oceanic heat transport leads to a reduction of all reservoirs and conversions of the Lorenz energy cycle but of different relative magnitude for the individual components. The available potential energy of the zonal mean flow and its conversion to eddy available potential energy are affected most. Both the Hadley and Ferrel cell show a decline for increasing oceanic heat transport, with the Hadley cell being more sensitive. Both cells exhibit a poleward shift of their maxima, and the Hadley cell broadens for larger oceanic transports. The partitioning, by means of the Kuo-Eliassen equation, reveals that zonal mean diabatic heating and friction are the most important sources for changes of the Hadley cell, while the behaviour of the Ferrell cell is mostly controlled by friction. [ABSTRACT FROM AUTHOR]

The performance of general circulation models (GCMs) in simulating horizontal winds is important because the distribution and variation in horizontal winds are central to investigating atmospheric dynamic characteristics and processes. Also, horizontal wind data can be used to extract some of the required information on gravity waves, tides, and planetary waves. In this context, the present paper evaluates the capability of the Institute of Atmospheric Physics atmospheric general circulation model high-top version (IAP-HAGCM) in simulating the horizontal winds and tides of the troposphere and lower stratosphere by presenting a climatological and statistical comparison against observations of the powerful Beijing mesosphere–stratosphere–troposphere (MST) radar (39.78°N, 116.95°E) during 2012–2014. The results illustrated that the IAP-HAGCM can successfully reproduce the time–altitude distribution of the monthly mean zonal wind and diurnal tide amplitude, albeit with some underestimation. The mean correlation coefficients and root-mean-square error for the zonal (meridional) winds were 0.94 (0.73) and 6.60 m s−1 (2.90 m s–1), respectively. Additionally, the IAP-HAGCM can capture the temporal variation in both the zonal and meridional winds. It is worth noting that, compared with the seven coupled model intercomparison project phase 6 (CMIP6) models, the IAP-HAGCM performs better in meridional wind simulations below 15 km. However, there are discrepancies in altitudinal ranges with large wind velocities, such as the westerly jet, in the transition region of the troposphere and stratosphere, and in February, April, July, and September. It is suggested that model users should take advantage of the model's simulation ability by combining this information regarding when and where it is optimal with their own research purposes. Moreover, the evaluation results in this paper can also serve as a reference for guiding improvements of the IAP-HAGCM. [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 study, we investigate how PCMDI/CMIP3 general circulation models (GCMs) represent the seasonal properties of the hydrological cycle in four major South and Southeast Asian river basins (Indus, Ganges, and Brahmaputra and Mekong). First, we examine the skill of GCMs by analysing their simulations for the XX century climate (1961-2000) under present-day forcing, and then we analyse the projected changes for the corresponding XXI and XXII century climates under SRESA1B scenario. CMIP3 GCMs show a varying degree of skill in simulating the basic characteristics of the monsoonal precipitation regimes of the Ganges, Brahmaputra and Mekong basins, while the representation of the hydrological cycle over the Indus basin is poor in most cases, with few GCMs not capturing the monsoon signal at all. Although the models' outputs feature a remarkable spread for the monsoonal precipitations, a satisfactory representation of the western mid-latitude precipitation regime is instead observed. Similarly, most of the models exhibit a satisfactory agreement for the basin-integrated runoff in winter and spring, while the spread is large for the runoff during the monsoon season. For future climate scenarios, winter (spring) P - E decreases over all four (Indus and Ganges) basins due to decrease in precipitation associated with the western midlatitude disturbances. Consequently, the spring (winter) runoff drops (rises) for the Indus and Ganges basins. Such changes indicate a shift from rather glacial and nival to more pluvial runoff regimes, particularly for the Indus basin. Furthermore, the rise in the projected runoff along with the increase in precipitations during summer and autumn indicates an intensification of the summer monsoon regime for all study basins. [ABSTRACT FROM AUTHOR]

