Potsdam Institute for Climate Impact Research

About: Potsdam Institute for Climate Impact Research is a facility organization based out in Potsdam, Germany. It is known for research contribution in the topics: Climate change & Global warming. The organization has 1519 authors who have published 5098 publications receiving 367023 citations.

Very early warning of next El Niño

Abstract: The most important driver of climate variability is the El Nino Southern Oscillation, which can trigger disasters in various parts of the globe. Despite its importance, conventional forecasting is still limited to 6 mo ahead. Recently, we developed an approach based on network analysis, which allows projection of an El Nino event about 1 y ahead. Here we show that our method correctly predicted the absence of El Nino events in 2012 and 2013 and now announce that our approach indicated (in September 2013 already) the return of El Nino in late 2014 with a 3-in-4 likelihood. We also discuss the relevance of the next El Nino to the question of global warming and the present hiatus in the global mean surface temperature.

Modeling bio-geophysical feedback in the African and Indian monsoon region

Abstract: An asynchronously coupled global atmosphere-biome model is used to assess the dynamics of deserts and drought in the Sahel, Saudi-Arabia and the Indian subcontinent. Under present-day conditions of solar irradiation and sea-surface temperatures, the model finds two solutions: the first solution yields the present-day distribution of vegetation and deserts and the second shows a northward spread of savanna and xerophytic shrub of some 600 km, particularly in the southwest Sahara. Comparison of atmospheric states associated with these solutions corroborates Charney’s theory of a self-induction of deserts through albedo enhancement in the Sahel. Over the Indian subcontinent, changes in vegetation are mainly caused by a positive feedback between increased soil moisture and stronger summer monsoon.

Climate sensitivity estimated from ensemble simulations of glacial climate

Abstract: The concentration of greenhouse gases (GHGs) in the atmosphere continues to rise, hence estimating the climate system’s sensitivity to changes in GHG concentration is of vital importance. Uncertainty in climate sensitivity is a main source of uncertainty in projections of future climate change. Here we present a new approach for constraining this key uncertainty by combining ensemble simulations of the last glacial maximum (LGM) with paleo-data. For this purpose we used a climate model of intermediate complexity to perform a large set of equilibrium runs for (1) pre-industrial boundary conditions, (2) doubled CO2 concentrations, and (3) a complete set of glacial forcings (including dust and vegetation changes). Using proxy-data from the LGM at low and high latitudes we constrain the set of realistic model versions and thus climate sensitivity. We show that irrespective of uncertainties in model parameters and feedback strengths, in our model a close link exists between the simulated warming due to a doubling of CO2, and the cooling obtained for the LGM. Our results agree with recent studies that annual mean data-constraints from present day climate prove to not rule out climate sensitivities above the widely assumed sensitivity range of 1.5–4.5°C (Houghton et al. 2001). Based on our inferred close relationship between past and future temperature evolution, our study suggests that paleo-climatic data can help to reduce uncertainty in future climate projections. Our inferred uncertainty range for climate sensitivity, constrained by paleo-data, is 1.2–4.3°C and thus almost identical to the IPCC estimate. When additionally accounting for potential structural uncertainties inferred from other models the upper limit increases by about 1°C.

The tolerable windows approach : Theoretical and methodological foundations

Abstract: The tolerable windows (TW) approach is presented as a novel scheme for integrated assessment of climate change. The TW approach is based on the specification of a set of guardrails for climate evolution which refer to various climate-related attributes. These constraints, which define what we call tolerable windows, can be purely systemic in nature – like critical thresholds for the North Atlantic Deep Water formation – or of a normative type – like minimum standards for per-capita food production worldwide. Starting from this catalogue of knock-out criteria and using appropriate modeling techniques, those policy strategies which are compatible with all the constraints specified are sought to be identified. In addition to the discussion of the basic elements and the general theory of the TW approach, a modeling exercise is carried out, based on simple models and assumptions adopted from the German Advisory Council on Global Change (WBGU). The analysis shows that if the global mean temperature is restricted to 2°C beyond the preindustrial level, the cumulative emissions of CO2 are asymptotically limited to about 1550 Gt C. Yet the temporal distribution of these emissions is also determined by the climate and socio-economic constraints: using, for example, a maximal tolerable rate of temperature change of 0.2°C/dec and a smoothly varying emissions profile, we obtain the maximal cumulative emissions, amounting to 370 Gt C in 2050 and 585 Gt C in 2100.