Helene T. Hewitt

Identifying uncertainties in Arctic climate change projections

Wide ranging climate changes are expected in the Arctic by the end of the 21st century, but projections of the size of these changes vary widely across current global climate models. This variation represents a large source of uncertainty in our understanding of the evolution of Arctic climate. Here we systematically quantify and assess the model uncertainty in Arctic climate changes in two CO2 doubling experiments: a multimodel ensemble (CMIP3) and an ensemble constructed using a single model (HadCM3) with multiple parameter perturbations (THC-QUMP). These two ensembles allow us to assess the contribution that both structural and parameter variations across models make to the total uncertainty and to begin to attribute sources of uncertainty in projected changes. We find that parameter uncertainty is an major source of uncertainty in certain aspects of Arctic climate. But also that uncertainties in the mean climate state in the 20th century, most notably in the northward Atlantic ocean heat transport and Arctic sea ice volume, are a significant source of uncertainty for projections of future Arctic change. We suggest that better observational constraints on these quantities will lead to significant improvements in the precision of projections of future Arctic climate change.

Assessing the forecast skill of Arctic sea ice extent in the GloSea4 seasonal prediction system

AbstractAn assessment of the ability of the Met Office seasonal prediction system, GloSea4, to accurately forecast Arctic sea ice concentration and extent over seasonal time scales is presented. GloSea4 was upgraded in November 2010 to include the initialization of the observed sea ice concentration from satellite measurements. GloSea4 is one of only a few operational seasonal prediction systems to include both the initialization of observed sea ice followed by its prognostic determination in a coupled dynamical model of sea ice. For the forecast of the September monthly mean ice extent the best skill in GloSea4, as judged from the historical forecast period of 1996–2009, is when the system is initialized in late March and early April near to the sea ice maxima with correlation skills in the range of 0.6. In contrast, correlation skills using May initialization dates are much lower due to thinning of the sea ice at the start of the melt season which allows ice to melt too rapidly. This is likely to be due both to a systematic bias in the ice-ocean forced model as well as biases in the ice analysis system. Detailing the forecast correlation skill throughout the whole year shows that for our system, the correlation skill for ice extent at five to six months lead time is highest leading up to the September minimum (from March/April start dates) and leading up to the March maximum (from October/November start dates). Conversely, little skill is found for the shoulder seasons of November and May at any lead time.

A review of recent developments in climate change science. Part I: Understanding of future change in the large-scale climate system:

This article reviews some of the major lines of recent scientific progress relevant to the choice of global climate policy targets, focusing on changes in understanding since publication of the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4). Developments are highlighted in the following major climate system components: ice sheets; sea ice; the Atlantic Meridional Overturning Circulation; tropical forests; and accelerated carbon release from permafrost and ocean hydrates. The most significant developments in each component are identified by synthesizing input from multiple experts from each field. Overall, while large uncertainties remain in all fields, some substantial progress in understanding is revealed.

Impact of ocean resolution on coupled air-sea fluxes and large-scale climate

Air-sea fluxes are a crucial component in the energetics of the global climate system. The largest air-sea fluxes occur in regions of high sea surface temperature variability, such as ocean boundary, frontal currents and eddies. In this paper we explore the importance of ocean model resolution to resolve air-sea flux relationships in these areas. We examine the SST-wind stress relationship in high-pass filtered observations and two versions of the Met Office climate model with eddy-permitting and eddy-resolving ocean resolution. Eddy-resolving resolution shows marginal improvement in the relationship over eddy-permitting resolution. However, by focussing on the North Atlantic we show that the eddy-resolving model has significant enhancement of latent heat loss over the North Atlantic Current region, a long-standing model bias. While eddy-resolving resolution does not change the air-sea flux relationship at small scale, the impact on the mean state has important implications for the reliability of future climate projections.

