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| Titel |
Uncertainty in Land Cover observations and its impact on near surface
climate |
| VerfasserIn |
Goran Georgievski, Stefan Hagemann |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250141947
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| Publikation (Nr.) |
 EGU/EGU2017-5508.pdf |
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| Zusammenfassung |
| Land Cover (LC) and its bio-geo-physical feedbacks are important for the understanding of
climate and its vulnerability to changes on the surface of the Earth. Recently ESA has
published a new LC map derived by combining remotely sensed surface reflectance and
ground-truth observations. For each grid-box at 300m resolution, an estimate of confidence is
provided. This LC data set can be used in climate modelling to derive land surface
boundary parameters for the respective Land Surface Model (LSM). However,
the ESA LC classes are not directly suitable for LSMs, therefore they need to be
converted into the model specific surface presentations. Due to different design and
processes implemented in various climate models they might differ in the treatment of
artificial, water bodies, ice, bare or vegetated surfaces. Nevertheless, usually vegetation
distribution in models is presented by means of plant functional types (PFT), which is a
classification system used to simplify vegetation representation and group different
vegetation types according to their biophysical characteristics. The method of LC
conversion into PFT is also called “cross-walking” (CW) procedure. The CW procedure
is another source of uncertainty, since it depends on model design and processes
implemented and resolved by LSMs. These two sources of uncertainty, (i) due to surface
reflectance conversion into LC classes, (ii) due to CW procedure, have been studied by
Hartley et al (2016) to investigate their impact on LSM state variables (albedo,
evapotranspiration (ET) and primary productivity) by using three standalone LSMs. The
present study is a follow up to that work and aims at quantifying the impact of these two
uncertainties on climate simulations performed with the Max Planck Institute for
Meteorology Earth System Model (MPI-ESM) using prescribed sea surface temperature
and sea ice. The main focus is on the terrestrial water cycle, but the impacts on
surface albedo, wind patterns, 2m temperatures, as well as plant productivity are also
examined.
The analysis of vegetation covered area indicates that the range of uncertainty might be
about the same order of magnitude as the estimated historical anthropogenic LC change. For
example, the area covered with managed grasses (crops and pasture in MPI-ESM PFT
classification) varies from 17 to 26 million km2, and area covered with trees ranges from 15
million km2 up to 51 million km2. These uncertainties in vegetation distribution lead to
noticeable variations in atmospheric temperature, humidity, cloud cover, circulation, and
precipitation as well as local, regional and global climate forcing. For example, the amount of
terrestrial ET ranges from 73 to 77 × 103 km3yr−1in MPI-ESM simulations and this range
has about the same order of magnitude as the current estimate of the reduction of annual ET
due to recent anthropogenic LC change. This and more impacts of LC uncertainty
on the near surface climate will be presented and discussed in the context of LC
change.
Hartley, A.J., MacBean, N., Georgievski, G., Bontemps, S.: Uncertainty in plant
functional type distributions and its impact on land surface models (in review with Remote
Sensing of Environment Special Issue) |
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