ENSO Amplitude Asymmetry in Met Office Hadley Centre Climate Models

Long climate simulations with the Met Office Hadley Centre General Circulation Model show weak El Niño-Southern Oscillation (ENSO) amplitude asymmetry between El Niño and La Niña phases compared with observations. This lack of asymmetry is explored through the framework of a perturbed parameter experiment. Two key hypotheses for the lack of asymmetry are tested. First, the possibility that westerly wind burst activity is biased is explored. It is found that the observed difference in wind burst activity during El Niño and La Niña tends to be underestimated by the model. Secondly, the warming due to subsurface non-linear advection is examined. While the model exhibits non-linear dynamic warming during both La Niña and El Niño, and thus a contribution to ENSO asymmetry, it is shown to be consistently underestimated in comparison with ocean reanalyses. The non-linear zonal advection term contributes most to the deficiency and the simulation of the anomalous zonal currents may be playing a key role in its underestimation. Compared with the ocean reanalyses, the anomalous zonal currents associated with ENSO are too weak in the vicinity of the equatorial undercurrent and the surface wind driven zonal currents extend too deep.

Combining Argo and Satellite Data Using Model-Derived Covariances: Blue Maps

Blue Maps aims to exploit the versatility of an ensemble data assimilation system to deliver gridded estimates of ocean temperature, salinity, and sea-level with the accuracy of an observation-based product. Weekly maps of ocean properties are produced on a 1/10°, near-global grid by combining Argo profiles and satellite observations using ensemble optimal interpolation (EnOI). EnOI is traditionally applied to ocean models for ocean forecasting or reanalysis, and usually uses an ensemble comprised of anomalies for only one spatiotemporal scale (e.g., mesoscale). Here, we implement EnOI using an ensemble that includes anomalies for multiple space- and time-scales: mesoscale, intraseasonal, seasonal, and interannual. The system produces high-quality analyses that produce mis-fits to observations that compare well to other observation-based products and ocean reanalyses. The accuracy of Blue Maps analyses is assessed by comparing background fields and analyses to observations, before and after each analysis is calculated. Blue Maps produces analyses of sea-level with accuracy of about 4 cm; and analyses of upper-ocean (deep) temperature and salinity with accuracy of about 0.45 (0.15) degrees and 0.1 (0.015) practical salinity units, respectively. We show that the system benefits from a diversity of ensemble members with multiple scales, with different types of ensemble members weighted accordingly in different dynamical regions.

The Importance of Central Pacific Meridional Heat Advection to the Development of ENSO

The relationship between the Warm Water Volume (WWV) ENSO precursor and ENSO SST weakened substantially after ~2000, coinciding with a degradation in dynamical model ENSO prediction skill. It is important to understand the drivers of the equatorial thermocline temperature variations and their linkage to ENSO onsets. In this study, a set of ocean reanalyses is employed to assess factors responsible for the variation of the equatorial Pacific Ocean thermocline during 1982-2019. Off-equatorial thermocline temperature anomalies carried equatorward by the mean meridional currents associated with Pacific Tropical Cells are shown to play an important role in modulating the central equatorial thermocline variations, which is rarely discussed in the literature. Further, ENSO events are delineated into two groups based on precursor mechanisms: the western equatorial type (WEP) ENSO, when the central equatorial thermocline is mainly influenced by the zonal propagation of anomalies from the western Pacific, and the off-equatorial central Pacific (OCP) ENSO, when off-equatorial central thermocline anomalies play the primary role. WWV is found to precede all WEP ENSO by 6-9 months, while the correlation is substantially lower for OCP ENSO events. In contrast, the central tropical Pacific (CTP) precursor, which includes off-equatorial thermocline signals, has a very robust lead correlation with the OCP ENSO. Most OCP ENSO events are found to follow the same ENSO conditions, and the number of OCP ENSO increases substantially since the 21st century. These results highlight the importance of monitoring off-equatorial subsurface preconditions for ENSO prediction and to understand multi-year ENSO.

Antarctic sea ice in global ocean reanalyses

<p>Ocean reanalyses (ORAs) are used extensively in polar research, hence their realism should be assessed regularly. Here the ORAs performance in the Antarctic region is analyzed with specific emphasis on sea ice concentration and thickness. We used four global ocean-sea ice products: C-GLORSv7, FOAM-GLOSEA5v13, GLORYS2v4, and ORAS5, and their ensemble mean GREP (provided by CMEMS) within the 1993 to 2018 period. All ORAs use the NEMO ocean model in a global eddy-permitting configuration (1/4° horizontal resolution and 75 vertical levels) and are forced by the ECMWF ERA-Interim atmospheric reanalysis.</p><p>Here we examine the ability of ORAs to reproduce sea ice properties in the Southern Ocean taking into account regional characteristics and sea ice types. Seasonal and interannual variability of sea ice concentration (SIC) and sea ice thickness (SIT) is examined in the hemispheric domain and in five sub-regions for three different sea ice classes: pack ice (SIC ≥ 80%), marginal ice zone (MIZ) (15% ≤ SIC < 80%), and sparse ice (0 < SIC <15%).  Modeled sea ice properties are compared to a set of satellite products: NSIDC CDR, Ifremer/CERSAT, and EUMETSAT OSI-SAF for SIC and Envisat and CryoSat-2 for SIT, together with PIOMAS and GIOMAS reanalyses. We revealed shortcomings of reanalysis systems to be improved in the future representation of Antarctic sea ice. Additionally, we focused on the assessment of the GREP ensemble mean product. We found that for certain metrics GREP minimizes the single errors and outperforms individual members. The evidence from this study implies that GREP can be a feasible product for a number of applications.</p>

