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  • 1
    In: Remote Sensing, MDPI AG, Vol. 11, No. 8 ( 2019-04-18), p. 941-
    Abstract: The authors wish to make the following corrections to this paper [...]
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2513863-7
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  • 2
    In: Journal of Geophysical Research: Atmospheres, American Geophysical Union (AGU), Vol. 126, No. 15 ( 2021-08-16)
    Abstract: Daily maximum land surface temperature in European Centre for Medium‐Range Weather Forecasting (ECMWF) model is affected by large biases associated with the representation of land cover An updated representation of vegetation in the ECMWF model based on state‐of‐the‐art Earth observations reduces this bias The implemented changes have an overall global positive impact, but a re‐calibration of related model parameters is required
    Type of Medium: Online Resource
    ISSN: 2169-897X , 2169-8996
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2021
    detail.hit.zdb_id: 710256-2
    detail.hit.zdb_id: 2016800-7
    detail.hit.zdb_id: 2969341-X
    SSG: 16,13
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  • 3
    In: International Journal of Climatology, Wiley, Vol. 33, No. 7 ( 2013-06-15), p. 1720-1729
    Abstract: This study evaluates the use of European Centre for Medium‐Range Weather Forecasts (ECMWF) products in monitoring and forecasting drought conditions during the recent 2010–2011 drought in the Horn of Africa (HoA). The region was affected by a precipitation deficit in both the October–December 2010 and March–May 2011 rainy seasons. These anomalies were captured by the ERA‐Interim reanalysis (ERAI), despite its limitations in representing the March–May interannual variability. Soil moisture anomalies of ERAI also identified the onset of the drought condition early in October 2010 with a persistent drought still present in September 2011. This signal was also evident in normalized difference vegetation index (NDVI) remote sensing data. The precipitation deficit in October–December 2010 was associated with a strong La Niña event. The ECMWF seasonal forecasts for the October–December 2010 season predicted the La Niña event from June 2010 onwards. The forecasts also predicted a below‐average October–December rainfall, from July 2010 onwards. The subsequent March–May rainfall anomaly was only captured by the new ECWMF seasonal forecast system in the forecasts starting in March 2011. Our analysis shows that a recent (since 1999) drying in the region during the March–May season is captured by the new ECMWF seasonal forecast system and is consistent with recently published results. The HoA region and its population are highly vulnerable to future droughts, thus global monitoring and forecasting of drought, such as that presented here, will become increasingly important in the future. Copyright © 2012 Royal Meteorological Society
    Type of Medium: Online Resource
    ISSN: 0899-8418 , 1097-0088
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2013
    detail.hit.zdb_id: 1491204-1
    SSG: 14
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  • 4
    In: Journal of Advances in Modeling Earth Systems, American Geophysical Union (AGU), Vol. 12, No. 11 ( 2020-11)
    Abstract: A unique simulation with 1.4 km average grid spacing is presented for model development and process evaluation The 1.4 km simulation shows remarkable fidelity with respect to the well‐calibrated simulation at 9 km with parametrized deep convection Switching off deep convection at a too coarse resolution (9 km) generates too strong convective gravity waves
    Type of Medium: Online Resource
    ISSN: 1942-2466 , 1942-2466
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2020
    detail.hit.zdb_id: 2462132-8
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  • 5
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 2019
    In:  Journal of Advances in Modeling Earth Systems Vol. 11, No. 12 ( 2019-12), p. 4687-4710
    In: Journal of Advances in Modeling Earth Systems, American Geophysical Union (AGU), Vol. 11, No. 12 ( 2019-12), p. 4687-4710
    Abstract: A multilayer snow scheme is implemented in the ECMWF Integrated Forecasting System (IFS) and evaluated in offline and coupled simulations The new multilayer snow scheme improves the snowpack representation on a wide range of spatial and temporal scales The new scheme improves the diurnal cycle of 2‐m temperature and the mean error of minimum 2‐m temperature over snow‐covered regions
    Type of Medium: Online Resource
    ISSN: 1942-2466 , 1942-2466
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2019
    detail.hit.zdb_id: 2462132-8
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  • 6
    Online Resource
    Online Resource
    Copernicus GmbH ; 2018
    In:  Geoscientific Model Development Vol. 11, No. 9 ( 2018-09-11), p. 3681-3712
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 11, No. 9 ( 2018-09-11), p. 3681-3712
