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  • 1
    Publication Date: 2023-11-13
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Owing to the complicated spatial–temporal characteristics of East Asian precipitation (EAP), climate models have limited skills in simulating the modern Asian climate. This consequently leads to large uncertainties in simulations of the past EAP variation and future projections. Here, we explore the performance of the newly developed Alfred Wegener Institute Climate Model, version 3 (AWI‐CM3) in simulating the climatological summer EAP. To test whether the model's skill depends on its atmosphere resolution, we design two AWI‐CM3 simulations with different horizontal resolutions. The result shows that both simulations have acceptable performance in simulating the summer mean EAP, generally better than the majority of individual models participating in the Coupled Model Intercomparison Project (CMIP6). However, for the monthly EAP from June to August, AWI‐CM3 exhibits a decayed skill, which is due to the subseasonal movement of the western Pacific subtropical high bias. The higher‐resolution AWI‐CM3 simulation shows an overall improvement relative to the one performed at a relatively lower resolution in all aspects taken into account regarding the EAP. We conclude that AWI‐CM3 is a suitable tool for exploring the EAP for the observational period. Having verified the model's skill for modern climate, we suggest employing the AWI‐CM3, especially with high atmosphere resolution, both for applications in paleoclimate studies and future projections.〈/p〉
    Description: 〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉This figure shows the skill scores of AWI‐CM3 and CMIP6 models in simulating the climatological summer East Asian precipitation (EAP), which indicates that AWI‐CM3 simulations perform better than most CMIP6 individual models for the summer mean EAP, while AWI‐CM3's skills decay from June to August.〈boxed-text position="anchor" content-type="graphic" id="joc8075-blkfxd-0001" xml:lang="en"〉 〈graphic position="anchor" id="jats-graphic-1" xlink:href="urn:x-wiley:08998418:media:joc8075:joc8075-toc-0001"〉 〈alt-text〉image〈/alt-text〉 〈/graphic〉 〈/boxed-text〉〈/p〉
    Description: National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: Helmholtz Climate Initiative REKLIM
    Description: Helmholtz Program
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Description: China Scholarship Council http://dx.doi.org/10.13039/501100004543
    Description: https://opendata.dwd.de/climate_environment/GPCC/html/fulldata-monthly_v2022_doi_download.html
    Description: https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.05
    Description: http://aphrodite.st.hirosaki-u.ac.jp/products.html
    Description: https://jra.kishou.go.jp/JRA-55/index_en.html
    Description: https://esgf-node.llnl.gov/search/cmip6
    Keywords: ddc:551.6 ; AWI‐CM3 ; CMIP6 ; East Asia ; summer precipitation
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2024-02-05
    Description: A new version of the AWI Coupled Prediction System is developed based on the Alfred Wegener Institute Climate Model v3.0. Both the ocean and the atmosphere models are upgraded or replaced, reducing the computation time by a factor of 5 at a given resolution. This allowed us to increase the ensemble size from 12 to 30, maintaining a similar resolution in both model components. The online coupled data assimilation scheme now additionally utilizes sea‐surface salinity and sea‐level anomaly as well as temperature and salinity profile observations. Results from the data assimilation demonstrate that the sea‐ice and ocean states are reasonably constrained. In particular, the temperature and salinity profile assimilation has mitigated systematic errors in the deeper ocean, although issues remain over polar regions where strong atmosphere‐ocean‐ice interaction occurs. One‐year‐long sea‐ice forecasts initialized on 1 January, 1 April, 1 July and 1 October from 2003 to 2019 are described. To correct systematic forecast errors, sea‐ice concentration from 2011 to 2019 is calibrated by trend‐adjusted quantile mapping using the preceding forecasts from 2003 to 2010. The sea‐ice edge raw forecast skill is within the range of operational global subseasonal‐to‐seasonal forecast systems, outperforming a climatological benchmark for about 2 weeks in the Arctic and about 3 weeks in the Antarctic. The calibration is much more effective in the Arctic: Calibrated sea‐ice edge forecasts outperform climatology for about 45 days in the Arctic but only 27 days in the Antarctic. Both the raw and the calibrated forecast skill exhibit strong seasonal variations.
    Description: Plain Language Summary: Ocean data sparseness and systematic model errors pose problems for the initialization of coupled seasonal forecasts, especially in polar regions. Our global forecast system follows a seamless approach with refined ocean resolution in the Arctic. The new version presented here features higher computational efficiency and utilizes more ocean and sea‐ice observations. Ice‐edge forecasts outperform a climatological benchmark for about 1 month, comparable to established systems.
    Description: Key Points: We describe an upgrade of the AWI Coupled Prediction System with new ocean and atmosphere models and more observations assimilated. Independent evaluations show advances in the new version on the analysis of the sea‐ice and ocean states against the old one. Calibrated sea‐ice edge forecasts outperform a climatological benchmark for around 1 month in both hemispheres.
