Investigating the predictability of North Atlantic sea surface height

Interannual sea surface height (SSH) forecasts are subject to several sources of uncertainty. Methods relying on statistical forecasts have proven useful in assessing predictability and associated uncertainty due to both initial conditions and boundary conditions. In this study, the interannual predictability of SSH dynamics in the North Atlantic is investigated using the output from a 150 year long control simulation based on HadGEM3, a coupled climate model at eddy-permitting resolution. Linear inverse modeling (LIM) is used to create a statistical model for the evolution of monthly-mean SSH anomalies. The forecasts based on the LIM model demonstrate skill on interannanual timescales O (1–2 years). Forecast skill is found to be largest in both the subtropical and subpolar gyres, with decreased skill in the Gulf Stream extension region. The SSH initial conditions involving a tripolar anomaly off Cape Hatteras lead to a maximum growth in SSH about 20 months later. At this time, there is a meridional shift in the 0 m-SSH contour on the order of 0.5∘ – 1.5∘ -latitude, coupled with a change in SSH along the US East Coast. To complement the LIM-based study, interannual SSH predictability is also quantified using the system’s average predictability time (APT). The APT analysis extracted large-scale SSH patterns which displayed predictability on timescales longer than 2 years. These patterns are responsible for changes in SSH on the order of 10 cm along the US East Coast, driven by variations in Ekman velocity. Our results shed light on the timescales of SSH predictability in the North Atlantic. In addition, the diagnosed optimal initial conditions and predictable patterns could improve interannual forecasts of the Gulf Stream’s characteristics and coastal SSH

The low-resolution version of HadGEM3 GC3.1: development and evaluation for global climate

A new climate model, HadGEM3 N96ORCA1, is presented that is part of the GC3.1 configuration of HadGEM3. N96ORCA1 has a horizontal resolution of ~135 km in the atmosphere and 1° in the ocean and requires an order of magnitude less computing power than its medium-resolution counterpart, N216ORCA025, while retaining a high degree of performance traceability. Scientific performance is compared both to observations and the N216ORCA025 model. N96ORCA1 reproduces observed climate mean and variability almost as well as N216ORCA025. Patterns of biases are similar across the two models. In the north-west Atlantic, N96ORCA1 shows a cold surface bias of up to 6K, typical of ocean models of this resolution. The strength of the Atlantic meridional overturning circulation (16 to 17 Sv) matches observations. In the Southern Ocean, a warm surface bias (up to 2K) is smaller than in N216ORCA025 and linked to improved ocean circulation. Model El Niño/Southern Oscillation and Atlantic Multidecadal Variability are close to observations. Both the cold bias in the Northern hemisphere (N96ORCA1) and the warm bias in the Southern hemisphere (N216ORCA025) develop in the first few decades of the simulations. As in many comparable climate models, simulated interhemispheric gradients of top-of-atmosphere radiation are larger than observations suggest, with contributions from both hemispheres. HadGEM3 GC3.1 N96ORCA1 constitutes the physical core of the UK Earth System Model (UKESM1) and will be used extensively in the Coupled Model Intercomparison Project 6 (CMIP6), both as part of UKESM1 and as a stand-alone coupled climate model

Coupled versus uncoupled hindcast simulations of the Madden-Julian oscillation in the Year of Tropical Convection

This study investigates the impact of a full interactive ocean on daily initialised 15 day hindcasts of the Madden-Julian oscillation (MJO), measured against a Met Office Unified Model (MetUM) atmosphere control simulation (AGCM) during a 3 month period of the Year of Tropical Convection (YOTC). Results indicated that the coupled configuration (CGCM) extends MJO predictability over that of the AGCM, by up to 3-5 days. Propagation is improved in the CGCM, which we partly attribute to a more realistic phase relationship between sea surface temperature (SST) and convection. In addition, the CGCM demonstrates skill in representing downwelling oceanic Kelvin and Rossby waves which warm SSTs along their trajectory, with the potential to feed back on the atmosphere. These results imply that an ocean model capable of simulating internal ocean waves may be required to capture the full effect of air-sea coupling for the MJO

The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations

We describe Global Atmosphere 6.0 and Global Land 6.0: the latest science configurations of the Met Office Unified Model and JULES land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model’s physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe Global Atmosphere 6.1 and Global Land 6.1, which include a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global NWP, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year

Heat balance in the Nordic Seas in a global 1/12° coupled model

The Nordic Seas are a gateway to the Arctic Ocean, where Atlantic water undergoes a strong cooling during its transit. Here we investigate the heat balance of these regions in the high resolution Met Office Global Coupled Model GC3 with a 1/12_ grid. The GC3 model reproduces resolution Met Office Global Coupled Model GC3 with a 1/12_ grid. The GC3 model reproduces the contrasted ice conditions and ocean heat loss between the eastern and western regions of the Nordic Seas. In the west (Greenland and Iceland seas), the heat loss experienced by the ocean is stronger than the atmospheric heat gain, because of the cooling by ice melt. The latter is a major contribution to the heat loss over the path of the East Greenland Current and west of Svalbard. In the model, surface fluxes balance the convergence of heat in each of the eastern and western regions. The net east-west heat exchange, integrated from Fram Strait to Iceland, is relatively small: the westward heat transport of the Return Atlantic Current over Knipovich Ridge balances the eastward heat transport by the East Icelandic Current. Time fluctuations, including eddies, are a significant contribution to the net heat transports. The eddy flux represents about 20% of the total heat transport in Denmark Strait and across Knipovich Ridge. The coupled ocean-atmosphere-ice model may overestimate the heat imported from the Atlantic and exported to the Arctic by 10 or 15%. This confirms the tendency toward higher northward heat transports as model resolution is refined, which will impact scenarios of future climate

Dynamical downscaling of unforced interannual sea-level variability in the North-West European shelf seas

Variability of Sea-Surface Height (SSH) from ocean dynamic processes is an important component of sea-level change. In this study we dynamically downscale a present-day control simulation of a climate model to replicate sea-level variability in the Northwest European shelf seas. The simulation can reproduce many characteristics of sea-level variability exhibited in tide gauge and satellite altimeter observations. We examine the roles of lateral ocean boundary conditions and surface atmospheric forcings in determining the sea-level variability in the model interior using sensitivity experiments. Variability in the oceanic boundary conditions leads to uniform sea-level variations across the shelf. Atmospheric variability leads to spatial SSH variability with a greater mean amplitude. We separate the SSH variability into a uniform loading term (change in shelf volume with no change in distribution), and a spatial redistribution term (with no volume change). The shelf loading variance accounted for 80% of the shelf mean total variance, but this drops to ~ 60% around Scotland and in the southeast North Sea. We analyse our modelled variability to provide a useful context to coastal planners and managers. Our 200-year simulation allows the distribution of the unforced trends (over 4–21 year) of sea-level changes to be quantified. We found that the 95th percentile change over a 4-year period can lead to coastal sea-level changes of ~ 58 mm, which must be considered when using smooth sea level projections. We also found that simulated coastal SSH variations have long correlation length-scales, suggesting that observations of interannual sea-level variability from tide gauges are typically representative of > 200 km of the adjacent coast. This helps guide the use of tide gauge variability estimates.Physical and Space Geodes