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    Towards global empirical upscaling of FLUXNET eddy covariance observations: Validation of a model tree ensemble approach using a biosphere model
    (München : European Geopyhsical Union, 2009) Jung, M.; Reichstein, M.; Bondeau, A.
    Global, spatially and temporally explicit estimates of carbon and water fluxes derived from empirical up-scaling eddy covariance measurements would constitute a new and possibly powerful data stream to study the variability of the global terrestrial carbon and water cycle. This paper introduces and validates a machine learning approach dedicated to the upscaling of observations from the current global network of eddy covariance towers (FLUXNET). We present a new model TRee Induction ALgorithm (TRIAL) that performs hierarchical stratification of the data set into units where particular multiple regressions for a target variable hold. We propose an ensemble approach (Evolving tRees with RandOm gRowth, ERROR) where the base learning algorithm is perturbed in order to gain a diverse sequence of different model trees which evolves over time. We evaluate the efficiency of the model tree ensemble (MTE) approach using an artificial data set derived from the Lund-Potsdam-Jena managed Land (LPJmL) biosphere model. We aim at reproducing global monthly gross primary production as simulated by LPJmL from 1998–2005 using only locations and months where high quality FLUXNET data exist for the training of the model trees. The model trees are trained with the LPJmL land cover and meteorological input data, climate data, and the fraction of absorbed photosynthetic active radiation simulated by LPJmL. Given that we know the "true result" in the form of global LPJmL simulations we can effectively study the performance of the MTE upscaling and associated problems of extrapolation capacity. We show that MTE is able to explain 92% of the variability of the global LPJmL GPP simulations. The mean spatial pattern and the seasonal variability of GPP that constitute the largest sources of variance are very well reproduced (96% and 94% of variance explained respectively) while the monthly interannual anomalies which occupy much less variance are less well matched (41% of variance explained). We demonstrate the substantially improved accuracy of MTE over individual model trees in particular for the monthly anomalies and for situations of extrapolation. We estimate that roughly one fifth of the domain is subject to extrapolation while MTE is still able to reproduce 73% of the LPJmL GPP variability here. This paper presents for the first time a benchmark for a global FLUXNET upscaling approach that will be employed in future studies. Although the real world FLUXNET upscaling is more complicated than for a noise free and reduced complexity biosphere model as presented here, our results show that an empirical upscaling from the current FLUXNET network with MTE is feasible and able to extract global patterns of carbon flux variability.
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    Tobac 1.2: Towards a flexible framework for tracking and analysis of clouds in diverse datasets
    (Katlenburg-Lindau : Copernicus, 2019) Heikenfeld, Max; Marinescu, Peter J.; Christensen, Matthew; Watson-Parris, Duncan; Senf, Fabian; van den Heever, Susan C.; Stier, Philip
    We introduce tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing individual clouds in different types of datasets, such as cloud-resolving model simulations and geostationary satellite retrievals. The software has been designed to be used flexibly with any two-or three-dimensional timevarying input. The application of high-level data formats, such as Iris cubes or xarray arrays, for input and output allows for convenient use of metadata in the tracking analysis and visualisation. Comprehensive analysis routines are provided to derive properties like cloud lifetimes or statistics of cloud properties along with tools to visualise the results in a convenient way. The application of tobac is presented in two examples. We first track and analyse scattered deep convective cells based on maximum vertical velocity and the threedimensional condensate mixing ratio field in cloud-resolving model simulations. We also investigate the performance of the tracking algorithm for different choices of time resolution of the model output. In the second application, we show how the framework can be used to effectively combine information from two different types of datasets by simultaneously tracking convective clouds in model simulations and in geostationary satellite images based on outgoing longwave radiation. The tobac framework provides a flexible new way to include the evolution of the characteristics of individual clouds in a range of important analyses like model intercomparison studies or model assessment based on observational data. © 2019 Author(s).
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    Ground-penetrating radar insight into a coastal aquifer: the freshwater lens of Borkum Island
    (Munich : EGU, 2013) Igel, J.; Günther, T.; Kuntzer, M.
    Freshwater lenses, as important resource for drinking water, are sensitive to climate changes and sea level rise. To simulate this impact on the groundwater systems, hydraulic subsurface models have to be designed. Geophysical techniques can provide information for generating realistic models. The aim of our work is to show how ground-penetrating radar (GPR) investigations can contribute to such hydrological simulations. In the pilot area, Borkum island, GPR was used to map the shape of the groundwater table (GWT) and to characterise the aquifer. In total, 20 km of constant offset (CO) profiles were measured with centre frequencies of 80 and 200 MHz. Wave velocities were determined by common midpoint (CMP) measurements and vertical radar profiling (VRP) in a monitoring well. The 80 MHz CO data show a clear reflection at the groundwater table, whereas the reflection is weaker for the 200 MHz data. After correcting the GPR water tables for the capillary rise, they are in good accordance with the pressure heads of the observation wells in the area. In the centre of the island, the groundwater table is found up to 3.5 m above sea level, however it is lower towards the coastline and marshland. Some local depressions are observed in the region of dune valleys and around pumping stations of the local water supplier. GPR also reveals details within the sediments and highly-permeable aeolian sands can be distinguished from less-permeable marine sediments. Further, a silt loam layer below the water table could be mapped on a large area. The reflection characteristics indicates scattered erosion channels in this layer that cause it to be an aquitard with some leakage. GPR provides a high resolution map of the groundwater table and insight into the stratigraphy of the sediments and their hydraulic properties. This is valuable complementary information to the observation of sparsely distributed monitoring wells as input to hydraulic simulation.
