Maria A. Jimenez

Dr. Maria A. Jimenez

Univ. Balearic Islands, Carretera de Valldemossa km 7.5, 07122 Palma, Mallorca, Spain
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Research Focus & Metrics

Academic Career Length

30Years (1997-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2006 in Boundary-Layer Meteorology
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Journal Article
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RBRobert J. Beare
Robert J. Beare
MMMalcolm K. Macvean
Malcolm K. Macvean
AHAlbert A. M. Holtslag
Albert A. M. Holtslag
Joan CuxartJoan Cuxart
Joan Cuxart
IEIgor Esau
Igor Esau
Peter P. SullivanPeter P. Sullivan
Peter P. Sullivan

4 August 2017 in Nature Communications
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Journal Article
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EMEva Mayol
Eva Mayol
Jesús ArrietaJesús Arrieta
Jesús Arrieta
Maria A. JimenezMaria A. Jimenez
Maria A. Jimenez
AMAdrián Martínez-Asensio
Adrián Martínez-Asensio
NGNeus Garcias-Bonet
Neus Garcias-Bonet
CDCarlos M Duarte
Carlos M Duarte
The atmosphere plays a fundamental role in the transport of microbes across the planet but it is often neglected as a microbial habitat. Although the ocean represents two thirds of the Earth’s surface, there is little information on the atmospheric microbial load over the open ocean. Here we provide a global estimate of microbial loads and air-sea exchanges over the tropical and subtropical oceans based on the data collected along the Malaspina 2010 Circumnavigation Expedition. Total loads of airborne prokaryotes and eukaryotes were estimated at 2.2 × 1021 and 2.1 × 1021 cells, respectively. Overall 33–68% of these microorganisms could be traced to a marine origin, being transported thousands of kilometres before re-entering the ocean. Moreover, our results show a substantial load of terrestrial microbes transported over the oceans, with abundances declining exponentially with distance from land and indicate that islands may act as stepping stones facilitating the transoceanic transport of terrestrial microbes.

16 October 2014 in Atmospheric Chemistry and Physics
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MLMarie LOTHON
Marie LOTHON
FLF. Lohou
F. Lohou
DPDavid Pino
David Pino
FCF. Couvreux
F. Couvreux
EPEric Pardyjak
Eric Pardyjak
Alessandro ZaldeiAlessandro Zaldei
Alessandro Zaldei
Due to the major role of the sun in heating the earth's surface, the atmospheric planetary boundary layer over land is inherently marked by a diurnal cycle. The afternoon transition, the period of the day that connects the daytime dry convective boundary layer to the night-time stable boundary layer, still has a number of unanswered scientific questions. This phase of the diurnal cycle is challenging from both modelling and observational perspectives: it is transitory, most of the forcings are small or null and the turbulence regime changes from fully convective, close to homogeneous and isotropic, toward a more heterogeneous and intermittent state. These issues motivated the BLLAST (Boundary-Layer Late Afternoon and Sunset Turbulence) field campaign that was conducted from 14 June to 8 July 2011 in southern France, in an area of complex and heterogeneous terrain. A wide range of instrumented platforms including full-size aircraft, remotely piloted aircraft systems, remote-sensing instruments, radiosoundings, tethered balloons, surface flux stations and various meteorological towers were deployed over different surface types. The boundary layer, from the earth's surface to the free troposphere, was probed during the entire day, with a focus and intense observation periods that were conducted from midday until sunset. The BLLAST field campaign also provided an opportunity to test innovative measurement systems, such as new miniaturized sensors, and a new technique for frequent radiosoundings of the low troposphere. Twelve fair weather days displaying various meteorological conditions were extensively documented during the field experiment. The boundary-layer growth varied from one day to another depending on many contributions including stability, advection, subsidence, the state of the previous day's residual layer, as well as local, meso- or synoptic scale conditions. Ground-based measurements combined with tethered-balloon and airborne observations captured the turbulence decay from the surface throughout the whole boundary layer and documented the evolution of the turbulence characteristic length scales during the transition period. Closely integrated with the field experiment, numerical studies are now underway with a complete hierarchy of models to support the data interpretation and improve the model representations.

11 September 2018 in Remote Sensing
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Vicente Garcia-SantosVicente Garcia-Santos
Vicente Garcia-Santos
Joan CuxartJoan Cuxart
Joan Cuxart
DMDaniel Martinez-Villagrasa
Daniel Martinez-Villagrasa
Maria A. JimenezMaria A. Jimenez
Maria A. Jimenez
GSGemma Simó
Gemma Simó
After Landsat 8 was launched in 2013, it was observed that for Thermal Infrared sensor (TIRS) bands, radiance from outside of an instrument’s field-of-view produced a non-uniform ghost signal across the focal plane that varied depending on the out-of-scene content (i.e., the stray light effect). A new stray light correction algorithm (SLCA) is currently operational and has been implemented into the United States Geological Survey (USGS) ground system since February 2017. The SLCA has also been applied to reprocess historical Landsat 8 scenes. After approximately two years of SLCA implementation, more land surface temperature (LST) validation studies are required to check the effect of correction in the estimation of LST from different retrieval algorithms. For this purpose, three different LST estimation method algorithms (i.e., the radiative transfer equation (RTE), single-channel algorithm (SCA), and split-window algorithm (SWA)) have been assessed. The study site is located on the campus of the University of Balearic Islands on the island of Mallorca (Spain) in the western Mediterranean Sea. The site is considered a heterogeneous area that is composed of different types of surfaces, such as buildings, asphalt roads, farming areas, sloped terrains, orange fields, almond trees, lawns, and some natural vegetation regions. Data from 21 scenes, which were acquired by the Landsat 8-TIRS sensor and extracted from a 100 × 100 m2 pixel, were used to retrieve the LST with different algorithms; then, they were compared with in situ LST measurements from a broadband thermal infrared radiometer located on the same Landsat 8 pixel. The results show good performances of the three methods, with the SWA showing the lowest observed RMSE (within 1.6–2 K), whereas the SCA applied to the TIRS band 10 (10 µm) was also appropriate, with a RMSE ranging within 2.0–2.3 K. The LST estimates using the RTE algorithm display the highest observed RMSE values (within 2.0–3.6 K) of all of the compared methods, but with an almost unbiased value of −0.1 K for the case of techniques applied to band 10 data. The SWAs are the preferred method to estimate the LST in our study area. However, further validation studies around the world are required.


1 May 2007 in Journal of the Atmospheric Sciences
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Joan CuxartJoan Cuxart
Joan Cuxart
Maria A. JimenezMaria A. Jimenez
Maria A. Jimenez
A steady-state low-level jet observed in the Stable Atmospheric Boundary Layer Experiment in Spain-1998 (SABLES-98) campaign is simulated using a large-eddy simulation model. The radiation is taken into account since its contribution to the budget of the tendency of temperature is as important as the contribution of the turbulence in the surface layer. The resulting regime is a two-layer flow separated by a change of the temperature gradient at the level of maximum speed. The upper part has turbulence originated by shear production extending up to 3 times the height of wind maximum and of the same order of magnitude as in the layer below. The jet nose is seen by the model as a decoupling layer, and the use of passive scalars allows for the inspection of the amount of transport across it, which is very small. The lower layer is very sensitive to the surface boundary conditions, but the principal patterns in the upper layer do not change significantly. The runs are compared to the observations through mean profiles, time series, and probability density functions.