| 1. |
- Bardakov, Roman, et al.
(författare)
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A Novel Framework to Study Trace Gas Transport in Deep Convective Clouds
- 2020
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 12:5
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Tidskriftsartikel (refereegranskat)abstract
- Deep convective clouds reach the upper troposphere (8-15 km height). In addition to moisture and aerosol particles, they can bring aerosol precursor gases and other reactive trace gases from the planetary boundary layer to the cloud top. In this paper, we present a method to estimate trace gas transport based on the analysis of individual air parcel trajectories. Large eddy simulation of an idealized deep convective cloud was used to provide realistic environmental input to a parcel model. For a buoyant parcel, we found that the trace gas transport approximately follows one out of three scenarios, determined by a combination of the equilibrium vapor pressure (containing information about water-solubility and pure component saturation vapor pressure) and the enthalpy of vaporization. In one extreme, the trace gas will eventually be completely removed by precipitation. In the other extreme, there is almost no vapor condensation on hydrometeors and most of the gas is transported to the top of the cloud. The scenario in between these two extremes is also characterized by strong gas condensation, but a small fraction of the trace gas may still be transported aloft. This approach confirms previously suggested patterns of inert trace gas behavior in deep convective clouds, agrees with observational data, and allows estimating transport in analytically simple and computationally efficient way compared to explicit cloud-resolving model calculations.
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| 2. |
- Bassiouni, Maoya
(författare)
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Comparing Model Representations of Physiological Limits on Transpiration at a Semi-arid Ponderosa Pine Site
- 2022
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Ingår i: Journal of advances in modeling earth systems. - 1942-2466. ; 14
-
Tidskriftsartikel (refereegranskat)abstract
- Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi-empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi-arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Although models can be parameterized to yield similar functional performance, alternate parameterizations could not overcome structural model constraints that underestimate the unique information contained in soil water potential about transpiration. Additionally, both multilayer canopy and big-leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature, and we demonstrate that errors in leaf temperature can propagate to considerable error in simulated transpiration. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations.
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| 3. |
- Buehler, S.A., et al.
(författare)
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A New Halocarbon Absorption Model Based on HITRAN Cross-Section Data and New Estimates of Halocarbon Instantaneous Clear-Sky Radiative Forcing
- 2022
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 14:11
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Tidskriftsartikel (refereegranskat)abstract
- The article describes a new practical model for the infrared absorption of chlorofluorocarbons and other gases with dense spectra, based on high-resolution transmission molecular absorption database (HITRAN) absorption cross-sections. The model is very simple, consisting of frequency-dependent polynomial coefficients describing the pressure and temperature dependence of absorption. Currently it is implemented for the halocarbon species required by the Radiative Forcing Model Intercomparison Project. In cases where cross-section data is available at a range of different temperatures and pressures, this approach offers practical advantages compared to previously available options, and is traceable, since the polynomial coefficients follow directly from the laboratory spectra. The new model is freely available and has several important applications, notably in remote sensing and in developing advanced radiation schemes for global circulation models that include halocarbon absorption. For demonstration, the model is applied to the problem of computing instantaneous clear-sky halocarbon radiative efficiencies and present day radiative forcing. Results are in reasonable agreement with earlier assessments that were carried out with the less explicit Pinnock method, and thus broadly validate that method. Plain Language Summary Chlorofluorocarbons and other related gases have dense and complicated absorption spectra that can be measured in the laboratory. We bring such measurements to a form that can be used for simulations of the transfer of radiation through the atmosphere. Then we use the new model to calculate new estimates of the climate impact of these man-made gases. The results broadly validate earlier calculations that were done with a less explicit method.
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| 4. |
- Carlson, Henrik, et al.
(författare)
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Enhanced MJO and transition to superrotation in warm climates
- 2016
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 8:1, s. 304-318
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Tidskriftsartikel (refereegranskat)abstract
- Using the NCAR CAM3 model in aquaplanet configuration, we perform a suite of simulations spanning a broad range of warm climates. The simulations show a spontaneous transition to superrotation, i.e., westerly winds at upper levels above the equator. The momentum convergence leading to superrotation is driven by eastward-propagating equatorial waves with structure similar to the modern Madden-Julian Oscillation (MJO), whose amplitude increases strongly with temperature. We analyze the moist static energy (MSE) budget of the model's MJO to identify mechanisms leading to its enhanced amplitude. Two such mechanisms are identified: a rapid increase of mean low-level MSE with rising temperature, as found in previous work, and reduced damping of the MJO by synoptic-scale eddies. Both effects imply a reduced gross moist stability and enhanced MJO amplitude. The reduced eddy damping is caused by the transition to superrotation, which allows a greater penetration of extratropical eddies into the equatorial zone; the dominant effect of this greater penetration is to flatten the meridional gradient zonal-mean MSE, which effectively impedes the generation of anomalous MSE divergence by MJO-modulated eddies. This mechanism implies a positive feedback between superrotation and the MJO which may hasten the transition into a strongly superrotating state.
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| 5. |
- Chen, Hans, 1988, et al.
(författare)
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Regional CO2 inversion through ensemble-based simultaneous state and parameter estimation: TRACE framework and controlled experiments
- 2023
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 15:3
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Tidskriftsartikel (refereegranskat)abstract
- Atmospheric inversions provide estimates of carbon dioxide (CO2) fluxes between the surface and atmosphere based on atmospheric CO2 concentration observations. The number of CO2 observations is projected to increase severalfold in the next decades from expanding in situ networks and next-generation CO2-observing satellites, providing both an opportunity and a challenge for inversions. This study introduces the TRACE Regional Atmosphere-Carbon Ensemble (TRACE) system, which employ an ensemble-based simultaneous state and parameter estimation (ESSPE) approach to enable the assimilation of large volumes of observations for constraining CO2 flux parameters. TRACE uses an online full-physics mesoscale atmospheric model and assimilates observations serially in a coupled atmosphere-carbon ensemble Kalman filter. The data assimilation system was tested in a series of observing system simulation experiments using in situ observations for a regional domain over North America in summer. Under ideal conditions with known prior flux parameter error covariances, TRACE reduced the error in domain-integrated monthly CO2 fluxes by about 97% relative to the prior flux errors. In a more realistic scenario with unknown prior flux error statistics, the corresponding relative error reductions ranged from 80.6% to 88.5% depending on the specification of prior flux parameter error correlations. For regionally integrated fluxes on a spatial scale of 10(6) km(2), the sum of absolute errors was reduced by 34.5%-50.9% relative to the prior flux errors. Moreover, TRACE produced posterior uncertainty estimates that were consistent with the true errors. These initial experiments show that the ESSPE approach in TRACE provides a promising method for advancing CO2 inversion techniques.
