We propose to quantify the climate sensitivity of the mean specific balance B of a glacier by a seasonal sensitivity characteristic (g). The SSC gives the dependence of B on monthly anomalies in temperature and precipitation. It is calculated from a mass-balance model. We show and discuss examples for Franz-Josef Glacier (New Zealand), Nigardsbreen (Norway), Hintereisferner (Austria), Peyto Glacier (Canadian Rockies), Abramov Glacier (Kirghizstan) and White Glacier (Canadian Arctic).With regard to the climate sensitivity of B, the gs clearly show that summer temperature is the most important factor for glaciers in a dry climate. For glaciers in a wetter climate, spring and fall temperatures also make a significant contribution to the overall sensitivity. The g is a 2612 matrix. Multiplying it with monthly perturbations of temperature and precipitation for a particular year yields an estimate of the balance for that year.We show that, with this technique, mass-balance series can be (re)constructed from long meteorological records or from output of atmospheric models.

[1] We investigate the interpretation of tree-ring data using the Vaganov-Shashkin forward model of tree-ring formation. This model is derived from principles of conifer wood growth, and explicitly incorporates a nonlinear daily timescale model of the multivariate environmental controls on tree-ring growth. The model results are shown to be robust with respect to primary moisture and temperature parameter choices. When applied to the simulation of tree-ring widths from North America and Russia from the Mann et al. (1998) and Vaganov et al. (2006) data sets, the forward model produces skill on annual and decadal timescales which is about the same as that achieved using classical dendrochronological statistical modeling techniques. The forward model achieves this without site-by-site tuning as is performed in statistical modeling. The results support the interpretation of this broad-scale network of tree-ring width chronologies primarily as climate proxies for use in statistical paleoclimatic field reconstructions, and point to further applications in climate science.

A process-oriented modeling approach is applied in order to simulate glacier mass balance for individual glaciers using statistically downscaled general circulation models (GCMs). Glacier-specific seasonal sensitivity characteristics based on a mass balance model of intermediate complexity are used to simulate mass balances of Nigardsbreen (Norway) and Rhonegletscher (Switzerland). Simulations using reanalyses (ECMWF) for the period 1979-93 are in good agreement with in situ mass balance measurements for Nigardsbreen. The method is applied to multicentury integrations of coupled (ECHAM4/OPYC) and mixed-layer (ECHAM4/MLO) GCMs excluding external forcing. A high correlation between decadal variations in the North Atlantic oscillation (NAO) and mass balance of the glaciers is found. The dominant factor for this relationship is the strong impact of winter precipitation associated with the NAO. A high NAO phase means enhanced (reduced) winter precipitation for Nigardsbreen (Rhonegletscher), typically leading to a higher (lower) than normal annual mass balance. This mechanism, entirely due to internal variations in the climate system, can explain observed strong positive mass balances for Nigardsbreen and other maritime Norwegian glaciers within the period 1980-95. It can also partly be responsible for recent strong negative mass balances of Alpine glaciers.

NowCastMIX is the core nowcasting guidance system at the German Weather Service. It automatically monitors several systems to capture rapidly developing high-impact mesoscale convective events, including 3D radar volume scanning, radar-based cell tracking and extrapolation, lightning detection, calibrated precipitation extrapolations, NWP, and live surface station reports. Within the context of the larger warning decision support process AutoWARN, NowCastMIX integrates the input data into a high-resolution analysis, based on a fuzzy logic approach for thunderstorm categorization and extrapolation, to provide an optimized warning solution with a 5-min update cycle for lead times of up to 1 h. Feature tracking is undertaken to optimize the direction of warning polygons, allowing individual, tangentially moving cells or cell clusters to be tracked explicitly. An adaptive ensemble clustering is deployed to reduce the spatial complexity of the resulting warning fields and smooth noisy temporal variations to a manageable level for duty forecasters. Further specialized outputs for civil aviation and for a public mobile phone warning app are generated. Now in its eighth year of operation, a comprehensive and complete set of thunderstorm analyses and nowcasts over Germany has been created, which is of unique value for ongoing research and development efforts for improving the system, as well as for addressing climatological aspects of severe convection. Verification has shown that NowCastMIX has helped to significantly improve the quality of the official warnings for severe convective weather events when used within the AutoWARN process.