EC-Earth-Consortium EC-Earth3-AerChem model output prepared for CMIP6 CMIP amip
Coupled Model Intercomparison Project Phase 6 (CMIP6) data sets: These data includes all datasets... more Coupled Model Intercomparison Project Phase 6 (CMIP6) data sets: These data includes all datasets published for 'CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.amip' according to the Data Reference Syntax defined as 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The model used in climate research named EC-Earth3-AerChem, released in 2019, includes the components: aerosol: TM5 (3 x 2 degrees; 120 x 90 longitude/latitude; 34 levels; top level: 0.1 hPa), atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), atmosChem: TM5 (3 x 2 degrees; 120 x 90 longitude/latitude; 34 levels; top level: 0.1 hPa), land: HTESSEL (land surface scheme built in IFS), ocean: NEMO3.6 (ORCA1 tripolar primarily 1 degree with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: ...
EC-Earth-Consortium EC-Earth3-CC model output prepared for CMIP6 C4MIP 1pctCO2-rad
Coupled Model Intercomparison Project Phase 6 (CMIP6) data sets: These data includes all datasets... more Coupled Model Intercomparison Project Phase 6 (CMIP6) data sets: These data includes all datasets published for 'CMIP6.C4MIP.EC-Earth-Consortium.EC-Earth3-CC.1pctCO2-rad' according to the Data Reference Syntax defined as 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The model used in climate research named EC-Earth3-CC, released in 2019, includes the components: atmos: IFS cy36r4 (TL255, linearly reduced Gaussian grid equivalent to 512 x 256 longitude/latitude; 91 levels; top level 0.01 hPa), atmosChem: TM5 (3 x 2 degrees; 120 x 90 longitude/latitude; 34 levels; top level: 0.1 hPa), land: HTESSEL (land surface scheme built in IFS) and LPJ-GUESS v4, ocean: NEMO3.6 (ORCA1 tripolar primarily 1 degree with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 75 levels; top grid cell 0-1 m), ocnBgchem: PISCES v2, seaIce: LIM3. The model was run by the AEMET, Spain; BSC, Spa...
In this paper we study the strengths and weaknesses of such reconstruction methods We apply a sur... more In this paper we study the strengths and weaknesses of such reconstruction methods We apply a surrogate ensemble method based on sea levels from a 500 years climate model simulation. Tide gauges are simulated by selecting time-series from grid-points along continental coastlines and on ocean islands. Reconstructions of global mean sea levels can then be compared to the known target and the ensemble method allows an estimation of the statistical properties originating from the stochastic nature of the reconstructions. We study different reconstruction methods previously used in the literature including projection and optimal interpolation methods based on EOF analysis of the calibration period. We also include methods where these EOFs are augmented with a homogeneous pattern with the purpose of better capturing a possible geographically homogeneous trend. These covariance based methods are compared to a simple weighted mean method. We conclude that the projection and optimal interpol...
Future European changes of extreme precipitation : What can we learn from inter-model cross-validation?