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| 6. |
- de Lavergne, C., et al.
(författare)
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A Parameterization of Local and Remote Tidal Mixing
- 2020
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 12:5
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Tidskriftsartikel (refereegranskat)abstract
- Vertical mixing is often regarded as the Achilles' heel of ocean models. In particular, few models include a comprehensive and energy-constrained parameterization of mixing by internal ocean tides. Here, we present an energy-conserving mixing scheme which accounts for the local breaking of high-mode internal tides and the distant dissipation of low-mode internal tides. The scheme relies on four static two-dimensional maps of internal tide dissipation, constructed using mode-by-mode Lagrangian tracking of energy beams from sources to sinks. Each map is associated with a distinct dissipative process and a corresponding vertical structure. Applied to an observational climatology of stratification, the scheme produces a global three-dimensional map of dissipation which compares well with available microstructure observations and with upper-ocean finestructure mixing estimates. This relative agreement, both in magnitude and spatial structure across ocean basins, suggests that internal tides underpin most of observed dissipation in the ocean interior at the global scale. The proposed parameterization is therefore expected to improve understanding, mapping, and modeling of ocean mixing. ©2020. The Authors.
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| 7. |
- Deng, Jia, et al.
(författare)
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Adding stable carbon isotopes improves model representation of the role of microbial communities in peatland methane cycling
- 2017
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 9:2, s. 1412-1430
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Tidskriftsartikel (refereegranskat)abstract
- Climate change is expected to have significant and uncertain impacts on methane (CH4) emissions from northern peatlands. Biogeochemical models can extrapolate site-specificCH(4) measurements to larger scales and predict responses of CH4 emissions to environmental changes. However, these models include considerable uncertainties and limitations in representing CH4 production, consumption, and transport processes. To improve predictions of CH4 transformations, we incorporated acetate and stable carbon (C) isotopic dynamics associated with CH4 cycling into a biogeochemistry model, DNDC. By including these new features, DNDC explicitly simulates acetate dynamics and the relative contribution of acetotrophic and hydro-genotrophic methanogenesis (AM and HM) to CH4 production, and predicts the C isotopic signature (delta C-13) in soil C pools and emitted gases. When tested against biogeochemical and microbial community observations at two sites in a zone of thawing permafrost in a subarctic peatland in Sweden, the new formulation substantially improved agreement with CH4 production pathways and delta C-13 in emitted CH4 (delta C-13-CH4), a measure of the integrated effects of microbial production and consumption, and of physical transport. We also investigated the sensitivity of simulated delta C-13-CH4 to C isotopic composition of substrates and, to fractionation factors for CH4 production (alpha(AM) and alpha(HM)), CH4 oxidation (alpha(MO)), and plant-mediated CH4 transport (alpha(TP)). The sensitivity analysis indicated that the delta C-13-CH4 is highly sensitive to the factors associated with microbial metabolism (alpha(AM), alpha(HM), and alpha(MO)). The model framework simulating stable C isotopic dynamics provides a robust basis for better constraining and testing microbial mechanisms in predicting CH4 cycling in peatlands.
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| 8. |
- Gülk, Birte, 1994, et al.
(författare)
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Impacts of Vertical Convective Mixing Schemes and Freshwater Forcing on the 2016-2017 Maud Rise Polynya Openings in a Regional Ocean Simulation
- 2024
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Ingår i: JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS. - 1942-2466. ; 16:5
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Tidskriftsartikel (refereegranskat)abstract
- The correct representation of the Maud Rise open-ocean polynya in the Weddell Sea remains a challenge for ocean models. Here we reproduce the most recent polynya openings in 2016-2017 using a regional configuration, and assess their dependencies on vertical convective mixing schemes and freshwater forcing, both separately and in combination. We test three vertical convective mixing schemes: the enhanced vertical diffusion (EVD), the Eddy-Diffusivity Mass-Flux (EDMF) parameterization, and a modified version of EDMF accounting for thermobaric effects. Using simulations for the period 2007-2017, we find that the modified EDMF reproduces the observed climatological evolution of the mixed layer depth better than the original EDMF and the EVD, but a polynya fails to open due to excessive freshwater forcing. We thus use the modified EDMF to perform sensitivity experiments with reduced precipitation during 2012-2017. The imposed freshwater forcing strongly affects the number of years with polynyas. The simulation with the best representation of the 2016-2017 polynyas is analyzed to evaluate the triggering mechanisms. The 2016 polynya was induced by the action of thermobaric instabilities on a weak ambient stratification. This opening preconditioned the water column for 2017, which produced a stronger polynya. By examining the impacts of the different convective mixing schemes, we show that the modified EDMF generates more realistic patterns of deep convection. Our results highlight the importance of surface freshwater forcing and thermobaricity in governing deep convection around Maud Rise, and the need to represent thermobaric instabilities to realistically model Maud Rise polynyas. We investigate the impacts of representing numerical vertical mixing and surface freshwater forcing in a regional ocean model on polynyas (large openings in the pack ice) at Maud Rise, Southern Ocean. Maud Rise is prone to hosting polynyas, often associated with deep convection, which is a local vertical mixing process homogenizing the water column between surface and depths of several hundred meters. Numerical models often use simplistic strategies to represent this process, but improved parameterizations have recently become available. In this work, we test the impact of the representation of convective mixing in a particularly sensitive region. The last Maud Rise polynyas were observed in 2016 and 2017. Our regional simulation is capable of reproducing these polynyas, which has long been a challenge for ocean-sea ice models. We show that the 2016 polynya resulted from the action of a vertical instability at depth acting on weak ambient stratification. This event preconditioned the stronger 2017 polynya and deep convection. We conclude that representing convective plumes as a sub-grid scale process in models leads to a more realistic representation of open-ocean polynyas and associated convection events. The Eddy-Diffusivity Mass-Flux (EDMF) parameterization is tested in a regional simulation of the ocean around Maud Rise Thermobaric effects on convective plumes are enabled by modifying the EDMF parameterization Simulations of Maud Rise polynyas are highly sensitive to freshwater forcing and mixing schemes
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| 9. |
- Hartung, Kerstin, 1989-, et al.
