Abstract. The potential of weather radar observations for hydrological and meteorological research and applications is undisputed, particularly with increasing world-wide radar coverage. However, several barriers impede the use of weather radar data. These barriers are of both scientific and technical nature. The former refers to inherent measurement errors and artefacts, the latter to aspects such as reading specific data formats, geo-referencing, visualisation. The radar processing library wradlib is intended to lower these barriers by providing a free and open source tool for the most important steps in processing weather radar data for hydro-meteorological and hydrological applications. Moreover, the community-based development approach of wradlib allows scientists to share their knowledge about efficient processing algorithms and to make this knowledge available to the weather radar community in a transparent, structured and well-documented way.

The potential of weather radar observations for hydrological and meteorological research and applications is undisputed, particularly with increasing world-wide radar coverage. However, several barriers impede the use of weather radar data. These barriers are of both scientific and technical nature. The former refers to inherent measurement errors and artefacts, the latter to aspects such as reading specific data formats, geo-referencing, visualisation. The radar processing library wradlib is intended to lower these barriers by providing a free and open source tool for the most important steps in processing weather radar data for hydro-meteorological and hydrological applications. Moreover, the community-based development approach of wradlib allows scientists to share their knowledge about efficient processing algorithms and to make this knowledge available to the weather radar community in a transparent, structured and well-documented way

Rainfall-induced attenuation is a major source of underestimation for radar-based precipitation estimation at C-band. Unconstrained gate-bygate correction procedures are known to be inherently unstable and thus not suited for unsupervised attenuation correction. In this study, we evaluate three different procedures to constrain gate-by-gate attenuation correction using reflectivity as the only input. These procedures are benchmarked against rainfall estimates from uncorrected radar data, using six years of radar observations from the single-polarized C-band radar in South-West Germany. The precipitation estimation error is obtained by comparing the radar-based estimates to rain gauge observations. All attenuation correction procedures benchmarked in this study lead to an effective improvement of precipitation estimation. The first method caps the corrections if the rain intensity increase exceeds a factor of two. The second method decreases the parameters of the attenuation correction iteratively for every radar beam calculation until attaining a stability criterion. The second method outperforms the first method and leads to a consistent distribution of path-integrated attenuation along the radar beam. As a third method, we propose a slight modification of Kraemer's approach which allows users to exert better control over attenuation correction by introducing an additional constraint that prevents unplausible corrections in cases of dramatic signal losses.

Abstract. Infrastructure built on perennially frozen ice-rich ground relies heavily on thermally stable subsurface conditions. Climate-warming-induced deepening of ground thaw puts such infrastructure at risk of failure. For better assessing the risk of large-scale future damage to Arctic infrastructure, improved strategies for model-based approaches are urgently needed. We used the laterally coupled 1D heat conduction model CryoGrid3 to simulate permafrost degradation affected by linear infrastructure. We present a case study of a gravel road built on continuous permafrost (Dalton highway, Alaska) and forced our model under historical and strong future warming conditions (following the RCP8.5 scenario). As expected, the presence of a gravel road in the model leads to higher net heat flux entering the ground compared to a reference run without infrastructure and thus a higher rate of thaw. Further, our results suggest that road failure is likely a consequence of lateral destabilisation due to talik formation in the ground beside the road rather than a direct consequence of a top-down thawing and deepening of the active layer below the road centre. In line with previous studies, we identify enhanced snow accumulation and ponding (both a consequence of infrastructure presence) as key factors for increased soil temperatures and road degradation. Using differing horizontal model resolutions we show that it is possible to capture these key factors and their impact on thawing dynamics with a low number of lateral model units, underlining the potential of our model approach for use in pan-Arctic risk assessments. Our results suggest a general two-phase behaviour of permafrost degradation: an initial phase of slow and gradual thaw, followed by a strong increase in thawing rates after the exceedance of a critical ground warming. The timing of this transition and the magnitude of thaw rate acceleration differ strongly between undisturbed tundra and infrastructure-affected permafrost ground. Our model results suggest that current model-based approaches which do not explicitly take into account infrastructure in their designs are likely to strongly underestimate the timing of future Arctic infrastructure failure. By using a laterally coupled 1D model to simulate linear infrastructure, we infer results in line with outcomes from more complex 2D and 3D models, but our model's computational efficiency allows us to account for long-term climate change impacts on infrastructure from permafrost degradation. Our model simulations underline that it is crucial to consider climate warming when planning and constructing infrastructure on permafrost as a transition from a stable to a highly unstable state can well occur within the service lifetime (about 30 years) of such a construction. Such a transition can even be triggered in the coming decade by climate change for infrastructure built on high northern latitude continuous permafrost that displays cold and relatively stable conditions today.

Abstract. From 6 to 9 August 2012, intense rainfall hit the northern Philippines, causing massive floods in Metropolitan Manila and nearby regions. Local rain gauges recorded almost 1000 mm within this period. However, the recently installed Philippine network of weather radars suggests that Metropolitan Manila might have escaped a potentially bigger flood just by a whisker, since the centre of mass of accumulated rainfall was located over Manila Bay. A shift of this centre by no more than 20 km could have resulted in a flood disaster far worse than what occurred during Typhoon Ketsana in September 2009.

Abstract. Infrastructure built on perennially frozen ice-rich ground relies heavily on thermally stable subsurface conditions. Climate warming-induced deepening of ground thaw puts such infrastructure at risk of failure. For better assessing the risk of large-scale future damage to Arctic infrastructure, improved strategies for model-based approaches are urgently needed. We used the laterally-coupled one-dimensional heat conduction model CryoGrid3 to simulate permafrost degradation affected by linear infrastructure. We present a case study of a gravel road built on continuous permafrost (Dalton highway, Alaska) and forced our model under historical and strong future warming conditions (following the RCP8.5 scenario). As expected, the presence of a gravel road in the model leads to higher net heat flux entering the ground compared to a reference run without infrastructure, and thus a higher rate of thaw. Further, our results suggest that road failure is likely a consequence of lateral destabilization due to talik formation in the ground beside the road, rather than a direct consequence of a top-down thawing and deepening of the active layer below the road centre. In line with previous studies, we identify enhanced snow accumulation and ponding (both a consequence of infrastructure presence) as key factors for increased soil temperatures and road degradation. Using differing horizontal model resolutions we show that it is possible to capture these key factors and their impact on thawing dynamics with a low number of lateral model units, underlining the potential of our model approach for use in pan-arctic risk assessments. Our results suggest a general two-phase behaviour of permafrost degradation: an initial phase of slow and gradual thaw, followed by a strong increase in thawing rates after exceedance of a critical ground warming. The timing of this transition and the magnitude of thaw rate acceleration differ strongly between undisturbed tundra and infrastructure-affected permafrost ground. Our model results suggest that current model-based approaches which do not explicitly take into account infrastructure in their designs are likely to strongly underestimate the timing of future Arctic infrastructure failure. By using a laterally-coupled one-dimensional model to simulate linear infrastructure, we infer results in line with outcomes from more complex 2D- and 3D-models, but our model's computational efficiency allows us to account for long-term climate change impacts on infrastructure from permafrost degradation. Our model simulations underline that it is crucial to consider climate warming when planning and constructing infrastructure on permafrost as a transition from a stable to a highly unstable state can well occur within the service life time (about 30 years) of such a construction. Such a transition can even be triggered in the coming decade by climate change for infrastructure built on high northern latitude continuous permafrost that displays cold and relatively stable conditions today.

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