We present a simple method to generate a perturbed parameter ensemble (PPE) of a fully-coupled atmosphere-ocean general circulation model (AOGCM), HadCM3, without requiring flux-adjustment. The aim was to produce an ensemble that samples parametric uncertainty in some key variables and displays a similar range of behavior as seen in multi-model ensembles (MMEs). Six atmospheric parameters, a sea-ice parameter and an ocean parameter were jointly perturbed within a reasonable range to generate an initial group of 200 members. To screen out implausible ensemble members, 20 yr pre-industrial control simulations were run and members whose tempera10 ture response to the parameter perturbations was projected to be outside the range of 13.6±2 °C, i.e. near to the observed pre-industrial global mean, were discarded. 21 members, including the standard unperturbed model, were accepted, covering almost the entire span of the eight parameters, challenging the argument that without fluxadjustment parameter ranges would be unduly restricted. This ensemble was used in 3 experiments; a 800 yr pre-industrial, a 150 yr quadrupled CO2, and a 150 yr 1% CO2 rise per annum simulation. The behavior of the PPE for the pre-industrial control compared well to the CMIP3 ensemble for a number of surface and atmospheric column variables with the exception of a few members in the Tropics. However, we find that members of the PPE with low values of the entrainment rate coefficient show very large increases in upper tropospheric and stratospheric water vapor concentrations in response to elevated CO2 and some show implausibly high climate sensitivities, and as such some of these members will be excluded from future experiments with this ensemble. The outcome of this study is a PPE of a fully-coupled AOGCM which samples parametric uncertainty with a range of behavior similar to the CMIP3 ensemble and a simple methodology which would be applicable to other GCMs. [ABSTRACT FROM AUTHOR]

Differencing predictions of linear regression models generated from hydrographic data collected at different times (the eMLR method) was proposed as a means of quantifying the dominant patterns of change in oceanic anthropogenic carbon in the context of sparse data sets subject to natural variability. The ability of eMLR to recover the anthropogenic carbon signal in the North Atlantic was tested using a global circulation and biogeochemistry model. Basin-scale applications of eMLR on horizontal layers can estimate the change in anthropogenic carbon inventory with an accuracy typically better than 10%. Regression model selection influences the distribution of the recovered anthropogenic carbon change signal. The systematic use of statistically optimum regression formulae does not produce the best estimates of anthropogenic carbon change if the distribution of the station locations emphasizes hydrographic features differently in time. Additional factors, such as a balanced station distribution and vertical continuity of the regression formulae should be considered to guide model selection. Accurate results are obtained when multiple formulae are used throughout the water column. Different formulae can yield results of similar quality. The fact that good results are obtained in the hydrographically complex North Atlantic suggests that eMLR can produce accurate estimates in other basins. [ABSTRACT FROM AUTHOR]

Estimates of the anthropogenic global-integrated sea-air carbon dioxide (CO2) flux from 1990 to 2009, based on different models and measurements, range from -1.4 to -2.6 PgCyr-1 . The median values of anthropogenic CO2 for each method show better agreement and are: -1.9 for PgCyr-1 for numerical ocean general circulation hind cast models (OGCMs) with parameterized biogeochemistry; -2.1 PgCyr-1 for atmospheric inverse models; -1.9 PgCyr-1 for global atmospheric constraints based on O2 /N2 ratios for 1990-2000; and -2.4 PgCyr-1 for oceanic inverse models. An updated estimate of this anthropogenic CO2 flux based on a climatology of sea-air partial pressure of CO2 differences (ΔpCO2) (Takahashi et al., 2009) and a bulk formulation of gas transfer with wind speed for year 2000 is -2.0 PgCyr-1 . Using this ΔpCO2 climatology and empirical relationships of pCO2 with sea-surface temperature (SST) anomalies (Park et al., 2010a), the interannual variability of the contemporary CO2 flux is estimated to be 0.20 PgCyr-1 (1σ) from 1990 through 2009. This is similar to the variability estimated by the OGCMs of 0.16 PgCyr-1 but smaller than the interannual variability from atmospheric inverse estimates of 0.40 PgCyr-1. The variability is largely driven by large-scale climate re-organizations. The decadal trends for different methods range from -0.13 (PgCyr-1) decade-1 to -0.50 (PgCyr-1) decade-1. The OGCMs and the data based sea-air CO2 flux estimates show smaller uptakes and appreciably smaller decadal trends than estimates based on changes in carbon inventory suggesting that methods capable of resolving shorter timescales are showing a slowing of the rate of ocean CO2 uptake. It is not clear if this large difference in trend is a methodological issue or a real natural feedback. [ABSTRACT FROM AUTHOR]

