TY - JOUR A1 - Sprinz, Detlef F. A1 - de Mesquita, Bruce Bueno A1 - Kallbekken, Steffen A1 - Stokman, Frans A1 - Saelen, Hakon A1 - Thomson, Robert T1 - Predicting Paris: Multi-Method Approaches to Forecast the Outcomes of Global Climate Negotiations JF - Politics and Governance N2 - We examine the negotiations held under the auspices of the United Nations Framework Convention of Climate Change in Paris, December 2015. Prior to these negotiations, there was considerable uncertainty about whether an agreement would be reached, particularly given that the world’s leaders failed to do so in the 2009 negotiations held in Copenhagen. Amid this uncertainty, we applied three different methods to predict the outcomes: an expert survey and two negotiation simulation models, namely the Exchange Model and the Predictioneer’s Game. After the event, these predictions were assessed against the coded texts that were agreed in Paris. The evidence suggests that combining experts’ predictions to reach a collective expert prediction makes for significantly more accurate predictions than individual experts’ predictions. The differences in the performance between the two different negotiation simulation models were not statistically significant. KW - climate policy KW - climate regime KW - expert survey KW - forecasting KW - global negotiations KW - Paris agreement KW - prediction KW - simulation Y1 - 2016 U6 - https://doi.org/10.17645/pag.v4i3.654 SN - 2183-2463 VL - 4 SP - 172 EP - 187 PB - Cogitatio Press CY - Lisbon ER - TY - GEN A1 - Kuik, Friderike A1 - Lauer, Axel A1 - Churkina, Galina A1 - Denier Van der Gon, Hugo Anne Cornelis A1 - Fenner, Daniel A1 - Mar, Kathleen A. A1 - Butler, Tim M. T1 - Air quality modelling in the Berlin–Brandenburg region using WRF-Chem v3.7.1 BT - sensitivity to resolution of model grid and input data T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenge, especially in urban areas. For studying summertime air quality in the Berlin-Brandenburg region of Germany, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014. The objective is to assess which resolution and level of detail in the input data is needed for simulating urban background air pollutant concentrations and their spatial distribution in the Berlin-Brandenburg area. The model setup includes three nested domains with horizontal resolutions of 15, 3 and 1 km and anthropogenic emissions from the TNO-MACC III inventory. We use RADM2 chemistry and the MADE/SORGAM aerosol scheme. Three sensitivity simulations are conducted updating input parameters to the single-layer urban canopy model based on structural data for Berlin, specifying land use classes on a sub-grid scale (mosaic option) and downscaling the original emissions to a resolution of ca. 1 km x 1 km for Berlin based on proxy data including traffic density and population density. The results show that the model simulates meteorology well, though urban 2m temperature and urban wind speeds are biased high and nighttime mixing layer height is biased low in the base run with the settings described above. We show that the simulation of urban meteorology can be improved when specifying the input parameters to the urban model, and to a lesser extent when using the mosaic option. On average, ozone is simulated reasonably well, but maximum daily 8 h mean concentrations are underestimated, which is consistent with the results from previous modelling studies using the RADM2 chemical mechanism. Particulate matter is underestimated, which is partly due to an underestimation of secondary organic aerosols. NOx (NO + NO2) concentrations are simulated reasonably well on average, but nighttime concentrations are overestimated due to the model's underestimation of the mixing layer height, and urban daytime concentrations are underestimated. The daytime underestimation is improved when using downscaled, and thus locally higher emissions, suggesting that part of this bias is due to deficiencies in the emission input data and their resolution. The results further demonstrate that a horizontal resolution of 3 km improves the results and spatial representativeness of the model compared to a horizontal resolution of 15 km. With the input data (land use classes, emissions) at the level of detail of the base run of this study, we find that a horizontal resolution of 1 km does not improve the results compared to a resolution of 3 km. However, our results suggest that a 1 km horizontal model resolution could enable a detailed simulation of local pollution patterns in the Berlin-Brandenburg region if the urban land use classes, together with the respective input parameters to the urban canopy model, are specified with a higher level of detail and if urban emissions of higher spatial resolution are used. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 531 KW - urban canopy model KW - aqmeii phase-2 KW - Mexico-City KW - Heat-Island KW - ozone KW - performance KW - transport KW - chemistry KW - meteorology KW - simulation Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-410131 SN - 1866-8372 IS - 531 ER -