AS5.1 | Advances in Numerical Earth System Modeling: Identifying Systematic Errors and Charting Innovative Approaches to Enhance Numerical Weather and Climate Prediction
EDI
Advances in Numerical Earth System Modeling: Identifying Systematic Errors and Charting Innovative Approaches to Enhance Numerical Weather and Climate Prediction
Convener: Werner Bauer | Co-conveners: Ariane FrassoniECSECS, Jemma Shipton, Nils Wedi, Hiroe YamazakiECSECS, Tim Graham, Fanglin Yang
Orals
| Tue, 16 Apr, 14:00–15:45 (CEST)
 
Room M1
Posters on site
| Attendance Wed, 17 Apr, 10:45–12:30 (CEST) | Display Wed, 17 Apr, 08:30–12:30
 
Hall X5
Orals |
Tue, 14:00
Posters on site
Wed, 10:45
In the domain of weather prediction and climate modeling, Earth System Models (ESMs) play a pivotal role. EMSs are built with advanced numerical techniques to simulate the dynamics, physics, and biogeochemistry of the Earth's components. These models integrate a fluid dynamics solver (dynamical core) coupled with physical parameterizations to represent sub-grid processes. Over time these models have become capable of sophisticated simulations, thanks to the growth of computing power and the development of new techniques, like Machine Learning (ML). This technological surge allows for more sophisticated modeling systems and larger ensembles, setting the frame for a new era of operational weather and climate prediction systems.

Despite significant progress, challenges persist in identifying and correcting errors within individual ESM components, exacerbated by complex inter-component interactions. Moreover, limitations in the observational network hinder the full constraint of ESMs. Efforts to assess, test, and enhance models have reduced major systematic errors, yet challenges persist while new ones have emerged. Ongoing research and development efforts focus on enhancing the accuracy, seeking a better representation of different processes in ESMs by identifying and correcting systematic errors, but also considering the efficiency, and scalability of ESM components, including the dynamical core, physics, and their coupling.

This session invites contributions related to the development, testing, and application of innovative techniques for ESMs, as well as contributions that provide a deep understanding of the nature and causes of systematic errors in ESMs. Topics encompass governing equations, horizontal and vertical discretizations, structure-preserving methods, time-stepping schemes (including parallel in time schemes), advection schemes, adaptive multi-scale models, model errors across space and time scales, hierarchies of models, physics-dynamics and physics-physics cross-component coupling, initialized predictions, climatology of weather prediction models, data assimilation methodologies, the use of ML to identify errors and detect causal connections, stochastic parameterization for uncertainty representation, and verification diagnostics and metrics for characterizing systematic errors and process understanding across various modeling communities (regional and global km-scale modeling).

Orals: Tue, 16 Apr | Room M1

Chairpersons: Werner Bauer, Tim Graham
14:00–14:05
5-minute convener introduction
14:05–14:15
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EGU24-12501
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ECS
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On-site presentation
A unifying moist shallow water framework and test cases for moist shallow water models 
Nell Hartney and Thomas Bendall

The rotating shallow water equations are widely used in the development of weather and climate models. They are a much simpler equation set than the full 3D atmospheric equations and so are computationally cheap, but they still retain many pertinent features of atmospheric dynamics. The usual shallow water equations model a ‘dry’ atmosphere and so neglect moist processes and moisture effects. Including moisture in the shallow water system not only extends the modelling potential of the equations, but also introduces numerical complexities that are of interest in the development of time-stepping schemes. These include features such as new timescales related to moist physics processes, discontinuities introduced by the notion of boundaries between ‘precipitating’ and ‘non-precipitating’ regions, and how the addition of moisture affects the ideas of balance and conservation in the equations. In this way the moist shallow water equations provide a simplified equation set for exploring physics-dynamics coupling and how this coupling is handled by different time steppers.

This talk will discuss our implementation of a flexible, unifying moist shallow water model that encompasses three different approaches to moist shallow water modelling. Our implementation is in the dynamical core toolkit Gusto, which follows a compatible finite element approach like that of the next-generation UK Met Office model. We will demonstrate some simple moist shallow water test cases using each of the three approaches with our unifying formulation in Gusto, and describe progress towards running tests with more complex dynamics to investigate questions about time-stepping with physics. 

How to cite: Hartney, N. and Bendall, T.: A unifying moist shallow water framework and test cases for moist shallow water models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12501, https://doi.org/10.5194/egusphere-egu24-12501, 2024.

14:15–14:25
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EGU24-8249
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ECS
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On-site presentation
Coupling hydrostatic and non-hydrostatic ocean circulation models. Vertical modes perspective. 
Pierre Lozano

Large-scale ocean modeling relies on the so-called primitive equations, which are a simplified form of the Navier-Stokes equations based on common assumptions. These assumptions include the Boussinesq approximation, the hydrostatic assumption and the incompressibility hypothesis. The hydrostatic assumption is yet no longer valid in the framework of high-resolution regional ocean modeling and is thus to be removed, leading to a significant increase in the computational load of the model. This gives rise to consideration of model coupling, where the hydrostatic assumption is selectively lifted within specific regions of the computational domain. This is the subject of this work.

One of the primary challenges involves accurately representing the various types of waves that propagate in the ocean. Waves are studied by analyzing the dispersion relations after linearizing the equations. A key distinction between hydrostatic and non-hydrostatic modeling lies in the dispersive nature of the wave propragation in the latter. We initially explore an idealized scenario by coupling a transport equation with a Korteweg-de Vries equation. To manage dispersive effects, we employ Perfectly Matched Layers (PML), typically used for replicating absorbing boundary conditions, they can also be regarded as a buffer zone for filtering dispersive effects.

Expanding this approach into a three-dimensional framework involves projecting the vertical ocean structure onto vertical modes associated with the ocean's background vertical stratification. We show that this projection allows us to reduce the problem to the previously studied case.

How to cite: Lozano, P.: Coupling hydrostatic and non-hydrostatic ocean circulation models. Vertical modes perspective., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8249, https://doi.org/10.5194/egusphere-egu24-8249, 2024.

14:25–14:35
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EGU24-10755
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ECS
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On-site presentation
Design of a generalized vertical coordinate to properly represent the structure of normal modes in an oceanic model  
Gabriel Derrida, Laurent Debreu, Florian Lemarie, and Jérôme Chanut

In ocean modeling, the choice of a suitable vertical coordinate system is crucial due to the complex vertical dynamics of the ocean, playing a significant role in climate considerations. The objective of this research is to develop a generalized vertical coordinate system applicable across various scales, from global to coastal applications. 