(författare)
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Exploring the Dynamics of an Arctic Sea Ice Melt Event Using a Coupled Atmosphere-Ocean Single-Column Model (AOSCM)
- 2022
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 14:6
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Tidskriftsartikel (refereegranskat)abstract
- The Arctic climate system is host to many processes which interact vertically over the tightly coupled atmosphere, sea ice and ocean. The coupled Atmosphere-Ocean Single-Column Model (AOSCM) allows to decouple local small-scale and large-scale processes to investigate the model performance in an idealized setting. Here, an observed Arctic warm air intrusion event is used to show how to identify model deficiencies using the AOSCM. The AOSCM allows us to effectively produce a large number of perturbation simulations, around 1,000, to map sensitivities of the model results due to changes in physical and model properties as well as to the large-scale tendencies. The analysis of the summary diagnostics, that is, aggregated results from sensitivity experiments evaluated against modeled physical properties, such as surface energy budget and mean sea ice thickness, reveals sensitivities to the chosen parameters. Further, we discuss how the conclusions can be used to understand the behavior of the global host model. The simulations confirm that the horizontal advection of heat and moisture plays an important role for maintaining a low-level cloud cover, as in earlier studies. The combined cloud layers increase the energy input to the surface, which in turn enhances the ongoing melt. The clouds present an additional sensitivity in terms of how they are represented but also their interaction with the large-scale advection and the model time step. The methodology can be used for a variety of other regions, where the coupling to the ocean is important.
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| 10. |
- He, J., et al.
(författare)
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Development and Evaluation of an Ensemble-Based Data Assimilation System for Regional Reanalysis Over the Tibetan Plateau and Surrounding Regions
- 2019
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 11:8, s. 2503-2522
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Tidskriftsartikel (refereegranskat)abstract
- The Tibetan Plateau is regarded as the Earth's Third Pole, which is the source region of several major rivers that impact more 20% the world population. This high‐altitude region is reported to have been undergoing much greater rate of weather changes under global warming, but the existing reanalysis products are inadequate for depicting the state of the atmosphere, particularly with regard to the amount of precipitation and its diurnal cycle. An ensemble Kalman filter (EnKF) data assimilation system based on the limited‐area Weather Research and Forecasting (WRF) model was evaluated for use in developing a regional reanalysis over the Tibetan Plateau and the surrounding regions. A 3‐month prototype reanalysis over the summer months (June−August) of 2015 using WRF‐EnKF at a 30‐km grid spacing to assimilate nonradiance observations from the Global Telecommunications System was developed and evaluated against independent sounding and satellite observations in comparison to the ERA‐Interim and fifth European Centre for Medium‐Range Weather Forecasts Reanalysis (ERA5) global reanalysis. Results showed that both the posterior analysis and the subsequent 6‐ to 12‐hr WRF forecasts of the prototype regional reanalysis compared favorably with independent sounding observations, satellite‐based precipitation versus those from ERA‐Interim and ERA5 during the same period. In particular, the prototype regional reanalysis had clear advantages over the global reanalyses of ERA‐Interim and ERA5 in the analysis accuracy of atmospheric humidity, as well as in the subsequent downscale‐simulated precipitation intensity, spatial distribution, diurnal evolution, and extreme occurrence.
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| 11. |
- He, Liyuan, et al.
(författare)
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Dynamics of Fungal and Bacterial Biomass Carbon in Natural Ecosystems: Site-level Applications of the CLM-Microbe Model
- 2021
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 13:2
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Tidskriftsartikel (refereegranskat)abstract
- Explicitly representing microbial processes has been recognized as a key improvement to Earth system models for the realistic projections of soil carbon (C) and climate dynamics. The CLM‐Microbe model builds upon the CLM4.5 and explicitly represents two major soil microbial groups, fungi and bacteria. Based on the compiled time‐series data of fungal (FBC) and bacterial (BBC) biomass C from nine biomes, we parameterized and validated the CLM‐Microbe model, and further conducted sensitivity analysis and uncertainty analysis for simulating C cycling. The model performance was evaluated with mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) for relative change in FBC and BBC. The CLM‐Microbe model is able to reasonably capture the seasonal dynamics of FBC and BBC across biomes, particularly for tropical/subtropical forest, temperate broadleaf forest, and grassland, with MAE < 0.49 for FBC and <0.36 for BBC and RMSE <0.52 FBC and <0.39 for BBC, while R2 values are relatively smaller in some biomes (e.g., shrub) due to small sample sizes. We found good consistencies between simulated and observed FBC (R2=0.70, P<0.001) and BBC (R2=0.26, P<0.05) on average across biomes, but the model is not able to fully capture the large variation in observed FBC and BBC. Sensitivity analysis shows the most critical parameters are turnover rate, carbon‐to‐nitrogen ratio of fungi and bacteria, and microbial assimilation efficiency. This study confirms that the explicit representation of soil microbial mechanisms enhances model performance in simulating C variables such as heterotrophic respiration and soil organic C density. The further application of the CLM‐Microbe model would deepen our understanding of microbial contributions to the global C cycle.
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| 12. |
- Jewson, Stephen, et al.
(författare)
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Developing Representative Impact Scenarios From Climate Projection Ensembles, With Application to UKCP18 and EURO-CORDEX Precipitation
- 2023
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 15:1
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Tidskriftsartikel (refereegranskat)abstract
- Calculating impacts from climate projection ensembles can be challenging. A simple approach might consider just the ensemble mean, but this ignores much of the information in the ensemble and does not explore the range of possible impacts. A more thorough approach would consider every ensemble member, but may be computationally unfeasible for many impact models. We investigate the compromise in which we represent the ensemble by the mean and a single deviation from the mean. The deviation from the mean would ideally be representative both of variability in the ensemble, and have a significant impact, according to some impact metric. We compare methods for calculating the deviation from the mean, based on traditional compositing and a statistical method known as Directional Component Analysis (DCA). DCA is based on linearizing the impact metric around the ensemble mean. We illustrate the methods with synthetic examples, and derive new mathematical results that clarify the interpretation of DCA. We then use the methods to derive scenarios from the UKCP18 and EURO-CORDEX projections of future precipitation in Europe. We find that the worst ensemble member is not robust, but that deviations from the ensemble mean calculated using compositing and DCA are robust. They thus give robust insight into the patterns of change in the ensemble. We conclude that mean and representative deviation methods may be suitable for climate projection users who wish to explore the implications of the uncertainty around the ensemble mean without having to calculate the impacts of every ensemble member.
