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Data assimilation systems and numerical weather and climate models are essential to understand the current and past state of the Earth System, and to predict it's future. This session will summarize the latest progress in the development of such models including the assimilation of space-borne and conventional observations, developments for the numerical formulation of the models regarding both the fluid dynamic solver and physical parametrisation schemes, and developments towards weather and climate simulations at higher resolution on modern supercomputers.

Public information:
We will divide the session chats into smaller groups of 4 abstracts based on the order of abstracts in the session programme. Each group will have ~15 minutes. Each mini-session will be organized as follows:

- All authors post a few sentences to present their work.
- Everyone attending the mini-session can post questions or comments to the authors.
- All post related to one particular abstract should begin with the name of the first author. E.g. @David: What is the y-axis of Figure 2?

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Co-organized by CL2/OS4
Convener: Peter Düben | Co-conveners: Werner Bauer, Daniel Klocke, Isaac Moradi, Jemma Shipton
Displays
| Thu, 07 May, 08:30–12:30 (CEST)

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Download all presentations (239MB)

Chat time: Thursday, 7 May 2020, 08:30–10:15

Chairperson: Daniel Klocke
D3028 |
EGU2020-17854
| solicited
David Leutwyler and Christoph Schär

Secondary disturbances spawning frontal waves along the fronts of mature midlatitude low-pressure systems were identified decades ago from satellite images. While their development has been studied using analytical models, field campaigns (e.g. FASTEX) and re-analysis datasets, simulation of the phenomenon in state-of-the-art global weather and climate models so far remained unattainable.

Today's flagship supercomputers allow performing simulations at kilometer-scale resolution on computational domains covering the entire lifecycle of synoptic-scale systems and thus enable explicit representation of small-scale disturbances embedded in large-scale circulations. We demonstrate these capabilities in two different types of kilometer-scale simulations. The first is a 10-day-long near-global simulation of an idealized moist baroclinic wave, performed at 1 km grid spacing and employing 16,001 × 36,006 × 60 grid points. The second is a real-case simulation of an extratropical low-pressure system, driven by the European Centre for Medium-Range Weather Forecasts's operational analysis. At kilometer-scale resolution, both simulations display clear evidence of embedded mesoscale vortices spawning along frontal systems of mature extratropical cyclones. The vortices appearing in the real-case simulation can also be identified in satellite imagery of the system.

The simulated developments are due to a barotropic instability mechanism and driven by strong low-level horizontal wind shear. While the simulation of the frontal systems is amenable at model resolutions around 10–50 km, the instability mechanism itself relies on the representation of a narrow shear zone, requiring about 5 times finer resolution. Results suggest that the flow regimes suppressing or fostering barotropic vortices can coexist in the same synoptic system. Far away from the cyclone core, the instability is suppressed by deformation associated with the large-scale flow, while close to the mature cyclone core, the narrow frontal structure becomes unstable.

Leutwyler, D. and C. Schär (2019): Barotropic instability of a cyclone core at kilometer-scale resolution, J. Adv. Model. Earth Sy., 11.

D3029 |
EGU2020-21769
Gerard van der Schrier, Antonello Squintu, Else van den Besselaar, Eveline van der Linden, Enrico Scoccimarro, Christopher Roberts, Retish Senan, Dian Putrasahan, Malcolm Roberts, and Albert Klein Tank

The comparison of simulated climate with observed daily values allows to assess their reliability and the soundness of their projections on the climate of the future. Frequency and amplitude of extreme events are fundamental aspects that climate simulations need to reproduce. In this work six models developed within the High Resolution Model Intercomparison Project are compared over Europe with the homogenized version of the observational E-OBS gridded dataset. This is done by comparing averages, extremes and trends of the simulated summer maximum temperature and winter minimum temperatures with the observed ones.

Extreme values have been analyzed making use of indices based on the exceedances of percentile-based thresholds. Winter minimum temperatures are generally underestimated by models in their averages (down to -4 deg. C of difference over Italy and Norway) while simulated trends in averages and extreme values are found to be too warm on western Europe and too cold on eastern Europe (e.g. up to a difference of -4% per decade on the number of Cold Nights over Spain). On the other hand the models tend to underestimate summer maximum temperatures averages in Northern Europe and overestimate them in the Mediterranean areas (up to +5 deg. C over the Balkans). The simulated trends are too warm on the North West part and too cold on the South East part of Europe (down to -3%/dec. on the number of Warm Days over Italy and Western Balkans).

These results corroborate the findings of previous studies about the underestimation of the warming trends of summer temperatures in Southern Europe, where these are more intense and have more impacts.  A comparison of the high resolution models  with the corresponding version in CMIP5 has been performed comparing the absolute biases of extreme values trends. This has shown a slight improvement for the simulation of winter minimum temperatures, while no signs of significant progresses have been found for summer maximum temperatures.

D3030 |
EGU2020-1545
Higher Vertical Resolution for Select Physical Processes in the Energy Exascale Earth System Model (E3SM)
(withdrawn)
Hsiang-He Lee, Peter Bogenschutz, and Takanobu Yamaguchi
D3031 |
EGU2020-10306
| Highlight
Xavier Lapillonne, William Sawyer, Philippe Marti, Valentin Clement, Remo Dietlicher, Luis Kornblueh, Sebastian Rast, Reiner Schnur, Monika Esch, Marco Giorgetta, Dmitry Alexeev, and Robert Pincus

The ICON modelling framework is a unified numerical weather and climate model used for applications ranging from operational numerical weather prediction to low and high resolution climate projection. In view of further pushing the frontier of possible applications and to make use of the latest evolution in hardware technologies, parts of the model were recently adapted to run on heterogeneous GPU system. This initial GPU port focus on components required for high-resolution climate application, and allow considering multi-years simulations at 2.8 km on the Piz Daint heterogeneous supercomputer. These simulations are planned as part of the QUIBICC project “The Quasi-Biennial Oscillation (QBO) in a changing climate”, which propose to investigate effects of climate change on the dynamics of the QBO.

Because of the low compute intensity of atmospheric model the cost of data transfer between CPU and GPU at every step of the time integration would be prohibitive if only some components would be ported to the accelerator. We therefore present a full port strategy where all components required for the simulations are running on the GPU. For the dynamics, most of the physical parameterizations and infrastructure code the OpenACC compiler directives are used. For the soil parameterization, a Fortran based domain specific language (DSL) the CLAW-DSL has been considered. We discuss the challenges associated to port a large community code, about 1 million lines of code, as well as to run simulations on large-scale system at 2.8 km horizontal resolution in terms of run time and I/O constraints. We show performance comparison of the full model on CPU and GPU, achieving a speed up factor of approximately 5x, as well as scaling results on up to 2000 GPU nodes. Finally we discuss challenges and planned development regarding performance portability and high level DSL which will be used with the ICON model in the near future.

D3032 |
EGU2020-11447
Helene Hewitt, Laura Jackson, Malcolm Roberts, Dorotea Iovino, Torben Koenigk, Virna Meccia, Christopher Roberts, Yohan Ruprich-Robert, and Richard Wood

We examine the weakening of the Atlantic Meridional Overturning Circulation (AMOC) in response to increasing CO2 at different horizontal resolutions in HadGEM3-GC3.1 and in a small ensemble of models with differing resolutions. There is a strong influence of the ocean mean state on the AMOC weakening: models with a more saline western subpolar gyre have a greater formation of deep water there. This makes the AMOC more susceptible to weakening from an increase in CO2 since weakening ocean heat transports weaken the contrast between ocean and atmospheric temperatures and hence weaken the buoyancy loss. In models with a greater proportion of deep water formation further north (in the Greenland-Iceland-Norwegian basin), deep-water formation can be maintained by shifting further north to where there is a greater ocean-atmosphere temperature contrast.

We show that ocean horizontal resolution can have an impact on the mean state, and hence AMOC weakening. In the models examined, those with higher resolutions tend to have a more westerly path of the North Atlantic Current and hence greater impact of the warm, saline subtropical Atlantic waters on the western subpolar gyre. This results in greater dense water formation in the western subpolar gyre. Although there is some improvement of the higher resolution models over the lower resolution models in terms of the mean state, both still have biases and it is not clear which biases are the most important for influencing the AMOC strength and response to increasing CO2.

