Search Results
Testing bias adjustment methods for regional climate change applications under observational uncertainty and resolution mismatch
Systematic biases in climate models hamper their direct use in impact studies and, as a consequence, many statistical bias adjustment methods have been developed to calibrate model outputs against observations. The application of these methods in a climate change context is problematic since there is no clear understanding on how these methods may affect key magnitudes, for example, the climate change signal or trend, under different sources of uncertainty. Two relevant sources of uncertainty, often overlooked, are the sensitivity to the observational reference used to calibrate the method and the effect of the resolution mismatch between model and observations (downscaling effect). In the present work, we assess the impact of these factors on the climate change signal of temperature and precipitation considering marginal, temporal and extreme aspects. We use eight standard and state-of-the-art bias adjustment methods (spanning a variety of methods regarding their nature—empirical or parametric—, fitted parameters and trend-preservation) for a case study in the Iberian Peninsula. The quantile trend-preserving methods (namely quantile delta mapping (QDM), scaled distribution mapping (SDM) and the method from the third phase of ISIMIP-ISIMIP3) preserve better the raw signals for the different indices and variables considered (not all preserved by construction). However, they rely largely on the reference dataset used for calibration, thus presenting a larger sensitivity to the observations, especially for precipitation intensity, spells and extreme indices. Thus, high-quality observational datasets are essential for comprehensive analyses in larger (continental) domains. Similar conclusions hold for experiments carried out at high (approximately 20 km) and low (approximately 120 km) spatial resolutions. © 2020 The Authors. Atmospheric Science Letters published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society.
Multimodel Evaluation of Nitrous Oxide Emissions From an Intensively Managed Grassland
Process-based models are useful for assessing the impact of changing management practices and climate on yields and greenhouse gas (GHG) emissions from agricultural systems such as grasslands. They can be used to construct national GHG inventories using a Tier 3 approach. However, accurate simulations of nitrous oxide (N2O) fluxes remain challenging. Models are limited by our understanding of soil-plant-microbe interactions and the impact of uncertainty in measured input parameters on simulated outputs. To improve model performance, thorough evaluations against in situ measurements are needed. Experimental data of N2O emissions under two management practices (control with typical fertilization versus increased clover and no fertilization) were acquired in a Swiss field experiment. We conducted a multimodel evaluation with three commonly used biogeochemical models (DayCent in two variants, PaSim, APSIM in two variants) comparing four years of data. DayCent was the most accurate model for simulating N2O fluxes on annual timescales, while APSIM was most accurate for daily N2O fluxes. The multimodel ensemble average reduced the error in estimated annual fluxes by 41% compared to an estimate using the Intergovernmental Panel on Climate Change (IPCC)-derived method for the Swiss agricultural GHG inventory (IPCC-Swiss), but individual models were not systematically more accurate than IPCC-Swiss. The model ensemble overestimated the N2O mitigation effect of the clover-based treatment (measured: 39–45%; ensemble: 52–57%) but was more accurate than IPCC-Swiss (IPCC-Swiss: 72–81%). These results suggest that multimodel ensembles are valuable for estimating the impact of climate and management on N2O emissions. ©2019. The Authors.
Silicon Isotopes in an EMIC's Ocean: Sensitivity to Runoff, Iron Supply, and Climate
The isotopic composition of Si in biogenic silica (BSi), such as opal buried in the oceans' sediments, has changed over time. Paleorecords suggest that the isotopic composition, described in terms of d30Si, was generally much lower during glacial times than today. There is consensus that this variability is attributable to differing environmental conditions at the respective time of BSi production and sedimentation. The detailed links between environmental conditions and the isotopic composition of BSi in the sediments remain, however, poorly constrained. In this study, we explore the effects of a suite of offset boundary conditions during the Last Glacial Maximum (LGM) on the isotopic composition of BSi archived in sediments in an Earth System Model of intermediate complexity (EMIC). Our model results suggest that a change in the isotopic composition of Si supply to the glacial ocean is sufficient to explain the observed overall low(er) glacial d30Si in BSi. All other processes explored trigger model responses of either wrong sign or magnitude or are inconsistent with a recent estimate of bottom water oxygenation in the Atlantic Sector of the Southern Ocean. Caveats, mainly associated with generic uncertainties in today's pelagic biogeochemical modules, remain. © 2020. The Authors.
Consecutive extreme flooding and heat wave in Japan: Are they becoming a norm?