<p>Severe precipitation events occur rarely and are often localized in spac... more <p>Severe precipitation events occur rarely and are often localized in space and of short duration, but are important for societal managing of infrastructure such as sewage systems, metros etc. Therefore, there is a demand for estimating expected future changes in the statistics of these rare events. These are usually projected using RCM scenario runs combined with extreme value analysis to obtain selected return levels of precipitation intensity. However, due to RCM imperfections, the modelled climate for the present-day usually has errors relative to observations. Therefore, the RCM results are ‘error corrected‘ to match observations more closely in order to increase reliability of results.</p> <p>In the present work we evaluate different error correction techniques and compare with non-corrected projections. This is done in an inter-model cross-validation setup, in which each model in turn plays the role of observations, against which the remaining error-corrected models are validated. The study uses hourly data (historical & RCP8.5 late 21<sup>st</sup> century) from 13 models covering the EURO-CORDEX ensemble at 0.11 degree resolution (about 12.5 km), from which fields of selected return levels are extracted for 1 h and 24 h duration. The error correction techniques applied to the return levels are based on extreme value analysis and include analytical quantile-quantile matching together with a simpler climate factor approach.</p> <p>The study identifies regions where the error correction techniques perform differently, and therefore contributes to guidelines on how and where to apply calibration techniques when projecting extreme return levels.</p>
The performance of short-range operational forecasts of significant wave height (SWH) in the Balt... more The performance of short-range operational forecasts of significant wave height (SWH) in the Baltic Sea is evaluated. Forecasts produced by a base configuration are intercompared with forecasts from two improved configurations: one with improved horizontal and spectral resolution and one with ensembles representing uncertainties in the physics of the forcing wind field and the initial conditions of this field. Both of the improved forecast classes represent an almost equal increase in computational costs. Therefore, the intercomparison addresses the question of whether more computer resources would be more favorably spent on enhancing the spatial and spectral resolution or, alternatively, on introducing ensembles. The intercomparison is based on comparisons with hourly observations of significant wave height from seven observation sites in the Baltic Sea during the 3-year period from 2015 to 2017. We conclude that for most wave measurement sites, the introduction of ensembles enhances the overall performance of the forecasts, whereas increasing the horizontal and spectral resolution does not. These sites represent offshore conditions, in that they are well exposed from all directions, are a large distance from the nearest coast and in deep water. Therefore, there is the a priori expectation that a detailed shoreline and bathymetry will not have any impact. Only at one site do we find that increasing the horizontal and spectral resolution significantly improves the forecasts. This site is situated in nearshore conditions, close to land and a nearby island, and is therefore shielded from many directions. Consequently, this study concludes that to improve wave forecasts in offshore areas, ensembles should be introduced. For near shore areas, in comparison, the study suggests that additional computational resources should be used to increase the resolution.
Estimating uncertainty caused by ocean heat transport to the North Sea: experiments downscaling EC-Earth
Climate Dynamics, 2015
ABSTRACT The heat content of the North Sea is determined by the surface heat flux and the ocean h... more ABSTRACT The heat content of the North Sea is determined by the surface heat flux and the ocean heat transport into the region. The uncertainty in the projected warming in the North Sea caused by ocean heat transport has rarely been quantified. The difference in the estimates using regional ocean models is known to arise from the poorly prescribed temperature boundary forcing, either provided by global models at coarse grid resolutions, or from anomaly correction (using difference of the simulation from observed climatology) without interannual variation. In this study, two marine downscaling experiments were performed using boundary temperature forcings prepared with the two above mentioned strategies: one interpolated from a global model simulation (MI: Model incl. Interannual variation), and the other from observed climatology with warming trends in the future ocean derived from the global model simulation (OT: Observed climatol. plus Trend). The comparative experiments allowed us to estimate the uncertainty caused by ocean heat transport to the North Sea. The global climate model EC-Earth CMIP5 simulations of historical and future scenarios were used to provide lateral boundary forcing for regional models. The OT boundary was found to affect deep water temperatures (below 50m) in the North Sea because of reduced interannual variability. The difference of mean temperature changes by 2100 (MI minus OT) was up to 0.5℃ near the bottom across 58°N. While the deep water temperature in the North Sea did not directly link to the large-scale atmospheric circulation, the Norwegian outflow was highly correlated with the NAO index and heat transport of the Atlantic inflow provided by EC-Earth. It was found that model uncertainty due to the choice of lateral boundary forcing could be significant in the interannual variation of thermal stratification in the northern North Sea in a long-term simulation.
Can proxy data actually tell us about the past climate?
IOP Conference Series: Earth and Environmental Science, 2009
This innovative new feature generates a list of articles' also read'by other us... more This innovative new feature generates a list of articles' also read'by other users based on them reading the original article. Article abstracts citations and references are all considered and weighted accordingly. We hope that this will help you find relevant papers for your ...
