Presentation on theme: "Objective: ●harmonized data sets on snow cover extent (SE), snow water equivalent (SWE), soil freeze and vegetation status from satellite information,"— Presentation transcript:
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). 1 Action B.2: Earth observation and data processing (SYKE, FMI)
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 ( ) Snow Extent [%] product ( ) Snow melt [day] data ( )
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) [%] ( ) ●Normalized Difference Water Index (NDWI) ( ) ●Normalized Difference Vegetation Index (NDVI) ( ) ●Reduced Simple Ration (RSR) ( ) ●Growth season canopy Leaf Area Index (LAI) ( ) ●Photochemical Reflectance Index (PRI) ( ) ●Start and end of growing season [day] in forest ecosystems ( ) ●End of melting [day] ( )
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 ( ) 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 processed 31/03/2016 ●EO products for year 2016 processed and all data delivered 31/03/2017
●Milestone: New vegetation indices (RSR, PRI) implemented in processing system by 31/01/2014 o Photochemical reflectance index calculation implemented by Saku Anttila for VACCIA project based on publication by Drolet et al. (2005) o Literature review and discussion with Uni Helsinki o Reduced Simple Ratio (Stenberg et al. 2004) for calculation of LAI o Discussion with Terhikki on implementation, atmospheric correction ? And time-resolution 6 Action B.2.: Next tasks Drolet et al. (2005). A MODIS-derived photochemical reflectance index to detect inter-annual variations in the photosynthetic light-use efficiency of a boreal decidous forest. RSE, 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.
●Milestone: EO products for year 2013 processed by 31/03/2014 o Basic products related to snow cover and vegetation indices o CryoLand (Copernicus service Snow and Land Ice) Fractional Snow Cover product? (http://neso.cryoland.enveo.at/cryoland/cryoclient/#)http://neso.cryoland.enveo.at/cryoland/cryoclient/# o Possibility to process simple vegetation indices (NDVI, NDWI) in FMI/Sodankylä? 7 Action B.2.: Next tasks
B4 Model calibration B1 Webcams B2 Earth Observations B3 In situ data B6 Uncertainty assessment D1 Dissemination Validation/ calibration - Snow and phenological observation Validation/ calibration - Phenological time-series and events Process calibration -Photosynthesis -Phenology -Hydrology Comparison with observations Indicator time-series and trends