 

D3033 |
EGU2020-21165
Anubhav Choudhary and Aiko Voigt

Previous work showed that simulations of extratropical cyclones and their intensity are significantly impacted by model resolution. This might be explained by the impact of resolution on cloud diabatic processes occurring within the warm conveyor belt (WCB), as these are linked to the strength of cyclones. To investigate this link, we move gradually from very coarse (80km) to very fine resolution (2.5km) simulations and study if there is a systematic impact of resolution on the simulated WCB processes. For this purpose, we analyse ICON simulations in a regional North Atlatnic setup for a specific case from the NAWDEX campaign -  cyclone Vladiana - that occurred on 23rd September, 2016. Furthermore, we compare simulations with 1- and 2- moment cloud microphysics and with explicit and parametrized convection. From these simulations WCB trajectories are calculated over 48 hours by means of the Lagranto tool and 1-hourly model output to sample cloud diabatic processes within the WCB. We find a systematic increase in the number of WCB trajectories with finer resolution, which also ascent higher. Moreover, the fine-resolution simulations show a new class of anticyclonic trajectories that is absent in the low-resolution simulations. This effect becomes more pronounced when convection is represented explicitly, but is not strongly affected by the treatment of cloud microphysics. We diagnose the impact of increasing resolution on WCB in terms of changes in processes like updraft velocity, diabatic heating and modification of potential vorticity by total diabatic heating and individual diabatic processes.

D3034 |
EGU2020-1725
Axel Timmermann, Sun-Seon Lee, and Jung-Eun Chu
To further improve our understanding of scale-interactions and key mechanisms leading to climate variability and extreme weather events, we conducted a series climate simulations using the ultrahigh-resolution Community Earth System Model (HR-CESM). The HR-CESM configuration uses a horizontal resolution of approximately 25 km for the atmospheric component and 10 km for the ocean. The simulations were carried out under present-day radiative forcing and for a variety of future greenhouse gas scenarios. This presentation highlights some key features of these simulations: the overall performance and important model biases, the representation of the Atlantic Meridional Overturning Circulation, tropical cyclone statistics, properties of sea-ice, the El Niño-Southern Oscillation, as well as their responses to future climate change. We will also present plans on how the data will be shared with the larger scientific community for further analysis and collaborative projects. 
D3035 |
EGU2020-2231
| solicited
Marat Khairoutdinov and Christopher Bretherton

The global version of the cloud-resolving System for Atmospheric Modeling (SAM) is used to simulate the global evolution of clouds and precipitation during the SOCRATES field campaign In Feb 2018 with particular focus on the Southern Ocean storm track region. The model has nonuniform horizontal resolution, which ranges from 4-km horizontal grid spacing over the Tropics up to 2-3 km isotropic grid-spacing over mid-latitudes. It includes a realistic topography and comprehensive land-surface model. The sea-surface temperature and sea ice are prescribed from observations. The results of two types of simulations are presented, weather-forecasting and observed-weather-nudged over 24-hour time scale; for the latter, hourly ERA5 reanalysis dataset is used. The cloud properties are compared to the SOCRATES observations. The sensitivity of the results to the choice of cloud microphysics, from simple single-moment to double-moment, is also discussed.

D3036 |
EGU2020-20969
Daniel Shipley, Hilary Weller, Peter Clark, and William McIntyre

Atmospheric convection remains one of the weakest parts of weather and climate models, especially in the tropics. As model resolutions increase, the assumptions underlying traditional convection parametrisations break down; however, we are still far from fully resolving all convective processes, showing a need for convection parametrisation well into the future.

A multi-fluid framework for parametrising convection has been proposed, based on conditionally filtering the Navier-Stokes equations. This results in a set of equations for multiple fluids, where each fluid has its own dynamic and thermodynamic fields. The approach is fully 3D and time-dependent, allowing for both convective memory and net mass transport due to convection. However, the approach differs from higher-order turbulence closures in that it attempts to capture the important coherent structures of convection via the partitioning into multiple fluids. In addition to the usual sub-filter fluxes, the equations contain terms involving the exchange of momentum, entropy, moisture, and tracers between different fluids. The problem of parametrising convection then becomes the problem of parametrising these exchange terms. This means that within this framework the convection is fundamentally a part of the dynamics: there is no separate “convection scheme" which is called by the dynamical core.

As a first step towards using this framework to parametrise atmospheric convection, we consider a highly simplified model: dry, 2D Rayleigh-Bénard convection in the Boussinesq limit. This model captures the essentials of buoyant convection, with additional symmetry constraints which help with building a parametrisation. In the single-column limit of the single-fluid case, no circulation can exist. This leads to a very poor solution, in particular vastly underestimating the heat transport.

In a two-fluid model, the separate dynamical fields for each fluid mean that a circulation can exist even at the coarsest resolutions. We show that a simple two-fluid single-column model can capture all the essentials of the horizontally-averaged time-mean high resolution solution, including the buoyancy, vertical velocity, and pressure profiles, as well as much better representation of the heat flux. We explore the consequences of different choices for the parametrisations of the exchange terms, showing that a good representation of volume, momentum, and buoyancy exchange, and of the pressure difference between the fluids, is required. For this simple case, this is achieved entirely without parametrisation of subfilter terms, showing that the multi-fluid approach is capturing the coherent structures of convection well.

D3037 |
EGU2020-8322
Luisa Cristini and the ESM Project Consortium

With climate change and the conjoint challenges of food availability, clean water and geo-energy resources, our society is facing major challenges in the near future. These challenges are hard to address, because projections of Earth system change involve uncertainties that require quantification. Therefore, the Earth system science community tries to develop tools that provide decision-makers with the information required to effectively manage these issues.

The Advanced Earth System Modelling Capacity project (ESM) aims to enable such tools, investigating problems by looking at interactions between different Earth system components and improve their representation in numerical models. The project was funded by the German Helmholtz Association in April 2017 and involves eight research centers across Germany. The ultimate goal of the project is to represent the Earth system and how it changes with a world-leading modelling infrastructure that will support the process of developing solutions for the grand challenges we are facing.

The five different work packages of the project are working on topics such as enhancing the representation of Earth system model compartments, develop a flexible framework for coupling of Earth system model components, advance the Earth system data assimilation capacity, diagnose Earth system models, further develop cutting-edge frontier simulations, cross-scale modelling, and contribute to the shaping of a national strategy for Earth system modelling. The project also engages in training activities to educate and transfer knowledge to the next generation of scientists.

Since its initiation the project contributed with important results to several key model systems and platforms. In this presentation, we will highlight some current results and discuss advances in our Earth system modelling community and the way forward.

D3038 |
EGU2020-11706
Sylvain Mailler, Mathieu Lachatre, and Laurent Menut

A well-known drawback of Eulerian models is excessive numerical diffusion of the transported species. This applies to chemical species but also to water vapor. We present a new way of dealing with this problem in the vertical direction by using the Després and Lagoutière (1999) scheme – hereinafter DL99, a simple 1st-order advection scheme with antidiffusive properties. These authors have only studied this scheme in the context of 1d transport. Here we test the applicability of this scheme in atmospheric modelling by applying it to tracer transport in the vertical direction in idealized 2d (zonal-vertical) atmospheric circulations and quantify the gain compared to classical advection schemes.

In this idealized framework, we have tested the efficiency of DL99 in two cases representative of important situations for atmospheric transport :
- Formation of a thin plume from an initially thick column of tracer (e.g. volcanic plume, biomass burning plume etc.) under the effect of zonal wind shear in presence of large-scale variations in vertical wind
- Long-range advection of a thin polluted layer under the action of zonal wind in presence of large scale oscillations in the vertical wind.

In these idealized case studies, we show that using DL99 in the vertical direction yields dramatically improved performance compared to any other scheme we have tested, including the 3rd-Order Piecewise Parabolic Method (PPM). As an example, in a simulation with a vertical resolution of 500m and a zonal resolution of 25 km initialized by a 1000m-thick, zonally uniform layer of tracer, after being transported horizontally over 2000km over 48 hours by a uniform zonal wind ~11.5ms-1 together with an oscillating vertical wind of +-0.05ms-1, maximal tracer concentration at the end of the simulation with DL99 is 94% of its initial value instead of 51% with PPM, l2 relative error is 10% instead of 61%, and 92% of the tracer mass is still confined in the correct 1000m-thick envelope instead of 50%.

This and other numerical experiments shows that, by design, DL99 reduces numerical diffusion, but it also proves it to be able to preserve the areas of uniform tracer concentration even if these areas cover only a very small number of cells in the vertical direction. We argue that this unique set of properties, along with the simplicity of its formulation and its minimal computational cost make the DL99 an extremely attractive candidate for a robust and non-diffusive representation of vertical advection in Eulerian meteorological and chemistry-transport models. This scheme has been implemented in the state-of-the-art CHIMERE chemistry-transport model (Mailler et al., 2017), and we have shown that it brings a clear improvement in the representation of the structure of a volcanic plume from the Etna volcano (Lachâtre et al., 2020, Atmos. Chem. Phys.)