    Description: National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Description: Deutsche Forschungsgemeinschaft
    Description: https://doi.org/10.5281/zenodo.6335383
    Description: https://github.com/FESOM/fesom2/releases/tag/AWI-CM3_v3.0
    Description: https://doi.org/10.5281/zenodo.6335498
    Description: https://oasis.cerfacs.fr/en/
    Description: https://doi.org/10.5281/zenodo.4905653
    Description: http://forge.ipsl.jussieu.fr/ioserver
    Description: https://doi.org/10.5281/zenodo.6335474
    Description: http://pdaf.awi.de/
    Description: https://doi.org/10.5281/zenodo.6481116
    Keywords: ddc:551.6 ; seamless sea ice forecast ; multivariate data assimilation ; forecast calibration ; spatial probability score
    Language: English
    Type: doc-type:article
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  • 3
    Publication Date: 2020-11-11
    Description: Observations and models agree that the Greenland Ice Sheet (GrIS) surface mass balance (SMB) has decreased since the end of the 1990s due to an increase in meltwater runoff and that this trend will accelerate in the future. However, large uncertainties remain, partly due to different approaches for modelling the GrIS SMB, which have to weigh physical complexity or low computing time, different spatial and temporal resolutions, different forcing fields, and different ice sheet topographies and extents, which collectively make an inter-comparison difficult. Our GrIS SMB model intercomparison project (GrSMBMIP) aims to refine these uncertainties by intercomparing 13 models of four types which were forced with the same ERA-Interim reanalysis forcing fields, except for two global models. We interpolate all modelled SMB fields onto a common ice sheet mask at 1 km horizontal resolution for the period 1980–2012 and score the outputs against (1) SMB estimates from a combination of gravimetric remote sensing data from GRACE and measured ice discharge; (2) ice cores, snow pits and in situ SMB observations; and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting model deficiencies in an accurate representation of the GrIS ablation zone extent and processes related to surface melt and runoff. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of the same order as RCMs compared with observations and therefore remain useful tools for long-term simulations or coupling with ice sheet models. Finally, it is interesting to note that the ensemble mean of the 13 models produces the best estimate of the present-day SMB relative to observations, suggesting that biases are not systematic among models and that this ensemble estimate can be used as a reference for current climate when carrying out future model developments. However, a higher density of in situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 m w.e. yr−1 due to large discrepancies in modelled snowfall accumulation.
    Print ISSN: 1994-0416
    Electronic ISSN: 1994-0424
    Topics: Geography , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 4
    Publication Date: 2020-11-23
    Description: Current activities at the GEOMAR Helmholtz Centre for Ocean Research in Kiel and the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) in Bremerhaven, Germany, include developing two new versions of high-resolution coupled climate models. Both climate models successfully use OpenIFS, a portable version of ECMWF’s Integrated Forecasting System (IFS) for use at universities and research institutes. The experience gained in using OpenIFS for climate modelling can in turn provide insights that will help ECMWF to further develop the IFS.
    Type: Article , NonPeerReviewed
    Format: text
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  • 5
    Publication Date: 2021-01-08
    Description: The Greenland Ice Sheet (GrIS) mass loss has been accelerating at a rate of about 20 ± 10 Gt/yr2 since the end of the 1990's, with around 60 % of this mass loss directly attributed to enhanced surface meltwater runoff. However, in the climate and glaciology communities, different approaches exist on how to model the different surface mass balance (SMB) components using: (1) complex physically-based climate models which are computationally expensive; (2) intermediate complexity energy balance models; (3) simple and fast positive degree day models which base their inferences on statistical principles and are computationally highly efficient. Additionally, many of these models compute the SMB components based on different spatial and temporal resolutions, with different forcing fields as well as different ice sheet topographies and extents, making inter-comparison difficult. In the GrIS SMB model intercomparison project (GrSMBMIP) we address these issues by forcing each model with the same data (i.e., the ERA-Interim reanalysis) except for two global models for which this forcing is limited to the oceanic conditions, and at the same time by interpolating all modelled results onto a common ice sheet mask at 1 km horizontal resolution for the common period 1980–2012. The SMB outputs from 13 models are then compared over the GrIS to (1) SMB estimates using a combination of gravimetric remote sensing data from GRACE and measured ice discharge, (2) ice cores, snow pits, in-situ SMB observations, and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Our results reveal that the mean GrIS SMB of all 13 models has been positive between 1980 and 2012 with an average of 340 ± Gt/yr, but has decreased at an average rate of −7.3 Gt/yr2 (with a significance of 96 %), mainly driven by an increase of 8.0 Gt/yr2 (with a significance of 98 %) in meltwater runoff. Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting the need for accurate representation of the GrIS ablation zone extent and processes driving the surface melt. In addition, a higher density of in-situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 mWE/yr due to large discrepancies in modelled snowfall accumulation. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of same order than RCMs with observations and remain then useful tools for long-term simulations. Finally, it is interesting to note that the ensemble mean of the 13 models produces the best estimate of the present day SMB relative to observations, suggesting that biases are not systematic among models.
