.. _ifs_fesom_model_historical_projection:

Historical and Projection Simulations
#####################################

The IFS-FESOM historical and projection experiment consists of two simulations.
The historical simulation that covers 1990-2014 and the projection that covers 2015-2049 (SSP3-7.0), in total 60 years.
The projection is a direct continuation of the historical simulation.
Both the atmosphere and ocean used a horizontal grid resolution of 5km.

+----------+------------------------------------+--------------+-------------+--------------------------------------------------+-----------------------------------+
| Model    | Spatial Resolution                 | Time         | Realization | Experiment ID                                    | DestinE Data Lake (bridge site)   |
+==========+====================================+==============+=============+==================================================+===================================+
| IFS-FESOM| 5km atmosphere; 5km ocean          |   1990-2014  | 1           |  climatedt-gen2-ifs-fesom-baseline-hist-5km-r1   | LUMI data bridge                  |
+----------+------------------------------------+--------------+-------------+--------------------------------------------------+-----------------------------------+
| IFS-FESOM| 5km atmosphere; 5km ocean          |   2015-2049  | 1           |climatedt-gen2-ifs-fesom-projections-ssp370-5km-r1| LUMI data bridge                  |
+----------+------------------------------------+--------------+-------------+--------------------------------------------------+-----------------------------------+

For evaluation of these simulations, see :ref:`evaluation_ifs_fesom`.

.. A comprehensive evaluation of the main model biases is provided by the performance index metric in :numref:`ifs-fesom_hist_pi`, covering a large selection of variables and regions. Performance is evaluated against the mean of the CMIP6 models, with values below 1 (blueish) indicating superior performance and values above 1 (reddish) indicating inferior performance. For most variables and regions IFS-FESOM shows exceptional performance, with values typically below 0.2. The dynamical atmospheric variables show the best performance, while net surface radiation, surface temperature and sea ice concentration present relatively weaker — though still good — scores.

.. .. figure:: ../../../../evaluation/general_evaluation/figures/climate_metrics.performance_indices.climatedt-o25.1.IFS-FESOM.historical-1990.r1.png
..     :name: ifs-fesom_hist_pi

..     Performance Index table for the IFS-FESOM historical simulation. Performance values refer to the mean of CMIP6 models, with values below 1 indicating improved performance and values above 1 indicating degraded performance.

.. Global mean temperatures (:numref:`ifs-fesom_hist_proj_gregory`, left panel) over the historical period track ERA5 closely, with a small mean-state cold bias of ~0.25 °C. The future projection depicts an acceleration of the historical warming trend. Simulated values of top-of-atmosphere net radiation (:numref:`ifs-fesom_hist_proj_gregory`, middle panel) are within the range of observed values. The Gregory plot (:numref:`ifs-fesom_hist_proj_gregory`, right panel) shows that the simulation stays largely within the observed ranges, with a potential overestimation of the response to Pinatubo in the years following the eruption (i.e. 1991).

.. .. figure:: ../../../../evaluation/mn5/figures/IFS-FESOM-Historical_SSP370_Tco2559_timeseries_Gregory_absoluteT-IFS_FESOM.png
..     :name: ifs-fesom_hist_proj_gregory

..     Left\: Time series of the globally averaged annual surface air temperature in ERA5 and the historical and scenario IFS-FESOM simulations. Middle\: Time series of the net heat fluxes at the top of the atmosphere (TOA), including observations from CERES. Right\: Gregory plot of the combined IFS-FESOM simulations. The mean values and ranges of the observed TOA fluxes and global mean surface air temperatures are included for reference.

.. Spatial maps of mean-state biases in annual surface air temperature (:numref:`ifs-fesom_bias_tas`) show very small differences with respect to ERA5 over the three major ocean basins and most continental areas (global mean bias 0.14 K, RMSE 1.22 K). The global cold bias mostly arises from the Arctic region and the Weddell Sea, likely linked to errors in sea ice representation. IFS-FESOM successfully mitigates the warm biases in eastern boundary coastal upwelling regions (e.g., Humboldt and Benguela currents) that commonly afflict coarser CMIP6 models.

