Investigating the drivers of midlatitude circulation biases in climate reanalysis ensembles
The projected response of the atmospheric circulation to radiative changes driven by increasing greenhouse gas concentrations is highly uncertain. One of the primary reasons for this is that the state-of-the-art models we employ to investigate these responses struggle to represent basic features of...
| Main Author: | |
|---|---|
| Format: | Conference Object |
| Language: | unknown |
| Published: |
2019
|
| Subjects: | |
| Online Access: | https://zenodo.org/record/3249049 https://doi.org/10.5281/zenodo.3249049 |
| Summary: | The projected response of the atmospheric circulation to radiative changes driven by increasing greenhouse gas concentrations is highly uncertain. One of the primary reasons for this is that the state-of-the-art models we employ to investigate these responses struggle to represent basic features of the midlatitude circulation such as storm tracks, jets and blocking. Biases also have detrimental effects on predictive skill for dynamically driven fields at climate prediction time scales of seasons to decades. Despite this, physical understanding of the controls on these features and the drivers of their biases is still limited. The present study investigates a hierarchy of large ensemble climate reanalysis and hindcast simulations performed using the Norwegian Earth System Model (NorESM). Each ensemble is 30 members and was run from 1985-2010 and monthly means calculated. For the reanalysis runs various data-assimilation strategies were employed. These are SST only (V0), SST plus hydrographic profiles (V1), SST plus hydrographic profiles plus sea-ice concentration (V2). The assimilation was performed monthly, after which the model runs freely. This choice likely has implications for the evolution of the biases in both the SSTs and atmospheric circulation. To investigate this, and attempt to elucidate drivers, we include analyses from a one-year simulation with daily to hourly output. The data-assimilated runs are compared to both free runs and AMIP-style simulations with ERA-Interim serving as ground truth. We evaluate the North Pacific and North Atlantic jets in winter and summer. We also identify where the observations lie within the predictive distribution of the ensemble. Results show that the North Atlantic jet is too zonal, extends too far into Europe and is shifted northwards. Virtually the entire North Atlantic sector lies outside the predictive distribution of the ensemble and performance actually degrades in the simulations with tighter constraints on the assimilation. By contrast the North Pacific jet ... |
|---|