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The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, are important characteristics in order to describe the impact of clouds on climate. In this work, several methods for estimating the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering the number and position of cloud layers, with a ground-based system that is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ in the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study, these methods are applied to 193 radiosonde profiles acquired at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site during all seasons of the year 2009 and endorsed by Geostationary Operational Environmental Satellite (GOES) images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The perfect agreement (i.e., when the whole CVS is estimated correctly) for the methods ranges between 26 and 64 %; the methods show additional approximate agreement (i.e., when at least one cloud layer is assessed correctly) from 15 to 41 %. Further tests and improvements are applied to one of these methods. In addition, we attempt to make this method suitable for low-resolution vertical profiles, like those from the outputs of reanalysis methods or from the World Meteorological Organization's (WMO) Global Telecommunication System. The perfect agreement, even when using low-resolution profiles, can be improved by up to 67 % (plus 25 % of the approximate agreement) if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement ; This research was funded by the Ministerio de Ciencia e Innovacion of the Spanish Government through grants CGL2007-62664 (NUCLIEREX) and CGL2010-18546 (NUCLIERSOL). M. Costa-Suros was supported by research ...

The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, is an important characteristic in order to describe the impact of clouds in a changing climate. In this work several methods to estimate the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering number and position of cloud layers, with a ground based system which is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ on the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study these methods are applied to 125 radiosonde profiles acquired at the ARM Southern Great Plains site during all seasons of year 2009 and endorsed by GOES images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The overall agreement for the methods ranges between 44–88%; four methods produce total agreements around 85%. Further tests and improvements are applied on one of these methods. In addition, we attempt to make this method suitable for low resolution vertical profiles, which could be useful in atmospheric modeling. The total agreement, even when using low resolution profiles, can be improved up to 91% if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement ; This research was funded by the Ministerio de Ciencia e Innovacion of the Spanish Government through grants CGL2007-62664 (NUCLIEREX) and CGL2010-18546 (NUCLIERSOL). M. Costa-Suros was supported by research fellowship FPI BES-2008-003129 from the Ministerio de Ciencia e Innovacion of the Spanish Government. C. N. Long acknowledges support from the Office of Science of the US Department of Energy as part of the Atmospheric Systems Research (ASR) program. Data and TSI animations were obtained from the Atmospheric Radiation Measurement (ARM) program sponsored ...

The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, are important characteristics in order to describe the impact of clouds on climate. In this work, several methods for estimating the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering the number and position of cloud layers, with a ground-based system that is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ in the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study, these methods are applied to 193 radiosonde profiles acquired at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site during all seasons of the year 2009 and endorsed by Geostationary Operational Environmental Satellite (GOES) images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The perfect agreement (i.e., when the whole CVS is estimated correctly) for the methods ranges between 26 and 64 %; the methods show additional approximate agreement (i.e., when at least one cloud layer is assessed correctly) from 15 to 41 %. Further tests and improvements are applied to one of these methods. In addition, we attempt to make this method suitable for low-resolution vertical profiles, like those from the outputs of reanalysis methods or from the World Meteorological Organization's (WMO) Global Telecommunication System. The perfect agreement, even when using low-resolution profiles, can be improved by up to 67 % (plus 25 % of the approximate agreement) if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement ; This research was funded by the Ministerio de Ciencia e Innovacion of the Spanish Government through grants CGL2007-62664 (NUCLIEREX) and CGL2010-18546 (NUCLIERSOL). M. Costa-Suros was supported by research fellowship FPI BES-2008-003129 from the Ministerio de Ciencia e Innovacion of the Spanish Government. C. N. Long acknowledges support from the Office of Science of the US Department of Energy as part of the Atmospheric Systems Research (ASR) program. Data and TSI animations were obtained from the Atmospheric Radiation Measurement (ARM) program sponsored by the US Department of Energy. We thank L. Dimitrieva-Arrago for her explanations and interesting discussions while visiting the University of Girona in the framework of the UE CLIMSEAS project (FP7-PEOPLE-2009-IRSES proposal no. 247512). We also thank the National Oceanic and Atmospheric Administration (NOAA) Comprehensive Large Array-data stewardship system (CLASS) for providing GOES images for research use