[No abstract available]
Oblique Gravity Wave Propagation During Sudden Stratospheric Warmings
Gravity waves (GWs) are important for coupling the mesosphere to the lower atmosphere during sudden stratospheric warmings (SSWs). Here, a minor SSW is internally generated in a simulation with the upper-atmosphere configuration of the ICOsahedral Nonhydrostatic model. At a horizontal resolution of 20 km the simulation uses no GW drag parameterizations but resolves large fractions of the GW spectrum explicitly, including orographic and nonorographic sources. Consistent with previous studies, the simulated zonal-mean stratospheric warming is accompanied by zonal-mean mesospheric cooling. During the course of the SSW the mesospheric GW momentum flux (GWMF) turns from mainly westward to mainly eastward. Waves of large phase speed (40–80 m s -1) dominate the eastward GWMF during the peak phase of the warming. The GWMF is strongest along the polar night jet axis. Parameterizations of GWs usually assume straight upward propagation, but this assumption is often not satisfied. In the case studied here, a substantial amount of the GWMF is significantly displaced horizontally between the source region and the dissipation region, implying that the local impact of GWs on the mesosphere does not need to be above their local transmission through the stratosphere. The simulation produces significant vertically misaligned anomalies between the stratosphere and mesosphere. Observations by the Microwave Limb Sounder confirm the poleward tilt with height of the polar night jet and horizontal displacements between mesospheric cooling and stratospheric warming patterns. Thus, lateral GW propagation may be required to explain the middle-atmosphere temperature evolution in SSW events with significant zonally asymmetric anomalies. ©2019. The Authors.
On the Sensitivity of the Devonian Climate to Continental Configuration, Vegetation Cover, Orbital Configuration, CO 2 Concentration, and Insolation
During the Devonian (419 to 359 million years ago), life on Earth witnessed decisive evolutionary breakthroughs, most prominently the colonization of land by vascular plants and vertebrates. However, it was also a period of major marine extinctions coinciding with marked changes in climate. The cause of these changes remains unknown, and it is therefore instructive to explore systematically how the Devonian climate responds to changes in boundary conditions. Here we use coupled climate model simulations to investigate separately the influence of changes in continental configuration, vegetation cover, carbon dioxide (CO2) concentrations, the solar constant, and orbital parameters on the Devonian climate. The biogeophysical effect of changes in vegetation cover is small, and the cooling due to continental drift is offset by the increasing solar constant. Variations of orbital parameters affect the Devonian climate, with the warmest climate states at high obliquity and high eccentricity. The prevailing mode of decadal to centennial climate variability relates to temperature fluctuations in high northern latitudes which are mediated by coupled oscillations involving sea ice cover, ocean convection, and a regional overturning circulation. The temperature evolution during the Devonian is dominated by the strong decrease in atmospheric CO2. Albedo changes due to increasing vegetation cover cannot explain the temperature rise found in Late Devonian proxy data. Finally, simulated temperatures are significantly lower than estimates based on oxygen isotope ratios, suggesting a lower d18O ratio of Devonian seawater. ©2019. The Authors.
Assessing changes in risk of amplified planetary waves in a warming world
Summer weather extremes are often associated with high-amplitude atmospheric planetary waves (Petoukhov et al., 2013). Such conditions lead to stationary weather patterns, triggering heat waves and sometimes prolonged intense rainfall. These wave events, referred to as periods of Quasi-Resonant Amplification (QRA), are relatively rare though and hence provide only a few data points in the meteorological record to analyse. Here, we use atmospheric models coupled to boundary conditions that have evolved slowly (i.e., climate), to supplement measurements. Specifically we assess altered probabilities of resonant episodes by employing a unique massive ensemble of atmosphere-only climate simulations to populate statistical distributions of event occurrence. We focus on amplified waves during the two most extreme European heat waves on record, in years 2003 and 2015 (Russo et al., 2015). These years are compared with other modelled recent years (1987–2011), and critically against a modelled world without climate change. We find that there are differences in the statistical characteristics of wave event likelihood between years, suggesting a strong dependence on the known and prescribed Sea Surface Temperature (SST) patterns. The differences are larger than those projected to have occurred under climate change since the pre-industrial period. However, this feature of small differences since pre-industrial is based on single large ensembles, with members consisting of a range of estimates of SST adjustment from pre-industrial to present. Such SST changes are from projections by a set of coupled atmosphere–ocean (AOGCM) climate models. When instead an ensemble for pre-industrial estimates is subdivided into simulations according to which AOGCM the SST changes are based on, we find differences in QRA occurrence. These differences suggest that to reliably estimate changes to extremes associated with altered amplification of planetary waves, and under future raised greenhouse gas concentrations, likely requires reductions in any spread of future modelled SST patterns. © 2019 The Authors. Atmospheric Science Letters published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society.