Overturning Variations in the Subpolar North Atlantic in an Ocean Reanalyses Ensemble

<p>The ocean’s Atlantic Meridional Overturning Circulation (AMOC) has a significant influence on global climate through its meridional transport of heat and carbon. Deep water formation occurring in the subpolar North Atlantic is an essential component the AMOC. Understanding the nature and causes of its multidecadal variation at these high latitudes is critical to more accurately predict future changes. We analyse the subpolar overturning in an ensemble of eddy permitting ¼ degree global ocean reanalyses, restrained by observations and historical forcings, over the period 1993-2018. This overturning transport is validated against the continuous measurements obtained along the Overturning in the Subpolar North Atlantic Program (OSNAP) mooring array since 2014. The ability of each reanalysis to capture the observed changes in the overturning will be determined, providing confidence in their ability to simulate changes prior to the availability of OSNAP, and exposing their limitations. We analyse the eastern and western sections of the OSNAP array to determine the relative importance of the overturning along these sections and the temporal variability on various timescales. This research complements a previous study investigating changes in the subtropical Atlantic overturning using the same reanalyses ensemble which was shown to provide a good approximation to observations.</p>

Year-round impact of winter sea ice thickness observations on seasonal forecasts

Nowadays many seasonal forecasting centres provide dynamical predictions of sea ice. While initializing sea ice by assimilating sea ice concentration (SIC) is common, constraining initial conditions of sea ice thickness (SIT) is only in its early stages. Here, we make use of the availability of Arctic-wide winter SIT observations covering 2011–2016 to constrain SIT in the ECMWF (European Centre for Medium-Range Weather Forecasts) ocean–sea-ice analysis system with the aim of improving the initial conditions of the coupled forecasts. The impact of the improved initialization on the predictive skill of pan-Arctic sea ice for lead times of up to 7 months is investigated in a low-resolution analogue of the currently operational ECMWF seasonal forecasting system SEAS5. By using winter SIT information merged from CS2 and SMOS (CS2SMOS: CryoSat-2 Soil Moisture and Ocean Salinity), substantial changes in sea ice volume and thickness are found in the ocean–sea-ice analysis, including damping of the overly strong seasonal cycle of sea ice volume. Compared with the reference experiment, which does not use SIT information, forecasts initialized using SIT data show a reduction of the excess sea ice bias and an overall reduction of seasonal sea ice area forecast errors of up to 5 % at lead months 2 to 5. Change in biases is the main forecast impact. Using the integrated ice edge error (IIEE) metric, we find significant improvement of up to 28 % in the September sea ice edge forecast started in April. However, sea ice forecasts for September started in spring still exhibit a positive sea ice bias, which points to a melting that is too slow in the forecast model. A slight degradation in skill is found in the early freezing season sea ice forecasts initialized in July and August, which is related to degraded initial conditions during these months. Both ocean reanalyses, with and without SIT constraint, show strong melting in the middle of the melt season compared to the forecasts. This excessive melting related to positive net surface radiation biases in the atmospheric flux forcing of the ocean reanalyses remains and consequently degrades analysed summer SIC. The impact of thickness initialization is also visible in the sea surface and near-surface temperature forecasts. While positive forecast impact is seen in near-surface temperature forecasts of early freezing season (September–October–November) initialized in May (when the sea ice initial conditions have been observationally constrained in the preceding winter months), negative impact is seen for the same season when initialized in the month of August when the sea ice initial conditions are degraded. We conclude that the strong thinning by CS2SMOS initialization mitigates or enhances seasonally dependent forecast model errors in sea ice and near-surface temperatures in all seasons. The results indicate that the memory of SIT in the spring initial conditions lasts into autumn, influencing forecasts of the peak summer melt and early freezing seasons. Our results demonstrate the usefulness of new sea ice observational products in both data assimilation and forecasting systems, and they strongly suggest that better initialization of SIT is crucial for improving seasonal sea ice forecasts.