Rahmstorf (Reports, 19 January 2007, p. 368) used the observed relation between rates of change o... more Rahmstorf (Reports, 19 January 2007, p. 368) used the observed relation between rates of change of global surface temperature and sea level to predict future sea-level rise. We revisit the application of the statistical methods used and show that estimation of the regression coefficient is not robust. Methods commonly used within econometrics may be more appropriate for the problem of projected sea-level rise.
The effects of serially correlated residuals on the accuracy of linear regression are considered,... more The effects of serially correlated residuals on the accuracy of linear regression are considered, and remedies are suggested. The Cochrane-Orcutt method specifically remedies the effects of serially correlated residuals and yields more accurate regression coefficients than does ordinary least squares. We illustrate the effects of serially correlated residuals, explain the application of the CO method, and evaluate the gains to be achieved in its use. We apply the method to an example from climate reconstruction, and we show that the effects of serial correlation in residuals are present and show the significantly improved result.
This study investigates the possibility of reconstructing past global mean sea levels. Reconstruc... more This study investigates the possibility of reconstructing past global mean sea levels. Reconstruction methods rely on historical measurements from tide gauges combined with knowledge about the spatial covariance structure of the sea level field obtained from a shorter period with spatially well-resolved satellite measurements. A surrogate ensemble method is applied based on sea levels from a 500-yr climate model simulation. Tide gauges are simulated by selecting time series from grid points along continental coastlines and on ocean islands. Reconstructions of global mean sea levels can then be compared to the known target, and the ensemble method allows an estimation of the statistical properties originating from the stochastic nature of the reconstructions. Different reconstruction methods previously used in the literature are studied, including projection and optimal interpolation methods based on EOF analysis of the calibration period. This study also includes methods where these...
Reconstruction of the earth’s surface temperature from proxy data is an important task because of... more Reconstruction of the earth’s surface temperature from proxy data is an important task because of the need to compare recent changes with past variability. However, the statistical properties and robustness of climate reconstruction methods are not well known, which has led to a heated discussion about the quality of published reconstructions. In this paper a systematic study of the properties of reconstruction methods is presented. The methods include both direct hemispheric-mean reconstructions and field reconstructions, including reconstructions based on canonical regression and regularized expectation maximization algorithms. The study will be based on temperature fields where the target of the reconstructions is known. In particular, the focus will be on how well the reconstructions reproduce low-frequency variability, biases, and trends. A climate simulation from an ocean–atmosphere general circulation model of the period a.d. 1500–1999, including both natural and anthropogeni...
Global sea level rise is widely understood as a consequence of thermal expansion and the melting ... more Global sea level rise is widely understood as a consequence of thermal expansion and the melting of glaciers and land-based ice caps. Because of the lack of representation of ice-sheet dynamics in present-day physically based climate models, semiempirical models have been applied as an alternative for projecting future sea levels. There are, however, potential pitfalls in this because of the trending nature of the time series. A statistical method called cointegration analysis that is capable of handling such peculiarities is applied to observed global sea level and land–ocean surface temperature. The authors find a relationship between sea level and temperature and find that temperature causally depends on the sea level, which can be understood as a consequence of the large heat capacity of the ocean. They further find that the warming episode in the 1940s is exceptional in the sense that sea level and warming deviate from the expected relationship. This suggests that this warming ...
The longest instrumental index of the North Atlantic Oscillation (NAO) is based on pressure measu... more The longest instrumental index of the North Atlantic Oscillation (NAO) is based on pressure measurements from Gibraltar and Reykjavik. Recently two long pressure series from the town of Cádiz and the nearby San Fernando observatory in southern Spain have been digitized. As Gibraltar is situated within 100 kilometers from Cádiz and San Fernando a long held suspicion that early pressure data from Gibraltar contains several problems can now be investigated. This leads to the creation of an improved version of the long NAO index in which the period from 1821 to 1856 has been revised.
Comment on “Trends and low frequency variability of extra-tropical cyclone activity in the ensemble of twentieth century reanalysis” by Xiaolan L. Wang, Y. Feng, GP Compo, VR Swail, FW Zwiers, RJ Allan, and PD Sardeshmukh, Climate Dynamics, 2012
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