Gerd Bürger

Climate change scenarios and runoff response in the Mulde catchment (Southern Elbe, Germany)

The impact of a climate change scenario on regional climate conditions and runoff characteristics has been investigated for the Mulde catchment, a meso-scale sub-basin of the Elbe in Germany. First, the semi-distributed, conceptual model HBV-D has been successfully applied to simulate discharge for present climate conditions. Further, the expanded downscaling method (EDS) was calibrated and applied to observed global circulation fields in order to produce local climate input data for HBV-D. Finally, the coupled atmosphere-ocean model ECHAM4/OPYC3, driven by a climate change scenario, provided simulated global circulation patterns for application with EDS. The regionalised scenario conditions then served as input to HBV-D in order to investigate the impact of global climate change on regional hydrology. The results indicate that an obvious increase in temperature is accompanied by a clear tendency to reduced precipitation over the investigated area for the next 100 years. These conditions lead to a decrease in simulated mean discharges of the Mulde. The study is considered to be a contribution for regional impact studies on global climate change. At the same time, it demonstrates existing shortcomings and limitations of current climate impact research.

Downscaling Extremes—An Intercomparison of Multiple Statistical Methods for Present Climate

AbstractFive statistical downscaling methods [automated regression-based statistical downscaling (ASD), bias correction spatial disaggregation (BCSD), quantile regression neural networks (QRNN), TreeGen (TG), and expanded downscaling (XDS)] are compared with respect to representing climatic extremes. The tests are conducted at six stations from the coastal, mountainous, and taiga region of British Columbia, Canada, whose climatic extremes are measured using the 27 Climate Indices of Extremes (ClimDEX; http://www.climdex.org/climdex/index.action) indices. All methods are calibrated from data prior to 1991, and tested against the two decades from 1991 to 2010. A three-step testing procedure is used to establish a given method as reliable for any given index. The first step analyzes the sensitivity of a method to actual index anomalies by correlating observed and NCEP-downscaled annual index values; then, whether the distribution of an index corresponds to observations is tested. Finally, this latter test is...

Impact of climate change on slope stability using expanded downscaling

Abstract Climate parameters affecting ground water and pore pressure fluctuations can, in many cases, trigger slope instability and hence landslide activity. Global warming due to the greenhouse effect and especially changes in precipitation patterns and air temperature might therefore have influences on future landslide activity. The present paper shows an assessment of climate change consequences for displacement rates of a mudslide in the Dolomites, Italy. The study is based on climate projections of a general circulation model (GCM). GCMs are able to succesfully reproduce large-scale patterns of climate, while they show a poor performance on the regional scale. Therefore, GCM output is postprocessed with a statistical downscaling technique to derive local-scale climate change information from simulated atmospheric circulation patterns of the European–North Atlantic sector. The resulting precipitation and temperature series are introduced in a hydrological tank model, which calculates daily groundwater levels. Based on the groundwater data, a visco-plastic rheological model is applied to derive displacement rates of the mudslide as final output. The climate change signal is most pronounced for air temperature, while it is weaker but still significant for yearly precipitation, which is decreasing. As a consequence, yearly displacement rates show a significant reduction. The most dramatic changes, however, occur in spring with strongly lowered groundwater levels and consequently decreasing displacement rates. This is seen as an effect of reduced storage of winter precipitation as snow and hence decreasing meltwater amounts in early spring. The presented model chain with statistical downscaling, hydrological and rheological models allows the assessment of future landslide displacement affected by the greenhouse effect. The results, however, have to be taken with caution since in all parts of the model chain there are uncertainties that are difficult to address.

Downscaling Extremes: An Intercomparison of Multiple Methods for Future Climate

AbstractThis study follows up on a previous downscaling intercomparison for present climate. Using a larger set of eight methods the authors downscale atmospheric fields representing present (1981–2000) and future (2046–65) conditions, as simulated by six global climate models following three emission scenarios. Local extremes were studied at 20 locations in British Columbia as measured by the same set of 27 indices, ClimDEX, as in the precursor study. Present and future simulations give 2 × 3 × 6 × 8 × 20 × 27 = 155 520 index climatologies whose analysis in terms of mean change and variation is the purpose of this study. The mean change generally reinforces what is to be expected in a warmer climate: that extreme cold events become less frequent and extreme warm events become more frequent, and that there are signs of more frequent precipitation extremes. There is considerable variation, however, about this tendency, caused by the influence of scenario, climate model, downscaling method, and location. Th...