Three primary algorithms for solving generalized vertical coordinate ocean equations are considered: quasi-Eulerian (QE) coordinate, Vertical Lagrangian Remapping (VLR), and the Arbitrary Lagrangian-Eulerian (V-ALE) method. The V-ALE method offers an alternative between QE and VLR, incorporating both Lagrangian and Eulerian components in the movement of the target grid. In this study, the focus is on the V-ALE method, with a particular emphasis on specifying the target grid. 

The proposed approach consists in defining the target grid to solve a propagation problem in an inhomogeneous environment. The stratification state, a key element of this environment, has a significant influence on the mode structure.

From a discrete point of view, the challenge is to identify the optimum grid point positions for correctly representing vertical modes. The aim is to understand the errors introduced by discretization and minimize them to find the optimal point positions. A variational method is also proposed, leading to a non-uniform grid that better represents vertical modes. We illustrate the results obtained with these methods using stratification profiles derived from climatological data.

How to cite: Derrida, G., Debreu, L., Lemarie, F., and Chanut, J.: Design of a generalized vertical coordinate to properly represent the structure of normal modes in an oceanic model , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10755, https://doi.org/10.5194/egusphere-egu24-10755, 2024.

14:35–14:45
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EGU24-16312
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On-site presentation
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PPM+W, an improved version of the Piecewise Parabolic Method advection scheme: Description, evaluation and implementation in the CHIMERE model. 
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian

We have developed a new advection scheme for Eulerian models by combining the Piecewise Parabolic Method “PPM” (Colella, 1984) and the Walcek scheme (Walcek, 2000). The concept is to keep the excellent accuracy of the PPM scheme in the areas of smooth gradient, and to use the flux modifications of Walcek to improve over the PPM scheme in the vicinity of extrema. This combination forms a new advection scheme that we call PPM+W (“Piecewise Parabolic Method + Walcek”). We have studied the properties of this new scheme in the idealized framework of ToyCTM v1.0.1, an academic model including advection and stiff chemistry mimicking tropospheric photochemistry, including inert species and reactive species such as nitrogen oxide, ozones and radicals. This study shows that PPM+W reduces advection error by 10-30% compared to both the Walcek scheme and the PPM scheme. The efficiency of PPM+W is also good: the computation time for PPM+W is not higher than in the classical PPM scheme. Following these results, PPM+W has been implemented in the CHIMERE chemistry-transport model (CHIMERE v2023r1), and could also be useful for other models including atmospheric and oceanic models.

Apart from the design of this new advection scheme, we present a novel method to evaluate advection schemes in contexts where mixing is weak / negligible, and show that this novel method gives results consistent with more classical methods, without requiring the knowledge of the exact solution.

References:
 Colella, P. and Woodward, P. R.: The piecewise parabolic method (PPM) for gas-dynamical simulations, J. Comput. Phys., 54, 174-201, https://doi.org/10.1016/0021-9991(84)90143-8, 1984
 
 Mailler, S., Pennel, R., Menut, L., and Cholakian, A.: An improved  version of the piecewise parabolic method advection scheme: description  and performance assessment in a bidimensional test case with stiff  chemistry in toyCTM v1.0.1, Geosci. Model Dev., 16, 7509–7526,  https://doi.org/10.5194/gmd-16-7509-2023, 2023

Walcek, C., Minor flux adjustment near mixing ratio extremes for simplified yet highly accurate monotonic calculation of tracer advection, J. Geophys. Res., 105, 9335–9348, https://doi.org/10.1029/1999JD901142, 2000

How to cite: Mailler, S., Pennel, R., Menut, L., and Cholakian, A.: PPM+W, an improved version of the Piecewise Parabolic Method advection scheme: Description, evaluation and implementation in the CHIMERE model., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16312, https://doi.org/10.5194/egusphere-egu24-16312, 2024.

14:45–14:55
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EGU24-11884
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On-site presentation
An efficient and accurate deep learning approach to weather prediction 
Tan Bui-Thanh and Arjit Seth

Machine learning is being increasingly applied as a surrogate modeling technique for weather prediction, providing fast forecasts with similar accuracy to numerical weather prediction models. However, developing accurate state-of-the-art machine learning models requires a significant allocation of high-performance computing resources for processing datasets and training. In this work, we investigate the essential components of a deep learning model architecture for accurate weather prediction and formulate strategies that reduce the number of parameters needed in such a model based on physical assumptions to lower training time. Specifically, we investigate autoencoder architectures with convolutional and attention-based neural network layers for capturing the necessary information provided by weather data for prediction. These architectures are incorporated within the neural ordinary differential equations framework and then trained based on reanalysis data constructed from simulation and observation data to provide forecasts. The results and conclusions based on these experiments are discussed, and recommendations for future work are provided.

How to cite: Bui-Thanh, T. and Seth, A.: An efficient and accurate deep learning approach to weather prediction, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11884, https://doi.org/10.5194/egusphere-egu24-11884, 2024.

14:55–15:15
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EGU24-2044
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solicited
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On-site presentation
Understanding Systematic Errors in Simulation of the Diurnal Cycle of Precipitation in Weather and Climate Models through a Multi-Model Intercomparison with a Hierarchical Modeling Framework  
Shaocheng Xie, Cheng Tao, Shuaiqi Tang, Hsi-Yen Ma, Peter Bechtold, and David Neelin

This presentation reports the WCRP GEWEX GASS multi-model intercomparison study on diurnal cycle of precipitation, which is aimed to understand the processes that control the diurnal variation of precipitation over different climate regimes. The study focuses on the interaction between convection and its environments, afternoon and nocturnal convection over land, and convection transition. It used a hierarchy of models with different levels of complexity to diagnose and investigate the associated processes and model biases in simulation of the diurnal cycle of precipitation. Confronting models with detailed observations allowed to identify the deficiencies and missing physics in current weather and climate models and gain insights for further improving the parameterization of convection in General Circulation Models (GCMs).