    Type: Article , PeerReviewed
    Format: text
    Format: text
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  • 6
    Publication Date: 2021-09-09
    Description: The impact of Arctic sea ice decline on the weather and climate in mid-latitudes is still much debated, with observation suggesting a strong and models a much weaker link. In this study, we use the atmospheric model OpenIFS, in a set of model experiments following the protocol outlined in the Polar Amplification Model Intercomparison Project (PAMIP), to investigate whether the simulated atmospheric response to future changes in Arctic sea ice fundamentally depends on model resolution. More specifically, we increase the horizontal resolution of the model from 125km to 39km with 91 vertical levels; in a second step resolution is further increased to 16km with 137 levels in the vertical. The model does produce a response to sea ice decline with a weaker mid latitude Atlantic jet and increased blocking in the high latitude Atlantic, but no sensitivity to resolution can be detected with 100 members. Furthermore we find that the ensemble convergence toward the mean is not impacted by the model resolutions considered here.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 7
    Publication Date: 2022-01-07
    Description: Widespread mismatches between proxy-based and modelling studies of the Last Glacial Maximum (LGM) has limited better understanding about interglacial-glacial climate change. In this study, we incorporate non-breaking surface waves (NBW) induced mixing into an ocean model to assess the potential role of waves in changing a simulation of LGM upper oceans. Our results show a substantial 40 m subsurface warming introduced by surface waves in LGM summer, with larger magnitudes relative to the present-day ocean. At the ocean surface, according to the comparison between the proxy data and our simulations, the incorporation of the surface wave process into models can potentially decrease the model-data discrepancy for the LGM ocean. Therefore, our findings suggest that the inclusion of NBW is helpful in simulating glacial oceans.
    Type: Article , PeerReviewed
    Format: text
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  • 8
    Publication Date: 2024-02-07
    Description: We developed a new version of the Alfred Wegener Institute Climate Model (AWI-CM3), which has higher skills in representing the observed climatology and better computational efficiency than its predecessors. Its ocean component FESOM2 (Finite-volumE Sea ice-Ocean Model) has the multi-resolution functionality typical of unstructured-mesh models while still featuring a scalability and efficiency similar to regular-grid models. The atmospheric component OpenIFS (CY43R3) enables the use of the latest developments in the numerical-weather-prediction community in climate sciences. In this paper we describe the coupling of the model components and evaluate the model performance on a variable-resolution (25-125 km) ocean mesh and a 61 km atmosphere grid, which serves as a reference and starting point for other ongoing research activities with AWI-CM3. This includes the exploration of high and variable resolution and the development of a full Earth system model as well as the creation of a new sea ice prediction system. At this early development stage and with the given coarse to medium resolutions, the model already features above-CMIP6-average skills (where CMIP6 denotes Coupled Model Intercomparison Project phase 6) in representing the climatology and competitive model throughput. Finally we identify remaining biases and suggest further improvements to be made to the model.
    Type: Article , PeerReviewed
    Format: text
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  • 9
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    In:  EPIC3EC-Earth meeting, Lisbon, 2018-10-22-2018-10-24
    Publication Date: 2018-11-12
    Description: The OpenIFS - FESOM2 coupled model is presented and first results of coupled climate simulations with the new model are shown. The model performs well for present day climate and is slightly too sensitive for reduced co2 in per-industrial settings. It shows similar long term sea surface biases as EC-Earth3, based on IFS&OpenIFS radiation biases. FESOM2 may be considered as alternative to NEMO for EC-Earth4, and OpenIFS as an alternative to ECHAM6 and ICON-A at AWI. Future work includes model tuneing, modifying resolutions and coupling of further Earth System Model components such as the dynamic land vegetation model LPJ-Guess. The model will be used within the ESM Project.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
    Format: application/pdf
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  • 10
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    Institut für Flugführung
    In:  EPIC3Institut für Flugführung, 84 p.
    Publication Date: 2017-10-04
    Description: The development of the third installment of the climate model EC-Earth is nearing its completion. The quality of EC-Earth simulations in the current state is analysed in comparison to a number of other climate models that are currently in use at the Alfred Wegener Institute’s Climate Sciences Department. By varying a set of greenhouse gases and orbital parameters, four scenarios of Present Day, Pre-Industrial, Last Interglacial and Mid-Holocene climate are designed. EC-Earth is set up and applied to simulate these climate scenarios. In conjunction with observational data, reanalysis data and proxy based climate reconstructions, these simulations are used to measure the quality of EC-Earth climate simulations. The variables examined for this purpose are land and sea surface temperature, air temperature, precipitation, and sea ice concentration. Furthermore, the ability of EC-Earth to reproduce global ocean currents and known climate patterns, such as the El Nino Southern Oscillation, is checked in order to gain insight into the variability of the simulated climate. EC-Earth is found to be in an advanced state of development with a rough setup process but mostly stable simulations. Both Present Day climate and paleoclimates are reproduced more accurately than in other climate models that are in use at Alfred Wegener Institute. Remaining issues to be solved are underestimated strength of important ocean currents and a high latitude warm bias in Present Day simulations.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Thesis , notRev
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