Main references:

Després, B., and F. Lagoutière, 1999, Un schéma non linéaire anti-dissipatif pour l'équation d'advection linéaire, Comptes Rendus de l’Académie des Sciences

D3039 |
EGU2020-14464
Daniel Caviedes-Voullième, Nils Gerhard, Aleksey Sikstel, and Siegfried Müller

Shallow water modelling is a widely used for a vast range of applications in Hydraulics, Hydrology and Environmental Geosciences. It is at the core of most fluvial flood modelling approaches, and increasingly turning into the model of choice for urban flood modelling, coastal modelling and rainfall-runoff hydrological simulation. Shallow water solvers have significantly matured in the last decade, and currently, robust and accurate first-order solvers are widely available. Relevant developments have also been achieved in terms of higher order solvers, based on MUSCL and WENO reconstructions and on Discontinuous Galerkin (DG) schemes. Despite all this, applying shallow water solvers on realistic problems is constrained by the multiscale nature of environmental surface flows, in which flows in large domains are strongly affected by small-scale features of both the topography and the flow fields. This inherently multiscale problem naturally calls for a multiresolution modelling strategy, which is the topic of this contribution.

 

In this work, we explore the application of a multidimensional Discontinuous Galerkin scheme with dynamic mesh adaptivity driven by multiresolution analysis based on wavelets. The scheme harnesses the locality and high-order properties of DG, and makes use of an additional decomposition into the multiwavelet space driving a multiresolution analysis. By assessing the relevance of local features of the solution across scales, mesh adaptivity is triggered. In previous works, the general scheme has been presented and tested. Herein, we test the capabilities of the scheme on well-known benchmark problems for 2D shallow flows, including both laboratory and field scale flows.

 

The results clearly show that the scheme is capable of solving such problems with a high accuracy and that the dynamically adaptive mesh is capable of tracking physically-meaningful interfaces (wetting and drying fronts, transcritical shocks, rotating vortices) accurately. Moreover, the adaptive scheme is capable of providing very high spatial resolution where and when it is required, while keeping the computational cost orders of magnitude lower than what a uniform high resolution mesh would impose. In particular, the results suggest that this type of adaptive scheme produces more efficient meshes than alternative schemes. The results showcase some of the advantages of high-order solvers, especially when combined with adaptive schemes and are a proof-of-concept of the applicability of this type of solvers for realistic problems. Finally, the results also evidence the capability of the adaptive multiresolution strategy to transparently incorporate the properties of the underlying shallow water solver, allowing for improvements on the core scheme to always benefit the adaptive solution.

D3040 |
EGU2020-14970
Konrad Simon and Jörn Behrens

Global simulations over long time scales in climate sciences often require coarse grids due to computational constraints. This leaves dynamically important smaller scales unresolved. Thus the influence of small scale processes has to be taken care of by different means. State-of-the-art dynamical cores represent the influence of subscale processes typically via subscale parametrizations and often employ heuristic coupling of scales. This, however, unfortunately often lacks mathematical consistency. The aim of this work is to improve mathematical consistency of the upscaling process that transfers information from the subgrid to the coarse scales of the dynamical core and to largely extend the idea of adding subgrid correctors to basis functions for scalar and vector valued elements discretizing various function spaces.

Discussing prototypically the issue of weighted Hodge decompositions I will show that standard techniques on coarse meshes fail to find good projections in all parts of a modified de Rham complex if rough data is involved and discuss an idea of how to construct multiscale finite element (MsFEM) correctors to scalar and vector valued finite elements and, further, how to construct stable multiscale element pairings using the theory of finite element exterior calculus (FEEC). This can be seen as a meta-framework that contains the construction of standard MsFEMs [Efendiev2009, Graham2012]. Application examples here comprise porous media, elasticity, and fluid flow as well as electromagnetism in fine-scale and high-contrast media. I will provide the necessary theoretical background in homological algebra and differential geometry, and discuss a scalable MPI based implementation technique suitable for large clusters. Several computational examples will be shown. I may, if time permits, discuss some ideas from homogenisation theory to attack the problem of a proof of accuracy.

D3041 |
EGU2020-1328
Yihui Zhou, Yi Zhang, Zhuang Liu, Jian Li, and Rucong Yu

High-resolution numerical weather and climate models have a great advantage in both prediction and simulation for their ability to resolve small-scale systems, but suffer from expensive computational cost. The aim of this study is to explore a cost-effective variable-resolution modeling approach within a newly developed global nonhydrostatic dynamical core based on an unstructured mesh. We provide a size-controllable formulation of hierarchical refinement mode by an adapted density function for more realistic high-resolution simulations. The dynamical core is tested regarding both dry and moist atmosphere to evaluate variable-resolution simulations against quasi-uniform ones. In baroclinic wave tests, the variable-resolution model, which owns much less grid points, captures a comparable fine-scale fluid structure with the high-resolution quasi-uniform one in the refinement region. In the coarse region, the result of the variable-resolution simulation matches that of the low-resolution quasi-uniform one, which contributes to smaller global errors of the variable-resolution simulation. A series of sensitivity tests regarding parameters of the hierarchical refinement mode validate the high stability of the variable-resolution model to preserve the intensity and vertical structure of tropical cyclones moving through the transition zone. The variable-resolution modeling lays a strong foundation for potential improvement of regional high-resolution simulations.

D3042 |
EGU2020-10375
| solicited
Hans Hersbach, Bill Bell, Paul Berrisford, Per Dahlgren, András Horányi, Joaquı́n Muñoz-Sabater, Julien Nicolas, Raluca Radu, Dinand Schepers, Adrian Simmons, and Cornel Soci

Reanalysis is a key contribution to the Copernicus Climate Change Service (C3S) that is implemented at the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the European Commission. The most recent ECMWF reanalysis, ERA5, provides hourly estimates of the global atmosphere, land surface and ocean waves at a horizontal resolution of 31km. Daily updates are provided with a latency of 5 days, while an extension back to 1950 is to be made available in the 2nd quarter of 2020.
ERA5 uses a 2016 version of the ECMWF numerical weather prediction model and data assimilation system (Integrated Forecasting System Cy41r2) to assimilate both in situ and satellite observations (95 billion for the period 1979 - 2019), many of which stem from reprocessed data records. The assimilation method includes a variational method for estimating observation biases that respects the heterogeneity within the observing system. Information on random uncertainties in the state estimates is provided by a 10-member ensemble of data assimilations at half the horizontal resolution (63km).
This presentation provides a concise overview of the ERA5 data assimilation system. A basic evaluation of characteristics and performance is presented, which includes an inter-comparison with other reanalysis products, such as its predecessor ERA-Interim and several major reanalyses produced elsewhere. Attention is given to the importance of the specification of the background error covariance matrix that determines the weight given to the model's first guess in the assimilation. In addition, a special focus will be on the back extension from 1950 to 1978, where the absence of satellite data prior to the 1970s puts a more demanding constraint on the data assimilation system.

D3043 |
EGU2020-3131
Kevin Raeder, Jeffrey Anderson, TImothy Hoar, Nancy Collins, and Moha El Gharamti

The National Center for Atmospheric Research (NCAR) has recently released version 2.1 of the Community Earth System Model (CESM 2.1). A twenty-year, 80-member ensemble atmospheric reanalysis with 1-degree resolution in the CAM6 atmospheric model is being produced using NCAR’s Data Assimilation Research Testbed (DART) to support a variety of climate research goals. A standard configuration of CAM and the CLM5 land surface model will be coupled to a prescribed ocean and sea ice. Eventually, the reanalyisis will generate a final product that extends from 1999 to the present. Observations being assimilated include in situ observations used in the operational NCEP CFSR reanalysis along with GPS occultation observations and remote sensing temperature retrievals. The primary goal is to provide an ensemble of atmospheric forcing that can be used to generate additional ensemble reanalyses for other components of CESM including CLM, the POP and MOM6 ocean models, and the CICE sea ice model. Highlights of results from the first 10-years of the reanalysis will be presented. Results will include evaluation of short-term forecasts in observation space for root mean square error, ensemble spread, and ensemble consistency. In addition, key aspects of the atmospheric forcing files for other components of the climate system will be discussed. 

D3044 |
EGU2020-2012
Sean Casey, Lidia Cucurull, and Andres Vidal

Under the Quantitative Observing System Assessment Program, the National Oceanic and Atmospheric Administration's (NOAA's) Atlantic Oceanographic and Meteorological Laboratory (AOML) is preparing to utilize the 9-km-resolution European Centre for Medium-Range Weather Forecasts (ECWMF) Cubic Octahedral grid global Nature Run (ECO1280) for observation simulation and conducting Observing System Simulation Experiments (OSSEs).   As part of the OSSE calibration, and before experiments can be run, it needs to be shown that the forecast model used in the OSSEs does not do a better job in predicting the Nature Run meteorology than it does in predicting the real world. Otherwise, the conclusions from the OSSEs in such a configuration may misstate the potential impact of a given instrument. In this presentation, the predictability of the new global OSSE system being developed at NOAA will be discussed. The NOAA/National Centers for Environmental Prediction (NCEP) Finite-Volume Cubed-Sphere Global Forecast System (FV3GFS) is used to test predictability over the first two months of ECO1280 (October-November 2015), comparing forecasts using simulated observations with added errors to real-world observations.  Only conventional observations will be utilized in both cases.  