Results from the recently completed long-term single-column model intercomparison and GCM intercomparison studies indicate that most of the participating models share common model biases in simulating the diurnal cycle of precipitation, as already illustrated in previous studies, such as the precipitation peak occurring too early during the day, a lack of nocturnal precipitation and transition from shallow to deep convection. The issues are primarily related to deficiencies in cumulus parameterizations. Sensitivity tests with different cumulus parameterizations suggest that a unified treatment of shallow and deep convection could better capture the transition from shallow to deep convection and help delay the daytime precipitation peak to late afternoon over land. However, this does not improve the simulation of nocturnal precipitation that is often caused by elevated convection associated with the passage of meso-scale convective systems. The key to capture the observed nocturnal peak is to allow elevated convection to be captured by incorporating a mid-level convection parameterization or removing the restriction of the source layer for launching air parcel within the boundary layer. Including convective memory in cumulus parameterizations acts to suppress light-to-moderate rain and promote intense rainfall, however, it weakens the diurnal variability of precipitation and does not show an improvement in the simulation of the diurnal cycle. Results also suggest that simply increasing model resolution cannot fully resolve the biases the diurnal cycle of precipitation in low-resolution models as long as cumulus parameterizations are needed. The hierarchical modeling framework is useful in identifying missing physics in GCMs and testing new developments of model physical parameterizations over different convective regimes.

How to cite: Xie, S., Tao, C., Tang, S., Ma, H.-Y., Bechtold, P., and Neelin, D.: Understanding Systematic Errors in Simulation of the Diurnal Cycle of Precipitation in Weather and Climate Models through a Multi-Model Intercomparison with a Hierarchical Modeling Framework , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2044, https://doi.org/10.5194/egusphere-egu24-2044, 2024.

15:15–15:25
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EGU24-9880
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ECS
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On-site presentation
Understanding the South-West Indian Ocean Temperature Bias: Forcing Ocean-Only Models with Coupled Model Atmospheric Output to Identify Drivers of Ocean Biases
(withdrawn)
Hannah Ellis
15:25–15:35
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EGU24-7246
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ECS
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On-site presentation
Algorithmic optimisation of key parameters of OpenIFS. Implications on ensemble forecasts 
Lauri Tuppi, Madeleine Ekblom, Daniel Köhler, Pirkka Ollinaho, and Heikki Järvinen

Numerical weather prediction models contain physical parameters describing various small-scale phenomena as a part of parameterization schemes. These parameters are uncertain and can be tuned manually, or more efficiently, using algorithmic methods. Algorithmic tuning is an appealing approach to increase transparency and repeatability of the tuning process. Often, the focus of model tuning is on deterministic forecasts and the effect of model tuning on ensemble forecasts receives little to no attention. This presentation exemplifies how a superficially justifiable choice of activating initial state perturbations in algorithmic tuning of model parameters can have a systematic (and potentially detrimental) effect on the spread-skill relationship of ensemble forecasts.

This presentation continues directly from the poster presented last year in EGU2023 (Tuppi et al. 2023). This time, the objective is to understand how algorithmic optimization of a weather model affects the skill of ensemble forecasts. This presentation focuses on ensemble forecasting-based verification of the tuned model versions using root-mean squared error/spread relationship, continuous ranked probability score, and filter likelihood score. The headline results show that ensemble forecasts run with tuned model parameters experience a significant reduction of spread when initial state perturbations are active during the tuning of the parameters. However, both choices of tuning the model with initial state perturbations activated and deactivated lead to optimal deterministic forecasts. This behavior likely arises from conflicting interests between the method to generate initial state perturbations and the method of determining goodness of the parameter values during tuning.

Tuppi, L., Ekblom, M., Ollinaho, P., and Järvinen, H.: Algorithmic optimisation of key parameters of OpenIFS, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4817, https://doi.org/10.5194/egusphere-egu23-4817, 2023.

How to cite: Tuppi, L., Ekblom, M., Köhler, D., Ollinaho, P., and Järvinen, H.: Algorithmic optimisation of key parameters of OpenIFS. Implications on ensemble forecasts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7246, https://doi.org/10.5194/egusphere-egu24-7246, 2024.

15:35–15:45
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EGU24-13684
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Virtual presentation
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Development of the signal-to-noise paradox in subseasonal forecasting models: After how long? Where? Why? 
Chen Schwartz, Chaim I. Garfinkel, Jeff Knight, Masakazu Taguchi, Judah Cohen, Wen Chen, Amy H. Butler, Daniela I.V. Domeisen, and Zachary Lawrence

Subseasonal forecast models are shown to suffer from the same  inconsistency found in climate models between the low strength of predictable signals and the relatively high level of agreement they exhibit with observed variability of the atmospheric circulation. That is, subseasonal forecast models show higher correlation with observed variability than with their own simulations, i.e., the signal-to-noise paradox. Also similar to climate models, this paradox is particularly evident in the North Atlantic sector.  The paradox is not evident in week 1 or week 2 forecasts, and hence is limited to subseasonal timescales. The paradox appears to be related to overly fast decay of Northern Annular  Mode regimes. Three possible causes of this overly fast decay and for the paradox in the Northern Hemisphere are identified:  a too-fast decay of polar stratospheric signals, overly weak downward coupling from the stratosphere to the surface (in some models),  and overly weak transient synoptic eddy feedbacks. While the paradox is clearly evident in the North Atlantic, things are qualitatively different in the Southern Hemisphere:  Southern Annular  Mode regimes persist realistically, the stratospheric signal is well maintained, and eddy feedback is, if anything, too strong and zonal.  

How to cite: Schwartz, C., Garfinkel, C. I., Knight, J., Taguchi, M., Cohen, J., Chen, W., Butler, A. H., Domeisen, D. I. V., and Lawrence, Z.: Development of the signal-to-noise paradox in subseasonal forecasting models: After how long? Where? Why?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13684, https://doi.org/10.5194/egusphere-egu24-13684, 2024.

Posters on site: Wed, 17 Apr, 10:45–12:30 | Hall X5

Display time: Wed, 17 Apr, 08:30–Wed, 17 Apr, 12:30
Chairperson: Hiroe Yamazaki
X5.84
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EGU24-17236
Low-effort stabilization for compressible Euler-Equations for volcanic plume simulation 
Joern Behrens and Michel Bänsch

A stabilization method for a discontinuous Galerkin discretization of the compressible Euler equations is presented, based on the idea of balancing the equations discretely. This method is very cost efficient with regards to computational effort while still effective in stabilizing the discrete numerical scheme. We apply the new numerical scheme to standard test cases as well as to a simplified volcanic plume model within an adaptive mesh refinement simulation framework. Comparisons with different adaptive mesh refinement environments (i.e. amatos and deal.II) are perfomed and demonstrate the applicability in particular in triangular adaptive meshes. Tests show that this method generates reliable and computationally efficient results.

