Stable, steady climate states on an Earth-size planet with no continents are determined as a function of the tilt of the planet's rotation axis (obliquity) and stellar irradiance. Using a general ...circulation model of the atmosphere coupled to a slab ocean and a thermodynamic sea ice model, two states, the Aquaplanet and the Cryoplanet, are found for high and low stellar irradiance, respectively. In addition, four stable states with seasonally and perennially open water are discovered if comprehensively exploring a parameter space of obliquity from 0° to 90° and stellar irradiance from 70% to 135% of the present-day solar constant. Within 11% of today's solar irradiance, we find a rich structure of stable states that extends the area of habitability considerably. For the same set of parameters, different stable states result if simulations are initialized from an aquaplanet or a cryoplanet state. This demonstrates the possibility of multiple equilibria, hysteresis, and potentially rapid climate change in response to small changes in the orbital parameters. The dynamics of the atmosphere of an aquaplanet or a cryoplanet state is investigated for similar values of obliquity and stellar irradiance. The atmospheric circulation substantially differs in the two states owing to the relative strength of the primary drivers of the meridional transport of heat and momentum. At 90° obliquity and present-day solar constant, the atmospheric dynamics of an Aquaplanet state and one with an equatorial ice cover is analyzed.
The North Atlantic Oscillation (NAO) is the major source of variability in winter atmospheric circulation in the Northern Hemisphere, with large impacts on temperature, precipitation and storm ...tracks, and therefore also on strategic sectors such as insurance, renewable energy production, crop yields and water management. Recent developments in dynamical methods offer promise to improve seasonal NAO predictions, but assessing potential predictability on multi-annual timescales requires documentation of past low-frequency variability in the NAO. A recent bi-proxy NAO reconstruction spanning the past millennium suggested that long-lasting positive NAO conditions were established during medieval times, explaining the particularly warm conditions in Europe during this period; however, these conclusions are debated. Here, we present a yearly NAO reconstruction for the past millennium, based on an initial selection of 48 annually resolved proxy records distributed around the Atlantic Ocean and built through an ensemble of multivariate regressions. We validate the approach in six past-millennium climate simulations, and show that our reconstruction outperforms the bi-proxy index. The final reconstruction shows no persistent positive NAO during the medieval period, but suggests that positive phases were dominant during the thirteenth and fourteenth centuries. The reconstruction also reveals that a positive NAO emerges two years after strong volcanic eruptions, consistent with results obtained from models and satellite observations for the Mt Pinatubo eruption in the Philippines.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
Within the last Millennium, the transition between the Medieval Climate Anomaly (MCA; ca. 1000–1300CE) and the Little Ice Age (LIA; ca. 1400–1800CE) has been recorded in a global array of climatic ...and oceanographic proxies. In this study, we review proxy evidence for two alternative hypotheses for the effects of this shift in the North Atlantic region. One hypothesis postulates that the MCA/LIA transition included a weakening of the Atlantic Meridional Overturning Circulation (AMOC) and a transition to more negative North Atlantic Oscillation (NAO) conditions, resulting in a strong cooling of the North Atlantic region. The alternative hypothesis proposes a MCA/LIA shift to an increased number of storms over the North Atlantic linked to increased mid-latitude cyclogenesis and hence a pervasive positive NAO state. The two sets of proxy records and thus of the two competing hypotheses are then reconciled based on available results from climate model simulations of the last Millennium. While an increase in storm frequency implicates positive NAO, increased intensity would be consistent with negative NAO during the LIA. Such an increase in cyclone intensity could have resulted from the steepening of the meridional temperature gradient as the poles cooled more strongly than the Tropics from the MCA into the LIA.
A 50 kyr‐long exceptionally well‐dated and highly resolved stalagmite oxygen (δ18O) and carbon (δ13C) isotope record from Sofular Cave in northwestern Turkey helps to further improve the dating of ...Greenland Interstadials (GI) 1, and 3–12. Timing of most GI in the Sofular record is consistent within ±10 to 300 years with the “iconic” Hulu Cave record. Larger divergences (>500 years) between Sofular and Hulu are only observed for GI 4 and 7. The Sofular record differs from the most recent NGRIP chronology by up to several centuries, whereas age offsets do not increase systematically with depth. The Sofular record also reveals a rapid and sensitive climate and ecosystem response in the eastern Mediterranean to GI, whereas a phase lag of ∼100 years between climate and full ecosystem response is evident. Finally, results of spectral analyses of the Sofular isotope records do not support a 1,470‐year pacing of GI.