The article presents a study regarding the significance of tropical cyclone (TC) in the excitation of Yanai and Kelvin waves that is shown in the ocean general circulation model (GCM). It highlights the use of community climate system model (CCSM3) based on parallel ocean program (POP v1.4.3). It notes that TC wind forcing could influence the amplitude and timing of El Ninñ events.

The article provides information on the ECHAM/MESSy Atmospheric Chemistry (EMAC) model which is coupled to the ocean general circulation (GCM) model MPIOM using the Modular Earth Submodel Sytem (MESSy) interface. It reveals that the coupling method is tested for different model configurations, proving to be very flexible in terms of parallel decomposition. In addition, the climate model simulation (CMIP3) performed with EMAC-MPIOM show that the results are comparable to those of other GCM.

The article presents a description and evaluation of the Commonwealth Scientific and Industrial Research Organization (CSIRO) Mk3L climate system model. It is inferred that the model is designed for millenial-scale climate simulation which includes representations of the atmosphere, ocean, sea ice, and land surface. Moreover, CSIRO Mk3L offers a combination of computational efficiency and a stable and realistic control climatology.

The article discusses a research study which evaluates a climate simulation through the Global Environmental and Ecological Simulation of Interactive Systems and Modular Ocean Model version 2 (GENMOM). Findings reveal that the said model developed a global temperature bias of 0.6 degree-Celsius. It indicates the development of a split intertropical convergence zone (ITCZ) and weaker-than-observed overturning circulation as the two main weaknesses depicted in the simulations.

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]

Xinjiang, located in the arid region of the northwest, is one of the areas most sensitive to global changes. The Kaidu River Basin, situated in the heart of Xinjiang, is one of the sources of China's largest inland river—the Tarim River. The Kaidu River not only bears the responsibility for supplying water for industrial use and agricultural production and people's daily life in the basin, but also plays a crucial role in ecological water supply to the Tarim River. Studying and analyzing the characteristics and trends of meteorological condition in the future under climate change can provide important references and a basis for a deeper understanding of changes in the hydrological process and water resources in the basin. Therefore, this paper selects seven precipitation bias correction methods and four temperature bias correction methods to adjust the precipitation and temperature output data of eight general circulation models of the Sixth Coupled Model Intercomparison Project (CMIP6) within the Kaidu River Basin. The applicability of different bias correction methods in the study area is evaluated, and based on the corrected future meteorological data and calculated extreme meteorological index, the trends of meteorological data (precipitation, temperature) in the future period (2025–2050) under four SSP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) in the Kaidu River Basin are analyzed. The results show that: (1) Different types of bias correction methods have different correction focus and effects; their reflections on evaluation indicators are also different. (2) In the future period (2025–2050), the annual precipitation and average temperature in the Kaidu River Basin are higher than those in the historical period (1975–2014). The average annual temperature shows an upward trend in the future, but the annual precipitation shows a downward trend in the future except for the SSP2-4.5 scenario. (3) Compared with the historical period, the extreme precipitation in the future period under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios is higher than that in the historical period, and the number of rainless days decreases. In the future, under the SSP1-2.6 and SSP5-8.5 scenarios, the probability of meteorological drought events occurring due to high temperatures in the basin may further increase, while under the SSP2-4.5 scenario, the situation of high temperatures and heavy rain in the basin may continue to increase. [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]