Selected precipitation scenarios across Europe

Abstract We report results of the project, European River Flood Occurrence and Total Risk Assessment System (EUROTAS), which was aimed at assessing the risk of current and future floodings for Europe, including the effects of climatic change. With respect to the latter, precipitation scenarios have been derived from a global climate model using the method of expanded downscaling (EDS), and regionalized for the catchment of the river Pinios (Greece). Jizera (Cechia), Saar (Germany), and Thames (UK). We present both the climate change information conveyed by the scenarios and an assessment about its statistical significance. For this report, all simulations were rerun using an improved EDS model version. Most notably, the inclusion of atmospheric humidity to the set of global predictor fields helped reducing the underlying uncertainty of the results. When driven by observed atmospheric fields (analyses), the EDS model performed in most cases satisfactorily, as it reproduced the larger precipitation clusters with good accuracy. To evaluate the precipitation scenarios, a statistical test was applied that compared what we defined as ‘current climate’ with the ‘changed climate’ of the scenario. To define current climate, local precipitation observations were used together with EDS regionalizations of the analyses and of a climate model control simulation. It turned out that in spite of the considerable uncertainty stemming from model errors and, more importantly, natural variability, a significant redistribution of rainfall is projected. Specifically, the scenarios show a decay of rainfall frequency for all catchments, which for Pinios leads to an overall negative water balance. This is accompanied, and for the other catchments outweighed, by a strong rainfall intensification. For the latter, we provide a more detailed extreme value analysis. We emphasize that the results should be interpreted with caution and not overemphasized quantitatively. Scenarios of precipitation are still of prototype nature and under steady development.

Towards Subdaily Rainfall Disaggregation via Clausius-Clapeyron

AbstractTwo lines of research are combined in this study: first, the development of tools for the temporal disaggregation of precipitation, and second, some newer results on the exponential scaling of heavy short-term precipitation with temperature, roughly following the Clausius–Clapeyron (CC) relation. Having no extra temperature dependence, the traditional disaggregation schemes are shown to lack the crucial CC-type temperature dependence. The authors introduce a proof-of-concept adjustment of an existing disaggregation tool, the multiplicative cascade model of Olsson, and show that, in principal, it is possible to include temperature dependence in the disaggregation step, resulting in a fairly realistic temperature dependence of the CC type. They conclude by outlining the main calibration steps necessary to develop a full-fledged CC disaggregation scheme and discuss possible applications.

Comment on "The Spatial Extent of 20th-Century Warmth in the Context of the Past 1200 Years"

Osborn and Briffa (Reports, 10 February 2006, p. 841) identified anomalous periods of warmth or cold in the Northern Hemisphere that were synchronous across 14 temperature-sensitive proxies. However, their finding that the spatial extent of 20th-century warming is exceptional ignores the effect of proxy screening on the corresponding significance levels. After appropriate correction, the significance of the 20th-century warming anomaly disappears.

Climate change impacts on river flooding: A modelling study of three meso-scale catchments

Whether the high number of river flood disasters in recent years in different European countries and many other areas of the globe are triggered or worsened by human activities has been the subject of a great deal of debate. Possible anthropogenic activities leading to increased flood risk include river regulation measures, intensified land use and forestry, and emissions of greenhouse gases causing a change in the global climate. This article discusses the latter by presenting modelling studies of three meso-scale catchments in Germany. These catchments represent different conditions of land-use, landscape morphology and climate type, therefore showing different dominating flood generation processes. The results of the case studies show how changes of temperature and rainfall regime can lead to significant changes in flood risk. A development towards both an increase or a decrease of the frequency and/or magnitude of flood events is possible, depending mainly on the altered timing of snow accumulation and snowmelt and of a possible shift in rainfall seasonality and intensity.

Complex Principal Oscillation Pattern Analysis

Abstract Complex principal oscillation pattern (CPOP) analysis is introduced as an extension of conventional POP analysis. Both are intended to resolve regular evolving patterns from processes with many degrees of freedom. While POP analysis, like many other techniques, deals with the concept of the system state as a real vector, it is argued that this notion be extended into the complex domain. The approach used here results from a critical review of the theory of linear systems of first order. It turns out that these systems cannot appropriately model standing oscillations. The notion of the traveling rate of a mode is defined, and it is demonstrated that the modes frequency and traveling rate are directly coupled via the system matrix. One consequence is that clean standing oscillations cannot be modeled by linear systems of first order. CPOP analysis introduces a new vector of state. By defining the complex state “state + i · momentum,” both the conventional state itself and its momentum are simultan...

The detectability of climate engineering

We assess the detection and attribution (D&A) of climate engineering (CE) as a function of their duration after initiation. We employ “surrogate” climates where observations are mimicked by simulations. Unlike classical, stationary D&A, the null hypothesis for this analysis is the non-stationary gradual warming caused by continued greenhouse gas (GHG) forcing, which creates a number of theoretical and technical complications. Adapting D&A to this non-stationary setting requires several ad-hoc assumptions whose validity is analyzed and discussed. We study the stratospheric sulfur injection scenarios G3 and G4 of the GeoMIP project. For G3, which smoothly balances global warming with a corresponding cooling, the effect is smaller initially and harder to detect. Temperature and precipitation signals are detectable about a decade after commencing CE and attributable a few years later (details depending on model and scenario). The G4 scenario consists of a continuous injection of 5Tg SO2 (roughly 1/4 of the Pinatubo eruption per year), which represents a shock-like forcing that is easier and earlier detectable, just after a few years. Later into the century, uncertainty in GHG sensitivity increasingly dominates the background noise, hampering G4 detection. Spatio-temporal CE fingerprints produce more stable D&A results, with smoother dependence on time. Spatial resolution (within the range of a few spherical harmonics) is less relevant. We argue that especially for early detectability, climate predictions (with proper initialization from observations) are more promising. Many details depend on the choice of climate model for observation and fingerprint. We discuss the potential and limitation of using multi-model ensembles.