.. .. figure:: ../../../../evaluation/ifs_fesom_eval/figures/tas_annual_bias_combined_cropped.png
..     :name: ifs-fesom_bias_tas

..     Spatial maps of the climatological biases of annual surface air temperature in the IFS-FESOM historical simulation and the CMIP6 multi-model mean. Biases are computed against Berkeley Earth climatology over the period 1990–2014.

.. In terms of mean sea level pressure (:numref:`ifs-fesom_bias_psl`), IFS-FESOM performs well (global mean bias -1.59 Pa, RMSE ~101 Pa), comparable to the CMIP6 multi-model mean (RMSE ~87 Pa). The polar regions show positive biases, characteristic of cold high-latitude mean states that are dynamically consistent with excessive surface cooling and sea ice, highlighting the strongly coupled nature of tropical and polar mean-state errors.

.. .. figure:: ../../../../evaluation/ifs_fesom_eval/figures/psl_annual_bias_combined_cropped.png
..     :name: ifs-fesom_bias_psl

..     Spatial maps of the climatological biases of annual mean sea level pressure in the IFS-FESOM historical simulation and the CMIP6 multi-model mean. Biases are computed against ERA5 climatology over the period 1990–2014.

.. IFS-FESOM shows good performance in terms of the climatological annual precipitation rate (:numref:`ifs-fesom_hist_pr_bias`), sharing the broad spatial structure of the CMIP6 multi-model mean, with wet biases along the mid-latitude storm tracks and a dipole pattern in the tropical Pacific indicative of a double-ITCZ or ITCZ displacement error. The amplitude of the tropical biases in IFS-FESOM tends to be smaller than for most individual CMIP6 models.

.. .. figure:: ../../../../evaluation/ifs_fesom_eval/figures/pr_annual_bias_combined_cropped.png
..     :name: ifs-fesom_hist_pr_bias

..     Spatial maps of the climatological biases of annual precipitation in the IFS-FESOM historical simulation and the CMIP6 multi-model mean. Biases are computed against MSWEP climatology over the period 1990–2014.

.. The Earth energy imbalance time series (:numref:`ifs-fesom_eei`) shows that IFS-FESOM accurately captures the observed annual mean energy imbalance of approximately 0.5–1.0 W/m² post-2000, significantly outperforming the CMIP6 multi-model mean which exhibits a systematic positive bias of approximately 1.0 W/m² relative to CERES observations. IFS-FESOM successfully reproduces the large-amplitude seasonal cycle in net TOA radiation. A transient negative energy imbalance is evident in the early 1990s, reflecting the radiative response to the Mt. Pinatubo eruption.

.. .. figure:: ../../../../evaluation/ifs_fesom_eval/figures/radiation_imbalance_timeseries.png
..     :name: ifs-fesom_eei

..     Time series of the global-mean net top-of-atmosphere radiation (Earth's energy imbalance) from 1990 to 2014, comparing IFS-FESOM with CERES observations and the CMIP6 multi-model mean.

.. Sea ice extent (:numref:`ifs-fesom_sea_ice_extent`) is significantly overestimated in the Northern Hemisphere but shows a declining trend since the 1990s consistent with observed Arctic sea ice loss. In the Southern Hemisphere, IFS-FESOM exhibits anomalous decadal-scale variability with a pronounced dip and recovery, which may reflect an initialization adjustment of the Southern Ocean rather than a forced climate signal, following a different long-term evolution from observations.

.. .. figure:: ../../../../evaluation/ifs_fesom_eval/figures/sea_ice_extent_timeseries.png
..     :name: ifs-fesom_sea_ice_extent

..     Time series of monthly and annual-mean sea ice extent for the Northern and Southern Hemispheres, comparing IFS-FESOM against OSI-SAF satellite observations and a CMIP6 multi-model ensemble.

