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Using soil moisture forecasts for sub-seasonal summer temperature predictions in Europe

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Abstract

Soil moisture exhibits outstanding memory characteristics and plays a key role within the climate system. Especially through its impacts on the evapotranspiration of soils and plants, it may influence the land energy balance and therefore surface temperature. These attributes make soil moisture an important variable in the context of weather and climate forecasting. In this study we investigate the value of (initial) soil moisture information for sub-seasonal temperature forecasts. For this purpose we employ a simple water balance model to infer soil moisture from streamflow observations in 400 catchments across Europe. Running this model with forecasted atmospheric forcing, we derive soil moisture forecasts, which we then translate into temperature forecasts using simple linear relationships. The resulting temperature forecasts show skill beyond climatology up to 2 weeks in most of the considered catchments. Even if forecasting skills are rather small at longer lead times with significant skill only in some catchments at lead times of 3 and 4 weeks, this soil moisture-based approach shows local improvements compared to the monthly European Centre for Medium Range Weather Forecasting (ECMWF) temperature forecasts at these lead times. For both products (soil moisture-only forecast and ECMWF forecast), we find comparable or better forecast performance in the case of extreme events, especially at long lead times. Even though a product based on soil moisture information alone is not of practical relevance, our results indicate that soil moisture (memory) is a potentially valuable contributor to temperature forecast skill. Investigating the underlying soil moisture of the ECMWF forecasts we find good agreement with the simple model forecasts, especially at longer lead times. Analyzing the drivers of the temperature forecast skills we find that they are mainly controlled by the strengths of (1) the soil moisture-temperature coupling and (2) the soil moisture memory. We find a negative relationship between these controls that weakens the forecast skills, nevertheless there is a middle ground between both controls in several catchments, as shown by our results.

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Acknowledgments

We acknowledge the E-OBS dataset established by the EU-FP6 project ENSEMBLES (http://ensembles-eu.metoffice.com [accessed on 25 March 2013]) and the data providers in the ECA&D project (http://www.ecad.eu [accessed on 25 March 2013]) for sharing precipitation and temperature data, the NASA/GEWEX SRB project (http://eosweb.larc.nasa.gov/PRODOCS/srb/table_srb.html [accessed on 25 March 2013]) for sharing radiation data, and the European water archive and the EU-FP6 project WATCH (http://www.eu-watch.org [accessed on 25 March 2013]) for sharing streamflow data. We also acknowledge the ECMWF VarEPS re-forecast dataset (http://www.ecmwf.int/products/changes/vareps/ [accessed on 25 March 2013]) and we are thankful to Dani Lthi for downloading and storing these data. We appreciate financial support by the Swiss National Foundation through the NRP61 DROUGHT-CH project, and partial support from the EU-FP7 DROUGHT-RSPI project. We thank Randy Koster, Christof Appenzeller, Boris Orlowsky and two anonymous reviewers for helpful comments on the manuscript. Furthermore we thank Gianpaolo Balsamo for help with the selection of the ECMWF forecasts.

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  1. Institute for Atmospheric and Climate Science, ETH Zurich, Universitaetstrasse 16, 8092, Zurich, Switzerland

    René Orth & Sonia I. Seneviratne

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  1. René Orth
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  2. Sonia I. Seneviratne
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Correspondence to René Orth.

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Orth, R., Seneviratne, S.I. Using soil moisture forecasts for sub-seasonal summer temperature predictions in Europe. Clim Dyn 43, 3403–3418 (2014). https://doi.org/10.1007/s00382-014-2112-x

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