ERA5, the fifth‐generation reanalysis of the European Center for Medium‐Range Weather Forecasts, provides long time series of atmospheric fields at high spatial and temporal resolution. It allows ...detailed studies of atmospheric flow features such as blocks or cyclones. We investigate characteristics of blocks and cyclones in ERA5 using different algorithms, compare the results to ERA5's predecessor, ERA‐interim, and investigate how these characteristics depend on spatial resolution. Generally, ERA5 and ERA‐interim characterize blocks and cyclones similarly. For Lagrangian detection and tracking methods, blocks are more robust than cyclones to changes in resolution and reanalysis choice. Eulerian methods are robust to changes in resolution. Thus, ERA5 provides a state‐of‐the‐art reanalysis for the synoptic‐scale extratropical circulation. We find that Lagrangian cyclone characteristics are strongly dependent on spatial resolution and therefore recommend that model and reanalysis data should be mapped to a common resolution for verification.
Plain Language Summary
Reanalyses are among the most widely used data sets in the geosciences as they provide a state of the atmosphere that is complete in both space and time by combining a state‐of‐the‐art weather prediction model with historical observations. Their applications range from climatological studies to the closer examination of extreme events. Reanalyses are often the primary tool to assess the performance of climate models. Recently, the ERA5 reanalysis was published, and thus, many users may consider using this new product. However, due to its novelty, ERA5 is not yet investigated extensively. We examine midlatitudinal atmospheric flow features such as blocks and cyclones and their dependence on input resolution and choice of reanalysis. We find that blocks and cyclones characteristics are very similar in ERA5 and its predecessor ERA‐interim. Input resolution often plays a more important role on block and cyclone characteristics than the choice between ERA5 and ERA‐interim, particularly in case of cyclone characteristics. For many applications, the full resolution of ERA5 may not be necessary, easing the computational requirement to use this high‐resolution data set. In case of modeling studies where reanalysis data is compared to modeled data, we recommend using the same resolution.
Key Points
Characteristics of blocks and cyclones are generally similar in ERA5 and ERA‐interim
Characteristics are more sensitive to the spatial resolution than the choice of the reanalysis, especially for cyclones
We recommend comparing climate model and reanalysis data using a common resolution
For the detection of climate change, not only the magnitude of a trend signal is of significance. An essential issue is the time period required by the trend to be detectable in the first place. An ...illustrative measure for this is time of emergence (ToE), that is, the point in time when a signal finally emerges from the background noise of natural variability. We investigate the ToE of trend signals in different biogeochemical and physical surface variables utilizing a multi-model ensemble comprising simulations of 17 Earth system models (ESMs). We find that signals in ocean biogeochemical variables emerge on much shorter timescales than the physical variable sea surface temperature (SST). The ToE patterns of pCO2 and pH are spatially very similar to DIC (dissolved inorganic carbon), yet the trends emerge much faster – after roughly 12 yr for the majority of the global ocean area, compared to between 10 and 30 yr for DIC. ToE of 45–90 yr are even larger for SST. In general, the background noise is of higher importance in determining ToE than the strength of the trend signal. In areas with high natural variability, even strong trends both in the physical climate and carbon cycle system are masked by variability over decadal timescales. In contrast to the trend, natural variability is affected by the seasonal cycle. This has important implications for observations, since it implies that intra-annual variability could question the representativeness of irregularly sampled seasonal measurements for the entire year and, thus, the interpretation of observed trends.
Estimating the likelihood of compound climate extremes such as concurrent drought and heatwaves or compound precipitation and wind speed extremes is important for assessing climate risks. Typically, ...simulations from climate models are used to assess future risks, but it is largely unknown how well the current generation of models represents compound extremes. Here, we introduce a new metric that measures whether the tails of bivariate distributions show a similar dependence structure across different datasets. We analyse compound precipitation and wind extremes in reanalysis data and different high-resolution simulations for central Europe. A state-of-the-art reanalysis dataset (ERA5) is compared to simulations with a weather model (Weather Research and Forecasting – WRF) either driven by observation-based boundary conditions or a global circulation model (Community Earth System Model – CESM) under present-day and future conditions with strong greenhouse gas forcing (Representative Concentration Pathway 8.5 – RCP8.5).