Key message: Drought severely worsened till 2100 and eventually outplayed growth-enhancing CO2 fertilization turning productivity gains into losses for beech and fir. Most scenarios generated notable losses in profitability but economic tipping points were later than for productivity due to lag effects related to discounting. Time mixture of fir and shortening rotation can counteract economic risks under climate change, but requires early admixture and moderate establishment costs. Context: Adaptation strategies to climate change (CC) such as establishing mixed forests are often based on ecological understanding while economic rationale is often disregarded. Aims: This paper studies CC uncertainty on productivity and profitability of European beech (Fagus sylvatica L.) and Silver fir (Abies alba Mill.). Besides, the economic consequences to actively adapt beech forests by admixing Silver fir are investigated. Methods: We used the process-based forest growth model GOTILWA + to simulate RCP2.6, RCP4.5 and RCP8.5 climatic projection by the MPI-ESM-LR global circulation model (MPI-ESM-LR) with the CO2 fertilization effect (eCO2) switched on and off. We analysed the sensitivity of the land expectation value (LEV) on CC and economic parameters. Results: CC initially increased productivity, but declined after a tipping point (2040–2070) and later also profitability (2045–2100). RCP8.5 had positive, RCP2.6 negative and RCP4.5 neutral effects on LEV. Switching off eCO2 turned RCP8.5 from the most profitable to the least profitable scenario and the opposite for RCP2.6. CC generally reduced optimal rotation (Ropt) being scenario dependant, but comparatively more for fir than beech. Admixing fir created an economic benefit when implemented before stand age 50 of beech. This benefit was nullified with protection costs for browsing control (fencing or tree shelters). Conclusions: Economic parameters (not CC) were the major source of uncertainty stemming from discounting factors and establishment costs. Admixture of fir and shortening rotation can provide a solution to tackle economic and climate uncertainties, but requires early admixture and browsing control. [ABSTRACT FROM AUTHOR]

When the negatively buoyant air in the cloud downdrafts reaches the surface, it spreads out horizontally, producing cold pools. A cold pool can trigger new convective cells. However, when combined with the ambient vertical wind shear, it can also connect and upscale them into large mesoscale convective systems (MCS). Given the broad spectrum of scales of the atmospheric phenomenon involving the interaction between cold pools and the MCS, a parameterization was designed here. Then, it is coupled with a classical convection parameterization to be applied in an atmospheric model with an insufficient spatial resolution to explicitly resolve convection and the sub‐cloud layer. A new scalar quantity related to the deficit of moist static energy detrained by the downdrafts mass flux is proposed. This quantity is subject to grid‐scale advection, mixing, and a sink term representing dissipation processes. The model is then applied to simulate moist convection development over a large portion of tropical land in the Amazon Basin in a wet and dry‐to‐wet 10‐days period. Our results show that the cold pool edge parameterization improves the organization, longevity, propagation, and severity of simulated MCS over the Amazon and other different continental areas. Plain Language Summary: In nature, cold pools are formed by cold air masses descending from the low to mid‐troposphere in thunderstorms. When these drafts reach the surface, they spread out horizontally. A manifestation of cold pools is the relatively high speed at the gust front, which can lift environmental air producing new convective cells. Moreover, depending on ambient conditions, the cold pools may help organize the new convective cells, increasing their aggregation and forming the so‐called mesoscale convective systems (MCSs). MCSs, which cover hundreds to thousands of km2, significantly impact the global scale circulation, energy budget, hydrological cycle, and population safety. Forecasting MCSs is challenging for global circulation models (GCM) due to the broad spectrum of scales of the involved atmospheric phenomenon. The computational limitations, at present and for some time to come, do not allow running in real‐time GCMs, which explicitly solves all relevant scales of motion. This paper describes a methodology to account for essential interplays between cold pools edges and moist convection to be applied in the GCMs of weather and climate forecasting. We show that the method improves the model simulation of the main types of MCSs over the Amazon Basin and other continental areas. Key Points: A model scheme for including effect of cold pools edges in triggering new convective cells and storm propagation is presentedThe scheme is coupled with a convection parameterization and applied in the modeling of moist convective systemsThe method improves the organization, longevity, propagation, and severity of the simulated mesoscale convective systems [ABSTRACT FROM AUTHOR]

