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This study investigates deep water formation in the Western Mediterranean by examining time series from 1974 to 2010. It focuses on air and sea temperature trends, seasonal shifts, and their effects on evaporation and precipitation. Utilizing advanced ocean models and data assimilation techniques, the research aims to assess the impact of turbulent coefficients on the evapotranspiration balance. Additionally, it explores the contributions of the SMOS mission in determining sea surface salinity and soil moisture, providing insights into hydrological cycles and climate change implications.
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ICM/UTM - CSIC Hymex activities • L’Estartit time series (1974-2010) • Western Mediterranean Deep water formation • E-P estimation in Ocean Models assimilation • SMOS mission
L’Estartit time series • Trends of air and sea warming • Seasonal shifts • Trends on period where Tair > Twater • Effect on evaporation/precipitation • New approach for latent heat exchange
Seasonal shifts days when T@20m>17°C 1st.day = -0,77·(year-1974)+176,3 last.day = 0,67·(year-1974)+297,8 360 320 Julian day 280 240 200 160 120 1974 1978 1982 1986 1990 1994 1998 2002 2006
WMDW formation • Evolution of WMDW • Western Mediterranean transient • Effects on the hydrological cycle • Control of Gibraltar inflow/outflow • How can we monitor inflow?
Rhone G. of Genova Carcassonne G. of Lions P C M S Catalan coast Deep Water Formation (DWF) area
Temperature and near-bottom current speed at the point C From: Puig et al., 2009 Temperature, Salinity and density at the point M From: Fuda et al., 2009 q (°C) ~12.89 S ~ 38.49 sq (kg.m-3) > 29.12 2007 2008 Shifts in DWF
Temperature 80 m 270 m 270 m 270 m Salinity 270 m 80 m Gibraltar input/output Input: zoom scale
E-P estimates in ocean models The amplitude of the water cycle over the oceans is given by E-P. In numerical models, Evaporation is calculated with empirical formulae using a fixed set of parameters. Our work aims to identify which parameters, of these empirical formulae, have the largest impact of the E-P fluxes in an ocean model (NEMO-OPA). Our objective is to infer the appropriate value of these parameters using Data Assimilation techniques.
Objective: Determining the turbulent coefficients that affect the E-P • balance of the model. • Standard deviation of E-P from a • reference simulation of the model: CE,orig • Difference between S+ and S-. S+ = simulation CE = 1.25 * CE,orig • S- = simulation CE = 0.75 * CE,orig Same order of magnitude
SMOS • Soil Moisture and Ocean Salinity, an Earth Explorer Opportunity Mission from the European Space Agency • Pioneer technology for earth observation (microwave interferometric radiometer) • Spain leading role (science, technology, industry, processing, Valencia validation site) • Launched November 2, 2009. In operations phase since May 2010 I. Corbella, UPC: SMOS brightness temperature
Sea Surface Salinity http://www.smos-bec.icm.csic.es Retrieved SSS along an orbit (SMOS L2OS Operational Processor) (M. Talone, SMOS-BEC, Barcelona) • Objective: Determining sea surface salinity with an accuracy of the order of 0.1 practical salinity units, 100 – 200 km spatial resolution and 10 – 30 days temporal resolution (N. Reul, IFREMER, Brest)
Soil Moisture • Objective: Determining soil moisture with a 4% accuracy, plus vegetation water content, with a spatial resolution of 50 km and a revisiting time of at least 3 days • Spanish SMOS level 3 and 4 • Data Processing Centre • http://www.cp34-smos.icm.csic.es/ • CESBIO/CNES, Toulouse: preliminary • soil moisture m3 water / m3 soil