D3045 |
EGU2020-17945
Matthias Schindler, Martin Weissmann, Andreas Schäfler, and Gabor Radnoti

Utilizing a multitude of in situ and remote sensing instruments, a comprehensive dataset was collected during the transatlantic field campaign NAWDEX in autumn 2016. Cycled data denial experiments with the global model of the ECMWF showed that additionally collected dropsonde and radiosonde observations contributed to a reduction in the short-range forecast error, with the most prominent error reductions being linked to Tropical Storm Karl, cyclones Matthew and Nicole and their subsequent interaction with the midlatitude waveguide. While the short-range forecast quality was improved, Schäfler et al. (2019, in review) demonstrated that ECMWF IFS analyses exhibit deficiencies in capturing observed wind speeds at and above the dynamical tropopause during NAWDEX. Therefore, data assimilation output from the ECMWF IFS is used to evaluate the observational influence on the tropopause. Statistics of data assimilation diagnostics such as the analysis increment and first guess departure will be assessed in observation space in a tropopause relative framework to quantify the impact of assimilated radiosonde observations on tropopause location and sharpness.

D3046 |
EGU2020-18011
Inti Pelupessy, Maria Chertova, Gijs van den Oord, and Ben van Werkhoven

The ERA5 dataset provides a comprehensive view on recent climate data by assimilating vast amounts of historical observations into the ECMWF integrated forecast system, and as such establishing a reference point in the field of weather and climate modelling. The successor of ERA-interim is ubiquitous in the earth sciences, with applications such as boundary conditions for regional simulations, atmospheric forcings to ocean or land surface models, initial conditions to climate prediction experiments, etc.. The conventional workflow for such applications is to download the data, extract the necessary variables, optionally regrid or resample and save it in a model specific format. This procedure is time consuming, difficult to document properly and generates a lot of intermediate data of low reuse value. Here, we provide an alternative to this by wrapping access to the ERA5 dataset in a standardized OMUSE model interface. OMUSE is a Python framework for Earth System modelling, developed to simplify the use of simulation codes and enable new model couplings. Within OMUSE the ERA5 dataset is transparently accessed using the CDSAPI and the resulting interface is very much like an OMUSE interface for a simulation code. Data is pulled from the online climate data store only when needed and cached for later reuse. This approach simplifies the access and coupling of the ERA5 dataset with OMUSE model components and makes it trivially easy to repeat a model run with a different dataset or even replace it with a life model.

D3047 |
EGU2020-20536
Roman Nuterman, Dion Häfner, Markus Jochum, and Brian Vinter
So far, our pure Python, primitive equation ocean model Veros has been
about 50% slower than a corresponding Fortran implementation. But recent
benchmarks show that, thanks to a thriving scientific and machine
learning library ecosystem, tremendous speed-ups on GPU, and to a lesser
degree CPU, are within reach. On GPU, we find that the same model code
can reach a 2-5 times higher energy efficiency compared to a traditional
Fortran model.
We thus propose a new generation of geophysical models. One that
combines high-level abstractions and user friendliness on one hand, and
that leverages modern developments in high-performance computing on the
other hand.
We discuss what there is to gain from building models in high-level
programming languages, what we have achieved, and what the future holds
for us and the modelling community.
D3048 |
EGU2020-20598
André Jüling, Anna von der Heydt, and Henk Dijkstra
Climate variability on decadal to multidecadal time scales appears to be organized in pronounced patterns with clear expressions in sea surface temperature, such as the Pacific Multidecadal Variability and the Atlantic Multidecadal Variability. These patterns are now well studied both in observations and in global climate models and are important in the attribution of climate change. Results in CMIP5 models have indicated large biases in these patterns with consequences for ocean heat storage variability and eventually the global mean surface temperature.
We use two multi-century Community Earth System Model simulations at coarse (1°) and fine (0.1°) ocean model horizontal grid spacing and study the effect of the representation of mesoscale ocean flows on major patterns of multidecadal variability. We find that resolving mesoscale ocean flows both improves the characteristics of the modes of variability with respect to observations and increases the amplitude of the heat content variability in the individual ocean basins. However, the effect on the global mean surface temperature is relatively minor.
D3049 |
EGU2020-1596
Ming Zhao

Atmospheric rivers (ARs) are narrow, elongated, synoptic jets of water vapor that play important roles in the global water cycle and regional weather and climate extremes. Accurate climate projections of high impact global severe flood and drought events hinge on the climate models' ability to simulate and predict the AR phenomenon. This presentation will provide a systematic evaluation of the AR statistics and characteristics simulated by the GFDL new generation high resolution global climate model participating in the CMIP6 High Resolution Model Intercomparison Project (HiResMIP). The analyses include the historical period (1950-2014) compared against the ERA-Interim reanalysis results as well as future projections under global warming scenarios. The AR characteristics such as the spatial distribution, frequency, and intensity are explored in conjunction with large-scale circulation patterns such as the El Niño–Southern Oscillation, the Arctic Oscillation, and the Pacific-North-American teleconnections pattern. Potential changes in AR characteristics with global warming scenarios and their implications to weather and climate extremes will be discussed.

D3050 |
EGU2020-1867
Hussain Alsarraf

The purpose of this study is to examine the impact of climate change on the changes on summer surface temperatures between present (2000-2010) and future (2050-2060) over the Arabian Peninsula and Kuwait. In this study, the influence of climate change in the Arabian Peninsula and especially in Kuwait was investigated by high resolution (36, 12, and 4 km grid spacing) dynamic downscaling from the Community Climate System Model CCSM4 using the WRF Weather Research and Forecasting model. The downscaling results were first validated by comparing National Centers for Environmental Prediction NCEP model outputs with the observational data. The global climate change dynamic downscaling model was run using WRF regional climate model simulations (2000-2010) and future projections (2050-2060). The influence of climate change in the Arabian Peninsula can be projected from the differences between the two period’s model simulations. The regional model simulations of the average maximum surface temperature in summertime predicted an increase from 1◦C to 3 ◦C over the summertime in Kuwait by midcentury.

 

D3051 |
EGU2020-1914
Xudong Liang, Jingfang Yin, Yanxin Xie, and Feng Li

    The EARS (East Asia Reanalysis System) is a project of China Meteorological Administration for developing a high resolution regional atmospheric reanalysis dataset in the East Asia with higher quality for meso-scale weather system simulation and regional climate analysis. The reanalysis system was established with a domain covers the East Asia with horizontal resolution of 12km and some sub-domains with horizontal resolution of 3km. In EARS, besides the Global Communication System (GTS) shared observations, dense local observations such as the ground-based automatic observations, and weather radar data are used. New data assimilation operator for radar data was developed, and data assimilation methods for high-density surface observation were tested. Based on the observation dataset and reanalysis system, 10 years primary test reanalysis dataset was established. Verifications of the dataset indicate a better quality in comparison with global reanalysis data.

D3052 |
EGU2020-1942
Peter Krizan

The aim of this presentation is to compare the occurrence of discontinuities in the ozone concentration data from the MERRA-2, ERA-5 and JRA-55 reanalyse, with the help of the Pettitt homogeneity test. We distinguish between the significant and insignificant discontinuities, according to the relation between the dispersion and the average ozone values before and after the discontinuity.    This occurrence is important for trend analyses, because the presence of discontinuities influences the values of trends and their significance. Discontinuities arise from the changing in the assimilation procedure, introducing new observation to the reanalyse, and changing of data quality. We search for their spatial, temporal and geographical occurrence. There are differences among these reanalyses. In the case of the MERRA-2 data, the transition from SBUV to EOS Aura data in 2004 has great impact on discontinuity behaviour. The frequent occurrence of discontinuities is seen in the uppermost model layers. The uppermost MERRA-2 layer is 0.1 hPa, while for ERA-5 this layer is 1 hPa. So there are differences in the vertical distribution of discontinuities among the reanalyses. The ozone data with the strong occurrence of the significant discontinuities is not suitable for trend analyses.   