.. .. rubric:: Further evaluation

.. Additional evaluation plots for the IFS-FESOM simulations are available
.. in the `Climate DT Evaluation Charts <link>`_.


.. Sea ice volume (:numref:`ifs-fesom_sea_ice_volume`) is overestimated in the Northern Hemisphere by up to a factor of two compared to observation-constrained estimates. An unphysical increase during the 1990s fails to capture the observed steady downward trend, strongly suggesting a model spin-up issue or a severe adjustment to the coupled state rather than a physical response to historical forcing. In the Southern Hemisphere, IFS-FESOM severely underestimates sea ice volume.

.. .. figure:: ../../../../evaluation/ifs_fesom_eval/figures/sea_ice_volume_timeseries.png
..     :name: ifs-fesom_sea_ice_volume

..     Time series of Northern and Southern Hemisphere sea ice volume from 1990 to 2015, comparing IFS-FESOM against observation-constrained estimates (PIOMAS for the Arctic, GIOMAS for the Antarctic) and the CMIP6 multi-model mean.

.. The subsurface ocean temperature Hovmöller diagram (:numref:`ifs-fesom_ocean_hovmoller`) shows that IFS-FESOM rapidly develops persistent cold biases exceeding -1.0 °C in the upper 700 m relative to the EN4 observational state. A persistent subsurface warm bias layer between roughly 500 and 1000 m depth is also evident. The deep ocean (>2000 m) remains relatively stable.

.. .. figure:: ../../../../evaluation/ifs_fesom_eval/figures/en4_thetao_hovmoller_anomref_combined.png
..     :name: ifs-fesom_ocean_hovmoller

..     Time-depth Hovmöller diagram of global-mean ocean temperature anomalies relative to the initial EN4 observational state from 1990 to 2014 for IFS-FESOM and EN4.

.. Ocean temperature evolution by depth layer (:numref:`ifs-fesom_ocean_depth_layers`) shows that IFS-FESOM exhibits a strong initial cooling adjustment in the upper 700 m during the first 5–10 years, starting significantly warmer than EN4 observations and drifting cold — opposite to the observed warming trend of approximately 0.15 °C over 25 years. At intermediate depths (700–2000 m), IFS-FESOM is too warm, while in the deep ocean (>2000 m) it is too cold.

.. .. figure:: ../../../../evaluation/ifs_fesom_eval/figures/en4_thetao_depth_timeseries.png
..     :name: ifs-fesom_ocean_depth_layers

..     Volume-weighted mean ocean temperature time series for three depth layers (0–700 m, 700–2000 m, 2000 m–bottom) comparing IFS-FESOM against EN4 v4.2.2 observations from 1990 to 2014.

.. Future Climate Projections
.. ^^^^^^^^^^^^^^^^^^^^^^^^^^

.. To assess the projected climate changes from the IFS-FESOM simulations, a delta approach is adopted whereby anomalies are computed relative to the historical 1990–2014 climatology. This baseline period coincides with the historical simulation evaluated in the preceding sections, providing a consistent reference for quantifying change. The model's ability to reproduce observed recent changes is first evaluated by comparing the simulated 2015–2024 anomaly against ERA5 (for 2 m temperature and SST) and MSWEP (for precipitation), before examining the projected 2025–2049 anomaly to characterise the expected evolution of the climate signal.