How to cite: Behrens, J. and Bänsch, M.: Low-effort stabilization for compressible Euler-Equations for volcanic plume simulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17236, https://doi.org/10.5194/egusphere-egu24-17236, 2024.

X5.85
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EGU24-9149
GC5-LFRic: Developing the next Met Office coupled atmosphere-ocean model with a cubed-sphere atmosphere grid. 
Tim Graham, Maria Carvalho, Dan Copsey, Duncan Ackerley, Paul Earnshaw, Charline Marzin, Marion Mittermaier, Nikesh Narayan, Ben Shipway, and Martin Willett

The Met Office uses its global coupled atmosphere-ocean model for predictions on timescales from days to centuries as part of its seamless prediction framework. The atmospheric component of the coupled system is the Unified Model on a latitude-longitude grid. With ever increasing resolution and significant changes to high performance computing such as new processor types and increased parallelisation, a fundamentally new atmosphere model is needed to meet future requirements.

A major effort is underway to develop a new version of the coupled model using the GungHo dynamical core on a cube-sphere grid with atmospheric physics from the existing unified model. This is coupled to the NEMO ocean model and SI3 sea-ice model on a tripolar grid.

We will show results from the latest prototype models for numerical weather prediction and climate simulations. We will also discuss the ongoing work and challenges to make these systems operational at the Met Office.

How to cite: Graham, T., Carvalho, M., Copsey, D., Ackerley, D., Earnshaw, P., Marzin, C., Mittermaier, M., Narayan, N., Shipway, B., and Willett, M.: GC5-LFRic: Developing the next Met Office coupled atmosphere-ocean model with a cubed-sphere atmosphere grid., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9149, https://doi.org/10.5194/egusphere-egu24-9149, 2024.

X5.86
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EGU24-9189
Time parallel integration and phase averaging for the nonlinear shallow water equations on the sphere 
Hiroe Yamazaki, Colin Cotter, and Beth Wingate

We present a phase-averaging framework for the rotating shallow-water equations and a time-integration methodology for it. Phase averaging consists of averaging the nonlinearity over phase shifts in the exponential of the linear wave operator. Phase averaging aims to capture the slow dynamics in a solution that is smoother in time (in transformed variables), so that larger timesteps may be taken. In our numerical implementation, the averaging integral is replaced by a Riemann sum, where each term can be evaluated in parallel. This creates an opportunity for parallelism in the timestepping method.

In this talk, we will show proof-of-concept results and analyse their errors in order to examine the impact of the phase averaging on the rotating shallow-water solution. We will also examine how the averaging allows us to use larger timesteps and where the optimal averaging window is at a chosen timestep size.

How to cite: Yamazaki, H., Cotter, C., and Wingate, B.: Time parallel integration and phase averaging for the nonlinear shallow water equations on the sphere, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9189, https://doi.org/10.5194/egusphere-egu24-9189, 2024.

X5.87
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EGU24-6718
Accurate solutions of highly oscillatory systems under large time steps using higher-order phase averages 
Werner Bauer and Colin J. Cotter

We introduce a time integrator for a prototype model of highly oscillatory PDEs that exhibits accurate solutions even under the usage of large time step sizes. To achieve large time steps, we apply a phase averaging technique that smooths out the fast waves from the system. To avoid the errors that such smoothing usually entails, we use a higher order (HO) phase averaging algorithm based on the idea of [1]. This algorithm expresses the sensitivity of the solutions on the phases in terms of an HO basis which the equations are projected onto. The resulting HO phase corrections reduce the errors in the solutions even for finite averaging windows. Rather than using monomials as such HO basis as originally suggested in [1], here we introduce an alternative basis in terms of exponentials and we discuss its properties.

Similarly to [1], we test this idea on an ODE describing the dynamics of a swinging spring, a model due to Peter Lynch. Although idealized, this model shows an interesting analogy to geophysical flows as it exhibits a high sensitivity of small scale oscillation on the large scale dynamics. On this example, we illustrate that the HO phase averaging method with an exponential basis allows for highly accurate solutions even when using large averaging windows and hence larger time step sizes than standard methods. These HO phase corrections (the reason for this improvement) can be evaluated independently, hence computed in parallel. In contrast, in standard averaging approaches, e.g. [2], arbitrarily accurate solutions could only be obtained with small averaging windows as well as small time step sizes.  We present these highly promising results and discuss challenges in generalizing them to highly oscillatory PDEs for applications in simulations of weather, ocean, and climate.

References

[1] Bauer, W., Cotter, C. J. and Wingate, B. [2022], Higher order phase averaging for highly oscillatory systems, SIAM Multiscale Modeling \& Simulation (SIAM MMS), 20, 936-956.

[2] Peddle, A. G., Haut, T., Wingate, B. [2019], Parareal convergence for oscillatory PDEs with finite time-scale separation. SIAM Journal on Scientific Computing, 41, A3476-A3497.

How to cite: Bauer, W. and Cotter, C. J.: Accurate solutions of highly oscillatory systems under large time steps using higher-order phase averages, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6718, https://doi.org/10.5194/egusphere-egu24-6718, 2024.

X5.88
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EGU24-5894
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ECS
Exploring mathematical formulations for a next-generation compatible finite element dynamical core 
Daniel Witt, Jemma Shipton, and Thomas Bendall

Compatible finite element methods are attractive for modelling geophysical fluids because they can replicate many of the desirable properties of the Arakawa C-grid, such as good wave dispersion. Compatible finite elements also facilitate alternative grid structures which avoid the clustering of grid points at the poles without the associated downsides these grids have with a finite difference scheme. For this reason compatible finite element methods are used in the Met Office's next-generation dynamical core, GungHo. The mathematical formulation used in GungHo is designed to be similar to that used in the Met Office's previous dynamical core, ENDGame. For instance, GungHo uses an advective form of the momentum equation and the lowest-order finite element spaces  

 

We present an investigation into formulation options, carried out in Gusto, a geophysical fluid toolkit built upon Firedrake, an automated code generation framework for solving PDEs via finite element methods. Gusto shares the same fundamental compatible finite element formulation as GungHo but provides greater flexibility to investigate other choices

 

Specifically, we investigate the effects of increasing the finite element order on the model. Due to the flexibility of Gusto, we can consider a generally higher order model as well as separately altering the horizontal and vertical orders. Additionally we investigate the effects brought about by writing the advective term in the momentum equation in its vector invariant form. We evaluate the impacts of these choices by conducting several test cases considering the short-term fluid dynamics and long-term statistical climate properties. 

