Imminent ocean acidification in the Arctic projected with the NCAR global coupled carbon cycle-climate model

Ocean acidification from the uptake of anthropogenic carbon is simulated for the industrial period and IPCC SRES emission scenarios A2 and B1 with a global coupled carbon cycle-climate model. Earlier studies identified seawater saturation state with respect to aragonite, a mineral phase of calcium carbonate, as a key variable governing impacts on corals and other shell-forming organisms. Globally in the A2 scenario, water saturated by more than 300%, considered suitable for coral growth, vanishes by 2070 AD (CO2≈630 ppm), and the ocean volume fraction occupied by saturated water decreases from 42% to 25% over this century. The largest simulated pH changes worldwide occur in Arctic surface waters, where hydrogen ion concentration increases by up to 185% (ΔpH=−0.45). Projected climate change amplifies the decrease in Arctic surface mean saturation and pH by more than 20%, mainly due to freshening and increased carbon uptake in response to sea ice retreat. Modeled saturation compares well with observation-based estimates along an Arctic transect and simulated changes have been corrected for remaining model-data differences in this region. Aragonite undersaturation in Arctic surface waters is projected to occur locally within a decade and to become more widespread as atmospheric CO2 continues to grow. The results imply that surface waters in the Arctic Ocean will become corrosive to aragonite, with potentially large implications for the marine ecosystem, if anthropogenic carbon emissions are not reduced and atmospheric CO2 not kept below 450 ppm.

Circulation dynamics and its influence on European and Mediterranean January-April climate over the past half millennium: results and insights from instrumental data, documentary evidence and coupled climate models

We use long instrumental temperature series together with available field reconstructions of sea-level pressure (SLP) and three-dimensional climate model simulations to analyze relations between temperature anomalies and atmospheric circulation patterns over much of Europe and the Mediterranean for the late winter/early spring (January–April, JFMA) season. A Canonical Correlation Analysis (CCA) investigates interannual to interdecadal covariability between a new gridded SLP field reconstruction and seven long instrumental temperature series covering the past 250 years. We then present and discuss prominent atmospheric circulation patterns related to anomalous warm and cold JFMA conditions within different European areas spanning the period 1760–2007. Next, using a data assimilation technique, we link gridded SLP data with a climate model (EC-Bilt-Clio) for a better dynamical understanding of the relationship between large scale circulation and European climate. We thus present an alternative approach to reconstruct climate for the pre-instrumental period based on the assimilated model simulations. Furthermore, we present an independent method to extend the dynamic circulation analysis for anomalously cold European JFMA conditions back to the sixteenth century. To this end, we use documentary records that are spatially representative for the long instrumental records and derive, through modern analogs, large-scale SLP, surface temperature and precipitation fields. The skill of the analog method is tested in the virtual world of two three-dimensional climate simulations (ECHO-G and HadCM3). This endeavor offers new possibilities to both constrain climate model into a reconstruction mode (through the assimilation approach) and to better asses documentary data in a quantitative way.

Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models

Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP) and export production (EP) of particulate organic carbon (POC). Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR) are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation). Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006) with stronger stratification (higher sea surface temperature; SST) being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL) also reproduces the inverse relationship between stratification (SST) and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

The coupled atmosphere–chemistry–ocean model SOCOL-MPIOM

The newly developed atmosphere–ocean-chemistry-climate model SOCOL-MPIOM is presented by demonstrating the influence of the interactive chemistry module on the climate state and the variability. Therefore, we compare pre-industrial control simulations with (CHEM) and without (NOCHEM) interactive chemistry. In general, the influence of the chemistry on the mean state and the variability is small and mainly restricted to the stratosphere and mesosphere. The largest differences are found for the atmospheric dynamics in the polar regions, with slightly stronger northern and southern winter polar vortices in CHEM. The strengthening of the vortex is related to larger stratospheric temperature gradients, which are attributed to a parametrization of the absorption of ozone and oxygen in the Lyman-alpha, Schumann–Runge, Hartley, and Higgins bands. This effect is parametrized in the version with interactive chemistry only. A second reason for the temperature differences between CHEM and NOCHEM is related to diurnal variations in the ozone concentrations in the higher atmosphere, which are missing in NOCHEM. Furthermore, stratospheric water vapour concentrations differ substantially between the two experiments, but their effect on the temperatures is small. In both setups, the simulated intensity and variability of the northern polar vortex is inside the range of present day observations. Sudden stratospheric warming events are well reproduced in terms of their frequency, but the distribution amongst the winter months is too uniform. Additionally, the performance of SOCOL-MPIOM under changing external forcings is assessed for the period 1600–2000 using an ensemble of simulations driven by a spectral solar forcing reconstruction. The amplitude of the reconstruction is large in comparison to other state-of-the-art reconstructions, providing an upper limit for the importance of the solar signal. In the pre-industrial period (1600–1850) the simulated surface temperature trends are in reasonable agreement with temperature reconstructions, although the multi-decadal variability is more pronounced. This enhanced variability can be attributed to the variability in the solar forcing. The simulated temperature reductions during the Maunder Minimum are in the lowest probability range of the proxy records. During the Dalton Minimum, when also volcanic forcing is an important driver of temperature variations, the agreement is better. In the industrial period from 1850 onward SOCOL-MPIOM overestimates the temperature increase in comparison to observational data sets. Sensitivity simulations show that this overestimation can be attributed to the increasing trend in the solar forcing reconstruction that is used in this study and an additional warming induced by the simulated ozone changes.

