One simulation, different conclusions—the baseline period makes the difference!

S Liersch,A Lobanova,H Koch,V Aich,M A D Larsen,S Salack,A Gädeke,K Halsnæ S,W Thiery,M Drews,D Sietz,S Huang,T Pilz,F F Hattermann

doi:10.1088/1748-9326/aba3d7

Abstract

The choice of the baseline period, intentionally chosen or not, as a reference for assessing future changes of any projected variable can play an important role for the resulting statement. In regional climate impact studies, well-established or arbitrarily chosen baselines are often used without being questioned. Here we investigated the effects of different baseline periods on the interpretation of discharge simulations from eight river basins in the period 1960–2099. The simulations were forced by four bias-adjusted and downscaled Global Climate Modelsunder two radiative forcing scenarios (RCP 2.6 and RCP 8.5). To systematically evaluate how far the choice of different baselines impacts the simulation results, we developed a similarity index that compares two time series of projected changes. The results show that 25% of the analyzed simulations are sensitive to the choice of the baseline period under RCP 2.6 and 32% under RCP 8.5. In extreme cases, change signals of two time series show opposite trends. This has serious consequences for key messages drawn from a basin-scale climate impact study. To address this problem, an algorithm was developed to identify flexible baseline periods for each simulation individually, which better represent the statistical properties of a given historical period.

Highlights

In the context of climate change mitigation and adaptation, decision-makers generally call for information about impacts of projected changes in a specific region at different global warming levels or in certain future periods
The present study systematically investigates the effect of the choice of the baseline period on the interpretation of simulation results
This study demonstrates how solely the choice of a baseline period can influence the interpretation of discharge projections in eight river basins using climate input from four bias-adjusted Global Climate Models (GCMs)

Summary

Introduction

In the context of climate change mitigation and adaptation, decision-makers generally call for information about impacts of projected changes in a specific region at different global warming levels or in certain future periods. They need answers to questions like: ‘Can we expect an increase or decrease in water availability, extreme events, such as floods, droughts, storm surges or heatwaves, around the year 2030, 2050 or by the end of the 21st century? What will be the consequences for, e.g. crop production, renewable electricity generation?’ To answer such questions, regional climate impact modelers face a variety of challenges, which relate to technical, methodological, and communication issues of simulation results [1] and corresponding recommendations under uncertainties in a comprehensible way. The uncertainty cascade in the impact modeling is basically associated with model structure, model parameterization, and input data quality [8–15]

Methods

Results

Conclusion