Melt ponds on Arctic sea ice determined from MODIS satellite data using an artificial neural network

In each case, time series are shown for the model bias (la- belled bias); the root-mean-squared difference (RMSD) be- tween the observations and the model background field (la-

The reconstructions are based on a multilinear regression of forecasted ice concentration, level ice thickness, ridge density, ice speed and an additional factor which is based,

Trends in the time series of annual mean MO dates indicate that MO is occurring earlier in the year for the majority of Arctic sea ice over the 1979–2012 data record

Available green biomass (NDVI) from Modis satellite data in May 2008 in the Mongolian-Russian border region. The red circle delineates the primary area where gazelles moved

The background colour shows the mean sea surface height computed from a free model run over the period 1993-1999; the gray colour shows land; the numbered boxes show regions used

To investigate the influence of snow depth, sea ice density, and area on sea ice thick- ness and volume estimates we use freeboard retrievals from ICESat, together with dif-

The present study investigates the possibil- ity of a relationship between the coastal topography with steep slopes and sea-salt snow chemistry, using high reso- lution data from

When we try different values for the ice temperature, snow density, and ice salinity (not shown here), we find that only the ice salinity impacts the modelled brightness