Regional changes in wind energy potential over Europe using regional climate model ensemble projections

The impact of climate change on wind power generation potentials over Europe is investigated by considering ensemble projections from two regional climate models (RCMs) driven by a global climate model (GCM). Wind energy density and its interannual variability are estimated based on hourly near-surface wind speeds. Additionally, the possible impact of climatic changes on the energy output of a sample 2.5-MW turbine is discussed. GCM-driven RCM simulations capture the behavior and variability of current wind energy indices, even though some differences exist when compared with reanalysis-driven RCM simulations. Toward the end of the twenty-first century, projections show significant changes of energy density on annual average across Europe that are substantially stronger in seasonal terms. The emergence time of these changes varies from region to region and season to season, but some long-term trends are already statistically significant in the middle of the twenty-first century. Over northern and central Europe, the wind energy potential is projected to increase, particularly in winter and autumn. In contrast, energy potential over southern Europe may experience a decrease in all seasons except for the Aegean Sea. Changes for wind energy output follow the same patterns but are of smaller magnitude. The GCM/RCM model chains project a significant intensification of both interannual and intra-annual variability of energy density over parts of western and central Europe, thus imposing new challenges to a reliable pan-European energy supply in future decades.

Climate determinism revisited: multiple equilibria in a complex climate model

Multiple equilibria in a coupled ocean–atmosphere–sea ice general circulation model (GCM) of an aquaplanet with many degrees of freedom are studied. Three different stable states are found for exactly the same set of parameters and external forcings: a cold state in which a polar sea ice cap extends into the midlatitudes; a warm state, which is ice free; and a completely sea ice–covered “snowball” state. Although low-order energy balance models of the climate are known to exhibit intransitivity (i.e., more than one climate state for a given set of governing equations), the results reported here are the first to demonstrate that this is a property of a complex coupled climate model with a consistent set of equations representing the 3D dynamics of the ocean and atmosphere. The coupled model notably includes atmospheric synoptic systems, large-scale circulation of the ocean, a fully active hydrological cycle, sea ice, and a seasonal cycle. There are no flux adjustments, with the system being solely forced by incoming solar radiation at the top of the atmosphere. It is demonstrated that the multiple equilibria owe their existence to the presence of meridional structure in ocean heat transport: namely, a large heat transport out of the tropics and a relatively weak high-latitude transport. The associated large midlatitude convergence of ocean heat transport leads to a preferred latitude at which the sea ice edge can rest. The mechanism operates in two very different ocean circulation regimes, suggesting that the stabilization of the large ice cap could be a robust feature of the climate system. Finally, the role of ocean heat convergence in permitting multiple equilibria is further explored in simpler models: an atmospheric GCM coupled to a slab mixed layer ocean and an energy balance model

Optimising the FAMOUS climate model: inclusion of global carbon cycling

FAMOUS fills an important role in the hierarchy of climate models, both explicitly resolving atmospheric and oceanic dynamics yet being sufficiently computationally efficient that either very long simulations or large ensembles are possible. An improved set of carbon cycle parameters for this model has been found using a perturbed physics ensemble technique. This is an important step towards building the "Earth System" modelling capability of FAMOUS, which is a reduced resolution, and hence faster running, version of the Hadley Centre Climate model, HadCM3. Two separate 100 member perturbed parameter ensembles were performed; one for the land surface and one for the ocean. The land surface scheme was tested against present-day and past representations of vegetation and the ocean ensemble was tested against observations of nitrate. An advantage of using a relatively fast climate model is that a large number of simulations can be run and hence the model parameter space (a large source of climate model uncertainty) can be more thoroughly sampled. This has the associated benefit of being able to assess the sensitivity of model results to changes in each parameter. The climatologies of surface and tropospheric air temperature and precipitation are improved relative to previous versions of FAMOUS. The improved representation of upper atmosphere temperatures is driven by improved ozone concentrations near the tropopause and better upper level winds.

