1 / 10

Action B.2: Earth observation and data processing (SYKE, FMI)

Action B.2: Earth observation and data processing (SYKE, FMI). Objective: harmonized data sets on snow cover extent (SE), snow water equivalent (SWE), soil freeze and vegetation status from satellite information, which will be used ( i ) for model calibration (Action B4) and

jui
Download Presentation

Action B.2: Earth observation and data processing (SYKE, FMI)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Action B.2: Earth observation and data processing (SYKE, FMI) Objective: • harmonized data sets on snow cover extent (SE), snow water equivalent (SWE), soil freeze and vegetation status from satellite information, which will be used (i) for model calibration (Action B4) and (ii) for the retrieval and assessment of past changes in climate change indicators (e.g. the length of the growing season, changes in snow cover) (Action B4/ B6).

  2. Action B.2: Earth observation and data processing (FMI) • For Finland and surrounding regions (modeling domain), • 3 coarse resolution datasets (25 x 25km grid cells) will be provided: • Snow Water Equivalent (SWE)[mm] product (1979-2016) • Snow Extent [%] product (1979-2016) • Snow melt [day] data (1979-2016)

  3. Action B.2: Earth observation and data processing (SYKE+FMI) • For the Finnish area the following products will be generated from MODIS (0.0025/0.005 degree grid): • Fractional Snow Cover (FSC) [%] (2012-2016) • Normalized Difference Water Index (NDWI) (2012-2016) • Normalized Difference Vegetation Index (NDVI) (2012-2016) • Reduced Simple Ration (RSR) (2012-2016) • Growth season canopy Leaf Area Index (LAI) (2012-2016) • Photochemical Reflectance Index (PRI) (2012-2016) • Start and end of growing season [day] in forest ecosystems (2003-2016) • End of melting [day] (2003-2016)

  4. Action B.2: Earth observation and data processing (FMI) • For the Finnish area the following products will be generated: • Start of the soil freezing [day] from SMOS and ASAR data (2010-2016) at 25 km resolution if only passive SMOS data used and in 1 km resolution with combined used of ASAR active instrument. • Date for the final thawing of the soil surface layer (depth of layer depending on the soil type) at 25 km resolution, passive product only.

  5. Action B.2: Earth observation and data processing (SYKE, FMI) • Deliverables: • First data document by 30/04/2014 • Report on data comparison 15/12/2015 • Report on EO products and comparison with in situ data 31/03/2017 • Milestones: • New vegetation indices (RSR, PRI) implemented in processing system by 31/01/2014 • EO products for year 2013 processed by 31/03/2014 • Product delivery to Action B4 by 30/04/2014 • Comparison of time-series with in situ observations (Action B1 and B3) 30/11/2015 • EO products for years 2014-2015 processed 31/03/2016 • EO products for year 2016 processed and all data delivered 31/03/2017

  6. Action B.2.: Nexttasks • Milestone: New vegetation indices (RSR, PRI) implemented in processing system by 31/01/2014 • Photochemicalreflectanceindexcalculationimplementedby Saku Anttila for VACCIA projectbased on publicationbyDrolet et al. (2005) • Literaturereview and discussion with Uni Helsinki • ReducedSimpleRatio (Stenberg et al. 2004) for calculation of LAI • Discussion with Terhikki on implementation, atmosphericcorrection ? And time-resolution Drolet et al. (2005). A MODIS-derivedphotochemicalreflectanceindex to detectinter-annualvariations in the photosyntheticlight-useefficiency of a borealdecidousforest. RSE, 212-224. Stenberg, P., Rautiainen, M., Manninen, T., Voipio, P., & Smolander, S. (2004). Reduced simple ratio better than NDVI for estimating LAI in Finnish pine and spruce stands. Silva Fennica, 38, 3-14.

  7. Action B.2.: Next tasks • Milestone: EO products for year 2013 processed by 31/03/2014 • Basic products related to snow cover and vegetation indices • CryoLand (Copernicus service Snow and Land Ice) Fractional Snow Cover product? (http://neso.cryoland.enveo.at/cryoland/cryoclient/#) • Possibility to process simple vegetation indices (NDVI, NDWI) in FMI/Sodankylä?

  8. B3 In situ data B1 Webcams B2 Earth Observations Validation/ calibration - Phenological time-series and events Validation/ calibration - Snow and phenological observation B6 Uncertaintyassessment B4 Modelcalibration • Process calibration • Photosynthesis • Phenology • Hydrology Comparison with observations D1 Dissemination Indicator time-series and trends

  9. Link to Action B.4: Model calibration:

  10. http://www.esa-ghg-cci.org/?q=overview

More Related