 

Understanding how these options impact the dynamical core will inform future research directions and improvements for GungHo.

How to cite: Witt, D., Shipton, J., and Bendall, T.: Exploring mathematical formulations for a next-generation compatible finite element dynamical core, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5894, https://doi.org/10.5194/egusphere-egu24-5894, 2024.

X5.89
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EGU24-2529
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ECS
Consistent inter-model spread of extratropical westerly jet meridional positions in CMIP6 models between the northern and southern hemispheres in boreal winter 
Li Tang, Riyu Lu, and Zhongda Lin

This study investigates the inter-model spread of extratropical westerly jets between 52 Coupled Model Intercomparison Project phase 6 (CMIP6) models in boreal winter. The results show that there is a substantial spread in latitude of upper-tropospheric westerly jet between models, characterized by large inter-model standard deviations to the poleward and equatorward of jet axis, although the multi-model ensemble mean (MME) of the models performs well in simulating meridional position of westerly jets. Furthermore, we detect the consistency of inter-model jet position spread between the northern and southern hemispheres, based on the inter-model empirical orthogonal function (EOF) decomposition and correlation of regional-averaged zonal winds. Specifically, the models that simulate the westerly jets poleward/equatorward than MME position in one hemisphere tend to also simulate the jets poleward/equatorward in the other hemisphere. Accordingly, we define a global jet spread index to depict the concurrence of jet shift in the two hemispheres. The results of regression analyses based on this index indicate that the models positioning the jets poleward than MME tend to simulate a wider Hadley Cell, a poleward-shifted Ferrel Cell in the southern hemisphere, and a wider intertropical convergence zone (ITCZ). Finally, the inter-model spread of ITCZ width is mainly determined by the spread of convective precipitations between the models, implying that different convection parameterization schemes may play a crucial role in inducing the inter-model spread of extratropical westerly jets and the concurrence of meridional jet shift in the two hemispheres.

How to cite: Tang, L., Lu, R., and Lin, Z.: Consistent inter-model spread of extratropical westerly jet meridional positions in CMIP6 models between the northern and southern hemispheres in boreal winter, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2529, https://doi.org/10.5194/egusphere-egu24-2529, 2024.

X5.90
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EGU24-2085
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ECS
Implementation and Evaluation of the Land Surface Model JSBACH in the ECHAM/MESSy Atmospheric Chemistry Model 
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer

We present the integration and evaluation of the land surface model JSBACH (Jena Scheme for Biosphere-Atmosphere Coupling in Hamburg) in EMAC (ECHAM/MESSy Atmospheric Chemistry General Circulation Model). 
JSBACH replaces the former simplistic SURFACE submodel, introducing a five-layer diffusive hydrological transport model for soil water and a five-layer snow scheme accounting for phase changes of water. It encompasses various land cover types, forest age structures, phenology, and introduces a range of new vegetation and soil-related features, including processes like photosynthesis, plant carbon uptake, and feedback mechanisms linked to surface energy and moisture fluxes. Additionally, JSBACH provides a three-layer canopy scheme, incorporating photosynthesis and solar radiation absorption within the canopy layers. The newly coupled model is evaluated based on ERA5 reanalysis datasets, observations of the Global Precipitation Climatology Project (GPCP), and MODIS satellite data. We Evaluate land surface temperature, terrestrial water storage, surface albedo, precipitation, top-of-atmosphere radiation flux, fraction of absorbed photosynthetic active radiation, leaf area index and gross primary productivity, representing a selection of the most important drivers within the Earth System. We show that, despite the many newly included processes and features, the coupled model performance is not significantly degraded and the run time increase using the new submodel is negligible. The coupling of JSBACH extends the capabilities and versatility of EMAC, taking it a step closer to a comprehensive Earth system model. Additionally, we discuss future work, including the investigation of land-atmosphere interactions, with a particular focus on the feedback of water stress on biogenic organic compound emissions and related changes in atmospheric composition. 

How to cite: Martin, A., Gayler, V., Steil, B., Klingmüller, K., Jöckel, P., Tost, H., Lelieveld, J., and Pozzer, A.: Implementation and Evaluation of the Land Surface Model JSBACH in the ECHAM/MESSy Atmospheric Chemistry Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2085, https://doi.org/10.5194/egusphere-egu24-2085, 2024.

X5.91
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EGU24-3509
|
ECS
Exploring Thermo-Electrohydrodynamic Flows with DifferentialRotation in AtmoFlow 
Yann Gaillard, Peter Szabo, and Christoph Egbers

The AtmoFlow experiment is a small-scale,  laboratory experiment  designed to explore idealized large-scale atmospheric flow fields and planned to become operational onboard the International Space Station by 2026. The experiment is composed of two independently rotating spherical shells, mimicking planetary rotation. The temperature on the shell's boundaries is heated at the equator and cooled at the poles to count for the equatorial and polar temperature difference in the presence of solar radiation. An electrical field is applied to a dielectric fluid confined between the shells that serves as an artificial gravity force, known as dielectrophoretic force, inducing the formation of buoyant flow patterns.

Beyond modelling terrestrial or explanatory atmospheres via solid body rotation, the experiment is also able to mimic atmospheric regimes of large celestial bodies by deferential rotation of each shell. The resulting combination of rotational momentum flux and buoyancy force gives rise to distinctive patterns that are dependent on the magnitude of the forcing parameter, enabling to study different regimes. Prior studies have shown that the electric gravity gives rise to a buoyant force leading to plume-like patterns [1,2] in the radial direction, while the Taylor vortices induced by differential rotation maintains an azimuth flow component. The main objective of this study is to investigate the interaction between these two different transport mechanism.

Complementing numerical investigations are therefore performed to model the experiment using the OpenFOAM ecosystem, an open source finite volume solver.  The emerging convective regimes close to the outer shell regions are evaluated. The observed patterns are the classified into these distinct regimes  and presented in a regime diagram showing the transition from different convective states. 
Beside the pattern analysis, the heat flux through the model is investigated in relation to the forcing strength. This provided  an estimation of the overall heat transported from the inner to the outer shell.  The changes in the thermal transport were also reflected in the kinetic energy, which was monitored for each case and brought in relation to the evaluated heat transfer.