Wave activity in the tropical tropopause layer in seven reanalysis and four chemistry climate model data sets

Sub-seasonal variability including equatorial waves significantly influence the dehydration and transport processes in the tropical tropopause layer (TTL). This study investigates the wave activity in the TTL in 7 reanalysis data sets (RAs; NCEP1, NCEP2, ERA40, ERA-Interim, JRA25, MERRA, and CFSR) and 4 chemistry climate models (CCMs; CCSRNIES, CMAM, MRI, and WACCM) using the zonal wave number-frequency spectral analysis method with equatorially symmetric-antisymmetric decomposition. Analyses are made for temperature and horizontal winds at 100 hPa in the RAs and CCMs and for outgoing longwave radiation (OLR), which is a proxy for convective activity that generates tropopause-level disturbances, in satellite data and the CCMs. Particular focus is placed on equatorial Kelvin waves, mixed Rossby-gravity (MRG) waves, and the Madden-Julian Oscillation (MJO). The wave activity is defined as the variance, i.e., the power spectral density integrated in a particular zonal wave number-frequency region. It is found that the TTL wave activities show significant difference among the RAs, ranging from ∼0.7 (for NCEP1 and NCEP2) to ∼1.4 (for ERA-Interim, MERRA, and CFSR) with respect to the averages from the RAs. The TTL activities in the CCMs lie generally within the range of those in the RAs, with a few exceptions. However, the spectral features in OLR for all the CCMs are very different from those in the observations, and the OLR wave activities are too low for CCSRNIES, CMAM, and MRI. It is concluded that the broad range of wave activity found in the different RAs decreases our confidence in their validity and in particular their value for validation of CCM performance in the TTL, thereby limiting our quantitative understanding of the dehydration and transport processes in the TTL.

Atmospheric blocking in a high resolution climate model: influences of mean state, orography and eddy forcing

An underestimate of atmospheric blocking occurrence is a well-known limitation of many climate models. This article presents an analysis of Northern Hemisphere winter blocking in an atmospheric model with increased horizontal resolution. European blocking frequency increases with model resolution, and this results from an improvement in the atmospheric patterns of variability as well as a simple improvement in the mean state. There is some evidence that the transient eddy momentum forcing of European blocks is increased at high resolution, which could account for this. However, it is also shown that the increase in resolution of the orography is needed to realise the improvement in blocking, consistent with the increase in height of the Rocky Mountains acting to increase the tilt of the Atlantic jet stream and giving higher mean geopotential heights over northern Europe. Blocking frequencies in the Pacific sector are also increased with atmospheric resolution, but in this case the improvement in orography actually leads to a decrease in blocking

The ocean's gravitational potential energy budget in a coupled climate model

This study examines, in a unified fashion, the budgets of ocean gravitational potential energy (GPE) and available gravitational potential energy (AGPE) in the control simulation of the coupled atmosphere–ocean general circulation model HadCM3. Only AGPE can be converted into kinetic energy by adiabatic processes. Diapycnal mixing supplies GPE, but not AGPE, whereas the reverse is true of the combined effect of surface buoyancy forcing and convection. Mixing and buoyancy forcing, thus, play complementary roles in sustaining the large scale circulation. However, the largest globally integrated source of GPE is resolved advection (+0.57 TW) and the largest sink is through parameterized eddy transports (-0.82 TW). The effect of these adiabatic processes on AGPE is identical to their effect on GPE, except for perturbations to both budgets due to numerical leakage exacerbated by non-linearities in the equation of state.