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| 13. |
- Jewson, Stephen, et al.
(författare)
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Developing Representative Impact Scenarios From Climate Projection Ensembles, With Application to UKCP18 and EURO‐CORDEX Precipitation
- 2022
-
Ingår i: Journal of Advances in Modeling Earth Systems. - : John Wiley & Sons. - 1942-2466. ; 15:1
-
Tidskriftsartikel (refereegranskat)abstract
- Calculating impacts from climate projection ensembles can be challenging. A simple approach might consider just the ensemble mean, but this ignores much of the information in the ensemble and does not explore the range of possible impacts. A more thorough approach would consider every ensemble member, but may be computationally unfeasible for many impact models. We investigate the compromise in which we represent the ensemble by the mean and a single deviation from the mean. The deviation from the mean would ideally be representative both of variability in the ensemble, and have a significant impact, according to some impact metric. We compare methods for calculating the deviation from the mean, based on traditional compositing and a statistical method known as Directional Component Analysis (DCA). DCA is based on linearizing the impact metric around the ensemble mean. We illustrate the methods with synthetic examples, and derive new mathematical results that clarify the interpretation of DCA. We then use the methods to derive scenarios from the UKCP18 and EURO-CORDEX projections of future precipitation in Europe. We find that the worst ensemble member is not robust, but that deviations from the ensemble mean calculated using compositing and DCA are robust. They thus give robust insight into the patterns of change in the ensemble. We conclude that mean and representative deviation methods may be suitable for climate projection users who wish to explore the implications of the uncertainty around the ensemble mean without having to calculate the impacts of every ensemble member.
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| 14. |
- Kuma, Peter, 1987-, et al.
(författare)
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Climate Model Code Genealogy and Its Relation to Climate Feedbacks and Sensitivity
- 2023
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 15:7
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Tidskriftsartikel (refereegranskat)abstract
- Contemporary general circulation models (GCMs) and Earth system models (ESMs) are developed by a large number of modeling groups globally. They use a wide range of representations of physical processes, allowing for structural (code) uncertainty to be partially quantified with multi-model ensembles (MMEs). Many models in the MMEs of the Coupled Model Intercomparison Project (CMIP) have a common development history due to sharing of code and schemes. This makes their projections statistically dependent and introduces biases in MME statistics. Previous research has focused on model output and code dependence, and model code genealogy of CMIP models has not been fully analyzed. We present a full reconstruction of CMIP3, CMIP5, and CMIP6 code genealogy of 167 atmospheric models, GCMs, and ESMs (of which 114 participated in CMIP) based on the available literature, with a focus on the atmospheric component and atmospheric physics. We identify 12 main model families. We propose family and ancestry weighting methods designed to reduce the effect of model structural dependence in MMEs. We analyze weighted effective climate sensitivity (ECS), climate feedbacks, forcing, and global mean near-surface air temperature, and how they differ by model family. Models in the same family often have similar climate properties. We show that weighting can partially reconcile differences in ECS and cloud feedbacks between CMIP5 and CMIP6. The results can help in understanding structural dependence between CMIP models, and the proposed ancestry and family weighting methods can be used in MME assessments to ameliorate model structural sampling biases.
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| 15. |
- Lambert, Marius S.A., et al.
(författare)
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Integration of a Frost Mortality Scheme Into the Demographic Vegetation Model FATES
- 2023
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 15:7
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Tidskriftsartikel (refereegranskat)abstract
- Frost is damaging to plants when air temperature drops below their tolerance threshold. The set of mechanisms used by cold-tolerant plants to withstand freezing is called “hardening” and typically take place in autumn to protect against winter damage. The recent incorporation of a hardening scheme in the demographic vegetation model FATES opens up the possibility to investigate frost mortality to vegetation. Previously, the hardening scheme was used to improve hydraulic processes in cold-tolerant plants. In this study, we expand upon the existing hardening scheme by implementing hardiness-dependent frost mortality into CLM5.0-FATES to study the impacts of frost on vegetation in temperate and boreal sites from 1950 to 2015. Our results show that the original freezing mortality approach of FATES, where each plant type had a fixed freezing tolerance threshold—an approach common to many other dynamic vegetation models, was restricted to predicting plant type distribution. The main results emerging from the new scheme are a high autumn and spring frost mortality, especially at colder sites, and increasing mid-winter frost mortality due to global warming, especially at warmer sites. We demonstrate that the new frost scheme is a major step forward in dynamically representing vegetation in ESMs by for the first time including a level of frost tolerance that is responding to the environment and includes some level of cost (implicitly) and benefit. By linking hardening and frost mortality in a land surface model, we open new ways to explore the impact of frost events in the context of global warming.
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| 16. |
- Lauritzen, P. H., et al.
(författare)
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Reconciling and Improving Formulations for Thermodynamics and Conservation Principles in Earth System Models (ESMs)
- 2022
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 14:9
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Tidskriftsartikel (refereegranskat)abstract
- This paper provides a comprehensive derivation of the total energy equations for the atmospheric components of Earth System Models (ESMs). The assumptions and approximations made in this derivation are motivated and discussed. In particular, it is emphasized that closing the energy budget is conceptually challenging and hard to achieve in practice without resorting to ad hoc fixers. As a concrete example, the energy budget terms are diagnosed in a realistic climate simulation using a global atmosphere model. The largest total energy errors in this example are spurious dynamical core energy dissipation, thermodynamic inconsistencies (e.g., coupling parameterizations with the host model) and missing processes/terms associated with falling precipitation and evaporation (e.g., enthalpy flux between components). The latter two errors are not, in general, reduced by increasing horizontal resolution. They are due to incomplete thermodynamic and dynamic formulations. Future research directions are proposed to reconcile and improve thermodynamics formulations and conservation principles.
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| 17. |
- Li, Xiang-Yu, et al.