Chat time: Thursday, 7 May 2020, 10:45–12:30

Chairperson: Jemma Shipton
D3053 |
EGU2020-3225
Junwen Chen, Chi-Yung Tam, Steve H.L. Yim, Meng Cai, Ran Wang, Xinwei Li, Chao Ren, Tuantuan Zhang, and Peng Gao

A new 10-type urban Local Climate Zone (LCZ) classification with 100-m resolution was developed, following the guidelines of the World Urban Database and Access Portal Tools (WUDAPT) over the Greater Bay Area (GBA). This LCZ dataset was incorporated into the Building Environment Parameterization (BEP)-Building Energy Model (BEM) multi-layer urban canopy scheme used by the Weather Research and Forecasting (WRF) model, with key parameters (such as fraction of impervious surface, building height/width, road width, air conditioning usage) determined from local building morphology and energy consumption patterns. The impacts of using such detailed 10-type LCZ, as compared to using remapped 3-type LCZ and using default WRF 1-type urban land cover were assessed, based on parallel integrations of the WRF system at 1-km resolution for a historical hot-and-polluted event over the GBA. It was found that the model surface temperature, air temperature, humidity and wind speed in the 10-type LCZ run were in closer agreement with in-situ observations, demonstrating the value of detailed urban LCZ data in improving the model performance. Smaller diurnal temperature range and higher nighttime temperature were found in the 10-type LCZ run compared to the 3-type LCZ and 1-type runs. Increased building height in the 10-type LCZ setting also reduces positive bias of wind speed in the lower planetary boundary layer at urban locations. The cold and dry biases over the non-urban areas in the 10-type LCZ run could be further reduced through considering updated land cover, soil type, soil hydraulic/thermal parameters, soil moisture/temperature. Owing to the improvement in capturing the urban meteorology, incorporating more detailed LCZ classification might also improve air-quality simulations. These findings should be relevant to the development of comprehensive, high-resolution earth system models, which are an indispensable tool for mitigation of and adaption to regional environmental and climate changes.

D3054 |
EGU2020-4183
Werner Bauer, Jörn Behrens, and Colin J. Cotter

We introduce an efficient split finite element (FE) discretization of a y-independent (slice) model of the rotating shallow water equations. The study of this slice model provides insight towards developing schemes for the full 2D case. Using the split Hamiltonian FE framework [1,2], we result in structure-preserving discretizations that are split into topological prognostic and metric-dependent closure equations. This splitting also accounts for the schemes' properties: the Poisson bracket is responsible for conserving energy (Hamiltonian) as well as mass, potential vorticity and enstrophy (Casimirs), independently from the realizations of the metric closure equations. The latter, in turn, determine accuracy, stability, convergence and discrete dispersion properties. We exploit this splitting to introduce structure-preserving approximations of the mass matrices in the metric equations avoiding to solve linear systems. We obtain a fully structure-preserving scheme with increased efficiency by a factor of two.

References

[1] Bauer, W. and Behrens, J. [2018], A structure-preserving split finite element discretization of the split wave equations, Applied Mathematics and Computation, 325, 375--400.

[2] Bauer, W., Behrens, J., Cotter, C.J. [2019], A structure-preserving split finite element discretization of the rotating shallow water equations in split Hamiltonian form, preprint: http://arxiv.org/abs/1912.10335.

D3055 |
EGU2020-4579
Qiang Tang, Xiaomeng Huang, and Xing Huang

Numerical simulation of nonlinear gravity internal waves with non-hydrostatic ocean models, especially these which using the terrain-following sigma-coordinate, is challenging. The expensive computation cost, which is caused by the dynamic pressure Poisson solver in cases using fine grid resolution in both directions (horizontal and vertical), is the main reason. A non-hydrostatic ocean model named NH-GOMO is constructed based on a partially implicit finite difference scheme for the dynamic pressure and adopts an idea of “decimation and interpolation”. A significant optimization for the pressure Poisson solver, which brings no obvious accuracy loss, is obtained with these technologies. The automatic parallel operator library named OpenArray is used as the bottom layer of this model and make it easy to transport between different computing platforms. Accuracy and efficiency have been validated by several ideal test cases.

D3056 |
EGU2020-4751
Michiel de Bode, Pierre Roubin, Thierry Hedde, and Pierre Durand

Complex terrain creates many challenges for modelling aerologic phenomenon. Local variations can have drastic effects on airflows; a good representation of local orography is, therefore, crucial in models. While finer-resolution improves the orographic description in models, it creates a “grey zone” problem for boundary layer schemes. The grey zone, for PBL schemes, is where model-resolution comes close to the size of turbulent structures, leading to the structures being partly resolved and partly sub-grid scale. Research on the grey zone has focused mostly on daytime, neutral-to-unstable conditions. In thinner nocturnal stable layers, local processes become predominant, such as channelling, the simulation of which demands higher resolution in models.

In this research, we run a nested grid version of WRF with a resolution of the innermost domain at 111 m and the coarsest domain at 9 km. We focus on the 1 km wide pre-Alpine valley of Cadarache, a tributary of the Durance River. Previous simulations did not succeed in representing the valley with resolutions of 1 km. We test the indicative value of turbulent length-scales for decisions on the grey zone. Based on the KASCADE 2017 data of several sonic anemometers, placed along the valley thalweg, we determine the turbulent length scales to verify whether the turbulence remains sub-grid or not.

Our first results indicate that turbulent structures in this sub-kilometre scale valley remain well below the model resolution for night time conditions. First runs with 111 m resolution show realistic night time winds and produced the correct overall-structure in the valley. A general under prediction of 2 m-temperatures was found, especially during daytime. Further runs aim to improve forecast precision.  

D3057 |
EGU2020-5403
Yuefei Zeng, Tijana Janjic, Alberto de Lozar, Ulrich Blahak, and Axel Seifert

 

Data assimilation on the convective scale uses high-resolution numerical models of the atmosphere
that resolve highly nonlinear dynamics and physics. These non-hydrostatic, convection
permitting models are in short runs very sensitive to proper initial conditions. 
However, the estimation of initial conditions is hampered by assumptions made in data assimilation algorithms
and in their models of the observation error and model error uncertainty. Within this work, an idealized testbed
for Radar Data Assimilation has been developed, which uses Kilometre-scale ENsemble Data Assimilation (KENDA) system
of the (Deutscher Wetterdienst) DWD. A series of data assimilation experiments for a supercell storm are conducted.
The sensitivity to the configurations of the radar forward operator and specification of the observation error
is investigated. Moreover, impacts of different observations (radial wind, reflectivity or both)
on the performance of data assimilation cycles and 6-h forecasts are shown, for instance,
the preservation of divergence, vorticity and mass of hydrometeors, compared to the nature run is of special interest.

 

D3058 |
EGU2020-5583
Nadine Mengis, David P. Keller, Andrew MacDougall, Michael Eby, Nesha Wright, Katrin J. Meissner, Andreas Oschlies, Andreas Schmittner, H. Damon Matthews, and Kirsten Zickfeld

The University of Victoria Earth system climate model of intermediate complexity has been a useful tool in recent assessments of long-term climate changes including paleo-climate modelling. Since the last official release of the UVic ESCM 2.9, and the two official updates during the last decade, a lot of model development has taken place in multiple groups. The new version 2.10 of the University of Victoria Earth System Climate Model (UVic ESCM), to be used in the 6th phase of the coupled model intercomparison project (CMIP6), presented here combines and brings together multiple model developments and new components that have taken place since the last official release of the model. To set the foundation of its use, we here describe the UVic ESCM 2.10 and evaluate results from transient historical simulations against observational data. We find that the UVic ESCM 2.10 is capable of reproducing well changes in historical temperature and carbon fluxes, as well as the spatial distribution of many ocean tracers, including temperature, salinity, phosphate and nitrate. This is connected to a good representation of ocean physical properties. For the moment, there remain biases in ocean alkalinity and dissolved inorganic carbon, which will be addressed in the next updates to the model.

D3059 |
EGU2020-8733
Omar Müller, Pier Luigi Vidale, Patrick McGuire, Benoît Vannière, Reinhard Schiemann, and Daniele Peano

Previous studies showed that high resolution GCMs overestimate land precipitation when compared against gridded observations or reanalysis (Demory et al. 2014, Vannière et al. 2019). In particular, grid point models (eg. HadGEM3) show a significant increase of precipitation on regions dominated by complex orography, where the scarcity of gauge stations increase the uncertainty of gridded observations. The goal of this work is to assess the effect of such differences in precipitation on river discharge, considering it as an integrator of the water balance at catchment scale. A set of JULES and CLM simulations have been conducted turning rivers on with Total Runoff Integrating Pathways (TRIP) and the River Transport Model (RTM) respectively. The simulations form three ensembles for each land surface model (LSM) which main difference is given by the forcing dataset. The forcings are WFDEI (reanalysis), LR (~1° resolution in meteorological data from GCMs) and HR (~0.25° resolution in meteorological data from GCMs). These ensembles are evaluated in a set of 280 catchments distributed around the world.