FAMOUS, faster: using parallel computing techniques to accelerate the FAMOUS/HadCM3 climate model with a focus on the radiative transfer algorithm

We have optimised the atmospheric radiation algorithm of the FAMOUS climate model on several hardware platforms. The optimisation involved translating the Fortran code to C and restructuring the algorithm around the computation of a single air column. Instead of the existing MPI-based domain decomposition, we used a task queue and a thread pool to schedule the computation of individual columns on the available processors. Finally, four air columns are packed together in a single data structure and computed simultaneously using Single Instruction Multiple Data operations. The modified algorithm runs more than 50 times faster on the CELL’s Synergistic Processing Elements than on its main PowerPC processing element. On Intel-compatible processors, the new radiation code runs 4 times faster. On the tested graphics processor, using OpenCL, we find a speed-up of more than 2.5 times as compared to the original code on the main CPU. Because the radiation code takes more than 60% of the total CPU time, FAMOUS executes more than twice as fast. Our version of the algorithm returns bit-wise identical results, which demonstrates the robustness of our approach. We estimate that this project required around two and a half man-years of work.

Observations of the eruption of the Sarychev volcano and simulations using the HadGEM2 climate model

In June 2009 the Sarychev volcano located in the Kuril Islands to the northeast of Japan erupted explosively, injecting ash and an estimated 1.2 ± 0.2 Tg of sulfur dioxide into the upper troposphere and lower stratosphere, making it arguably one of the 10 largest stratospheric injections in the last 50 years. During the period immediately after the eruption, we show that the sulfur dioxide (SO2) cloud was clearly detected by retrievals developed for the Infrared Atmospheric Sounding Interferometer (IASI) satellite instrument and that the resultant stratospheric sulfate aerosol was detected by the Optical Spectrograph and Infrared Imaging System (OSIRIS) limb sounder and CALIPSO lidar. Additional surface‐based instrumentation allows assessment of the impact of the eruption on the stratospheric aerosol optical depth. We use a nudged version of the HadGEM2 climate model to investigate how well this state‐of‐the‐science climate model can replicate the distributions of SO2 and sulfate aerosol. The model simulations and OSIRIS measurements suggest that in the Northern Hemisphere the stratospheric aerosol optical depth was enhanced by around a factor of 3 (0.01 at 550 nm), with resultant impacts upon the radiation budget. The simulations indicate that, in the Northern Hemisphere for July 2009, the magnitude of the mean radiative impact from the volcanic aerosols is more than 60% of the direct radiative forcing of all anthropogenic aerosols put together. While the cooling induced by the eruption will likely not be detectable in the observational record, the combination of modeling and measurements would provide an ideal framework for simulating future larger volcanic eruptions.

Parameterization of contrails in the UK Met Office Climate Model

Persistent contrails are believed to currently have a relatively small but significant positive radiative forcing on climate. With air travel predicted to continue its rapid growth over the coming years, the contrail warming effect on climate is expected to increase. Nevertheless, there remains a high level of uncertainty in the current estimates of contrail radiative forcing. Contrail formation depends mostly on the aircraft flying in cold and moist enough air masses. Most studies to date have relied on simple parameterizations using averaged meteorological conditions. In this paper we take into account the short‐term variability in background cloudiness by developing an on‐line contrail parameterization for the UK Met Office climate model. With this parameterization, we estimate that for the air traffic of year 2002 the global mean annual linear contrail coverage was approximately 0.11%. Assuming a global mean contrail optical depth of 0.2 or smaller and assuming hexagonal ice crystals, the corresponding contrail radiative forcing was calculated to be less than 10 mW m−2 in all‐sky conditions. We find that the natural cloud masking effect on contrails may be significantly higher than previously believed. This new result is explained by the fact that contrails seem to preferentially form in cloudy conditions, which ameliorates their overall climate impact by approximately 40%.