    Abstract: Abstract. This paper presents atmosphere-only and coupled climate model configurations of the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) for different combinations of ocean and atmosphere resolution. These configurations are used to perform multi-decadal ensemble experiments following the protocols of the High Resolution Model Intercomparison Project (HighResMIP) and phase 6 of the Coupled Model Intercomparison Project (CMIP6). These experiments are used to evaluate the sensitivity of major biases in the atmosphere, ocean, and cryosphere to changes in atmosphere and ocean resolution. All configurations successfully reproduce the observed long-term trends in global mean surface temperature. Furthermore, following an adjustment to account for drift in the subsurface ocean, coupled configurations of ECMWF-IFS realistically reproduce observation-based estimates of ocean heat content change since 1950. Climatological surface biases in ECMWF-IFS are relatively insensitive to an increase in atmospheric resolution from  ∼ 50 to  ∼ 25 km. However, increasing the horizontal resolution of the atmosphere while maintaining the same vertical resolution enhances the magnitude of a cold bias in the lower stratosphere. In coupled configurations, there is a strong sensitivity to an increase in ocean model resolution from 1 to 0.25°. However, this sensitivity to ocean resolution takes many years to fully manifest and is less apparent in the first year of integration. This result has implications for the ECMWF coupled model development strategy that typically relies on the analysis of biases in short ( 〈 1 year) ensemble (re)forecast data sets. The impacts of increased ocean resolution are particularly evident in the North Atlantic and Arctic, where they are associated with an improved Atlantic meridional overturning circulation, increased meridional ocean heat transport, and more realistic sea-ice cover. In the tropical Pacific, increased ocean resolution is associated with improvements to the magnitude and asymmetry of El Niño–Southern Oscillation (ENSO) variability and better representation of non-linear sea surface temperature (SST)–radiation feedbacks during warm events. However, increased ocean model resolution also increases the magnitude of a warm bias in the Southern Ocean. Finally, there is tentative evidence that both ocean coupling and increased atmospheric resolution can improve teleconnections between tropical Pacific rainfall and geopotential height anomalies in the North Atlantic.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2018
    detail.hit.zdb_id: 2456725-5
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  • 7
    In: Earth System Science Data, Copernicus GmbH, Vol. 13, No. 9 ( 2021-09-07), p. 4349-4383
    Abstract: Abstract. Framed within the Copernicus Climate Change Service (C3S) of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5-Land. Once completed, the period covered will span from 1950 to the present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, which, among others, could be used to analyse trends and anomalies. This is achieved through global high-resolution numerical integrations of the ECMWF land surface model driven by the downscaled meteorological forcing from the ERA5 climate reanalysis, including an elevation correction for the thermodynamic near-surface state. ERA5-Land shares with ERA5 most of the parameterizations that guarantees the use of the state-of-the-art land surface modelling applied to numerical weather prediction (NWP) models. A main advantage of ERA5-Land compared to ERA5 and the older ERA-Interim is the horizontal resolution, which is enhanced globally to 9 km compared to 31 km (ERA5) or 80 km (ERA-Interim), whereas the temporal resolution is hourly as in ERA5. Evaluation against independent in situ observations and global model or satellite-based reference datasets shows the added value of ERA5-Land in the description of the hydrological cycle, in particular with enhanced soil moisture and lake description, and an overall better agreement of river discharge estimations with available observations. However, ERA5-Land snow depth fields present a mixed performance when compared to those of ERA5, depending on geographical location and altitude. The description of the energy cycle shows comparable results with ERA5. Nevertheless, ERA5-Land reduces the global averaged root mean square error of the skin temperature, taking as reference MODIS data, mainly due to the contribution of coastal points where spatial resolution is important. Since January 2020, the ERA5-Land period available has extended from January 1981 to the near present, with a 2- to 3-month delay with respect to real time. The segment prior to 1981 is in production, aiming for a release of the whole dataset in summer/autumn 2021. The high spatial and temporal resolution of ERA5-Land, its extended period, and the consistency of the fields produced makes it a valuable dataset to support hydrological studies, to initialize NWP and climate models, and to support diverse applications dealing with water resource, land, and environmental management. The full ERA5-Land hourly (Muñoz-Sabater, 2019a) and monthly (Muñoz-Sabater, 2019b) averaged datasets presented in this paper are available through the C3S Climate Data Store at https://doi.org/10.24381/cds.e2161bac and https://doi.org/10.24381/cds.68d2bb30, respectively.
