A critical assessment of the long term changes in the wintertime surface Arctic Oscillation and Northern Hemisphere storminess in the ERA20C reanalysis

This study investigates the robustness of the long-term changes in the wintertime surface Arctic Oscillation (AO) in the ERA20C reanalysis. A statistically significant trend in the AO is found in ERA20C over the period 1900-2010. These long-term changes in the AO are not found in two other observational datasets. The long term change in the AO in ERA20C is associated with statistically significant negative trend (approximately -6hPa per century) in mean-sea level pressure (MSLP) over the Northern Hemisphere (NH) polar regions. This is not seen in the HADSLP2 observational dataset, suggesting that the trends in the ERA20C AO index may be spurious. The spurious long term changes in MSLP and the AO index in ERA20C result in a strengthening of the meridional MSLP gradient in ERA20C. The strengthening of the meridional MSLP gradient is consistent with increases in wintertime storminess in Northern Europe and the NH high latitudes

The sensitivity of Euro-Atlantic regimes to model horizontal resolution

There is growing evidence that the atmospheric dynamics of the Euro-Atlantic sector during winter is driven in part by the presence of quasi-persistent regimes. However, general circulation models typically struggle to simulate these with, for example, an overly weakly persistent blocking regime. Previous studies have showed that increased horizontal resolution can improve the regime structure of a model but have so far only considered a single model with only one ensemble member at each resolution, leaving open the possibility that this may be either coincidental or model dependent. We show that the improvement in regime structure due to increased resolution is robust across multiple models with multiple ensemble members. However, while the high-resolution models have notably more tightly clustered data, other aspects of the regimes may not necessarily improve and are also subject to a large amount of sampling variability that typically requires at least three ensemble members to surmount

On the treatment of soil water stress in GCM simulations of vegetation physiology

Current land surface schemes in weather and climate models make use of the so-called coupled photosynthesis–stomatal conductance (A–gs) models of plant function to determine the surface fluxes that govern the terrestrial energy, water and carbon budgets. Plant physiology is controlled by many environmental factors, and a number of complex feedbacks are involved, but soil moisture control on root water uptake is primary, particularly in sub-tropical to temperate ecosystems. Land surface models (LSMs) represent plant water stress in different ways, but most implement a water stress factor, beta, which ranges linearly (more recently also curvilinearly) between beta =1 for unstressed vegetation and beta = 0 at the wilting point, expressed in terms of volumetric water content ("θ" ). beta is most commonly used to either limit A or gs, and hence carbon and water fluxes, and a pertinent research question is whether these treatments are in fact interchangeable. Following Egea et al. (2011) and Verhoef and Egea (2014), we have implemented new beta treatments, reflecting higher levels of biophysical complexity in a state-of-the-art LSM, JULES, by allowing root zone soil moisture to limit plant function non-linearly and via individual routes (carbon assimilation, stomatal conductance, or mesophyll conductance) as well as any (non-linear) combinations thereof. The treatment of beta does matter to the prediction of water and carbon fluxes: this study demonstrates that it represents a key structural uncertainty in contemporary LSMs, in terms of predictions of GPP, energy fluxes and soil moisture evolution, both in terms of climate means and response to a number of European droughts, including the 2003 heat wave. Treatments allowing beta to act on vegetation fluxes via stomatal and mesophyll routes are able to simulate the spatiotemporal variability in water use efficiency with higher fidelity during the growing season; they also support a broader range of ecosystem responses, e.g. those observed in regions that are radiation limited or water limited. We conclude that current practice in weather and climate modelling is inconsistent, as well as too simplistic, failing to credibly simulate vegetation response to soil water stress across the typical range of variability that is encountered for current European weather and climate conditions, including extremes of land surface temperature and soil moisture drought. A generalized approach performs better in current climate conditions and promises to be, based on responses to recently observed extremes, more trustworthy for predicting the impacts of climate change

Mitigating Climate Biases in the Midlatitude North Atlantic by Increasing Model Resolution: SST Gradients and Their Relation to Blocking and the Jet