The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, are important characteristics in order to describe the impact of clouds on climate. In this work, several methods for estimating the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering the number and position of cloud layers, with a ground-based system that is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ in the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study, these methods are applied to 193 radiosonde profiles acquired at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site during all seasons of the year 2009 and endorsed by Geostationary Operational Environmental Satellite (GOES) images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The perfect agreement (i.e., when the whole CVS is estimated correctly) for the methods ranges between 26 and 64 %; the methods show additional approximate agreement (i.e., when at least one cloud layer is assessed correctly) from 15 to 41 %. Further tests and improvements are applied to one of these methods. In addition, we attempt to make this method suitable for low-resolution vertical profiles, like those from the outputs of reanalysis methods or from the World Meteorological Organization's (WMO) Global Telecommunication System. The perfect agreement, even when using low-resolution profiles, can be improved by up to 67 % (plus 25 % of the approximate agreement) if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement ; This research was funded by the Ministerio de Ciencia e Innovacion of the Spanish Government through grants CGL2007-62664 (NUCLIEREX) and CGL2010-18546 (NUCLIERSOL). M. Costa-Suros was supported by research fellowship FPI BES-2008-003129 from the Ministerio de Ciencia e Innovacion of the Spanish Government. C. N. Long acknowledges support from the Office of Science of the US Department of Energy as part of the Atmospheric Systems Research (ASR) program. Data and TSI animations were obtained from the Atmospheric Radiation Measurement (ARM) program sponsored by the US Department of Energy. We thank L. Dimitrieva-Arrago for her explanations and interesting discussions while visiting the University of Girona in the framework of the UE CLIMSEAS project (FP7-PEOPLE-2009-IRSES proposal no. 247512). We also thank the National Oceanic and Atmospheric Administration (NOAA) Comprehensive Large Array-data stewardship system (CLASS) for providing GOES images for research use

This cross-sectional study evaluated the sprint and jump mechanical profiles of male academy rugby league players, the differences between positions, and the associations between mechanical profiles and sprint performance. Twenty academy rugby league players performed 40-m sprints and squat jumps at increasing loads (0–80 kg) to determine individual mechanical (force-velocity-power) and performance variables. The mechanical variables (absolute and relative theoretical maximal force-velocity-power, force-velocity linear relationship, and mechanical efficiency) were determined from the mechanical profiles. Forwards had significantly (p < 0.05) greater vertical and horizontal force, momentum but jumped lower (unloaded) and were slower than backs. No athlete presented an optimal jump profile. No associations were found between jump and sprint mechanical variables. Absolute theoretical maximal vertical force significantly (p < 0.05) correlated (r = 0.71–0.77) with sprint momentum. Moderate (r = −0.47) to near-perfect (r = 1.00) significant associations (p < 0.05) were found between sprint mechanical and performance variables. The largest associations shifted from maximum relative horizontal force-power generation and application to maximum velocity capabilities and force application at high velocities as distance increased. The jump and sprint mechanical profiles appear to provide distinctive and highly variable information about academy rugby league players' sprint and jump capacities. Associations between mechanical variables and sprint performance suggest horizontal and vertical profiles differ and should be trained accordingly.

The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, is an important characteristic in order to describe the impact of clouds in a changing climate. In this work several methods to estimate the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering number and position of cloud layers, with a ground based system which is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ on the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study these methods are applied to 125 radiosonde profiles acquired at the ARM Southern Great Plains site during all seasons of year 2009 and endorsed by GOES images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The overall agreement for the methods ranges between 44–88%; four methods produce total agreements around 85%. Further tests and improvements are applied on one of these methods. In addition, we attempt to make this method suitable for low resolution vertical profiles, which could be useful in atmospheric modeling. The total agreement, even when using low resolution profiles, can be improved up to 91% if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement ; This research was funded by the Ministerio de Ciencia e Innovacion of the Spanish Government through grants CGL2007-62664 (NUCLIEREX) and CGL2010-18546 (NUCLIERSOL). M. Costa-Suros was supported by research fellowship FPI BES-2008-003129 from the Ministerio de Ciencia e Innovacion of the Spanish Government. C. N. Long acknowledges support from the Office of Science of the US Department of Energy as part of the Atmospheric Systems Research (ASR) program. Data and TSI animations were obtained from the Atmospheric Radiation Measurement (ARM) program sponsored by the US Department of Energy. We thank L. Dimitrieva-Arrago for her explanations and interesting discussions while visiting the University of Girona in the framework of the UE CLIMSEAS project (FP7-PEOPLE-2009-IRSES proposal no. 247512). We also thank the National Oceanic and Atmospheric Administration (NOAA) Comprehensive Large Array-data stewardship system (CLASS) for providing GOES images for research use

The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, is an important characteristic in order to describe the impact of clouds in a changing climate. In this work several methods to estimate the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering number and position of cloud layers, with a ground based system which is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ on the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study these methods are applied to 125 radiosonde profiles acquired at the ARM Southern Great Plains site during all seasons of year 2009 and endorsed by GOES images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The overall agreement for the methods ranges between 44–88%; four methods produce total agreements around 85%. Further tests and improvements are applied on one of these methods. In addition, we attempt to make this method suitable for low resolution vertical profiles, which could be useful in atmospheric modeling. The total agreement, even when using low resolution profiles, can be improved up to 91% if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement ; This research was funded by the Ministerio de Ciencia e Innovacion of the Spanish Government through grants CGL2007-62664 (NUCLIEREX) and CGL2010-18546 (NUCLIERSOL). M. Costa-Suros was supported by research fellowship FPI BES-2008-003129 from the Ministerio de Ciencia e Innovacion of the Spanish Government. C. N. Long acknowledges support from the Office of Science of the US Department of Energy as part of the Atmospheric Systems Research (ASR) program. Data and TSI animations were obtained from the Atmospheric Radiation Measurement (ARM) program sponsored by the US Department of Energy. We thank L. Dimitrieva-Arrago for her explanations and interesting discussions while visiting the University of Girona in the framework of the UE CLIMSEAS project (FP7-PEOPLE-2009-IRSES proposal no. 247512). We also thank the National Oceanic and Atmospheric Administration (NOAA) Comprehensive Large Array-data stewardship system (CLASS) for providing GOES images for research use