(författare)
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Eulerian and Lagrangian approaches to multidimensional condensation and collection
- 2017
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Ingår i: Journal of Advances in Modeling Earth Systems. - : American Geophysical Union (AGU). - 1942-2466. ; 9:2, s. 1116-1137
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Tidskriftsartikel (refereegranskat)abstract
- Turbulence is argued to play a crucial role in cloud droplet growth. The combined problem of turbulence and cloud droplet growth is numerically challenging. Here an Eulerian scheme based on the Smoluchowski equation is compared with two Lagrangian superparticle (or superdroplet) schemes in the presence of condensation and collection. The growth processes are studied either separately or in combination using either two-dimensional turbulence, a steady flow or just gravitational acceleration without gas flow. Good agreement between the different schemes for the time evolution of the size spectra is observed in the presence of gravity or turbulence. The Lagrangian superparticle schemes are found to be superior over the Eulerian one in terms of computational performance. However, it is shown that the use of interpolation schemes such as the cloud-in-cell algorithm is detrimental in connection with superparticle or superdroplet approaches. Furthermore, the use of symmetric over asymmetric collection schemes is shown to reduce the amount of scatter in the results. For the Eulerian scheme, gravitational collection is rather sensitive to the mass bin resolution, but not so in the case with turbulence. Plain Language Summary The bottleneck problem of cloud droplet growth is one of the most challenging problems in cloud physics. Cloud droplet growth is neither dominated by condensation nor gravitational collision in the size range of 15 mu m similar to 40 mu m [1]. Turbulence-generated collection has been thought to be the mechanism to bridge the size gap, i.e., the bottleneck problem. This study compares the Lagrangian and Eulerian schemes in detail to tackle with the turbulence-generated collection.
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| 18. |
- Lindgren, Amelie, et al.
(författare)
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Reconstructing Past Global Vegetation With Random Forest Machine Learning, Sacrificing the Dynamic Response for Robust Results
- 2021
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 13:2
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Tidskriftsartikel (refereegranskat)abstract
- Vegetation is an important component in the Earth system, providing a direct link between the biosphere and atmosphere. As such, a representative vegetation pattern is needed to accurately simulate climate. We attempt to model global vegetation (biomes) with a data‐driven approach, to test if this allows us to create robust global and regional vegetation patterns. This not only provides quantitative reconstructions of past vegetation cover as a climate forcing, but also improves our understanding of past land cover‐climate interactions which have important implications for the future. By using a Random Forest (RF) machine learning tool, we train the vegetation reconstruction with available biomized pollen data of present and past conditions to produce broad‐scale vegetation patterns for the preindustrial (PI), the mid‐Holocene (MH, ∼6,000 years ago), and the Last Glacial Maximum (LGM, ∼21,000 years ago). We test the method's robustness by introducing a systematic temperature bias based on existing climate model spread and compare the result with that of LPJ‐GUESS, an individual‐based dynamic global vegetation model. The results show that the RF approach is able to produce robust patterns for periods and regions well constrained by evidence (the PI and the MH), but fails when evidence is scarce (the LGM). The apparent robustness of this method is achieved at the cost of sacrificing the ability to model dynamic vegetation response to a changing climate.
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| 19. |
- Luo, Yiqi, et al.
(författare)
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Matrix Approach to Land Carbon Cycle Modeling
- 2022
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 14:7
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Forskningsöversikt (refereegranskat)abstract
- Land ecosystems contribute to climate change mitigation by taking up approximately 30% of anthropogenically emitted carbon. However, estimates of the amount and distribution of carbon uptake across the world's ecosystems or biomes display great uncertainty. The latter hinders a full understanding of the mechanisms and drivers of land carbon uptake, and predictions of the future fate of the land carbon sink. The latter is needed as evidence to inform climate mitigation strategies such as afforestation schemes. To advance land carbon cycle modeling, we have developed a matrix approach. Land carbon cycle models use carbon balance equations to represent carbon exchanges among pools. Our approach organizes this set of equations into a single matrix equation without altering any processes of the original model. The matrix equation enables the development of a theoretical framework for understanding the general, transient behavior of the land carbon cycle. While carbon input and residence time are used to quantify carbon storage capacity at steady state, a third quantity, carbon storage potential, integrates fluxes with time to define dynamic disequilibrium of the carbon cycle under global change. The matrix approach can help address critical contemporary issues in modeling, including pinpointing sources of model uncertainty and accelerating spin-up of land carbon cycle models by tens of times. The accelerated spin-up liberates models from the computational burden that hinders comprehensive parameter sensitivity analysis and assimilation of observational data to improve model accuracy. Such computational efficiency offered by the matrix approach enables substantial improvement of model predictions using ever-increasing data availability. Overall, the matrix approach offers a step change forward for understanding and modeling the land carbon cycle.
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| 20. |
- Mauritsen, Thorsten, et al.
(författare)
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Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and Its Response to Increasing CO2
- 2019
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 11:4, s. 998-1038
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Tidskriftsartikel (refereegranskat)abstract
- A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI-ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low-level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO2 forcing, which nonetheless can be represented by a simple two-layer model.
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| 21. |
- Mauritsen, Thorsten, et al.
(författare)
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Tuning the MPI-ESM1.2 Global Climate Model to Improve the Match With Instrumental Record Warming by Lowering Its Climate Sensitivity
- 2020
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 12:5
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Tidskriftsartikel (refereegranskat)abstract
- A climate model's ability to reproduce observed historical warming is sometimes viewed as a measure of quality. Yet, for practical reasons it cannot be considered a purely empirical result of the modeling efforts because the desired result is known in advance and so is a potential target of tuning. Here we report how the latest edition of the Max Planck Institute for Meteorology Earth System Models (MPI-ESM1.2) atmospheric component (ECHAM6.3) had its sensitivity systematically tuned in order to improve the modeled match with the instrumental record. In practice, this was done by targeting an equilibrium climate sensitivity of about 3 K, slightly lower than in the previous model generation (MPI-ESM), which warmed more than observed, and in particular by addressing a climate sensitivity of about 7 K in an intermediate version of the model. In the process we identified several controls on cloud feedback, some of which confirm recently proposed hypotheses. We find the model exhibits excellent fidelity with the observed centennial global warming. We further find that an alternative approach with high climate sensitivity compensated by strong aerosol cooling instead would yield colder than observed results in the second half of the twentieth century.
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| 22. |
- Morel, X., et al.