[1] Futterer, B., R. Hollerbach, and C. Egbers, ‘GeoFlow: 3D Numerical Simulation of Supercritical Thermal Convective States’, Journal of Physics: Conference Series, 137/1 (2008), 012026
[2] Futterer, B., A. Krebs, A.-C. Plesa, F. Zaussinger, R. Hollerbach, D. Breuer, and others, ‘Sheet-like and Plume-like Thermal Flow in a Spherical Convection Experiment Performed under Microgravity’, Journal of Fluid Mechanics, 735 (2013), 647–83

How to cite: Gaillard, Y., Szabo, P., and Egbers, C.: Exploring Thermo-Electrohydrodynamic Flows with DifferentialRotation in AtmoFlow, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3509, https://doi.org/10.5194/egusphere-egu24-3509, 2024.

X5.92
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EGU24-7742
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ECS
The identification of wetlands in Noah-MP and their regional environmental effects
(withdrawn)
Quanyu Zhang and Yanhong Gao
X5.93
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EGU24-12060
|
ECS
|
Idealized test cases in GFDL's FV3 demonstrating the new Duo-Grid. 
Joseph Mouallem, Lucas Harris, and Xi Chen

The Duo-Grid is a novel algorithm that addresses grid imprinting in generic gnomonic cubed-sphere grids. The algorithm aims to overcome grid discontinuities at the edges and corners by remapping data in a cube’s face halo region from its kinked coordinates to its natural location along extended great circle lines. We recently implemented the Duo-Grid in the Geophysical Fluid Dynamics Laboratory's (GFDL) Finite-Volume Cubed-Sphere Dynamical Core (FV3). We apply the Duo-Grid in idealized tests of 2D shallow water solver and the 3D hydrostatic and non-hydrostatic solvers. Our findings reveal that error norms are greatly reduced and grid imprinting is practically eliminated when employing the Duo-Grid. Most notably we find that a Rossby-Haurwitz wave is maintained significantly longer in the Rossby-Haurwitz tests, from about 80 to beyond 100 days. These results strongly suggest an improvement in FV3's accuracy and robustness.

How to cite: Mouallem, J., Harris, L., and Chen, X.: Idealized test cases in GFDL's FV3 demonstrating the new Duo-Grid., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12060, https://doi.org/10.5194/egusphere-egu24-12060, 2024.

X5.94
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EGU24-10860
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ECS
Performance portability across CPUs, GPUs and FPGAs for an unstructured grid shallow water model 
Markus Büttner, Christoph Alt, Tobias Kenter, and Vadym Aizinger

By re-implementing our unstructured grid discontinuous Galerkin solver for the 2D shallow water equations in SYCL we produce a single code which not only runs on various CPUs and GPUs from AMD, Intel, and NVIDIA as well as on Intel Field Programmable Gate Arrays (FPGAs), but also achieves excellent performance on each of those architectures. The separation of concerns concept is realized in SYCL by using a modern C++ standard for model code implementation and handling all hardware-specifics automatically in the SYCL runtime. This makes this programming model very flexible in terms of data structures and algorithmic constructs and reduces the developer exposure to various hardware architectures with their differing performance optimization requirements. Furthermore, we demonstrate that the FPGAs, which consist of generic logic blocks configured for a specific code and data structures, outperform all other architectures for small-size problems if one uses the SYCL implementation provided by Intel oneAPI.

How to cite: Büttner, M., Alt, C., Kenter, T., and Aizinger, V.: Performance portability across CPUs, GPUs and FPGAs for an unstructured grid shallow water model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10860, https://doi.org/10.5194/egusphere-egu24-10860, 2024.

X5.95
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EGU24-16005
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ECS
Block-structured grids for finite element models of coastal ocean 
Jonathan Schmalfuß, Sara Faghih-Naini, Daniel Zint, and Vadym Aizinger

For numerical models of the ocean, the choice of the underlying grid is a crucial technical decision affecting the accuracy, stability, computational performance, and, ultimately, modeling skill. This is a particularly important issue for high-resolution simulations of coastal and regional oceans, where a precise representation of irregular land boundaries and geometric features such as islands, channels, rivers, etc. is a key requirement. For these types of applications, unstructured triangular meshes are often the preferred type of horizontal mesh due to their adaptability and ease of construction. However, optimizing the computational performance of unstructured mesh codes on many modern hardware architectures is quite challenging compared to doing the same for stencil-based numerical schemes used in structured grid models. As a viable alternative to unstructured meshes, we propose block structured grids (BSGs) consisting of a topologically unstructured mesh of blocks, each of which is partitioned using a structured grid. Our methodology allows to automatically generate BSGs for realistic ocean domains with a prescribed number of blocks of given resolution already load-balanced for execution on a parallel computer of given configuration. To allow generating BSGs for ocean domain geometries and topographies of varying complexity our approach supports three different types of BSGs:

1. standard BSGs -- very computationally efficient but only practical for rather simple geometries

2. masked BSGs -- an extension of the standard BSGs that permits masking of elements to allow meshing of small geometric features using large blocks

3. hybrid BSGs -- an entirely new method combining structured with unstructured blocks to offer the optimal compromise between geometric accuracy and computational efficiency

We present grid generation techniques, validation of simulation results, and computational performance evaluations for the proposed methods.

How to cite: Schmalfuß, J., Faghih-Naini, S., Zint, D., and Aizinger, V.: Block-structured grids for finite element models of coastal ocean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16005, https://doi.org/10.5194/egusphere-egu24-16005, 2024.

X5.96
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EGU24-5172
The sensitivity of ocean heat uptake to numerical mixing in forced and coupled ocean models 
Alex Megann

The oceans are believed to be responsible for taking up over 90% of the heat retained by anthropogenic greenhouse gases in the atmosphere. For this reason it is important for the ocean component in climate models to have an acceptably realistic representation of the processes that transport heat from the surface into the ocean interior. It is known that ocean models tend to have significant levels of spurious numerical diapycnal mixing, arising chiefly from truncation errors in the tracer advection scheme. It is therefore important to quantify the sensitivity of the simulated climate to numerical mixing, and then to evaluate remedies for the numerical mixing.     

A large ensemble of forced and coupled simulations with a 1/4° NEMO ocean is shown to have a global mean surface heat flux ranging from -1.5 to +1.5 W/m2. We demonstrate a strong negative correlation between global ocean surface heat flux and the global mean effective diapycnal diffusivity, a metric of total ocean mixing that includes both explicit and numerical contributions. Several potential mechanisms for this apparently paradoxical result are discussed, including changes in upwelling in the Southern Ocean, mixing of bottom waters in the Pacific and Atlantic, and the Atlantic meridional overturning circulation. Approaches to reducing numerical mixing will be described. 