Wind power plants are becoming a generally accepted resource in the generation mix of many utilities. At the same time, the size and the power rating of individual wind turbines have increased considerably. Under these circumstances, the sector is increasingly demanding an accurate characterization of vertical wind speed profiles to estimate properly the incoming wind speed at the rotor swept area and, consequently, assess the potential for a wind power plant site. The present paper describes a shape-based clustering characterization and visualization of real vertical wind speed data. The proposed solution allows us to identify the most likely vertical wind speed patterns for a specific location based on real wind speed measurements. Moreover, this clustering approach also provides characterization and classification of such vertical wind profiles. This solution is highly suitable for a large amount of data collected by remote sensing equipment, where wind speed values at different heights within the rotor swept area are available for subsequent analysis. The methodology is based on z-normalization, shape-based distance metric solution and the Ward-hierarchical clustering method. Real vertical wind speed profile data corresponding to a Spanish wind power plant and collected by using a commercialWindcube equipment during several months are used to assess the proposed characterization and clustering process, involving more than 100000 wind speed data values. All analyses have been implemented using open-source R-software. From the results, at least four different vertical wind speed patterns are identified to characterize properly over 90% of the collected wind speed data along the day. Therefore, alternative analytical function criteria should be subsequently proposed for vertical wind speed characterization purposes. ; The authors are grateful for the financial support from the Spanish Ministry of the Economy and Competitiveness and the European Union —ENE2016-78214-C2-2-R—and the Spanish Education, Culture and Sport Ministry —FPU16/0428

The Regional Atmospheric Modeling System (RAMS) is being used for different and diverse purposes, ranging from atmospheric and dispersion of pollutants forecasting to agricultural meteorology and ecological modelling as well as for hydrological purposes, among others. The current paper presents a comprehensive assessment of the RAMS forecasts, comparing the results not only with observed standard surface meteorological variables, measured at FLUXNET stations and other portable and permanent weather stations located over the region of study, but also with non-standard observed variables, such as the surface energy fluxes, with the aim of evaluating the surface energy budget and its relation with a proper representation of standard observations and key physical processes for a wide range of applications. In this regard, RAMS is assessed against in-situ surface observations during a selected period within July 2011 over Eastern Spain. In addition, the simulation results are also compared with different surface remote sensing data derived from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) (MSG-SEVIRI) as well as the uncoupled Land Surface Models (LSM) Global Land Data Assimilation System (GLDAS). Both datasets complement the available in-situ observations and are used in the current study as the reference or ground truth when no observations are available on a selected location. Several sensitivity tests have been performed involving the initial soil moisture content, by adjusting this parameter in the vertical soil profile ranging from the most superficial soil layers to those located deeper underground. A refined adjustment of this parameter in the initialization of the model has shown to better represent the observed surface energy fluxes. The results obtained also show an improvement in the model forecasts found in previous studies in relation to standard observations, such as the air temperature and the moisture fields. Therefore, the application of a drier or wetter soil in distinct soil layers within the whole vertical soil profile has been found to be crucial in order to produce a better agreement between the simulation and the observations, thus reiterating the determining role of the initial soil moisture field in mesoscale modelling, but in this case considering the variation of this parameter vertically. ; This work has been funded by the Regional Government of Valencia through the project PROMETEOII/2014/086 and by the Spanish Ministerio de Economía y Competitividad and the European Regional Development Fund (FEDER) through the project CGL2015-64268-R (MINECO/FEDER,UE).

We present a seabed profile estimation and following method for close proximity inspection of 3D underwater structures using autonomous underwater vehicles (AUVs). The presented method is used to determine a path allowing the AUV to pass its sensors over all points of the target structure, which is known as coverage path planning. Our profile following method goes beyond traditional seabed following at a safe altitude and exploits hovering capabilities of recent AUV developments. A range sonar is used to incrementally construct a local probabilistic map representation of the environment and estimates of the local profile are obtained via linear regression. Two behavior-based controllers use these estimates to perform horizontal and vertical profile following. We build upon these tools to address coverage path planning for 3D underwater structures using a (potentially inaccurate) prior map and following cross-section profiles of the target structure. The feasibility of the proposed method is demonstrated using the GIRONA 500 AUV both in simulation using synthetic and real-world bathymetric data and in pool trials ; This research was sponsored by the Spanish government (COMAROB Project, DPI2011-27977-C03-02) and the MORPH EU FP7-Project under the Grant agreement FP7-ICT-2011-7-288704. We are grateful for this support