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DDC: 550 × Subject: Meteorology ×

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    Effects of climate model radiation, humidity and wind estimates on hydrological simulations
    (Chichester : John Wiley and Sons Ltd, 2012) Haddeland, I.; Heinke, J.; Voß, F.; Eisner, S.; Chen, C.; Hagemann, S.; Ludwig, F.
    Due to biases in the output of climate models, a bias correction is often needed to make the output suitable for use in hydrological simulations. In most cases only the temperature and precipitation values are bias corrected. However, often there are also biases in other variables such as radiation, humidity and wind speed. In this study we tested to what extent it is also needed to bias correct these variables. Responses to radiation, humidity and wind estimates from two climate models for four large-scale hydrological models are analysed. For the period 1971-2000 these hydrological simulations are compared to simulations using meteorological data based on observations and reanalysis; i.e. the baseline simulation. In both forcing datasets originating from climate models precipitation and temperature are bias corrected to the baseline forcing dataset. Hence, it is only effects of radiation, humidity and wind estimates that are tested here. The direct use of climate model outputs result in substantial different evapotranspiration and runoff estimates, when compared to the baseline simulations. A simple bias correction method is implemented and tested by rerunning the hydrological models using bias corrected radiation, humidity and wind values. The results indicate that bias correction can successfully be used to match the baseline simulations. Finally, historical (1971-2000) and future (2071-2100) model simulations resulting from using bias corrected forcings are compared to the results using non-bias corrected forcings. The relative changes in simulated evapotranspiration and runoff are relatively similar for the bias corrected and non bias corrected hydrological projections, although the absolute evapotranspiration and runoff numbers are often very different. The simulated relative and absolute differences when using bias corrected and non bias corrected climate model radiation, humidity and wind values are, however, smaller than literature reported differences resulting from using bias corrected and non bias corrected climate model precipitation and temperature values.
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    Comparative analysis of meteorological performance of coupled chemistry-meteorology models in the context of AQMEII phase 2
    (Amsterdam : Elsevier, 2014) Brunner, Dominik; Savage, Nicholas; Jorba, Oriol; Eder, Brian; Giordano, Lea; Badia, Alba; Balzarini, Alessandra; Baró, Rocío; Bianconi, Roberto; Chemel, Charles; Curci, Gabriele; Forkel, Renate; Jiménez-Guerrero, Pedro; Hirtl, Marcus; Hodzic, Alma; Honzak, Luka; Im, Ulas; Knote, Christoph; Makar, Paul; Manders-Groot, Astrid; van Meijgaard, Erik; Neal, Lucy; Pérez, Juan L.; Pirovano, Guido; San Jose, Roberto; Schröder, Wolfram; Sokhi, Ranjeet S.; Syrakov, Dimiter; Torian, Alfreida; Tuccella, Paolo; Werhahn, Johannes; Wolke, Ralf; Yahya, Khairunnisa; Zabkar, Rahela; Zhang, Yang; Hogrefe, Christian; Galmarini, Stefano
    Air pollution simulations critically depend on the quality of the underlying meteorology. In phase 2 of the Air Quality Model Evaluation International Initiative (AQMEII-2), thirteen modeling groups from Europe and four groups from North America operating eight different regional coupled chemistry and meteorology models participated in a coordinated model evaluation exercise. Each group simulated the year 2010 for a domain covering either Europe or North America or both. Here were present an operational analysis of model performance with respect to key meteorological variables relevant for atmospheric chemistry processes and air quality. These parameters include temperature and wind speed at the surface and in the vertical profile, incoming solar radiation at the ground, precipitation, and planetary boundary layer heights. A similar analysis was performed during AQMEII phase 1 (Vautard et al., 2012) for offline air quality models not directly coupled to the meteorological model core as the model systems investigated here. Similar to phase 1, we found significant overpredictions of 10-m wind speeds by most models, more pronounced during night than during daytime. The seasonal evolution of temperature was well captured with monthly mean biases below 2 K over all domains. Solar incoming radiation, precipitation and PBL heights, on the other hand, showed significant spread between models and observations suggesting that major challenges still remain in the simulation of meteorological parameters relevant for air quality and for chemistry–climate interactions at the regional scale.