How to cite: Megann, A.: The sensitivity of ocean heat uptake to numerical mixing in forced and coupled ocean models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5172, https://doi.org/10.5194/egusphere-egu24-5172, 2024.

X5.97
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EGU24-6500
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Biases in stratosphere-troposphere coupling processes in S2S forecast systems 
Amy Butler, Chaim Garfinkel, and Zachary Lawrence

Two-way coupling between the stratosphere and troposphere is recognized as an important source of subseasonal-to-seasonal (S2S) predictability. Extratropical coupling between the stratosphere and the surface may modulate the tropospheric circulation in predictable ways and/or provide forecast windows of opportunity. S2S forecast models may struggle to represent such coupling processes; at longer lead times, drifts in a model’s circulation related to model configurations, biases, and parameterizations have the potential to feedback and affect stratosphere-troposphere coupling. This presentation will highlight results from an international SPARC-SNAP (Stratospheric Network for the Assessment of Predictability) community effort to diagnose and characterize biases in stratosphere-troposphere coupling in S2S models. We find that in the Northern Hemisphere, the S2S forecast systems struggle to reproduce the strength of observed upward coupling from the troposphere to the stratosphere, while downward coupling is mostly well represented. In the Southern Hemisphere, forecast systems generally overestimate downward coupling strength, despite underestimating radiative persistence in the lower stratosphere.

How to cite: Butler, A., Garfinkel, C., and Lawrence, Z.: Biases in stratosphere-troposphere coupling processes in S2S forecast systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6500, https://doi.org/10.5194/egusphere-egu24-6500, 2024.

X5.98
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EGU24-10839
The Common Community Physics Package: Recent Updates and New Frontiers 
Ligia Bernardet, Dustin Swales, Grant Firl, Mike Kavulich, Samuel Trahan, Soren Rasmussen, Daniel Abdi, Vanderlei Vargas, Jimy Dudhia, Man Zhang, Tracy Hertneky, Weiwei Li, Lulin Xue, and Isidora Jankov

The Common Community Physics Package (CCPP) is a collection of atmospheric physical parameterizations and a framework that couples the physics for use in Earth system models. The CCPP Framework was developed by the U.S. Developmental Testbed Center (DTC) and is now an integral part of the Unified Forecast System (UFS). The UFS is a community-based, coupled, comprehensive Earth modeling system designed to support research and be the source system for NOAA‘s multi-scale operational numerical weather prediction applications.  The CCPP is now operational at NOAA as part of the UFS Hurricane Analysis and Forecast System, and it is planned for upcoming implementations of the Global Forecast System and other models. The CCPP Framework is also being used in developmental mode to connect aerosol parameterizations to the UFS. Additionally, the CCPP is employed in the experimental U.S. Navy Environmental Prediction sysTem Utilizing the Non-hydrostatic corE (NEPTUNE) and is currently being integrated into National Center for Atmospheric Research (NCAR) models such as the Community Earth System Model (CESM) and the Model for Prediction Across Scales (MPAS). 

A primary goal for this effort is to facilitate research and development of physical parameterizations, while simultaneously offering capabilities for use in operational models. The CCPP Framework supports configurations ranging from process studies to operational numerical weather prediction as it enables host models to assemble the parameterizations in flexible suites. Framework capabilities include flexibility with respect to the order in which schemes are called, ability to group parameterizations for calls in different parts of the host model, and ability to call some parameterizations more often than others. Furthermore, the CCPP is distributed with a single-column model (SCM) that can be used to test innovations,  conduct hierarchical studies in which physics and dynamics are decoupled, and isolate processes to more easily identify issues associated with systematic model biases. The CCPP SCM is also being updated to be forced by the UFS output.

The CCPP v6.0.0 public release includes 23 primary parameterizations (and six supported suites), representing a wide range of meteorological and land-surface processes. Experimental versions of the CCPP also contain chemical schemes, making it possible to represent processes in which chemistry and meteorology are tightly coupled. It is anticipated that soon the CCPP will have schemes that utilize machine learning.

The CCPP is developed as open-source code and has received contributions from the wide community in the form of new schemes and innovations within existing schemes. In this presentation, we will provide an update on recent CCPP development, including transition to single-precision and initial work toward its deployment in Graphical Processing Units (GPUs), and discuss the outcomes of the CCPP Visioning Workshop held in August 2023. The latter was a multi-institutional event intended to inform the community about the CCPP and to gather input on a range of subjects. Topics covered include code management, releases, documentation, support, and best practices for interoperability to foster collaborative development. 

How to cite: Bernardet, L., Swales, D., Firl, G., Kavulich, M., Trahan, S., Rasmussen, S., Abdi, D., Vargas, V., Dudhia, J., Zhang, M., Hertneky, T., Li, W., Xue, L., and Jankov, I.: The Common Community Physics Package: Recent Updates and New Frontiers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10839, https://doi.org/10.5194/egusphere-egu24-10839, 2024.

X5.99
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EGU24-10945
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ECS
Numerical implementation of ESMs: an additional source of uncertainty in climate prediction?
(withdrawn after no-show)
Francisco de Melo Viríssimo and David Stainforth
X5.100
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EGU24-10960
Improving Earth System Models via Hierarchical System Development 
Michael Ek and the DTC HSD team

Hierarchical System Development (HSD) is an efficient way to effectively integrate the model development process, with the ability to test small elements (e.g., physics schemes) in an Earth System Model (ESM) first in isolation, then progressively connecting elements with increased coupling between ESM components. System in HSD is end-to-end: it includes data ingest/quality control, data assimilation, modeling, post-processing, and verification. HSD includes individual physics simulators, Single Column Models (SCMs; including “on/off switches” for individual physics elements), small-domain and regional models, all the way to complex fully-coupled global ESMs with atmosphere/chemistry/aerosol, ocean/wave/sea-ice, land-hydrology/snow/land-ice, and biogeochemical cycle/ecosystem components. Datasets used for the different HSD steps are obtained from observational networks and field programs, ESM output, or idealized conditions (e.g., used to “stress-test” ESM elements and components). Advancing from one HSD step to the next requires appropriate verification metrics of ESM performance, many at the process level. This process is concurrent and iterative such that more complex HSD steps can provide information to be used at simpler HSD steps and vice versa.  The HSD approach can also help understand spatial and temporal dependencies in model solutions, where consistency for different models and resolutions across HSD steps is required. The Common Community Physics Package (CCPP) is designed to lower the bar for community involvement in physics testing and development through increased interoperability, improved documentation, and continuous support to developers and users. Together, CCPP and its companion SCM, developed and supported by the Developmental Testbed Center (DTC), provide an enabling software infrastructure to connect HSD steps. The HSD approach and use of CCPP will be illustrated and discussed through testing and evaluation examples. This work also supports the NOAA Earth Prediction Innovation Center (EPIC) program.