It is shown that a recently developed hybrid modeling approach that combines machine learning (ML) with an atmospheric global circulation model (AGCM) can serve as a basis for capturing atmospheric processes not captured by the AGCM. This power of the approach is illustrated by three examples from a decades‐long climate simulation experiment. The first example demonstrates that the hybrid model can produce sudden stratospheric warming, a dynamical process of nature not resolved by the low resolution AGCM component of the hybrid model. The second and third example show that introducing 6‐hr cumulative precipitation and sea surface temperature (SST) as ML‐based prognostic variables improves the precipitation climatology and leads to a realistic ENSO signal in the SST and atmospheric surface pressure. Plain Language Summary: This paper introduces and tests schemes for efficiently enabling significant expansion of the utility and scope of a recently introduced hybrid modeling technique that combines machine learning with an atmospheric global circulation model (AGCM). Simulation experiments are carried out with an implementation of the approach on a low resolution simplified AGCM. An examination of the simulated atmospheric circulation suggests that the hybrid model can capture dynamical process not captured by the AGCM. Moreover, the addition of precipitation and sea surface temperature (SST) as machine learning predicted physical quantities to the model improves the precipitation climatology and leads to a realistic El Niño‐La Niña signal in the SST and atmospheric surface pressure. Key Points: A hybrid system combining an atmospheric global circulation model (AGCM) with a machine‐learning component can capture processes not captured by the AGCMMachine learning provides a flexible framework to introduce additional prognostic variables into the hybrid modelThe prototype hybrid model tested in the paper is stable and has a realistic climate in decades‐long simulation experiments [ABSTRACT FROM AUTHOR]

Air-sea CO2 fluxes over the Pacific Ocean are known to be characterized by coherent large-scale structures that reflect not only ocean subduction and upwelling patterns, but also the combined effects of wind-driven gas exchange and biology. On the largest scales, a large net CO2 influx into the extra-tropics is associated with a robust seasonal cycle, and a large net CO2 efflux from the tropics is associated with substantial inter-annual variability. In this work, we have synthesized estimates of the net air-sea CO2 flux from a variety of products drawing upon a variety of approaches in three sub-basins of the Pacific Ocean, i.e., the North Pacific extra-tropics (18° N-66° N), the tropical Pacific (18° S-18° N), and the South Pacific extra-tropics (44.5° S-18° S). These approaches include those based on the measurements of CO2 partial pressure in surface seawater (pCO2sw), inversions of ocean interior CO2 data, forward ocean biogeochemistry models embedded in the ocean general circulation models (OBGCMs), a model with assimilation of pCO2sw data, and inversions of atmospheric CO2 measurements. Long-term means, inter-annual variations and mean seasonal variations of the regionally-integrated fluxes were compared in each of the sub-basins over the last two decades, spanning the period from 1990 through 2009. A simple average of the long-term mean fluxes obtained with surface water pCO2 diagnostics and those obtained with ocean interior CO2 inversions are -0.47 ± 0.13PgCyr-1 in the North Pacific extra-tropics, +0.44 ± 0 .14PgCyr-1 in the tropical Pacific, and -0.37 ± 0.08PgCyr-1 in the South Pacific extra-tropics, where positive fluxes are into the atmosphere. This suggests that approximately half of the CO2 taken up over the North and South Pacific extra-tropics is released back to the atmosphere from the tropical Pacific. These estimates of the regional fluxes are also supported by the estimates from OBGCMs after adding the riverine CO2 flux, i.e., -0.49 ± 0.02PgCyr-1 in the North Pacific extratropics, +0.41 ± 0.05PgCyr-1 in the tropical Pacific, and -0.39 ± 0.11 PgCyr-1 in the South Pacific extra-tropics. The estimates from the atmospheric CO2 inversions show large variations amongst different inversion systems, but their median fluxes are consistent with the estimates from climatological pCO2sw data and pCO2sw diagnostics. In the South Pacific extra-tropics, where CO2 variations in the surface and ocean interior are severely under-sampled, the difference in the air-sea CO2 flux estimates between the diagnostic models and ocean interior CO2 inversions is larger (0.18 PgCyr-1). The range of estimates from forward OBGCMs is also large (-0.19 to -0.72 PgCyr-1). Regarding inter-annual variability of air-sea CO2 fluxes, positive and negative anomalies are evident in the tropical Pacific during the cold and warm events of the El Nino Southern Oscillation in the estimates from pCO2sw diagnostic models and from OBGCMs. They are consistent in phase with the Southern Oscillation Index, but the peak-to-peak amplitudes tend to be higher in OBGCMs (0.40 ± 0.09 PgCyr-1) than in the diagnostic models (0.27 ± 0.07PgCyr-1). [ABSTRACT FROM AUTHOR]