(författare)
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A New Process-Based Soil Methane Scheme : Evaluation Over Arctic Field Sites With the ISBA Land Surface Model
- 2019
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 11:1, s. 293-326
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Tidskriftsartikel (refereegranskat)abstract
- Permafrost soils and arctic wetlands methane emissions represent an important challenge for modeling the future climate. Here we present a process-based model designed to correctly represent the main thermal, hydrological, and biogeochemical processes related to these emissions for general land surface modeling. We propose a new multilayer soil carbon and gas module within the Interaction Soil-Biosphere-Atmosphere (ISBA) land-surface model (LSM). This module represents carbon pools, vertical carbon dynamics, and both oxic and anoxic organic matter decomposition. It also represents the soil gas processes for CH4, CO2, and O2 through the soil column. We base CH4 production and oxydation on an O2 control instead of the classical water table level strata approach used in state-of-the-art soil CH4 models. We propose a new parametrization of CH4 oxydation using recent field experiments and use an explicit O2 limitation for soil carbon decomposition. Soil gas transport is computed explicitly, using a revisited formulation of plant-mediated transport, a new representation of gas bulk diffusivity in porous media closer to experimental observations, and an innovative advection term for ebullition. We evaluate this advanced model on three climatically distinct sites : two in Greenland (Nuuk and Zackenberg) and one in Siberia (Chokurdakh). The model realistically reproduces methane and carbon dioxide emissions from both permafrosted and nonpermafrosted sites. The evolution and vertical characteristics of the underground processes leading to these fluxes are consistent with current knowledge. Results also show that physics is the main driver of methane fluxes, and the main source of variability appears to be the water table depth.
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| 23. |
- Nilsson, Mats
(författare)
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PEAT-CLSM: A Specific Treatment of Peatland Hydrology in the NASA Catchment Land Surface Model
- 2019
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Ingår i: Journal of advances in modeling earth systems. - 1942-2466. ; 11, s. 2130-2162
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Tidskriftsartikel (refereegranskat)abstract
- Peatlands are poorly represented in global Earth system modeling frameworks. Here we add a peatland-specific land surface hydrology module (PEAT-CLSM) to the Catchment Land Surface Model (CLSM) of the NASA Goddard Earth Observing System (GEOS) framework. The amended TOPMODEL approach of the original CLSM that uses topography characteristics to model catchment processes is discarded, and a peatland-specific model concept is realized in its place. To facilitate its utilization in operational GEOS efforts, PEAT-CLSM uses the basic structure of CLSM and the same global input data. Parameters used in PEAT-CLSM are based on literature data. A suite of CLSM and PEAT-CLSM simulations for peatland areas between 40 degrees N and 75 degrees N is presented and evaluated against a newly compiled data set of groundwater table depth and eddy covariance observations of latent and sensible heat fluxes in natural and seminatural peatlands. CLSM's simulated groundwater tables are too deep and variable, whereas PEAT-CLSM simulates a mean groundwater table depth of -0.20 m (snow-free unfrozen period) with moderate temporal fluctuations (standard deviation of 0.10 m), in significantly better agreement with in situ observations. Relative to an operational CLSM version that simply includes peat as a soil class, the temporal correlation coefficient is increased on average by 0.16 and reaches 0.64 for bogs and 0.66 for fens when driven with global atmospheric forcing data. In PEAT-CLSM, runoff is increased on average by 38% and evapotranspiration is reduced by 19%. The evapotranspiration reduction constitutes a significant improvement relative to eddy covariance measurements.
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| 24. |
- Olivetti, Leonardo, et al.
(författare)
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A Quantile Generalized Additive Approach for Compound Climate Extremes : Pan-Atlantic Extremes as a Case Study
- 2024
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Ingår i: Journal of Advances in Modeling Earth Systems. - : American Geophysical Union (AGU). - 1942-2466. ; 16:1
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Tidskriftsartikel (refereegranskat)abstract
- We present an application of quantile generalized additive models (QGAMs) to study spatially compounding climate extremes, namely extremes that occur (near-) simultaneously in geographically remote regions. We take as an example wintertime cold spells in North America and co-occurring wet or windy extremes in Western Europe, which we collectively term Pan-Atlantic compound extremes. QGAMS are largely novel in climate science applications and present a number of key advantages over conventional statistical models of weather extremes. Specifically, they remove the need for a direct identification and parametrization of the extremes themselves, since they model all quantiles of the distributions of interest. They thus make use of all information available, and not only of a small number of extreme values. Moreover, they do not require any a priori knowledge of the functional relationship between the predictors and the dependent variable. Here, we use QGAMs to both characterize the co-occurrence statistics and investigate the role of possible dynamical drivers of the Pan-Atlantic compound extremes. We find that cold spells in North America are a useful predictor of subsequent wet or windy extremes in Western Europe, and that QGAMs can predict those extremes more accurately than conventional peak-over-threshold models. In this paper we propose a new data-driven method to study climate extremes occurring simultaneously in multiple, possibly remote, locations. Such extremes can pose a greater threat to human societies than single, isolated extremes, as their effects may exacerbate each other and lead to correlated losses. The method we suggest requires fewer assumptions than conventional extreme value statistical techniques, and can help us to identify previously unknown relationships between the extremes themselves and their possible drivers. We exemplify its use by studying the co-occurrence of periods of unusually cold weather in North America and subsequent uncommonly strong wind and abundant precipitation in Western Europe. We find that the new method has better predictive power for the European extremes than conventional statistical approaches. Furthermore, we confirm the results of previous studies suggesting an association between the wintertime extremes in North America and Western Europe. Quantile general additive models (QGAMs) can model the relationship between compound climate extremes flexibly and robustlyNorth American cold spells show some predictive skill for wet or windy extremes in Western Europe, even when accounting for confoundersGiven relevant atmospheric predictors, QGAMs can predict these extremes more accurately than peak-over-threshold models in most regions
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| 25. |
- Ovchinnikov, Mikhail, et al.
(författare)
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Intercomparison of large-eddy simulations of Arctic mixed-phase clouds : Importance of ice size distribution assumptions
- 2014
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 6:1, s. 223-248
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Tidskriftsartikel (refereegranskat)abstract
- Large-eddy simulations of mixed-phase Arctic clouds by 11 different models are analyzed with the goal of improving understanding and model representation of processes controlling the evolution of these clouds. In a case based on observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC), it is found that ice number concentration, N-i, exerts significant influence on the cloud structure. Increasing N-i leads to a substantial reduction in liquid water path (LWP), in agreement with earlier studies. In contrast to previous intercomparison studies, all models here use the same ice particle properties (i.e., mass-size, mass-fall speed, and mass-capacitance relationships) and a common radiation parameterization. The constrained setup exposes the importance of ice particle size distributions (PSDs) in influencing cloud evolution. A clear separation in LWP and IWP predicted by models with bin and bulk microphysical treatments is documented and attributed primarily to the assumed shape of ice PSD used in bulk schemes. Compared to the bin schemes that explicitly predict the PSD, schemes assuming exponential ice PSD underestimate ice growth by vapor deposition and overestimate mass-weighted fall speed leading to an underprediction of IWP by a factor of two in the considered case. Sensitivity tests indicate LWP and IWP are much closer to the bin model simulations when a modified shape factor which is similar to that predicted by bin model simulation is used in bulk scheme. These results demonstrate the importance of representation of ice PSD in determining the partitioning of liquid and ice and the longevity of mixed-phase clouds.