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    Heinrich event 1: An example of dynamical ice-sheet reaction to oceanic changes
    (München : European Geopyhsical Union, 2011) Álvarez-Solas, J.; Montoya, M.; Ritz, C.; Ramstein, G.; Charbit, S.; Dumas, C.; Nisancioglu, K.; Dokken, T.; Ganopolski, A.
    Heinrich events, identified as enhanced ice-rafted detritus (IRD) in North Atlantic deep sea sediments (Heinrich, 1988; Hemming, 2004) have classically been attributed to Laurentide ice-sheet (LIS) instabilities (MacAyeal, 1993; Calov et al., 2002; Hulbe et al., 2004) and assumed to lead to important disruptions of the Atlantic meridional overturning circulation (AMOC) and North Atlantic deep water (NADW) formation. However, recent paleoclimate data have revealed that most of these events probably occurred after the AMOC had already slowed down or/and NADW largely collapsed, within about a thousand years (Hall et al., 2006; Hemming, 2004; Jonkers et al., 2010; Roche et al., 2004), implying that the initial AMOC reduction could not have been caused by the Heinrich events themselves. Here we propose an alternative driving mechanism, specifically for Heinrich event 1 (H1; 18 to 15 ka BP), by which North Atlantic ocean circulation changes are found to have strong impacts on LIS dynamics. By combining simulations with a coupled climate model and a three-dimensional ice sheet model, our study illustrates how reduced NADW and AMOC weakening lead to a subsurface warming in the Nordic and Labrador Seas resulting in rapid melting of the Hudson Strait and Labrador ice shelves. Lack of buttressing by the ice shelves implies a substantial ice-stream acceleration, enhanced ice-discharge and sea level rise, with peak values 500–1500 yr after the initial AMOC reduction. Our scenario modifies the previous paradigm of H1 by solving the paradox of its occurrence during a cold surface period, and highlights the importance of taking into account the effects of oceanic circulation on ice-sheets dynamics in order to elucidate the triggering mechanism of Heinrich events.
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    High-resolution numerical modeling of mesoscale island wakes and sensitivity to static topographic relief data
    (München : European Geopyhsical Union, 2015) Nunalee, C.G.; Horváth, Á.; Basu, S.
    Recent decades have witnessed a drastic increase in the fidelity of numerical weather prediction (NWP) modeling. Currently, both research-grade and operational NWP models regularly perform simulations with horizontal grid spacings as fine as 1 km. This migration towards higher resolution potentially improves NWP model solutions by increasing the resolvability of mesoscale processes and reducing dependency on empirical physics parameterizations. However, at the same time, the accuracy of high-resolution simulations, particularly in the atmospheric boundary layer (ABL), is also sensitive to orographic forcing which can have significant variability on the same spatial scale as, or smaller than, NWP model grids. Despite this sensitivity, many high-resolution atmospheric simulations do not consider uncertainty with respect to selection of static terrain height data set. In this paper, we use the Weather Research and Forecasting (WRF) model to simulate realistic cases of lower tropospheric flow over and downstream of mountainous islands using the default global 30 s United States Geographic Survey terrain height data set (GTOPO30), the Shuttle Radar Topography Mission (SRTM), and the Global Multi-resolution Terrain Elevation Data set (GMTED2010) terrain height data sets. While the differences between the SRTM-based and GMTED2010-based simulations are extremely small, the GTOPO30-based simulations differ significantly. Our results demonstrate cases where the differences between the source terrain data sets are significant enough to produce entirely different orographic wake mechanics, such as vortex shedding vs. no vortex shedding. These results are also compared to MODIS visible satellite imagery and ASCAT near-surface wind retrievals. Collectively, these results highlight the importance of utilizing accurate static orographic boundary conditions when running high-resolution mesoscale models.
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    Recurrence analysis of extreme event-like data
    (Katlenburg-Lindau : European Geophysical Society, 2021) Banerjee, Abhirup; Goswami, Bedartha; Hirata, Yoshito; Eroglu, Deniz; Merz, Bruno; Kurths, Jürgen; Marwan, Norbert
    The identification of recurrences at various timescales in extreme event-like time series is challenging because of the rare occurrence of events which are separated by large temporal gaps. Most of the existing time series analysis techniques cannot be used to analyze an extreme event-like time series in its unaltered form. The study of the system dynamics by reconstruction of the phase space using the standard delay embedding method is not directly applicable to event-like time series as it assumes a Euclidean notion of distance between states in the phase space. The edit distance method is a novel approach that uses the point-process nature of events. We propose a modification of edit distance to analyze the dynamics of extreme event-like time series by incorporating a nonlinear function which takes into account the sparse distribution of extreme events and utilizes the physical significance of their temporal pattern. We apply the modified edit distance method to event-like data generated from point process as well as flood event series constructed from discharge data of the Mississippi River in the USA and compute their recurrence plots. From the recurrence analysis, we are able to quantify the deterministic properties of extreme event-like data. We also show that there is a significant serial dependency in the flood time series by using the random shuffle surrogate method.