Over the historical period, the high-resolution WRF simulations capture precipitation and wind extremes as well as their response to orographic effects more realistically than ERA5. Thus, WRF simulations driven by observation-based boundary conditions are used as a benchmark for evaluating the dependence structure of wind and precipitation extremes.
Overall, boundary conditions in WRF appear to be the key factor in explaining differences in the dependence behaviour between strong wind and heavy precipitation between simulations. In comparison, external forcings (RCP8.5) are of second order. Our approach offers new methodological tools to evaluate climate model simulations with respect to compound extremes.
Understanding natural climate variability and its driving factors is crucial to assessing future climate change. Therefore, comparing proxy-based climate reconstructions with forcing factors as well ...as comparing these with paleoclimate model simulations is key to gaining insights into the relative roles of internal versus forced variability. A review of the state of modelling of the climate of the last millennium prior to the CMIP5-PMIP3 (Coupled Model Intercomparison Project Phase 5-Paleoclimate Modelling Intercomparison Project Phase 3) coordinated effort is presented and compared to the available temperature reconstructions. Simulations and reconstructions broadly agree on reproducing the major temperature changes and suggest an overall linear response to external forcing on multidecadal or longer timescales. Internal variability is found to have an important influence at hemispheric and global scales. The spatial distribution of simulated temperature changes during the transition from the Medieval Climate Anomaly to the Little Ice Age disagrees with that found in the reconstructions. Thus, either internal variability is a possible major player in shaping temperature changes through the millennium or the model simulations have problems realistically representing the response pattern to external forcing. A last millennium transient climate response (LMTCR) is defined to provide a quantitative framework for analysing the consistency between simulated and reconstructed climate. Beyond an overall agreement between simulated and reconstructed LMTCR ranges, this analysis is able to single out specific discrepancies between some reconstructions and the ensemble of simulations. The disagreement is found in the cases where the reconstructions show reduced covariability with external forcings or when they present high rates of temperature change.
This study presents a new dynamical downscaling strategy for extreme events. It is based on a combination of statistical downscaling of coarsely resolved global model simulations and dynamical ...downscaling of specific extreme events constrained by the statistical downscaling part. The method is applied to precipitation extremes over the upper Aare catchment, an area in Switzerland which is characterized by complex terrain. The statistical downscaling part consists of an Artificial Neural Network (ANN) framework trained in a reference period. Thereby, dynamically downscaled precipitation over the target area serve as predictands and large-scale variables, received from the global model simulation, as predictors. Applying the ANN to long term global simulations produces a precipitation series that acts as a surrogate of the dynamically downscaled precipitation for a longer climate period, and therefore are used in the selection of events. These events are then dynamically downscaled with a regional climate model to 2 km. The results show that this strategy is suitable to constraint extreme precipitation events, although some limitations remain, e.g., the method has lower efficiency in identifying extreme events in summer and the sensitivity of extreme events to climate change is underestimated.
Decadal and longer timescale variability in the winter North Atlantic Oscillation (NAO) has considerable impact on regional climate, yet it remains unclear what fraction of this variability is ...potentially predictable. This study takes a new approach to this question by demonstrating clear physical differences between NAO variability on interannual-decadal (<30 year) and multidecadal (>30 year) timescales. It is shown that on the shorter timescale the NAO is dominated by variations in the latitude of the North Atlantic jet and storm track, whereas on the longer timescale it represents changes in their strength instead. NAO variability on the two timescales is associated with different dynamical behaviour in terms of eddy-mean flow interaction, Rossby wave breaking and blocking. The two timescales also exhibit different regional impacts on temperature and precipitation and different relationships to sea surface temperatures. These results are derived from linear regression analysis of the Twentieth Century and NCEP-NCAR reanalyses and of a high-resolution HiGEM General Circulation Model control simulation, with additional analysis of a long sea level pressure reconstruction. Evidence is presented for an influence of the ocean circulation on the longer timescale variability of the NAO, which is particularly clear in the model data. As well as providing new evidence of potential predictability, these findings are shown to have implications for the reconstruction and interpretation of long climate records.
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