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| 26. |
- Pithan, Felix, et al.
(författare)
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Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice : the Larcform 1 single column model intercomparison
- 2016
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 8:3, s. 1345-1357
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Tidskriftsartikel (refereegranskat)abstract
- Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Here, the transformation from a moist to a cold dry air mass is modeled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first Lagrangian Arctic air formation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: some models lack the cloudy state of the boundary layer due to the representation of mixed-phase microphysics or to the interaction between micro- and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behavior.
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| 27. |
- Rasp, Stephan, et al.
(författare)
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WeatherBench : A Benchmark Data Set for Data-Driven Weather Forecasting
- 2020
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 12:11
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Tidskriftsartikel (refereegranskat)abstract
- Data-driven approaches, most prominently deep learning, have become powerful tools for prediction in many domains. A natural question to ask is whether data-driven methods could also be used to predict global weather patterns days in advance. First studies show promise but the lack of a common data set and evaluation metrics make intercomparison between studies difficult. Here we present a benchmark data set for data-driven medium-range weather forecasting (specifically 3-5 days), a topic of high scientific interest for atmospheric and computer scientists alike. We provide data derived from the ERA5 archive that has been processed to facilitate the use in machine learning models. We propose simple and clear evaluation metrics which will enable a direct comparison between different methods. Further, we provide baseline scores from simple linear regression techniques, deep learning models, as well as purely physical forecasting models. The data set is publicly available at and the companion code is reproducible with tutorials for getting started. We hope that this data set will accelerate research in data-driven weather forecasting.
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| 28. |
- Retsch, M. H., et al.
(författare)
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Climate Change Feedbacks in Aquaplanet Experiments With Explicit and Parametrized Convection for Horizontal Resolutions of 2,525 Up to 5 km
- 2019
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 11:7, s. 2070-2088
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Tidskriftsartikel (refereegranskat)abstract
- Earth's equilibrium climate sensitivity (ECS) is the long-term response to doubled atmospheric CO2 and likely between 1.5 and 4.5 K. Conventional general circulation models do not convincingly narrow down this range, and newly developed nonhydrostatic models with relatively fine horizontal resolutions of a few kilometers have thus far delivered diverse results. Here we use the nonhydrostatic ICON model with the physics package normally used for climate simulations at resolutions as fine as 5 km to study the response to a uniform surface warming in an aquaplanet configuration. We apply the model in two setups: one with convection parametrization employed and one with explicit convection. ICON exhibits a negative total feedback independent of convective representation, thus providing a stable climate with an ECS comparable to other general circulation models, though three interesting new results are found. First, ECS varies little across resolution for both setups but runs with explicit convection have systematically lower ECS than the parametrized case, mainly due to more negative tropical clear-sky longwave feedbacks. These are a consequence of a drier mean state of about 6% relative humidity for explicit convection and less midtropospheric moistening with global warming. Second, shortwave feedbacks switch from positive to negative with increasing resolution, originating foremost in the tropics and high latitudes. Third, the model shows no discernible high cloud area feedback (iris effect) in any configuration. It is possible that ICON's climate model parametrizations applied here are less appropriate for cloud resolving scales, and therefore, ongoing developments aim at implementing a more advanced prognostic cloud microphysics scheme.
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| 29. |
- Savre, Julien, et al.
(författare)
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Technical note : Introduction to MIMICA, a large-eddy simulation solver for cloudy planetary boundary layers
- 2014
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 6:3, s. 630-649
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Tidskriftsartikel (refereegranskat)abstract
- In large-eddy simulation (LES), large-scale turbulent structures are explicitly resolved on the numerical grid while the dissipative turbulent eddies, typically smaller than the grid size, must be modeled. Because in the atmospheric boundary layer a large disparity of turbulent scales exists (about 9 orders of magnitude separate the largest and smallest scales), LES is considered as an essential modeling approach to capture the physics and dynamics of boundary layer clouds. A new LES solver developed at Stockholm University is presented here for the first time. The model solves for nonhydrostatic anelastic equations using high-order low-dissipative numerical schemes for the advection of scalars and momentum. A two-moment bulk microphysics scheme is implemented representing five types of hydrometeors including ice crystals and snow. The LES is evaluated based on simulations of two well-documented stratiform cloud events that were previously used for LES intercomparisons. In the first one, a marine drizzling stratocumulus observed during DYCOMS-II, the model is shown to predict bulk cloud microphysical and dynamical properties within the range of the intercomparison model results. In the second case, based on a monolayer Arctic mixed-phase cloud observed during ISDAC, we found that when using fast-falling crystals, ice quickly precipitates out of the cloud without significant growth, resulting in very low ice water paths. The simulated clouds are also found to be very sensitive to the prescribed ice crystal number concentration: multiplying the ice concentration by a factor 2.5 results in rapid cloud dissipation in the most extreme case. Overall, these results are found to be consistent with former studies of Arctic mixed-phase clouds as well as in situ measurements. More specifically, when the ice number concentration and parameterized ice habit are constrained by measurements, simulated microphysical properties such as the ice water path and ice crystal size distribution are found to agree well with observations.
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| 30. |
- Scher, Sebastian, et al.
(författare)
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Ensemble Methods for Neural Network-Based Weather Forecasts
- 2021
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Ingår i: Journal of Advances in Modeling Earth Systems. - : American Geophysical Union (AGU). - 1942-2466. ; 13:2
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Tidskriftsartikel (refereegranskat)abstract
- Ensemble weather forecasts enable a measure of uncertainty to be attached to each forecast, by computing the ensemble's spread. However, generating an ensemble with a good spread-error relationship is far from trivial, and a wide range of approaches to achieve this have been explored-chiefly in the context of numerical weather prediction models. Here, we aim to transform a deterministic neural network weather forecasting system into an ensemble forecasting system. We test four methods to generate the ensemble: random initial perturbations, retraining of the neural network, use of random dropout in the network, and the creation of initial perturbations with singular vector decomposition. The latter method is widely used in numerical weather prediction models, but is yet to be tested on neural networks. The ensemble mean forecasts obtained from these four approaches all beat the unperturbed neural network forecasts, with the retraining method yielding the highest improvement. However, the skill of the neural network forecasts is systematically lower than that of state-of-the-art numerical weather prediction models.
