Abstract

Abstract. This work uses a network of GPS stations over Europe from which a homogenized integrated water vapor (IWV) dataset has been retrieved, completed with colocated temperature and precipitation measurements over specific stations to (i) estimate the biases of six regional climate models over Europe in terms of humidity; (ii) understand their origins; and (iii) finally assess the impact of these biases on the frequency of occurrence of precipitation. The evaluated simulations have been performed in the framework of HYMEX/Med-CORDEX programs and cover the Mediterranean area and part of Europe at horizontal resolutions of 50 to 12 km. The analysis shows that models tend to overestimate the low values of IWV and the use of the nudging technique reduces the differences between GPS and simulated IWV. Results suggest that physics of models mostly explain the mean biases, while dynamics affects the variability. The land surface–atmosphere exchanges affect the estimation of IWV over most part of Europe, especially in summer. The limitations of the models to represent these processes explain part of their biases in IWV. However, models correctly simulate the dependance between IWV and temperature, and specifically the deviation that this relationship experiences regarding the Clausius–Clapeyron law after a critical value of temperature (Tbreak). The high spatial variability of Tbreak indicates that it has a strong dependence on local processes which drive the local humidity sources. This explains why the maximum values of IWV are not necessarily observed over warmer areas, which are often dry areas. Finally, it is shown over the SIRTA observatory (near Paris) that the frequency of occurrence of light precipitation is strongly conditioned by the biases in IWV and by the precision of the models to reproduce the distribution of IWV as a function of the temperature. The results of the models indicate that a similar dependence occurs in other areas of Europe, especially where precipitation has a predominantly convective character. According to the observations, for each range of temperature, there is a critical value of IWV from which precipitation starts to increase. The critical values and the probability of exceeding them are simulated with a bias that depends on the model. Those models, which generally present light precipitation too often, show lower critical values and higher probability of exceeding them.

Highlights

  • Humidity plays a major role in the water and energy cycles due to its strong radiative effect associated with a positive feedback on climate (Randall et al, 2007) and its impor-Published by Copernicus Publications on behalf of the European Geosciences Union.S

  • Humidity variability at regional scale – and at the surface – needs to be assessed to better anticipate the precipitation change, and the rate of heavy precipitation, which are not well estimated by global models (e.g., Allan and Soden, 2008). Another aspect that links integrated water vapor (IWV) and precipitation concerns the triggering of precipitation and the frequency of occurrence of precipitation: Holloway and Neelin (2009) showed that precipitation over the tropical oceans is strongly sensitive to free-tropospheric humidity even more than surface humidity, and Neelin et al (2009) and Sahany et al (2012) further conclude that there exists a threshold of IWV, which depends on the mean tropospheric temperature, over which precipitation starts to increase significantly

  • This work uses Global Positioning System (GPS) integrated water vapor measurements associated with temperature and precipitation measurements to (i) estimate the biases of six regional climate models over Europe in terms of humidity; (ii) understand their origins; and (iii) assess the impact of these biases on the occurrence of precipitation

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Summary

Introduction

Humidity plays a major role in the water and energy cycles due to its strong radiative effect associated with a positive feedback on climate (Randall et al, 2007) and its impor-. Humidity variability at regional scale – and at the surface – needs to be assessed to better anticipate the precipitation change, and the rate of heavy precipitation, which are not well estimated by global models (e.g., Allan and Soden, 2008) Another aspect that links IWV and precipitation concerns the triggering of precipitation and the frequency of occurrence of precipitation: Holloway and Neelin (2009) showed that precipitation over the tropical oceans is strongly sensitive to free-tropospheric humidity even more than surface humidity, and Neelin et al (2009) and Sahany et al (2012) further conclude that there exists a threshold of IWV, which depends on the mean tropospheric temperature, over which precipitation starts to increase significantly.

GPS IWV data
Observations at SIRTA
Med-CORDEX simulations
Others datasets
Comparison between GPS dataset and model outputs
Comparison with SIRTA observations
Comparison with GPS dataset at regional scale
Scaling of IWV with temperature
Over SIRTA
Generalization
Findings
Conclusions
Full Text
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