.. The projected changes in annual mean 2 m temperature from IFS-FESOM (:numref:`ifs-fesom_proj_2t`) broadly reproduce the spatial pattern of recent observed warming derived from ERA5, with a predominance of positive anomalies relative to the 1990–2014 baseline across both land and ocean. However, IFS-FESOM underestimates the magnitude of the near-present warming signal, with a global mean anomaly of +0.34 K over 2015–2024 compared to +0.49 K in ERA5. The spatial structure is nonetheless well captured, with stronger warming over continental interiors and the Arctic consistent with observed patterns. In the period 2025–2049, IFS-FESOM projects a global mean warming of +1.06 K relative to the historical baseline, with a clear amplification of the signal particularly over land areas and the Arctic, consistent with polar amplification. Localised cooling anomalies emerge in the North Atlantic, which may reflect a weakening of the Atlantic meridional overturning circulation, a feature that is physically plausible under continued greenhouse gas forcing.

.. .. figure:: ../../../../evaluation/ifs_fesom_eval/figures/IFS-FESOM_bias_2D_2t_delta_proj_hist.png
..     :name: ifs-fesom_proj_2t

..     Spatial maps of the change in annual mean 2 m air temperature relative to the 1990–2014 climatology. The observed change (2015–2024) is shown from ERA5, alongside the corresponding IFS-FESOM simulated change for the same near-present period (2015–2024) and for a future period (2025–2049). Global mean changes (Δ\ :sub:`glb`) are indicated for each panel.

.. The projected changes in annual mean precipitation from IFS-FESOM (:numref:`ifs-fesom_proj_pr`) broadly follow the pattern of observed recent changes derived from MSWEP, both showing a modest global mean increase relative to the 1990–2014 baseline, though the model slightly underestimates the magnitude of the near-present signal (Δ\ :sub:`glb` of 9.46 × 10\ :sup:`-3` mm d\ :sup:`-1` in IFS-FESOM versus 1.41 × 10\ :sup:`-2` mm d\ :sup:`-1` in MSWEP over 2015–2024). Spatially, both the observed and simulated near-present anomalies are characterised by a wet-gets-wetter and dry-gets-drier pattern, with precipitation increases along the ITCZ and subtropical drying, though the model signal is somewhat weaker in amplitude. In the 2025–2049 period, IFS-FESOM projects an amplification of these tendencies, with a global mean increase of 4.15 × 10\ :sup:`-2` mm d\ :sup:`-1`, and a clearer emergence of regional contrasts including enhanced drying in the subtropics and increased precipitation in the deep tropics, consistent with the expected thermodynamic response to continued warming.

.. .. figure:: ../../../../evaluation/ifs_fesom_eval/figures/IFS-FESOM_bias_2D_pr_delta_proj_hist.png
..     :name: ifs-fesom_proj_pr

..     Spatial maps of the change in annual mean total precipitation relative to the 1990–2014 climatology. The observed change (2015–2024) is shown from MSWEP, alongside the corresponding IFS-FESOM simulated change for the same near-present period (2015–2024) and for a future period (2025–2049). Global mean changes (Δ\ :sub:`glb`) are indicated for each panel.

.. The projected changes in annual mean sea surface temperature from IFS-FESOM (:numref:`ifs-fesom_proj_sst`) show a spatial pattern broadly consistent with ERA5 observations over the recent period. IFS-FESOM captures the observed warming across most ocean basins, with a global mean SST anomaly of +0.25 K over 2015–2024 compared to +0.31 K in ERA5. In the 2025–2049 projection, the global mean SST warming reaches +0.76 K, with enhanced warming in the western boundary current regions and the Arctic. A pronounced North Atlantic cooling anomaly emerges in the subpolar gyre, consistent with a weakening of the AMOC. Localised cooling is also evident in parts of the Southern Ocean.

.. .. figure:: ../../../../evaluation/ifs_fesom_eval/figures/IFS-FESOM_bias_2D_sst_delta_proj_hist.png
..     :name: ifs-fesom_proj_sst

..     Spatial maps of the change in annual mean sea surface temperature relative to the 1990–2014 climatology. The observed change (2015–2024) is shown from ERA5, alongside the corresponding IFS-FESOM simulated change for the same near-present period (2015–2024) and for a future period (2025–2049). Global mean changes (Δ\ :sub:`glb`) are indicated for each panel.