by Thomas Rackow*, Daniel Klocke**, and the MPI-M and ECMWF-AWI modelling teams***

The nextGEMS model development is structured into simulation cycles. Each simulation cycle is followed by a hackathon, where simulation results are evaluated extensively by the nextGEMS community. The first nextGEMS hackathon in Berlin in October 2021 analysed the very first simulations. Based on the results, the two models participating in the project, IFS and ICON, were updated significantly for the cycle 2 simulations. These simulations where just completed and the unique datasets are waiting for the community to analyse them at the upcoming hackathon at the end of June. 
In case of IFS, besides updates to the atmospheric model component (read more here) and a more realistic treatment of snow, another update has been the use of a higher-resolution ocean that resolves eddies over large parts of the globe. Eddies in the ocean impact exchanges of energy and matter across the ocean-atmosphere interface, they transport heat both horizontally and vertically, and they were shown to alter projections of global climate in a warming world.

Figure 1: Ocean resolution used in the IFS-FESOM simulations for Cycle 2. The grid points of the NG5 configuration are concentrated in higher latitudes in order to resolve ocean eddies over larger areas of the globe compared to a more homogeneous distribution of grid points.

The operational high-resolution 9km forecasts at ECMWF include an ocean that applies a ¼ degree resolution (about 25km at the equator). While many coupled effects such as the atmospheric and oceanographic interaction during tropical cyclone conditions (Mogensen et al. 2017) can be realistically simulated at this resolution, ocean eddies are still only ‘permitted’ in mid-latitudes compared to the even coarser 1 degree standard-resolution climate models. This is far from the goal to explicitly resolve mesoscale ocean eddies all around the globe and is a potential source of many long-standing biases in climate models. Importantly, mesoscale features can also affect the predictability of European weather downstream of the Gulf Stream area.

A recent development for the IFS Cycle 2 simulations is a nextGEMS grid (NG5) for FESOM2, which was designed to be of equivalent size to the ICON-5km ocean grid with about 7.5 million surface nodes (Figure 1). Making use of the multi-resolution capability of FESOM2, relatively more surface nodes were concentrated in higher latitudes in order to extend the area where eddies are resolved – from the mid-latitudes into higher latitudes. Similar to the initialization strategy in ICON, the ocean grid has been spun up for several years with ERA5 forcing until 20 January 2020, the common starting point of the nextGEMS simulations, before being coupled to IFS. 

Early preliminary analyses of Cycle 2 compare rather well to the ERA5 reanalysis, OSI-SAF, and observational data, such as a long 40-day forecast of sea ice concentration evolution (Figure 2). We are looking very much forward to the next Hackathon in Vienna later this month where in-depth analyses from all project partners might reveal new surprises – both in terms of weaknesses but also in terms of novel strengths that only this new generation of climate models can provide.

Figure 2: 40-day forecast of sea ice concentration in the coupled IFS-FESOM Cycle 2 simulation with 2.5km IFS and FESOM2-NG5 (left), compared to data from OSI SAF (right). (figure kindly provided by Lorenzo Zampieri, NCAR,

* Scientist at ECMWF

** Model development at MPI-M
*** Special thanks to all participants of the 1st nextGEMS hackathon

by Tobias Becker* and ECMWF modelling teams**

One of the advantages of having a community of people looking at the behaviour of our models is that it makes us look at old problems in a new light. A good example is the first nextGEMS hackathon in October 2021, at which we found that both of our nextGEMS models, ICON and the Integrated Forecasting System (IFS), do not conserve energy well. The atmospheric energy leakage amounts to 6.6 W m-2 in ICON and 6.3 W m-2 in the IFS, at 4 to 5 km resolution with no parametrisation of deep convection. Analysis quickly showed that most of the energy imbalance in the IFS is related to water non-conservation, and that this issue gets worse when spatial resolution is increased and when the parametrisation of deep convection is switched off. Figure 1 shows that the nextGEMS Cycle 1 simulations with the IFS have an artificial source of water in the atmosphere, which is responsible for 4.6% and 10.7% of the total precipitation, in the simulation with deep convection parameterisation at 9 km (the configuration used for ECMWF’s operational high resolution ten-day forecasts) and without deep convection parameterisation at 4 km, respectively.

Figure 1: Daily mean water non-conservation in the IFS, computed as the difference between evaporation and precipitation, subtracted from the time derivative of total column water, as a fraction of precipitation. Results are shown as a function of lead time for NextGEMS Cycle 1 and Cycle 1.2 simulations, with and without deep convection parameterisation, at 9 km and 4 km, started on January 20, 2020.

The water non-conservation of the IFS had been known for a long time, given that the departure point interpolation of the Semi-Lagrangian advection scheme used in the IFS is non-conserving. However, while this issue was acknowledged to be detrimental for the accuracy of climate integrations (Roberts et al., 2018), so far it was thought that it does not affect the quality of numerical weather forecasts which span timescales ranging from a few hours to seasons ahead. Further analysis after the hackathon by the modelling teams at ECMWF has shown that about 50% of this artificial atmospheric water source is created as water vapour. The additional water vapour not only affects the radiation energy budget of the atmosphere, but can also cause energy non-conservation when heat is released through condensation. The other 50% of water is created as cloud liquid, cloud ice, rain or snow. The artificial source of water is related to higher-order interpolation in the semi-Lagrangian advection scheme, causing spurious extrema. For the moist species, spurious minima can result in negative values, which are clipped, leaving the spurious maxima to increase condensate mass.

To address the problem of water non-conservation in the IFS, three adjustments were required: a small bug fix in the IFS code, a switch from cubic to linear horizontal interpolation  in the advection scheme for cloud liquid, cloud ice, rain and snow, and most importantly, the activation of a global tracer mass fixer for all moist species, including water vapour. Activating tracer mass fixers increases the computational cost of running a simulation, but we succeeded to find an accurate yet cost-effective setup that uses a Finite Differences approach rather than a Finite Elements approach to calculate the vertical integrals for the tracer mass fixers. Note that tracer mass fixers assure global mass conservation, so locally tracer non-conservation is still possible but is expected to have been significantly reduced. Figure 1 shows that with these three model changes, global water non-conservation is essentially eliminated (less than 0.1%) in our new nextGEMS simulations (labelled Cycle1.2), while the global energy budget imbalance has reduced to less than 1 W m-2 (not shown). 

Importantly, global water conservation turns out to be beneficial not only for long integrations, but also for the quality of ECMWF’s medium-range weather forecasts. Preliminary results suggest that the model changes performed to fix the water and energy imbalances improve the skill scores of the medium-range weather forecasts for many variables, but most robustly for precipitation. Figure 2 shows that the mean absolute error against rain gauge measurements is about 2-3% smaller in 9 km forecasts that ensure global water conservation compared to the default 9 km forecasts.

Figure 2: Scaled differences between forecasts with and without global water conservation with respect to the mean absolute error in precipitation against rain gauge measurements over the Northern Hemisphere, as a function of lead time. Forecasts are run at 9 km resolution for summer 2020 and winter 2021.


* Alexander von Humboldt Fellow at ECMWF
** Special thanks to Thomas Rackow, Xabier Pedruzo, Irina Sandu, Richard Forbes, Michail Diamantakis, Peter Bechtold, Inna Polichtchouk
and to the participants of the 1st nextGEMS hackathon


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