Progress in space-borne studies of permafrost for climate science: Towards a multi-ECV approach

REMOTE SENSING OF ENVIRONMENT

卷:203

Article

Trofaier, Anna Maria^1,2  Westermann, Sebastian³  Bartsch, Annett^4,5 

[1] ECSAT, ESA Climate Off, Harwell Campus, Didcot OX11 OFD, Oxon, England

[2] Univ Ctr Svalbard, Svalbard Integrated Arct Earth Observing Syst SIO, POB 156, N-9171 Longyearbyen, Norway

[3] Univ Oslo, Dept Geosci, N-0316 Oslo, Norway

[4] Zentralanstalt Meteorol & Geodynam ZAMG, Hohe Warte 38, A-1190 Vienna, Austria

[5] Univ Vienna, Austrian Polar Res Inst, A-1010 Vienna, Austria

关键词: Permafrost;    ESA CCI;    EO CDR;   

DOI  :  10.1016/j.rse.2017.05.021

来源: Elsevier

【 摘 要 】

Remotely-sensed climate data records (CDRs) provide a basis for spatially distributed global climate model (GCM) inputs and validation methods. GCMs can take advantage of land surface models (LSMs), which aim to resolve surface energy, water and carbon budgets and hence these LSMs present important boundary conditions at the land-atmosphere interface. Pertinently, satellite data assimilation approaches are essential for improved land surface modelling for northern high latitudes ecosystems where permafrost degradation is reported to be ongoing. Permafrost, however, is an Essential Climate Variable (ECV) that cannot directly be monitored from space. Here, we advocate that CDRs, such as those compiled under the European Space Agency (ESA) Climate Change Initiative (CCI) programme, may be used in combination with permafrost models to improve our understanding of permafrost extent and degradation in a changing climate system. We describe the current types of remotely-sensed surface feature products that are widely used as indicators for permafrost related features. Furthermore, we highlight issues of using these site-specific permafrost proxies related to spatial scale, as well as the uncertainties in establishing present-day permafrost extent itself. Our assessment of the key ECVs that impact on permafrost, demonstrates how models that incorporate EO CDRs have the potential to boost our knowledge of permafrost conditions through better parametrisation of the thermal regime of permafrost soils. (C) 2017 The Authors. Published by Elsevier Inc.

【 授权许可】

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