In terms of correlation between simulated and observed river discharge observations, the results show that LSMs forced by reanalysis have higher performance than LSMs forced by GCMs as expected. In terms of biases, the river discharge is underestimated in eight out of eleven major basins when LSMs are forced by reanalysis. On those basins, the extra precipitation estimated by GCMs help to simulate an amount of river discharge closer to observations (Eg. Yenisey and Lena). Moreover, 37 small basins with a strong component of orographic precipitation over the Andes, the Rocky Mountains, the Alps and in the Maritime Continent were evaluated. In most cases HR offers notably better results than LR and WFDEI, suggesting that high resolution models produce orographic precipitation in the correct place and time.

In future works offline TRIP simulations will be carried out directly forced by runoff and subsurface runoff from GCMs. It will allow to discard errors in evapotranspiration produced by JULES or CLM when they are used to simulate river discharge. This work is part of the European Process-based climate sIMulation: AdVances in high resolution modelling and European climate Risk Assessment (PRIMAVERA) Project. PRIMAVERA is a collaboration between 19 funded by the European Union’s Horizon 2020 Research & Innovation Programme.

Demory, M. E., Vidale, P. L., Roberts, M. J., Berrisford, P., Strachan, J., Schiemann, R., & Mizielinski, M. S. (2014). The role of horizontal resolution in simulating drivers of the global hydrological cycle. CLIM DYNAM, 42(7-8), 2201-2225.

Vannière, B., Demory, M. E., Vidale, P. L., Schiemann, R., Roberts, M. J., Roberts, C. D., ... & Senan, R. (2018). Multi-model evaluation of the sensitivity of the global energy budget and hydrological cycle to resolution. CLIM DYNAM, 1-30.

D3060 |
EGU2020-5951
Yefim Kogan

Neglecting subgrid-scale (SGS) variability can lead to substantial bias in calculations of microphysical process rates. The solution to the SGS variability bias problem lies in representing the variability using two-dimensional joint probability distribution functions (JPDFs) for the pairs of different microphysical variables. The JPDFs have also been shown to vary in the vertical: as a result their implementation in mesoscale models presents a challenging task.

We developed a more efficient formulation of cloud inhomogeneity by using a concept of “generic” JPDF. Using Large Eddy Simulation (LES) studies of shallow cumulus and cumulus congestus clouds we showed that JPDFs calculated based on datasets representing “typical” cloud types (“generic” JPDFs) provide good approximation of microphysical process rates. The generic JPDF, therefore, represent the cloud type in general, i.e. they do not depend on changing ambient conditions. The advantage of generic JPDFs is that they can be a-priory integrated and yield a one-dimensional variability factor (V-factor) specific for each cloud type. A quite accurate approximation of V-factors by an analytical function in the form of a 3rd order polynomial was obtained and can be easily implemented in mesoscale models.

How big is the effect of cloud inhomogeneity on precipitation? To answer this question we evaluated the effect of accounting for cloud inhomogeneity on precipitation in sensitivity simulations. In the shallow Cu case over the 24 hr simulation the surface precipitation increased by about 40% when inhomogeneity was accounted. In the congestus Cu case the increase in precipitation was even more significant: by more than 75% over only 8 hours since rain first appeared at the surface. The sensitivity experiments also revealed that most of the increase resulted from the augmented autoconversion process. The effect of modified by the V-factor accretion rates was much less significant, primarily, because of the nearly linear dependence of accretion on its parameters.  This shows importance of the most accurate formulation of the autoconversion process.

 

 

D3061 |
EGU2020-12075
Xin Li

A reliable simulation of the spatiotemporal characteristics of the meteorological field is of great significance for hydrological impact studies. To approach this target, a number of weather generators (WGs) have been developed over the past few decades. However, a detailed literature review shows that currently developed WGs are subject to one or several aspects of the following limitations: (1) low spatial and temporal resolutions to describe the real spatiotemporal dynamics of meteorological processes; 2) incapability to simulate a spatially coherent, temporally consistent, and physically meaningful meteorological field; and 3) inability to extend into the future in a climate change context. To tackle these problems, this study proposes some potential solutions: (1) using the multi-site multivariate WGs (MMWGs) to simulate the spatial, temporal, and inter-variable dependencies in the meteorological field; (2) coupling the MMWGs with the resampling-based algorithms to generate high-resolution spatiotemporal meteorological data; and (3) perturbing the parameters of the distribution and dependency models based on the future climate projection. A case study is carried out and shows that the proposed solutions are effective in addressing the aforementioned challenges. These findings could assist in developing high-resolution MMWGs for weather simulation and impact assessment.

D3062 |
EGU2020-6558
Dai Koshin, Kaoru Sato, Kazuyuki Miyazaki, and Shingo Watanabe

A data assimilation system with a four-dimensional local ensemble transform Kalman filter (4D-LETKF) is developed to make a new analysis data for the atmosphere up to the lower thermosphere using the Japanese Atmospherics General Circulation model for Upper Atmosphere Research. The time period from 10 January 2017 to 20 February 2017, when an international radar network observation campaign was performed, is focused on. The model resolution is T42L124 which can resolve phenomena at synoptic and larger scales. A conventional observation dataset provided by National Centers for Environmental Prediction, PREPBUFR, and satellite temperature data from the Aura Microwave Limb Sounder (MLS) for the stratosphere and mesosphere are assimilated. First, the performance of the forecast model is improved by modifying the vertical profile of the horizontal diffusion coefficient and modifying the source intensity in the non-orographic gravity wave parameterization, by comparing it with radar wind observations in the mesosphere. Second, the MLS observational bias is estimated as a function of the month and latitude and removed before the data assimilation. Third, data assimilation parameters, such as the degree of gross error check, localization length, inflation factor, and assimilation window are optimized based on a series of sensitivity tests. The effect of increasing the ensemble member size is also examined. The obtained global data are evaluated by comparison with the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) reanalysis data covering pressure levels up to 0.1 hPa and by the radar mesospheric observations which are not assimilated.

D3063 |
EGU2020-7881
Nalini Krishnankutty, Sijikumar Sivaraman, Vinu Valsala, Yogesh Tiwari, and Radhika Ramachandran

The present study aims to design an optimal CO2 monitoring network over India to better constrain the Indian terrestrial surface fluxes using Lagrangian Particle Dispersion Model FLEXPART and Bayesian inversion methods. Prior and posterior cost functions are calculated using potential emission sensitivity from FLEXPART, prior flux uncertainties from CASA-GFED biosphere fluxes and CDIAC fossil fuel fluxes, and assumed uniform observational uncertainty of 2 ppm. A total of 73 regular grid cells are identified over the Indian land mass in 2°x2° latitude by longitude resolution assuming each cell can hold a potential site. Further, using incremental optimization methodology, the effectiveness of CO2 observations from these locations to reduce the Indian terrestrial flux uncertainty is quantified. The study is carried out in three parts. Firstly, we evaluated the existing stations over India in terms of reduction in uncertainty brought out by them in the surface flux estimation over the Indian landmass. This provides a unique opportunity for the representative stations to restart the observational programs based on their role in the flux estimation. In second part, we devised a methodology to design an extended network by adding a few more potential stations to the existing stations. Thirdly, we identified a completely new set of optimal stations for measuring atmospheric CO2 over India, which do not have any liabilities of pre-existing stations. The study depicts that the existing stations could bring down the uncertainty in the range of 18% to 36%. Among the existing stations, Kharagpur, Sagar, Shadnagar, Kodaikanal and Pondicherry are the best stations, which are indeed adding value to the CO2 flux inversions by reducing the uncertainty in the range of 4% to 13%. Addition of five new stations to the base network formed an extended network, which could reduce the uncertainty by an additional 15% for all the seasons reaching up to 45%. The new stations are mainly located over the east and north-east India with few exceptions during post-monsoon where stations are identified over the west and south India as well. The study identified 12 stations for each season and formed a ‘new network’ that could achieve the equivalent uncertainty reduction as compared with the 14 stations in the ‘extended network’. From this, an ‘optimal network’ and the best network consisting of 17 stations were identified that could best represent flux scenario and transport over India in all the four seasons. In northeast India, flux uncertainty is quite large, also the prevailing westerly wind in most parts of the year contributes to the surface CO2 signature of India to that location, demanding requirement of CO2 observations throughout the year. The study highlights a major zone of CO2 ‘observational void’ that exists in potential locations near east and northeast parts of India. Immediate requirement of CO2 monitoring initiative in these areas is highly recommended.