How to cite: Ek, M. and the DTC HSD team: Improving Earth System Models via Hierarchical System Development, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10960, https://doi.org/10.5194/egusphere-egu24-10960, 2024.

X5.101
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EGU24-11421
Thompson Microphysics Updates in the Unified Forecast System 
Ruiyu Sun, Fanglin Yang, Songyou Hong, Jianwen Bao, Jongil Han, Eric Aligo, Anning Cheng, Greg Thompson, Jili Dong, and Qingfu Liu

The Thompson microphysics scheme was evaluated in the Unified Forecast System (UFS) for medium-range weather application in both atmosphere-only and fully coupled atmosphere-ocean-ice-wave system configurations. Initial tests based on the Global Forecast System (GFS) version 16 configuration showed that the Thompson microphysics scheme became unstable with a typical GFS time step. An inner-loop time-splitting approach and a new semi-Lagrangian sedimentation algorithm for rain and graupel were implemented in the scheme to alleviate this numerical instability problem. To reduce biases of radiative fluxes  at the surface and at the top of the atmosphere, the conversions from cloud ice to snow and from snow to graupel in the scheme were modified along with the falling velocity of cloud ice. A few other parameters related to the cloud ice formation process were also adjusted to help improve the accuracy of radiative fluxes. Convective cloud condensate was included in the calculations of the total cloud cover and radiative transfer. Both atmosphere-only and air-sea coupled experiments were conducted to examine the impacts of these changes on global and regional forecast skills at different temporal and spatial scales. 

 

How to cite: Sun, R., Yang, F., Hong, S., Bao, J., Han, J., Aligo, E., Cheng, A., Thompson, G., Dong, J., and Liu, Q.: Thompson Microphysics Updates in the Unified Forecast System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11421, https://doi.org/10.5194/egusphere-egu24-11421, 2024.

X5.102
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EGU24-17639
Development of systematic errors in the East Asian summer monsoon 
Jose M. Rodriguez

Mean-state errors in the simulation of the Asian summer monsoon are common to many CMIP6 climate models, with some biases persisting over several generations of models.  In this work, we use the Met Office Unified Model (MetUM) as an example to understand the physical processes involved in the emerged circulation patterns.  We focus on the west Pacific subtropical high (WPSH), an important feature of the East Asian summer monsoon, that modulates the distribution of summer rainfall in the region and influences the tropical cyclone activity in the Western North Pacific.    MetUM exhibits robust systematic biases in its representation of the WPSH, including a weakening of the anticyclone and a location too far east, which leads to an underestimation of the southwesterly monsoon flow over East Asia and contributes to seasonal precipitation errors in the area.

We present results from a combination of various techniques and sensitivity experiments, used to understand the sources of the circulation errors.    We benefit from MetUM’s seamless approach of employing the same dynamical core and physical parameterisations in configurations used for various forecast systems, from NWP to climate projections.  Previous studies have shown that many systematic errors in the climate model develop within the first few days of simulation and persist to climate timescales.   Using an ensemble of NWP hindcasts, we examine the error development after initialisation. This allows to reduce the impact of circulation-physics feedbacks and separate the roles played by local physical processes and remote teleconnections.  We apply the nudging methodology, where velocities and temperatures are relaxed towards analysis in chosen regions, to examine the remote effect that biases developing in one region produce in other regions.  The information from these experiments highlights a key role for physical deficiencies over the Maritime Continent in the development of the WPSH biases in MetUM.  The use of an idealised model (semi-geotriptic balance), which allows to study the effect of individual physics tendencies, shows that diabatic heating errors associated with convection are the main source of MetUM WPSH circulation bias.  Further analysis with moisture tendencies reveals that in the model’s parameterised convection, a large drying of the lower boundary layer occurs, balanced only by surface fluxes.  In places with low exchange coefficient (low surface wind), surface fluxes are not able to sustain convection over a long period and the bias is established. 

We examine the persistence of the circulation bias in various models, by evaluating   a perturbed parameter ensemble (PPE) of MetUM climate simulations, which samples climate uncertainties arising from differences in parameter values in physics schemes.   We compare the circulation biases in the ensemble members with model simulations with a new convection parameterisation scheme, CoMorph, and with a convection-permitting simulation. We also show preliminary results of circulation bias development in a machine-learning model for weather forecast.

How to cite: Rodriguez, J. M.: Development of systematic errors in the East Asian summer monsoon, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17639, https://doi.org/10.5194/egusphere-egu24-17639, 2024.

X5.103
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EGU24-9316
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ECS
Precipitation bias correction: A novel method combining wavelet analysis and quantile mapping (WA-QM) 
Xia Wu, Zhu Liu, and Qingyun Duan

While CMIP6 has made notable improvements compared to CMIP5, there are still biases present in its simulations of different climate features due to limitations in model physics and uncertainties in input data. To address these biases, effective bias correction methods need to be employed. One commonly used method is quantile mapping, which aligns the probability density function (PDF) of climate simulations with observed data. However, this method has a limitation as it fails to maintain the temporal correspondence between model predictions and observations.

To overcome this limitation, a new approach called Wavelet Analysis-Quantile Mapping (WA-QM) has been proposed. This method involves decomposing GCM simulations into different frequency bands using discrete wavelet transformation. The scaling factors of these bands are adjusted based on their correlations with observed data. Additionally, a quantile mapping procedure is applied to modify the overall PDF of the simulations.

The WA-QM method was tested in monthly precipitation simulation data from five CMIP6 models covering the period 1951-2010 in the Pan Third Pole (PTP) region, which includes the Tibetan Plateau, Central Asia, and Southeast Asia. Results showed that WA-QM combines the advantages of wavelet analysis and quantile mapping. It effectively improves the representation of seasonal and monthly climatology varying through wavelet analysis, while also correcting mean and variance biases using quantile mapping. Consequently, the PDF closely resembles the observed data. The effectiveness of the WA-QM approach extends to correcting precipitation biases across different spatial areas and CMIP6 models.

How to cite: Wu, X., Liu, Z., and Duan, Q.: Precipitation bias correction: A novel method combining wavelet analysis and quantile mapping (WA-QM), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9316, https://doi.org/10.5194/egusphere-egu24-9316, 2024.