Using the general circulation model ECHAM5-JSBACH forced by observed sea surface temperatures (SSTs) for the 20th century, we investigate the role of vegetation and land surface albedo dynamics in shaping rainfall variability in the Sahel.We use two different land surface albedo schemes, one in which the albedo of the canopy is varying and one in which additionally the albedo changes of the surface below the canopy are taken into account. The SST-forcing provides the background for simulating the observed decadal signal in Sahelian rainfall, though the respone to SST-forcing only is not strong enough to fully capture the observed signal. The introduction of dynamic vegetation leads to an increase in inter-annual variability of the rainfall, and gives rise to an increased number of high amplitude rainfall anomaly events. The dynamic background albedo leads to an increased persistence of the rainfall anomalies. The increase in persistence means that the difference between the dry and the wet decades is increased compared to the other simulations, and thus more closely matching the observed absolute change between these two periods. These results highlight the need for a consistent representation of land surface albedo dynamics for capturing the full extent of rainfall anomalies in the Sahel. [ABSTRACT FROM AUTHOR]

One of the largest sources of uncertainties in modelling of the future global climate is the response of the terrestrial carbon cycle. Studies have shown that it is likely that the extant land sink of carbon will weaken in a warming climate. Should this happen, a larger portion of the annual carbon dioxide emissions will remain in the atmosphere, and further increase the global warming, which in turn may further weaken the land sink. We investigate the potential sensitivity of global terrestrial ecosystem carbon balance to differences in future climate simulated by four general circulation models (GCMs) under three different CO2 concentration scenarios. We find that the response in simulated carbon balance is more influenced by GCMs than CO2 concentration scenarios. Singular Value Decomposition (SVD) analysis of sea surface temperatures (SSTs) reveals differences in the GCMs SST variability leading to decreased tropical ecosystem productivity in two out of four GCMs. We extract parameters describing GCM characteristics by parameterizing a statistical replacement model mimicking the simulated carbon balance results. By sampling two GCM-specific parameters and global temperatures we create 60 new "artificial" GCMs and investigate the extent to which the GCM characteristics may explain the uncertainty in global carbon balance under future radiative forcing. Our analysis suggests that differences among GCMs in the representation of SST variability and ENSO and its effect on precipitation and temperature patterns explains the majority of the uncertainty in the future evolution of global terrestrial ecosystem carbon. [ABSTRACT FROM AUTHOR]