D3064 |
EGU2020-8684
Urs Schaefer-Rolffs

Scale invariance of geophysical fluids is investigated in terms of a scale invariance criterion. It was developed by Schaefer-Rolffs et al. (2015) based on the implication that each scale invariant subrange shall have its own criterion. Two particular cases are considered, namely the synoptic scales with a significant Coriolis term and a case at smaller scales where the anelastic approximation is valid. The first case is characterized by a constant enstrophy cascade, while in the second case small-scale fluctuations of density, pressure, and temperature are taken into account. In both cases, the respective scale invariance criteria are applied to simple parameterizations of turbulent diffusion. It is demonstrated that only dynamic approaches are scale invariant.

D3065 |
EGU2020-11976
Yassir Eddebbar

The distribution of dissolved oxygen in the tropical Pacific acts as a major control on marine ecosystems habitats and the foraging range of tuna fiheries in this region. A basic understanding of processes driving the mean structure and variability of the oxygen minimum zones (OMZs) in this region, however, remains challenged by sparse observations and coarse model resolution. In this study, we examine the influence of mesoscale processes on equatorial Pacific oxygen distribution and variability, with a particular focus on tropical instability vortices (TIVs). We employ an eddy-resolving configuration of the Community Earth System Model (CESM) and Lagrangian analysis to evaluate the impacts and governing mechanisms by which TIVs influence oxygen distribution and budgets in this region. The westward seasonal propagation of TIVs from summer through winter is found to drive a deepening of the oxygen minima along the equatorial Pacific band (10oN-10oS), and thus a seasonal expansion of the equatorial oxygenated tongue separating the north and south tropical Pacific OMZs. Strong hemispheric asymmetry is evident in TIV impacts on oxygen due to relatively weaker TIV activity and less pronounced oxygen gradients south of the equator. Mechanisms governing TIV oxygenation of the upper equatorial Pacific include a complex interplay of physical and biogeochemical processes. Isopycnal displacements act in concert with vortex trapping and lateral stirring to mix oxygenated waters from the upper layers into the equatorial boundaries of the north and south tropical Pacific OMZs. TIV-induced advection and upwelling, on the other hand, intensifies nutrient supply and productivity, organic carbon export, and oxygen respiration demand at depth, thus acting (though only slightly) to counteract the physical effects. The influence of these processes varies with TIV phase, from vortex generation in the eastern Pacific through vortex dissipation in the west. TIVs are found to have a profound influence on upper equatorial Pacifc oxygen distribution and budget, with major implications for understanding the coupling between oxygen and ocean circulation, predicting marine ecosystem dynamics, and designing observation networks in this region.

D3066 |
EGU2020-12129
Jang-Woon Wang, Jae-Jin Kim, and Ho-Jin Yang

In this study, we developed a new urban parameterization method of wind speeds. The parameterization method uses building morphology parameters (the volumetric fraction, the plane area fraction, and the average height of buildings) for three different areas. For this, we investigated the relationships between the wind speed change rates by buildings and the urban parameters in three target areas. Each target area includes an automated weather station (AWS) at its center. We conducted the multiple regression analysis to make look-up tables for the relationships between the wind speed change rates and the urban morphology parameters for 32 inflow directions in the target areas. For validation, we simulated the wind speeds at the AWSs using a CFD model coupled to the local data assimilation and prediction system (LDAPS), one of the operational numerical prediction systems of the Korean Meteorological Administration. The results showed that the estimated wind speeds at the AWSs in the three target areas were very similar to those simulated by the LDAPS-CFD coupled model as well as those observed at the AWSs.

D3067 |
EGU2020-12626
Mingkui Li and Shaoqing Zhang

A regional coupled prediction system for the Asia-Pacific area (AP-RCP) has been established. The AP-RCP system consists of WRF-ROMS (Weather Research and Forecast and Regional Ocean Model System) coupled models combined with local observing information through dynamically downscaling coupled data assimilation. The system generates 18-day atmospheric and oceanic environment forecasts on a daily quasi-operational schedule at Qingdao Pilot National Laboratory for Marine Science and Technology (QNLM). The AP-RCP system mainly includes 2 different coupled model resolutions: 27km WRF coupled with 9km ROMS, and 9km WRF coupled with 3km ROMS. This study evaluates the impact of enhancing coupled model resolution on the extended-range forecasts, focusing on forecasts of typhoon onset, and improved precipitation and typhoon intensity forecasts. Results show that enhancing coupled model resolution is a necessary step to realize the extended-range predictability of the atmosphere and ocean environmental conditions that include a plenty of local details. The next challenges include improving the planetary boundary physics and the representation of air-sea and air-land interactions when the model can resolve the kilometer or sub-kilometer processes.

D3068 |
EGU2020-12907
Young Ho Kim, Gyundo Pak, Yign Noh, Myong-In Lee, Sang-Wook Yeh, Daehyun Kim, Sang-Yeob Kim, Joon-Lee Lee, Ho Jin Lee, Seung-Hwon Hyun, Kwang-Yeon Lee, and Jae-Hak Lee

In our presentation, we will show the performance of a new earth system model developed at the Korea Institute of Ocean Science and Technology (KIOST), called the KIOST-ESM. The KIOST-ESM is based on a low-resolution version of the Geophysical Fluid Dynamics Laboratory Climate Model version 2.5. The main changes made to the base model include using new cumulus convection and ocean mixed layer parameterization schemes, which improve the model fidelity significantly. In addition, the KIOST-ESM adopts dynamic vegetation and new soil respiration schemes in its land model component. The performance of the KIOST-ESM was assessed in pre-industrial and historical simulations that are made as part of its participation into Climate Model Intercomparison Project phase 6. The response of the earth system to increases in greenhouse gas concentrations were analyzed in the ScenarioMIP simulations. The KIOST-ESM exhibited superior performance compared to the base model in terms of the mean sea surface temperature over the Southern Ocean and over the cold tongue in the tropical Pacific. The KIOST-ESM can also simulate the dominant tropical variability in the intraseasonal (Madden-Julian Oscillation) and interannual (El Niño-Southern Oscillation) timescales more realistically than the base model. On the other hand, like many other contemporary ESMs, the KIOST-ESM showed notable cold bias in the Northern Hemisphere, and the so-called double-Intertropical Convergence Zone bias remains. The ScenarioMIP results confirm the global average surface atmospheric temperature responds to the CO2 concentration.

D3069 |
EGU2020-13552
Yongqiang Jiang, Chaohui Chen, Hongrang He, Yudi Liu, Hong Huang, Xuezhong Wang, and Huawen Wang

The col field (a region between two lows and two highs in the isobaric surface) is a common pattern leading to the generation of mesoscale vortex and heavy rainfall in China. The mesoscale vortex usually forms near the col point and the dilatation axis of the col field in the low-level troposphere.

The Mesoscale model WRF was used to numerically simulate a rainfall process in col field. A temperature perturbation column (TPC) was introduced into the low-level col field near the col point, and the effects of TPC on mesoscale vortex and rainfall was analyzed.

It was shown that in the region of strong wind background, the TPC moves downstream and has little effect on the environment, while near the col point, the wind speed and the vertical wind shear are small, the TPC can stay in the col field for a long time, which can have a greater impact on the environment. The strong TPC near the col point can trigger the vortex. As the temperature of the air column increases, the pressure drops, leading to the low-level convergence and the upper-level divergence, and the low-level cyclonic vorticity form under the effect of ageostrophic winds, which is favor of the formation of mesoscale vortex in the weak wind field. The formation of vortex promotes the intensification of precipitation. The release of the latent heat of the condensation induced by the TPC makes a positive feedback for the mesoscale vortex. The southwestly low-level jet enhances through the thermodynamic action, resulting in convergence of the leeward low-level jet and increase of precipitation, and divergence of the upwind low-level jet and decrease of precipitation, respectively. The col field is a favorable circumstance for the formation of mesoscale vortex.

Acknowledgements. This research was supported by the National Natural Science Foundation of China (Grant Nos. 41975128 and 41275099).

D3070 |
EGU2020-16687
Fabian Jakub and Bernhard Mayer
Recent studies have shown that the effects of three dimensional
radiative transfer may impact cloud formation and precipitation.
While one-dimensional solvers are favoured due to their computational
simplicity, they do however neglect any horizontal energy transport.
In particular, the 1D approximation neglects 3D effects such as cloud side illumination
and the displacement of the cloud's shadow at the surface which are
relevant whenever the sun is not in the zenith.
This has a detrimental effect on the results of high resolution simulations.
3D radiative transfer has the potential to considerably change the
boundary layer dynamics, the evolution of clouds, their lifetime and
precipitation onset.
To this date, studies that investigate the influence of 3D effects on
realistic NWP settings are rare,
primarily because there haven't been 3D radiative transfer solvers
around that were fast enough to be run interactively in a forecast
simulation.