Starting to resolve the oceanic mesoscale in climate models is a step change in model fidelity. This study examines how certain obstinate biases in the midlatitude North Atlantic respond to increasing resolution (from 18 to 0.258 in the ocean) and how such biases in sea surface temperature (SST) affect the atmosphere. Using a multimodel ensemble of historical climate simulations run at different horizontal resolutions, it is shown that a severe cold SST bias in the central North Atlantic, common to many ocean models, is significantly reduced with increasing resolution. The associated bias in the time-mean meridional SST gradient is shown to relate to a positive bias in low-level baroclinicity, while the cold SST bias causes biases also in static stability and diabatic heating in the interior of the atmosphere. The changes in baroclinicity and diabatic heating brought by increasing resolution lead to improvements in European blocking and eddy-driven jet variability. Across the multimodel ensemble a clear relationship is found between the climatological meridional SST gradients in the broader Gulf Stream Extension area and two aspects of the atmospheric circulation: the frequency of high-latitude blocking and the southern-jet regime. This relationship is thought to reflect the two-way interaction (with a positive feedback) between the respective oceanic and atmospheric anomalies. These North Atlantic SST anomalies are shown to be important in forcing significant responses in the midlatitude atmospheric circulation, including jet variability and the storm track. Further increases in oceanic and atmospheric resolution are expected to lead to additional improvements in the representation of Euro-Atlantic climate

Northern Hemisphere blocking simulation in current climate models: evaluating progress from the Climate Model Intercomparison Project Phase 5 to 6 and sensitivity to resolution

Global climate models (GCMs) are known to suffer from biases in the simulation of atmospheric blocking, and this study provides an assessment of how blocking is represented by the latest generation of GCMs. It is evaluated (i) how historical CMIP6 (Climate Model Intercomparison Project Phase 6) simulations perform compared to CMIP5 simulations and (ii) how horizontal model resolution affects the simulation of blocking in the CMIP6-HighResMIP (PRIMAVERA – PRocess-based climate sIMulation: AdVances in high-resolution modelling and European climate Risk Assessment) model ensemble, which is designed to address this type of question. Two blocking indices are used to evaluate the simulated mean blocking frequency and blocking persistence for the Euro-Atlantic and Pacific regions in winter and summer against the corresponding estimates from atmospheric reanalysis data. There is robust evidence that CMIP6 models simulate blocking frequency and persistence better than CMIP5 models in the Atlantic and Pacific and during winter and summer. This improvement is sizeable so that, for example, winter blocking frequency in the median CMIP5 model in a large Euro-Atlantic domain is underestimated by 33 % using the absolute geopotential height (AGP) blocking index, whereas the same number is 18 % for the median CMIP6 model. As for the sensitivity of simulated blocking to resolution, it is found that the resolution increase, from typically 100 to 20 km grid spacing, in most of the PRIMAVERA models, which are not re-tuned at the higher resolutions, benefits the mean blocking frequency in the Atlantic in winter and summer and in the Pacific in summer. Simulated blocking persistence, however, is not seen to improve with resolution. Our results are consistent with previous studies suggesting that resolution is one of a number of interacting factors necessary for an adequate simulation of blocking in GCMs. The improvements reported in this study hold promise for further reductions in blocking biases as model development continues

Mean and extreme precipitation over European river basins better simulated in a 25km AGCM

Limited spatial resolution is one of the factors that may hamper applications of global climate models (GCMs), in particular over Europe with its complex coastline and orography. In this study, the representation of European mean and extreme precipitation is evaluated in simulations with an atmospheric GCM (AGCM) at different resolutions between about 135 and 25km grid spacing in the mid-latitudes. The continent-wide root-mean-square error in mean precipitation in the 25km model is about 25% smaller than in the 135km model in winter. Clear improvements are also seen in autumn and spring, whereas the model's sensitivity to resolution is very small in summer. Extreme precipitation is evaluated by estimating generalised extreme value distributions (GEVs) of daily precipitation aggregated over river basins whose surface area is greater than 50000km2. GEV location and scale parameters are measures of the typical magnitude and of the interannual variability of extremes, respectively. Median model biases in both these parameters are around 10% in summer and around 20% in the other seasons. For some river basins, however, these biases can be much larger and take values between 50% and 100%. Extreme precipitation is better simulated in the 25km model, especially during autumn when the median GEV parameter biases are more than halved, and in the North European Plains, from the Loire in the west to the Vistula in the east. A sensitivity experiment is conducted showing that these resolution sensitivities in both mean and extreme precipitation are in many areas primarily due to the increase in resolution of the model orography. The findings of this study illustrate the improved capability of a global high-resolution model in simulating European mean and extreme precipitation