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Open AccessArticle

Moisture Recycling over the Iberian Peninsula: The Impact of 3DVAR Data Assimilation

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Oeschger Centre for Climate Change Research, University of Bern, 3012 Bern, Switzerland
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Climate and Environmental Physics, University of Bern, 3012 Bern, Switzerland
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Department of Applied Physics II, University of the Basque Country (UPV/EHU), 48940 Leioa, Spain
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Plentzia Itsas Estazioa, University of the Basque Country (PiE-UPV/EHU), 48620 Plentzia, Spain
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Department of Applied Physics I, University of the Basque Country (UPV/EHU), 01006 Vitoria-Gazteiz, Spain
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Department of NE and Fluid Mechanics, University of the Basque Country (UPV/EHU), Bilbao Engineering School, 48013 Bilbao, Spain
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Author to whom correspondence should be addressed.
Atmosphere 2020, 11(1), 19; https://doi.org/10.3390/atmos11010019
Received: 6 November 2019 / Revised: 29 November 2019 / Accepted: 19 December 2019 / Published: 24 December 2019
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
In this paper, we have estimated the spatiotemporal distribution of moisture recycling over the Iberian Peninsula (IP). The recycling ratio was computed from two simulations over the IP using the Weather Research and Forecasting (WRF) model with a horizontal resolution of 15 km spanning the period 2010–2014. The first simulation (WRF N) was nested inside the ERA-Interim with information passed to the domain through the boundaries. The second run (WRF D) is similar to WRF N, but it also includes 3DVAR data assimilation every six hours (12:00 a.m., 6:00 a.m., 12:00 p.m. and 6:00 p.m. UTC). It was also extended until 2018. The lowest values of moisture recycling (3%) are obtained from November to February, while the highest ones (16%) are observed in spring in both simulations. Moisture recycling is confined to the southeastern corner during winter. During spring and summer, a gradient towards the northeastern corner of the IP is observed in both simulations. The differences between both simulations are associated with the dryness of the soil in the model and are higher during summer and autumn. WRF D presents a lower bias and produces more reliable results because of a better representation of the atmospheric moisture. View Full-Text
Keywords: moisture recycling; recycling; data assimilation; WRF; iberian peninsula moisture recycling; recycling; data assimilation; WRF; iberian peninsula
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MDPI and ACS Style

González-Rojí, S.J.; Sáenz, J.; Díaz de Argandoña, J.; Ibarra-Berastegi, G. Moisture Recycling over the Iberian Peninsula: The Impact of 3DVAR Data Assimilation. Atmosphere 2020, 11, 19.

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