    Type of Medium: Online Resource
    ISSN: 1866-3516
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2021
    detail.hit.zdb_id: 2475469-9
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  • 8
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 13, No. 9 ( 2020-09-03), p. 3975-3993
    Abstract: Abstract. Earth observations were used to evaluate the representation of land surface temperature (LST) and vegetation coverage over Iberia in two state-of-the-art land surface models (LSMs) – the European Centre for Medium-Range Weather Forecasts (ECMWF) Carbon-Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (CHTESSEL) and the Météo-France Interaction between Soil Biosphere and Atmosphere model (ISBA) within the SURface EXternalisée modeling platform (SURFEX-ISBA) for the 2004–2015 period. The results showed that the daily maximum LST simulated by CHTESSEL over Iberia was affected by a large cold bias during summer months when compared against the Satellite Application Facility on Land Surface Analysis (LSA-SAF), reaching magnitudes larger than 10 ∘C over wide portions of central and southwestern Iberia. This error was shown to be tightly linked to a misrepresentation of the vegetation cover.  In contrast, SURFEX simulations did not display such a cold bias. We show that this was due to the better representation of vegetation cover in SURFEX, which uses an updated land cover dataset (ECOCLIMAP-II) and an interactive vegetation evolution, representing seasonality. The representation of vegetation over Iberia in CHTESSEL was improved by combining information from the European Space Agency Climate Change Initiative (ESA-CCI) land cover dataset with the Copernicus Global Land Service (CGLS) leaf area index (LAI) and fraction of vegetation coverage (FCOVER). The proposed improvement in vegetation also included a clumping approach that introduces seasonality to the vegetation cover. The results showed significant added value, removing the daily maximum LST summer cold bias completely, without reducing the accuracy of the simulated LST, regardless of season or time of the day. The striking performance differences between SURFEX and CHTESSEL were fundamental to guiding the developments in CHTESSEL highlighting the importance of using different models. This work has important implications: first, it takes advantage of LST, a key variable in surface–atmosphere energy and water exchanges, which is closely related to satellite top-of-atmosphere observations, to improve the model's representation of land surface processes. Second, CHTESSEL is the land surface model employed by ECMWF in the production of their weather forecasts and reanalysis; hence systematic errors in land surface variables and fluxes are then propagated into those products. Indeed, we showed that the summer daily maximum LST cold bias over Iberia in CHTESSEL is present in the widely used ECMWF fifth-generation reanalysis (ERA5). Finally, our results provided hints about the interaction between vegetation land–atmosphere exchanges, highlighting the relevance of the vegetation cover and respective seasonality in representing land surface temperature in both CHTESSEL and SURFEX. As a whole, this work demonstrated the added value of using multiple earth observation products for constraining and improving weather and climate simulations.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
    detail.hit.zdb_id: 2456725-5
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  • 9
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 2020
    In:  Earth and Space Science Vol. 7, No. 5 ( 2020-05)
    In: Earth and Space Science, American Geophysical Union (AGU), Vol. 7, No. 5 ( 2020-05)
    Abstract: Environmental lapse rate derived from atmospheric reanalysis vertical profiles agrees with observational estimates Surface downscaling outperforms ERA5, but the impact of different ELR corrections to the driving data is reduced Systematic biases in ERA5 near‐surface temperature require further efforts from modeling and data assimilation
    Type of Medium: Online Resource
    ISSN: 2333-5084 , 2333-5084
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2020
    detail.hit.zdb_id: 2807271-6
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  • 10
    In: Scientific Data, Springer Science and Business Media LLC, Vol. 9, No. 1 ( 2022-04-11)
    Abstract: The CO 2 Human Emissions project has generated realistic high-resolution 9 km global simulations for atmospheric carbon tracers referred to as nature runs to foster carbon-cycle research applications with current and planned satellite missions, as well as the surge of in situ observations. Realistic atmospheric CO 2 , CH 4 and CO fields can provide a reference for assessing the impact of proposed designs of new satellites and in situ networks and to study atmospheric variability of the tracers modulated by the weather. The simulations spanning 2015 are based on the Copernicus Atmosphere Monitoring Service forecasts at the European Centre for Medium Range Weather Forecasts, with improvements in various model components and input data such as anthropogenic emissions, in preparation of a CO 2 Monitoring and Verification Support system. The relative contribution of different emissions and natural fluxes towards observed atmospheric variability is diagnosed by additional tagged tracers in the simulations. The evaluation of such high-resolution model simulations can be used to identify model deficiencies and guide further model improvements.
    Type of Medium: Online Resource
    ISSN: 2052-4463
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2775191-0
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