D6.1: Report on the SR-ESMs evaluation
Creators: name: Tian, Fangxing
name: Bastin, Swantje
name: Koldunov, Aleksei
name: Jungclaus, Johann
name: Bordoni, Simona
name: Mohino, Elsa
name: Belinchón, Fernando
name: Baker, Alexander
name: Vidale, Pier Luigi
name: Dragaud, Ian
name: Mellado Gonzalez, Juan Pedro
name: Dengler, Marcus
name: Mrozowska, Marta
name: Peinado Bravo, Angel
name: Praturi, Divya Sri
name: Segura, Hans
name: Winkler, Marius
name: Shevchenko, Radomyra
Publisher: name: Zenodo
Year: 2023

description: About this document

Report describing the performance of storm-resolving models based on the first three development cycles.

Work package in charge

WP6

Executive summary

This report provides an overview of NextGEMS model performance in simulating tropical air-sea interaction systems. Our analysis encompasses an examination of the general circulation patterns in both the ocean and the atmosphere at large scales. Furthermore, we assess the models’ capabilities in replicating smaller-scale, short-term phenomena, including the Madden-Julian Oscillation (MJO), tropical cyclones, boundary layer profiles on selected grid points, and the interaction between latent heat flux and surface winds. Finally, we evaluate air-sea feedback mechanisms, focusing on how small-scale extreme precipitation events influence the ocean’s mixed layer.

Conclusion & Results

We compared SR-ESMs, focusing on model development cycles 1-3 with data summarised in Table 3. Our assessment covered large-scale ocean and atmosphere circulation, the atmospheric boundary layer profiles on selected grid points, latent heat flux sensitivity to surface wind, intra-seasonal variability, tropical cyclones, and ocean mixed layer feedback. The main results are listed as follows:

1. The SR-ESMs reproduce general features of the ocean circulation, the sea surface temperature distribution and the sea-ice cover reasonably well, but with biases that are often similar to coarse resolution GCMs. During the development cycles, we diagnosed improvement in ICON’s SST distribution and the Atlantic Meridional Overturning Circulation and in the seasonal cycle of Southern Hemisphere sea-ice concentration in IFS-FESOM. The evaluation of mixed layer depth (MLD) shows that in Cycle 3 of ICON, MLD biases decrease near the equator but increase in the northern tropical Atlantic compared to Cycle 2. In high-resolution Cycle 3 of FESOM, MLD biases decrease near the equator but increase in the North Brazil Current region.

2. We find that tropical precipitation biases persist in SRGCMs. First, tropical precipitation amounts are systematically overestimated in tropical rainbands, which appears closely related to biases in surface enthalpy fluxes. Second, the zonally averaged distribution is shifted southward, which is in line with biases found in the cross-equatorial atmospheric energy flux. Finally, the double-ITCZ bias is identified as unimproved w.r.t. standard GCMs, which we find reflected in an anomalous Hadley circulation.

3. The MJO is better simulated in cycle 3 of IFS model, especially the version run at higher resolution, in simulating MJO, and equatorial Kelvin and Rossby waves, which are too weak in the ICON model. The 30-year length of some simulations in cycle 2 allows a better estimation of the spectral content than the 5-year length of cycle 3 simulations.

4. Higher-resolution simulations in cycles 2 and 3 better match observed tropical cyclone frequency, with ICON showing less sensitivity to resolution. IFS outperforms ICON in representing central pressure and wind speed relationships. Both IFS (2.5 km and 4.4 km) and ICON (5 km) simulate 24-hour intensification rates effectively.

5. Both ICON and IFS models represent the main characteristics of the vertical structure of the atmospheric boundary layer under trade-cumulus conditions in the region east of Barbados. This comprises a variety of grid resolutions and physical parameterizations considered in the simulations. Both models show greater sensitivity to parameterization than for grid resolution changes, which is promising for certain grid independence in SRMs. In the ICON model, the Smagorinsky turbulence model led to a better representation of the winds compared to using the total turbulence energy scheme, which was designed for coarser-resolution applications and overestimated the wind speed.

6. Latent heat flux is overestimated in both the IFS and the ICON models. The overestimation can be attributed to the absence of weak surface latent heat flux during calm conditions. It is also influenced by the significant sensitivity of surface latent heat flux to changes in surface wind speed, especially during strong wind conditions.

7. In the tropical Atlantic, sea surface salinity (SSS) distributions from cycle 2 and cycle 3 runs show good agreement with the satellite-derived distributions. However, particularly during the boreal summer period, zonal bands of low SSS consistently appear in the tropical Atlantic ITCZ indicating too localized precipitation patterns.

8. Precipitation events exceeding 20 mm d−1 can shallow the mixed layer depth, leading to accelerated ocean currents. This phenomenon results from the production of lower-salinity water during precipitation, which reduces density and sharpens density gradients, impeding vertical mixing and allowing momentum to be trapped in a shallow layer.