For that purpose we adapted the TenStream solver (parallel 3D radiative
transfer solver for LES) to unstructured meshes and coupled it to ICON-LEM.
We will present the new solver in the context of ICON-LEM simulations,
the methodologies used and its characteristics.
D3071 |
EGU2020-18092
Andreas Wagner, Benjamin Fersch, Peng Yuan, and Harald Kunstmann

The assimilation of observations in local area models (LAMs) assures that the states of meteorological variables are as close to reality as possible. Water vapor is an important constituent in terms of cloud and precipitation formation. Its highly variable nature in space and time is often insufficiently represented in models.

The aim of our work is to improve the simulation of water vapour in the Weather Research and Forecasting model WRF by assimilation of different observations. At the current stage, temperature, relative humidity, and surface pressure derived from climate stations are applied as well as zenith total delay (ZTD) data from global navigation satellite system (GNSS) stations. We try to identify the best setup of assimilation parameters which all of them directly or indirectly influence water vapour simulations. We will show case studies of high-resolution WRF simulations (2.1 km) between 2016 and 2018 for different seasons in southwest Germany. The impact of assimilation (3D-VAR) of different variables, combinations of variables, background error option as well as the temporal resolution of assimilation is evaluated. We look at column values and also at profiles derived from radiosondes. Our results show a positive impact when assimilating measured data, but deteriorations are also possible. A distinct influence of assimilation is only apparent for a few time steps. If the temporal resolution of the assimilated variables is too coarse and there is no assimilation close to these time steps, the positive effect vanishes.

D3072 |
EGU2020-18216
Dorotea Iovino, Malcolm J. Roberts, Laura C. Jackson, Christopher D. Roberts, Virna Meccia, David Docquier, Torben Koenigk, Pablo Ortega, Eduardo Moreno-Chamarro, Alessio Bellucci, Andrew Coward, Sybren Drijfhout, Eleftheria Exarchou, Oliver Gutjahr, Helene Hewitt, Katja Lohmann, Reinhard Schiemann, Jon Seddon, Laurent Terray, and Xiaobiao Xu and the iHESP group members

The Atlantic Meridional Overturning Circulation (AMOC) is a key component of the three-dimensional ocean circulation that transports warm and salty water northward, and exports cold and dense water from the Arctic southward.

The simulated AMOC in Coupled Model Intercomparison Project models (both coupled and ocean-only) has been studied extensively. However, correctly simulating the AMOC with these models remains a challenge for the climate modelling community. One model aspect that can affect the AMOC representation is the model resolution (i.e. grid spacing).

Here, we examine key aspects of the North Atlantic Ocean circulation using a multi-model, multi-resolution ensemble based on the CMIP6 HighResMIP coupled experiments. The AMOC and associated heat transport tend to become stronger as model resolution increases, particularly when the ocean resolution changes from non-eddying to eddy-present and eddy-rich. However, the circulation remains too shallow compared to observations for most models, and this, together with temperature biases, cause the northward heat transport to be too low for a given overturning strength.

In the period 2015-2050, the overturning circulation tends to decline more rapidly in the higher resolution models by more than 20% compared to the control state, which is related to both themean state and to the subpolar gyre contribution to deep water formation. The main part of the decline comes from the Florida Current component of the circulation.

D3073 |
EGU2020-18254
Johannes Flemming, Alessio Bozzo, Jerome Barre, Richard Engelen, Sebastien Garrigues, Robin Hogan, Vincent Huijnen, Antje Inness, Zak Kipling, Mark Parrington, Samuel Remy, Ivan Tsonevsky, and Vincent-Herni Peuch

The Copernicus Atmosphere Monitoring Service (CAMS) produces operationally global 5-day forecast of atmospheric composition and the weather using ECMWF’s Integrated Forecasting System (IFS) since 2015.Beginning with a system upgrade in June 2018 (45r1), the ozone and aerosol fields have been used in the radiation scheme to account for their radiative impact in the global CAMS forecasts. This approach replaced an aerosol and ozone climatology, which had been used before and which is still used in ECMWF's operational high-resolution medium-range NWP forecasts. The CAMS forecast system, which runs at a resolution of about 40 km, is applied here as a test-bed to explore the importance of aerosol direct feedback in an operational configuration, which can guide developments on composition-weather feedbacks for ECMWF's medium-range, monthly and seasonal forecasts.

We will discuss the changes and improvements of temperature forecast errors (i) using typical NWP scores and (ii) by applying an event based approach that focuses on episodes of high aerosol burdens such as the transport of Sahara dust to Europe during the heatwave in June 2019. In more detail we will show to what extent the realism of the prognostic aerosol fields influences the temperature response by considering aerosol forecast which were, or were not, improved by data assimilation of aerosol optical depth at the start of the forecast. We will further demonstrate that the consistent updates of both the climatological and prognostic aerosol fields are an important prerequisite for a making progress.

D3074 |
EGU2020-19344
Peter Düben, Nils Wedi, Sami Saarinen, and Christian Zeman

Global simulations with 1.45 km grid-spacing are presented that were performed with the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). Simulations are uncoupled (without ocean, sea-ice or wave model), using 62 or 137 vertical levels and the full complexity of weather forecast simulations including recent date initial conditions, real-world topography, and state-of-the-art physical parametrizations and diabatic forcing including shallow convection, turbulent diffusion, radiation and five categories for the water substance (vapour, liquid, ice, rain, snow). Simulations are evaluated with regard to computational efficiency and model fidelity. Scaling results are presented that were performed on the fastest supercomputer in Europe - Piz Daint (Top 500, Nov 2018). Important choices for the model configuration at this unprecedented resolution for the IFS are discussed such as the use of hydrostatic and non-hydrostatic equations or the time resolution of physical phenomena which is defined by the length of the time step. 

Our simulations indicate that the IFS model — based on spectral transforms with a semi-implicit, semi-Lagrangian time-stepping scheme in contrast to more local discretization techniques — can provide a meaningful baseline reference for O(1) km global simulations.

D3075 |
EGU2020-19869
Stefano Materia, Daniele Peano, Marianna Benassi, Tomas Lovato, Silvio Gualdi, Annalisa Cherchi, Andrea Alessandri, and Antonio Navarra

Large-scale river routing schemes are essential to close the hydrological cycle in fully coupled Earth System Models (ESMs). The availability of a realistic water flow is a powerful instrument to evaluate modeled land surface, a crucial component of the global climate whosproperties are often simplified by heavy parameterization, due to lack of process knowledge and validation data. We built up a new concept of river routing model, named HYDROS (HYdro-Dynamic ROuting Scheme), that replaces the present scheme embedded in the CMCC-CM2 global coupled model. The new scheme aims at overcoming one of the current major limitations, that is the use of time-independent flow velocities parameterized as a function of topography. Through the imposition of hydraulic equations, HYDROS defines a time-varying flow velocity associated with the amount of lateral runoff generated by the ESM's land component and the flow through the river system. Compared to the scheme currently in place, HYDROS show improvements in the simulation of mean annual discharge phase, especially for the Arctic rivers and the Amazon. In the Mississippi case, an extreme flood episode is better caught by the new representation, indicating that the improved flow velocity better catches the discharge peaks after extreme rainfalls. The new routing model is not able to improve the volumes of simulated river discharge, whose magnitude depends on the ability of the ESM land surface scheme to generate correct surface and sub-surface runoff. Once implemented in coupled mode, HYDROS will guarantee a plausible amount and timing of freshwater discharge into the global ocean, unveiling possible unresolved feedback mechanisms occurring in proximity of river mouths.

D3076 |
EGU2020-22676
Jemma Shipton, Colin Cotter, Tom Bendall, Thomas Gibson, Lawrence Mitchell, David Ham, and Beth Wingate

I will describe Gusto, a dynamical core toolkit built on top of the Fire- drake finite element library; present recent results from a range of test cases and outline our plans for future code development.

Gusto uses compatible finite element methods, a form of mixed finite element methods (meaning that different finite element spaces are used for different fields) that allow the exact representation of the standard vector calculus identities div-curl=0 and curl-grad=0. The popularity of these methods for numerical weather prediction is due to the flexibility to run on non-orthogonal grid, thus avoiding the communication bottleneck at the poles, while retaining the necessary convergence and wave propagation prop- erties required for accuracy.

Although the flexibility of the compatible finite element spatial discreti- sation improves the parallel scalability of the model it does not solve the parallel scalability problem inherent in spatial domain decomposition: we need to find a way to perform parallel calculations in the time domain. Ex- ponential integrators, approximated by a near optimal rational expansion, offer a way to take large timesteps and form the basis for parallel timestep- ping schemes based on wave averaging. I will describe the progress we have made towards implementing these schemes in Gusto.