The CO5 configuration of the 7 km Atlantic Margin Model: large-scale biases and sensitivity to forcing, physics options and vertical resolution

We describe the physical model component of the standard Coastal Ocean version 5 configuration (CO5) of the European North West Shelf (NWS). CO5 was developed jointly between the Met Office and the National Oceanography Centre. CO5 is designed with the seamless approach in mind, which allows for modeling of multiple timescales for a variety of applications from short-range ocean forecasting through to climate projections. The configuration constitutes the basis of the latest update 5 to the ocean and data assimilation components of the Met Office’s operational Forecast Ocean Assimilation Model (FOAM) for the NWS. A 30.5 year non-assimilating control hindcast of CO5 was integrated from January 1981 to June 2012. Sensitivity simulations were conducted with reference to the control run. The control run is compared against a previous non-assimilating Proudman Oceanographic Laboratory Coastal Ocean Modelling System (POLCOMS) hindcast of the NWS. The CO5 control hindcast is shown to have much reduced biases compared to POLCOMS. Emphasis in the system description is weighted to 10 updates in CO5 over previous versions. Updates include an increase in vertical resolution, a new vertical coordinate stretching function, the replacement of climatological riverine sources with the pan-European hydrological model E-HYPE, a new Baltic boundary condition and switching from directly imposed atmospheric model boundary fluxes to calculating the fluxes within the model using bulk formula. Sensitivity tests of the updates are detailed with a view to attributing observed changes in the new system from the previous system and suggesting future directions of research to further improve the system. 15

A seamless approach to understanding and predicting Arctic sea ice in Met Office modelling systems

Recent CMIP5 models predict large losses of summer Arctic sea ice, with only mitigation scenarios showing sustainable summer ice. Sea ice is inherently part of the climate system, and heat fluxes affecting sea ice can be small residuals of much larger air–sea fluxes. We discuss analysis of energy budgets in the Met Office climate models which point to the importance of early summer processes (such as clouds and meltponds) in determining both the seasonal cycle and the trend in ice decline. We give examples from Met Office modelling systems to illustrate how the seamless use of models for forecasting on time scales from short range to decadal might help to unlock the drivers of high latitude biases in climate models.

Critical Southern Ocean climate model biases traced to atmospheric model cloud errors

The Southern Ocean is a pivotal component of the global climate system yet it is poorly represented in climate models, with significant biases in upper-ocean temperatures, clouds and winds. Combining Atmospheric and Coupled Model Inter-comparison Project (AMIP5/CMIP5) simulations, with observations and equilibrium heat budget theory, we show that across the CMIP5 ensemble variations in sea surface temperature biases in the 40–60°S Southern Ocean are primarily caused by AMIP5 atmospheric model net surface flux bias variations, linked to cloud-related short-wave errors. Equilibration of the biases involves local coupled sea surface temperature bias feedbacks onto the surface heat flux components. In combination with wind feedbacks, these biases adversely modify upper-ocean thermal structure. Most AMIP5 atmospheric models that exhibit small net heat flux biases appear to achieve this through compensating errors. We demonstrate that targeted developments to cloud-related parameterisations provide a route to better represent the Southern Ocean in climate models and projections.The Southern Ocean is critically important for global climate yet poorly represented by climate models. Here the authors trace sea surface temperature biases in this region to cloud-related errors in atmospheric-model simulated surface heat fluxes and provide a pathway to improve the models.

The benefits of global high-resolution for climate simulation: process-understanding and the enabling of stakeholder decisions at the regional scale.

Capsule summary:A perspective on current and future capabilities in global high-resolution climate simulation for assessing climate risks over next few decades, including advances in process representation and analysis, justifying the emergence of dedicated, coordinated experimental protocols.

A mechanism for lack of sea ice reversibility in the Southern Ocean

We find evidence that ocean processes during global warming may result in irreversible changes to the Antarctic sea ice, whereas the Arctic sea ice changes appear to be reversible. Increased forcing gives rise to strong heat uptake in the Southern Ocean, and existing pathways provide an increased transport of heat to the Weddell Sea. As atmospheric concentrations of CO2 are returned to preindustrial levels, the Antarctic ice extent at first recovers, but a rapid change in the position of the an ocean front in the South Atlantic maintains the heat transport into the Weddell Sea. A cooling surface initiates deep convection, accessing the stored heat, resulting in a substantial loss of sea ice, which has not recovered after a further 150 years at preindustrial CO2.