Enhanced Atlantic subpolar gyre variability through baroclinic threshold in a coarse resolution model

Direct observations, satellite measurements and paleo records reveal strong variability in the Atlantic subpolar gyre on various time scales. Here we show that variations of comparable amplitude can only be simulated in a coupled climate model in the proximity of a dynamical threshold. The threshold and the associated dynamic response is due to a positive feedback involving increased salt transport in the subpolar gyre and enhanced deep convection in its centre. A series of sensitivity experiments is performed with a coarse resolution ocean general circulation model coupled to a statistical-dynamical atmosphere model which in itself does not produce atmospheric variability. To simulate the impact of atmospheric variability, the model system is perturbed with freshwater forcing of varying, but small amplitude and multi-decadal to centennial periodicities and observational variations in wind stress. While both freshwater and wind-stress-forcing have a small direct effect on the strength of the subpolar gyre, the magnitude of the gyre's response is strongly increased in the vicinity of the threshold. Our results indicate that baroclinic self-amplification in the North Atlantic ocean can play an important role in presently observed SPG variability and thereby North Atlantic climate variability on multi-decadal scales.

Tropopause level Rossby wave breaking in the Northern Hemisphere: a feature-based validation of the ECHAM5-HAM climate model

Breaking synoptic-scale Rossby waves (RWB) at the tropopause level are central to the daily weather evolution in the extratropics and the subtropics. RWB leads to pronounced meridional transport of heat, moisture, momentum, and chemical constituents. RWB events are manifest as elongated and narrow structures in the tropopause-level potential vorticity (PV) field. A feature-based validation approach is used to assess the representation of Northern Hemisphere RWB in present-day climate simulations carried out with the ECHAM5-HAM climate model at three different resolutions (T42L19, T63L31, and T106L31) against the ERA-40 reanalysis data set. An objective identification algorithm extracts RWB events from the isentropic PV field and allows quantifying the frequency of occurrence of RWB. The biases in the frequency of RWB are then compared to biases in the time mean tropopause-level jet wind speeds. The ECHAM5-HAM model captures the location of the RWB frequency maxima in the Northern Hemisphere at all three resolutions. However, at coarse resolution (T42L19) the overall frequency of RWB, i.e. the frequency averaged over all seasons and the entire hemisphere, is underestimated by 28%.The higher-resolution simulations capture the overall frequency of RWB much better, with a minor difference between T63L31 and T106L31 (frequency errors of −3.5 and 6%, respectively). The number of large-size RWB events is significantly underestimated by the T42L19 experiment and well represented in the T106L31 simulation. On the local scale, however, significant differences to ERA-40 are found in the higher-resolution simulations. These differences are regionally confined and vary with the season. The most striking difference between T106L31 and ERA-40 is that ECHAM5-HAM overestimates the frequency of RWB in the subtropical Atlantic in all seasons except for spring. This bias maximum is accompanied by an equatorward extension of the subtropical westerlies.

Reanalysis-driven climate simulation over CORDEX North America domain using the Canadian Regional Climate Model, version 5: model performance evaluation

The performance of reanalysis-driven Canadian Regional Climate Model, version 5 (CRCM5) in reproducing the present climate over the North American COordinated Regional climate Downscaling EXperiment domain for the 1989–2008 period has been assessed in comparison with several observation-based datasets. The model reproduces satisfactorily the near-surface temperature and precipitation characteristics over most part of North America. Coastal and mountainous zones remain problematic: a cold bias (2–6 °C) prevails over Rocky Mountains in summertime and all year-round over Mexico; winter precipitation in mountainous coastal regions is overestimated. The precipitation patterns related to the North American Monsoon are well reproduced, except on its northern limit. The spatial and temporal structure of the Great Plains Low-Level Jet is well reproduced by the model; however, the night-time precipitation maximum in the jet area is underestimated. The performance of CRCM5 was assessed against earlier CRCM versions and other RCMs. CRCM5 is shown to have been substantially improved compared to CRCM3 and CRCM4 in terms of seasonal mean statistics, and to be comparable to other modern RCMs.

Is the Atlantic subpolar gyre bistable in comprehensive coupled climate models?

The Atlantic subpolar gyre (SPG) is one of the main drivers of decadal climate variability in the North Atlantic. Here we analyze its dynamics in pre-industrial control simulations of 19 different comprehensive coupled climate models. The analysis is based on a recently proposed description of the SPG dynamics that found the circulation to be potentially bistable due to a positive feedback mechanism including salt transport and enhanced deep convection in the SPG center. We employ a statistical method to identify multiple equilibria in time series that are subject to strong noise and analyze composite fields to assess whether the bistability results from the hypothesized feedback mechanism. Because noise dominates the time series in most models, multiple circulation modes can unambiguously be detected in only six models. Four of these six models confirm that the intensification is caused by the positive feedback mechanism.