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| 31. |
- Voigt, Aiko, et al.
(författare)
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Fast and slow shifts of the zonal-mean intertropical convergence zone in response to an idealized anthropogenic aerosol
- 2017
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 9:2, s. 870-892
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Tidskriftsartikel (refereegranskat)abstract
- Previous modeling work showed that aerosol can affect the position of the tropical rain belt, i.e., the intertropical convergence zone (ITCZ). Yet it remains unclear which aspects of the aerosol impact are robust across models, and which are not. Here we present simulations with seven comprehensive atmosphere models that study the fast and slow impacts of an idealized anthropogenic aerosol on the zonalmean ITCZ position. The fast impact, which results from aerosol atmospheric heating and land cooling before sea-surface temperature (SST) has time to respond, causes a northward ITCZ shift. Yet the fast impact is compensated locally by decreased evaporation over the ocean, and a clear northward shift is only found for an unrealistically large aerosol forcing. The local compensation implies that while models differ in atmospheric aerosol heating, this does not contribute to model differences in the ITCZ shift. The slow impact includes the aerosol impact on the ocean surface energy balance and is mediated by SST changes. The slow impact is an order of magnitude more effective than the fast impact and causes a clear southward ITCZ shift for realistic aerosol forcing. Models agree well on the slow ITCZ shift when perturbed with the same SST pattern. However, an energetic analysis suggests that the slow ITCZ shifts would be substantially more modeldependent in interactive-SST setups due to model differences in clear-sky radiative transfer and clouds. We also discuss implications for the representation of aerosol in climate models and attributions of recent observed ITCZ shifts to aerosol.
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| 32. |
- Vukicevic, T., et al.
(författare)
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Sensitivity of Modeled Microphysics to Stochastically Perturbed Parameters
- 2022
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 14:7
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Tidskriftsartikel (refereegranskat)abstract
- This study examines the characteristics of several model parameter perturbation methodologies for ensemble simulations of cloud microphysical processes in convection. A simplified 1D model is used to focus the results on cloud microphysics without the complication of feedbacks to the dynamics and environment. Several parameter perturbation methods are tested, including non-stochastic and stochastic with various distributions and parameter covariance. We find that an ensemble comprised of different time-invariant parameters (non-stochastic) exhibits little bias, but small spread. In addition, its behavior does not respect the time evolution of convection through its various phases. Stochastic parameter (SP) methods in which no inter-parameter covariance is applied produce greater spread, but significant bias. The bias is particularly large for lognormal parameter perturbation distributions. The ensemble spread is retained and the bias reduced when time-varying parameter covariance is applied. In this case, the SP scheme is able to adapt to the time and state-dependent covariance structures and produce ensemble characteristics that are consistent with the specific microphysical processes operating at any given time. The results suggest that SP schemes would benefit from inclusion of parameter covariances, and specifically those that vary with the state of the system. It also suggests that a Normal or LogNormal SP scheme with no covariance may significantly impact the ensemble bias. Finally, the results indicate that high temporal and spatial resolution observations may be needed to characterize the variability in parameter values and covariance.
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| 33. |
- Watson-Parris, D., et al.
(författare)
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ClimateBench v1.0 : A Benchmark for Data-Driven Climate Projections
- 2022
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 14:10
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Tidskriftsartikel (refereegranskat)abstract
- Many different emission pathways exist that are compatible with the Paris climate agreement, and many more are possible that miss that target. While some of the most complex Earth System Models have simulated a small selection of Shared Socioeconomic Pathways, it is impractical to use these expensive models to fully explore the space of possibilities. Such explorations therefore mostly rely on one-dimensional impulse response models, or simple pattern scaling approaches to approximate the physical climate response to a given scenario. Here we present ClimateBench-the first benchmarking framework based on a suite of Coupled Model Intercomparison Project, AerChemMIP and Detection-Attribution Model Intercomparison Project simulations performed by a full complexity Earth System Model, and a set of baseline machine learning models that emulate its response to a variety of forcers. These emulators can predict annual mean global distributions of temperature, diurnal temperature range and precipitation (including extreme precipitation) given a wide range of emissions and concentrations of carbon dioxide, methane and aerosols, allowing them to efficiently probe previously unexplored scenarios. We discuss the accuracy and interpretability of these emulators and consider their robustness to physical constraints such as total energy conservation. Future opportunities incorporating such physical constraints directly in the machine learning models and using the emulators for detection and attribution studies are also discussed. This opens a wide range of opportunities to improve prediction, robustness and mathematical tractability. We hope that by laying out the principles of climate model emulation with clear examples and metrics we encourage engagement from statisticians and machine learning specialists keen to tackle this important and demanding challenge.
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| 34. |
- Wu, Lichuan, et al.
(författare)
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Ocean‐Wave‐Atmosphere Interaction Processes in a Fully Coupled Modeling System
- 2019
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 11:11, s. 3852-3874
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Tidskriftsartikel (refereegranskat)abstract
- A high‐resolution coupled ocean‐wave‐atmosphere model (Uppsala University Coupled model, UU‐CM) of the Baltic Sea and the North Sea with improved representation of ocean‐wave‐atmosphere interaction processes is presented. In the UU‐CM model, the stress on the air‐sea interface is estimated as a balance of four stress terms, that is, the air‐side stress, ocean‐side stress, wave‐supported stress (absorption of momentum by the wave field), and the momentum flux from waves to currents (breaking waves). The vector differences between these four stress terms are considered in the coupled system. The turbulent kinetic energy flux induced by wave breaking, the Stokes‐Coriolis force and the Stokes drift material advection terms are added to the ocean circulation model component. Based on two‐month‐long (January and July) simulations, we find that the ocean‐wave‐atmosphere coupling has a significant influence on coastal areas. The coupled system captures the influence of surface currents and local systems such as coastal upwelling and their impact on the atmosphere. The wave‐current interaction enhances the upper ocean mixing and reduces the sea surface temperature in July significantly. However, the pattern of the wave‐current processes influences on the ocean current and waves are complex due to the stress differences in both magnitude and direction.
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