@article{KokhanovskyLamareDanneetal.2019,
  author    = {Kokhanovsky, Alexander and Lamare, Maxim and Danne, Olaf and Brockmann, Carsten and Dumont, Marie and Picard, Ghislain and Arnaud, Laurent and Favier, Vincent and Jourdain, Bruno and Le Meur, Emmanuel and Di Mauro, Biagio and Aoki, Teruo and Niwano, Masashi and Rozanov, Vladimir and Korkin, Sergey and Kipfstuhl, Sepp and Freitag, Johannes and Hoerhold, Maria and Zuhr, Alexandra and Vladimirova, Diana and Faber, Anne-Katrine and Steen-Larsen, Hans Christian and Wahl, Sonja and Andersen, Jonas K. and Vandecrux, Baptiste and van As, Dirk and Mankoff, Kenneth D. and Kern, Michael and Zege, Eleonora and Box, Jason E.},
  title     = {Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument},
  series = {Remote sensing},
  volume    = {11},
  journal   = {Remote sensing},
  number    = {19},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2072-4292},
  doi       = {10.3390/rs11192280},
  pages     = {43},
  year      = {2019},
  abstract  = {The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing. In this work, we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A/B measurements over clean and polluted snow fields. Using OLCI spectral reflectance measurements in the range 400-1020 nm, we derived important snow properties such as spectral and broadband albedo, snow specific surface area, snow extent and grain size on a spatial grid of 300 m. The algorithm also incorporated cloud screening and atmospheric correction procedures over snow surfaces. We present validation results using ground measurements from Antarctica, the Greenland ice sheet and the French Alps. We find the spectral albedo retrieved with accuracy of better than 3\% on average, making our retrievals sufficient for a variety of applications. Broadband albedo is retrieved with the average accuracy of about 5\% over snow. Therefore, the uncertainties of satellite retrievals are close to experimental errors of ground measurements. The retrieved surface grain size shows good agreement with ground observations. Snow specific surface area observations are also consistent with our OLCI retrievals. We present snow albedo and grain size mapping over the inland ice sheet of Greenland for areas including dry snow, melted/melting snow and impurity rich bare ice. The algorithm can be applied to OLCI Sentinel-3 measurements providing an opportunity for creation of long-term snow property records essential for climate monitoring and data assimilation studies-especially in the Arctic region, where we face rapid environmental changes including reduction of snow/ice extent and, therefore, planetary albedo.},
  language  = {en}
}
@article{SicardThammMaronaetal.2014,
  author    = {Sicard, Adrien and Thamm, Anna and Marona, Cindy and Lee, Young Wha and Wahl, Vanessa and Stinchcombe, John R. and Wright, Stephen I. and Kappel, Christian and Lenhard, Michael},
  title     = {Repeated evolutionary changes of leaf morphology caused by mutations to a homeobox gene},
  series = {Current biology},
  volume    = {24},
  journal   = {Current biology},
  number    = {16},
  publisher = {Cell Press},
  address   = {Cambridge},
  issn      = {0960-9822},
  doi       = {10.1016/j.cub.2014.06.061},
  pages     = {1880 -- 1886},
  year      = {2014},
  abstract  = {Elucidating the genetic basis of morphological changes in evolution remains a major challenge in biology [1-3]. Repeated independent trait changes are of particular interest because they can indicate adaptation in different lineages or genetic and developmental constraints on generating morphological variation [4-6]. In animals, changes to "hot spot" genes with minimal pleiotropy and large phenotypic effects underlie many cases of repeated morphological transitions [4-8]. By contrast, only few such genes have been identified from plants [8-11], limiting cross-kingdom comparisons of the principles of morphological evolution. Here, we demonstrate that the REDUCED COMPLEXITY (RCO) locus [12] underlies more than one naturally evolved change in leaf shape in the Brassicaceae. We show that the difference in leaf margin dissection between the sister species Capsella rubella and Capsella grandiflora is caused by cis-regulatory variation in the homeobox gene RCO-A, which alters its activity in the developing lobes of the leaf. Population genetic analyses in the ancestral C. grandiflora indicate that the more-active C. rubella haplotype is derived from a now rare or lost C. grandiflora haplotype via additional mutations. In Arabidopsis thaliana, the deletion of the RCO-A and RCO-B genes has contributed to its evolutionarily derived smooth leaf margin [12], suggesting the RCO locus as a candidate for an evolutionary hot spot. We also find that temperature-responsive expression of RCO-A can explain the phenotypic plasticity of leaf shape to ambient temperature in Capsella, suggesting a molecular basis for the well-known negative correlation between temperature and leaf margin dissection.},
  language  = {en}
}