The sensitivity of the tropical circulation and Maritime Continent precipitation to climate model resolution

The dependence of the annual mean tropical precipitation on horizontal resolution is investigated in the atmospheric version of the Hadley Centre General Environment Model (HadGEM1). Reducing the grid spacing from about 350 km to 110 km improves the precipitation distribution in most of the tropics. In particular, characteristic dry biases over South and Southeast Asia including the Maritime Continent as well as wet biases over the western tropical oceans are reduced. The annual-mean precipitation bias is reduced by about one third over the Maritime Continent and the neighbouring ocean basins associated with it via the Walker circulation. Sensitivity experiments show that much of the improvement with resolution in the Maritime Continent region is due to the specification of better resolved surface boundary conditions (land fraction, soil and vegetation parameters) at the higher resolution. It is shown that in particular the formulation of the coastal tiling scheme may cause resolution sensitivity of the mean simulated climate. The improvement in the tropical mean precipitation in this region is not primarily associated with the better representation of orography at the higher resolution, nor with changes in the eddy transport of moisture. Sizeable sensitivity to changes in the surface fields may be one of the reasons for the large variation of the mean tropical precipitation distribution seen across climate models.

Communicating probabilistic information from climate model ensembles—lessons from numerical weather prediction

Climate model ensembles are widely heralded for their potential to quantify uncertainties and generate probabilistic climate projections. However, such technical improvements to modeling science will do little to deliver on their ultimate promise of improving climate policymaking and adaptation unless the insights they generate can be effectively communicated to decision makers. While some of these communicative challenges are unique to climate ensembles, others are common to hydrometeorological modeling more generally, and to the tensions arising between the imperatives for saliency, robustness, and richness in risk communication. The paper reviews emerging approaches to visualizing and communicating climate ensembles and compares them to the more established and thoroughly evaluated communication methods used in the numerical weather prediction domains of day-to-day weather forecasting (in particular probabilities of precipitation), hurricane and flood warning, and seasonal forecasting. This comparative analysis informs recommendations on best practice for climate modelers, as well as prompting some further thoughts on key research challenges to improve the future communication of climate change uncertainties.

Climate model benchmarking with glacial and mid-Holocene climates

Past climates provide a test of models’ ability to predict climate change. We present a comprehensive evaluation of state-of-the-art models against Last Glacial Maximum and mid-Holocene climates, using reconstructions of land and ocean climates and simulations from the Palaeoclimate Modelling and Coupled Modelling Intercomparison Projects. Newer models do not perform better than earlier versions despite higher resolution and complexity. Differences in climate sensitivity only weakly account for differences in model performance. In the glacial, models consistently underestimate land cooling (especially in winter) and overestimate ocean surface cooling (especially in the tropics). In the mid-Holocene, models generally underestimate the precipitation increase in the northern monsoon regions, and overestimate summer warming in central Eurasia. Models generally capture large-scale gradients of climate change but have more limited ability to reproduce spatial patterns. Despite these common biases, some models perform better than others.

Assimilation of sea-ice concentration in a global climate model — physical and statistical aspects

We investigate the initialization of Northern-hemisphere sea ice in the global climate model ECHAM5/MPI-OM by assimilating sea-ice concentration data. The analysis updates for concentration are given by Newtonian relaxation, and we discuss different ways of specifying the analysis updates for mean thickness. Because the conservation of mean ice thickness or actual ice thickness in the analysis updates leads to poor assimilation performance, we introduce a proportional dependence between concentration and mean thickness analysis updates. Assimilation with these proportional mean-thickness analysis updates significantly reduces assimilation error both in identical-twin experiments and when assimilating sea-ice observations, reducing the concentration error by a factor of four to six, and the thickness error by a factor of two. To understand the physical aspects of assimilation errors, we construct a simple prognostic model of the sea-ice thermodynamics, and analyse its response to the assimilation. We find that the strong dependence of thermodynamic ice growth on ice concentration necessitates an adjustment of mean ice thickness in the analysis update. To understand the statistical aspects of assimilation errors, we study the model background error covariance between ice concentration and ice thickness. We find that the spatial structure of covariances is best represented by the proportional mean-thickness analysis updates. Both physical and statistical evidence supports the experimental finding that proportional mean-thickness updates are superior to the other two methods considered and enable us to assimilate sea ice in a global climate model using simple Newtonian relaxation.