Year-round Impact of Winter Sea Ice Thickness Observations on Seasonal Forecasts

Nowadays many seasonal forecasting centres provide dynamical predictions of sea ice. While initializing sea ice by assimilating sea ice concentration (SIC) is common, constraining initial conditions of sea ice thickness (SIT) is only at its early stages. Here, we make use of the availability of Arctic-wide winter SIT observations covering 2011–2016 to constrain SIT in the ECMWF (European Centre for Medium-Range Weather Forecasts) ocean–sea-ice analysis system with the aim of improving the initial conditions of the coupled forecasts. The impact of the improved initialization on the predictive skill of Arctic sea ice for lead times of up to 7 months is investigated in a low-resolution analogue of the currently operational ECMWF seasonal forecasting system SEAS5. By using winter SIT information merged from CS2 and SMOS (CS2SMOS: CryoSat2 Soil Moisture and Ocean Salinity), substantial changes of sea ice volume and thickness are found in the ocean–sea-ice analysis, including damping of the overly strong seasonal cycle of sea ice volume. Compared with the reference experiment, which does not use SIT information, forecasts initialized using SIT data show a reduction of the excess sea ice bias and an overall reduction of seasonal sea ice area forecast errors of up to 5 % at lead months 2 to 5. Using the Integrated Ice Edge Error (IIEE) metric, we find significant improvement of up to 28 % in the September sea ice edge forecast started from April. However, sea ice forecasts for September started in spring still exhibit a positive sea ice bias, which points to too slow melting in the forecast model. A slight degradation in skill is found in the early freezing season sea ice forecasts initialized in July and August, which is related to degraded initial conditions during these months. Both the ocean reanalyses, with and without SIT constraint, show strong melting in the middle of the melt season compared to the forecasts. This excessive melting related to positive net surface radiation biases in the atmospheric flux forcing of the ocean reanalyses remains and consequently degrades analysed summer SIC. The impact of thickness initialization is also visible in the sea surface and near-surface temperature forecasts. While positive forecast impact is seen in near-surface temperature forecasts of early freezing season initialized in May (when the sea ice initial conditions have been observationally constrained in the preceding winter months), negative impact is seen for the same season when initialised in August month when the sea ice initial conditions are degraded. We conclude that the strong thinning by CS2SMOS initialization mitigates or enhances seasonally dependent forecast model errors in sea ice and near-surface temperatures in all seasons. The results indicate that the memory of SIT in the spring initial conditions last into autumn, influencing forecasts of the peak summer melt and early freezing seasons. Our results demonstrate the usefulness of new sea ice observational products in both data assimilation and forecasting systems, and strongly suggest that better initialization of SIT is crucial for improving seasonal sea ice forecasts.

The mean state and variability of the North Atlantic circulation: a perspective from ocean reanalyses

<p>The observational network around the North Atlantic has improved significantly over the last few decades with the advent of Argo and satellite observations, and the more recent efforts to monitor the Atlantic Meridional Overturning Circulation (AMOC) using arrays such as RAPID and OSNAP. These have shown decadal timescale changes across the North Atlantic including in heat content, heat transport and the circulation. </p><p>However there are still significant gaps in the observational coverage, and significant uncertainties around some observational products. Ocean reanalyses integrate the observations with a dynamically consistent ocean model and are potentially tools that can be used to understand the observed changes. However the suitability of the reanalyses for the task must also be assessed.<br>We use an ensemble of global ocean reanalyses in comparison with observations in order to examine the mean state and interannual-decadal variability of the North Atlantic ocean since 1993. We assess how well the reanalyses are able to capture different processes and whether any understanding can be inferred. In particular we look at ocean heat content, transports, the AMOC and gyre strengths, water masses and convection. </p><p> </p>

Depth and properties of freshwater export from the Greenland Ice Sheet modulated by ice-ocean processes

<p>Freshwater export from the Greenland Ice Sheet to the surrounding ocean has increased by 50% since the early 1990s, and may triple over the coming century under high greenhouse gas emissions. This increasing freshwater has the potential to influence both the regional and large-scale ocean, including marine ecosystems. Yet quantification of these impacts remains uncertain in part due to poor characterization of freshwater export, and in particular the transformation of freshwater around the ice sheet margin by ice-ocean processes, such as submarine melting, plumes and fjord circulation. Here, we combine in-situ observations, ocean reanalyses and simple models for ice-ocean processes to estimate the depth and properties of freshwater export around the full Greenland ice sheet from 1991 to present. The results show significant regional variability driven primarily by the depth at which freshwater runoff leaves the ice sheet. Areas with deeply-grounded marine-terminating glaciers are likely to export freshwater to the ocean as a dilute mixture of freshwater and externally-sourced deep water masses, while freshwater from areas with many land-terminating glaciers is exported as a more concentrated mixture of freshwater and near-surface waters. A handful of large glacier-fjord systems dominate ice sheet freshwater export, and the vast majority of freshwater export occurs subsurface. Our results provide an ice sheet-wide first-order characterization of how ice-ocean processes modulate Greenland freshwater export, and are an important step towards accurate representation of Greenland freshwater in large-scale ocean models.</p>