Earth System Science: Bridging the Gaps between Disciplines: by Gerrit Lohmann, Klaus Grosfeld, Dieter Wolf-Gladrow, Vikram

By Gerrit Lohmann, Klaus Grosfeld, Dieter Wolf-Gladrow, Vikram Unnithan, Justus Notholt, Anna Wegner

Earth method technological know-how is characteristically cut up into a variety of disciplines (Geology, Physics, Meteorology, Oceanography, Biology etc.) and several other sub-disciplines. total, the variety of workmanship presents an effective base for interdisciplinary examine. even if, gaining holistic insights into the Earth process calls for the combination of observations, paleoclimate info, research instruments and modeling. those various ways of Earth approach technology are rooted in a variety of disciplines that lower throughout a large diversity of timescales. it truly is, hence, essential to hyperlink those disciplines at a comparatively early degree in PhD courses. The linking of ‘data and modeling’, because it is the distinctive emphasis in our graduate institution, permits graduate scholars from quite a few disciplines to cooperate and alternate perspectives at the universal subject of Earth procedure technological know-how, which ends up in a greater realizing of tactics inside a world context.

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2007): • Its reduced dependency on the snow crystal shape allows better results as the crystals may have different shapes (columns, plates, fractals) of different reflection characteristics, where the shape information is not available a priori on large areas in polar regions. e. sun elevation down to 15°) allows applying the retrieval in polar regions where the sun is often low. 3 Validation Studies The SGSP-retrieved snow grain size has been validated with ground truth data from six different measurements campaigns.

9 Validation of the Snow Grain Size Retrieval 49 Fig. 21 Scatter plot of the SGSP-retrieved versus the ground-measured snow grain size for the 6 different data sets. Dots and error bars are local daily averages and their standard deviation. 4 Discussion and Conclusion The comparison of the SGSP-retrieved to the ground-measured snow grain size from the six ground truth data sets shows a good agreement. Most cases of larger differences are influenced by cirrus clouds, wet snow, surface hoar, or wind crust.

Furthermore, the ground measurements are point measurements, whereas one satellite pixel has a size of 500 9 500 m2 inside of which the snow may not be distributed homogeneously. In the Aoki et al. (2007) data set, measuring the microphysical snow grain size, the ground observations have a large spread at one site and day (large error bars in Fig. 21) and larger discrepancies to the SGSP-retrieved grain size. Therefore, ground measurements of the optical snow grain size are preferable for validating satellite retrievals.

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