GLORIA

GEOMAR Library Ocean Research Information Access

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    In: Journal of Climate, American Meteorological Society, Vol. 27, No. 22 ( 2014-11-15), p. 8563-8577
    Abstract: In this study, the impact of coupling and initializing the leaf area index from the dynamic vegetation model Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS) is analyzed on skill of decadal predictions in the fully coupled atmosphere–land–ocean–sea ice model, the European Consortium Earth System Model (EC-Earth). Similar to the impact of initializing the model with the observed oceanic state, initializing the leaf area index (LAI) fields obtained from an offline LPJ-GUESS simulation forced by the observed atmospheric state leads to a systematic drift. A different treatment of the water and soil moisture budget in LPJ-GUESS is a likely cause of this drift. The coupled system reduces the cold bias of the reference model over land by reducing LAI (and the associated evaporative cooling), particularly outside the growing season. The coupling with the interactive vegetation module implies more degrees of freedom in the coupled model, which generates more noise that can mask a portion of the extra signal that is generated. The forecast reliability improves marginally, particularly early in the forecast. Ranked probability skill scores are also improved slightly in most areas analyzed, but the signal is not fully coherent over the forecast interval because of the relatively low number of ensemble members. Methods to remove the LAI drift and allow coupling of other variables probably need to be implemented before significant forecast skill can be expected.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    RVK:
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2014
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 2
    Online Resource
    Online Resource
    Stockholm University Press ; 2014
    In:  Tellus B: Chemical and Physical Meteorology Vol. 66, No. 1 ( 2014-01-01), p. 23037-
    In: Tellus B: Chemical and Physical Meteorology, Stockholm University Press, Vol. 66, No. 1 ( 2014-01-01), p. 23037-
    Type of Medium: Online Resource
    ISSN: 1600-0889 , 0280-6509
    RVK:
    RVK:
    Language: Unknown
    Publisher: Stockholm University Press
    Publication Date: 2014
    detail.hit.zdb_id: 2026992-4
    detail.hit.zdb_id: 246061-0
    SSG: 16,13
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 3
    Online Resource
    Online Resource
    Wiley ; 2014
    In:  Quarterly Journal of the Royal Meteorological Society Vol. 140, No. 684 ( 2014-10), p. 2353-2363
    In: Quarterly Journal of the Royal Meteorological Society, Wiley, Vol. 140, No. 684 ( 2014-10), p. 2353-2363
    Abstract: To evaluate the effect of sampling frequency on the global monthly mean aerosol optical thickness (AOT), we use 6 years of geographical coordinates of Moderate Resolution Imaging Spectroradiometer (MODIS) L2 aerosol data, daily global aerosol fields generated by the Goddard Institute for Space Studies General Circulation Model and the chemical transport models Global Ozone Chemistry Aerosol Radiation and Transport, Spectral Radiation‐transport Model for Aerosol Species and Transport Model 5, at a spatial resolution between 1.125°× 1.125° and 2°× 3°: the analysis is restricted to 60°S–60°N geographical latitude. We found that, in general, the MODIS coverage causes an underestimate of the global mean AOT over the ocean. The long‐term mean absolute monthly difference between all and dark target (DT) pixels was 0.01–0.02 over the ocean and 0.03–0.09 over the land, depending on the model dataset. Negative DT biases peak during boreal summers, reaching 0.07–0.12 (30–45% of the global long‐term mean AOT). Addition of the Deep Blue pixels tempers the seasonal dependence of the DT biases and reduces the mean AOT difference over land by 0.01–0.02. These results provide a quantitative measure of the effect the pixel exclusion due to cloud contamination, ocean sun‐glint and land type has on the MODIS estimates of the global monthly mean AOT. We also simulate global monthly mean AOT estimates from measurements provided by pixel‐wide along‐track instruments such as the Aerosol Polarimetry Sensor and the Cloud–Aerosol LiDAR with Orthogonal Polarization. We estimate the probable range of the global AOT standard error for an along‐track sensor to be 0.0005–0.0015 (ocean) and 0.0029–0.01 (land) or 0.5–1.2% and 1.1–4% of the corresponding global means. These estimates represent errors due to sampling only and do not include potential retrieval errors. They are smaller than or comparable to the published estimate of 0.01 as being a climatologically significant change in the global mean AOT, suggesting that sampling density is unlikely to limit the use of such instruments for climate applications at least on a global, monthly scale.
    Type of Medium: Online Resource
    ISSN: 0035-9009 , 1477-870X
    URL: Issue
    RVK:
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2014
    detail.hit.zdb_id: 3142-2
    detail.hit.zdb_id: 2089168-4
    SSG: 14
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...