El "encounter group" en la orientación personalizada

El pasado curso escolar 1971-1972 tuve la oportunidad de trabajar, becado por la New York University, en el Center for Educational Research and Field Services de la School of Education de aquella universidad norteamericana. Entre las valiosas experiencias y los nuevos métodos que aprendí, quiero presentar en esta breve comunicación por su novedad y eficacia el "encounter group" como técnica de orientación persanalizada. Al redactar este trabajo deseo expresar mi agradecimiento al Dr. Robert M. Wasson, profesor de "Counselor Education" y "Group Counseling" de la School of; Education de la New York Untversity, discípulo de Karl Rogers y mi maestro en técnicas intensivas de grupo. El profesor Wasson me introdujo e inició en la práctica del "encounter group" haciéndome participar como miembro de uno de los grupos en los que actuaba como facilitador, y posteriormente me brindó la oportunidad de actuar a su lado como co-lider en varias ocasiones. Estas líneas tienen por objeto divulgar mis experiencias y ofrecer una sencilla y sintética visión de los orígenes, características, dinámica, ventajas e inconvenientes de los "encounter groups" aplicados a la orientación personal

Correction of a lunar-irradiance model for aerosol optical depth retrieval and comparison with a star photometer

Spanish Ministry of Science, Innovation and Universities RTI2018-097864-b-I00Spanish Ministry of Economy and Competitiveness CGL2016-81092-R CGL2017-90884-REDTEuropean Union's Horizon 2020 research and innovation programme ACTRIS IMP 871115Andalusia Regional Government P18-RT-382

Implementation of UV rotational Raman channel to improve aerosol retrievals from multiwavelength lidar

Vibrational Raman effect is widely used in atmospheric lidar systems, but rotational Raman present several advantages. We have implemented a new setup in the ultraviolet branch of an existing multiwavelength lidar system to collect signal from rotational Raman lines of Oxygen and Nitrogen. We showed that, with an appropriate filter wavelength selection, the systematic error introduced in the particle optical properties due to temperature dependence was less than 4%. With this new setup, we have been able to retrieve aerosol extinction and backscatter coefficients profiles at 355 nm with 1-h time resolution during daytime and up to 1-min time resolution during nighttime.Grupo de Física de la Atmósfera (RNM119

Seasonal analysis of the atmosphere during five years by using microwave radiometry over a mid-latitude site

This work focuses on the analysis of the seasonal cycle of temperature and relative humidity (RH) profiles and integrated water vapor (IWV) obtained from microwave radiometer (MWR) measurements over the mid-latitude city of Granada, southern Spain. For completeness the study, the maximum atmospheric boundary layer height (ABLHmax) is also included. To this end, we have firstly characterized the HATPRO-RPG MWR errors using 55 co-located radiosondes (RS) by means of the mean-bias (biasbar) profile and the standard deviation (SDbias) profile classified under all-weather conditions and cloud-free conditions. This characterization pointed out that temperature from HATPRO-MWR presents a very low biasbar respects RS mostly below 2.0 km agl, ranging from positive to negative values under all-weather conditions (from 1.7 to -0.4 K with SDbias up to 3.0 K). Under cloud-free conditions, the bias was very similar to that found under all-weather conditions (1.8 to -0.4 K) but with smaller SDbias (up to 1.1 K). The same behavior is also seen in this lower part (ground to 2.0 km agl) for RH. Under all-weather conditions, the mean RH bias ranged from 3.0 to -4.0% with SDbias between 10 and 16.3% while under cloud-free conditions the bias ranged from 2.0 to -0.4% with SDbias from 0.5 to 13.3%. Above 2.0 km agl, the SDbias error increases considerably up to 4 km agl (up to -20%), and then decreases slightly above 7.0 km agl (up to -5%). In addition, IWV values from MWR were also compared with the values obtained from the integration of RS profiles, showing a better linear fit under cloud-free conditions (R2 = 0.96) than under all-weather conditions (R2 = 0.82). The mean bias under cloud-free conditions was -0.80 kg/m2 while for all-weather conditions it was -1.25 kg/m2. Thus, the SDbiasfor all the statistics (temperature, RH and IWV) of the comparison between MWR and RS presented higher values for all-weather conditions than for cloud-free conditions ones. It points out that the presence of clouds is a key factor to take into account when MWR products are used. The second part of this work is devoted to a seasonal variability analysis over five years, leading us to characterize thermodynamically the troposphere over our site. This city atmosphere presents a clear seasonal cycle where temperature, ABLHmax and IWV increase from winter to summer and decrease in autumn, meanwhile RH decreases along the warmer seasons. This city presents cold winters (mean daily maximum temperature: 10.6 ± 1.1 °C) and dry/hot summers (mean daily maximum temperature of 28.8 ± 0.9 °C and mean daily maximum of surface RH up to 55.0 ± 6.0%) at surface (680 m asl). Moreover, considering temporal trends, our study pointed out that only temperature and RH showed a linear increase in winters with a mean-rate of (0.5 ± 0.1) °C/year and (3.4 ± 1.7) %/year, respectively, from ground to 2.0 km agl, meanwhile IWV presented a linear increase of 1.0 kg·m-2/year in winters, 0.78 kg·m-2/year in summers and a linear decrease in autumns of -0.75 kg·m-2/year.Andalusia Regional Government through project P12-RNM-2409Spanish Ministry of Economy and Competitiveness through projects CGL2013-45410-R, CGL2015-73250-JIN and CGL2016-81092-RJuan de la Cierva grant IJCI-2016-3000

Retrieval of aerosol profiles combining sunphotometer and ceilometer measurements in GRASP code

This is a preprint version of article accepted "Roman, A.; et al. Retrieval of aerosol profiles combining sunphotometer and ceilometer measurements in GRASP code. Atmospheric Research, 204: 161-177 (2018). DOI: https://doi.org/10.1016./j.atmosres.2018.01.021".In this paper we present an approach for the profiling of aerosol microphysical and optical properties combining ceilometer and sun/sky photometer measurements in the GRASP code (General Retrieval of Aerosol and Surface Properties). For this objective, GRASP is used with sun/sky photometer measurements of aerosol optical depth (AOD) and sky radiances, both at four wavelengths and obtained from AErosol RObotic NETwork (AERONET), and ceilometer measurements of range corrected signal (RCS) at 1064 nm. A sensitivity study with synthetic data evidences the capability of the method to retrieve aerosol properties such as size distribution and profiles of volume concentration (VC), especially for coarse particles. Aerosol properties obtained by the mentioned method are compared with airborne in-situ measurements acquired during two flights over Granada (Spain) within the framework of ChArMEx/ADRIMED (Chemistry-Aerosol Mediterranean Experiment/Aerosol Direct Radiative Impact on the regional climate in the MEDiterranean region) 2013 campaign. The retrieved aerosol VC profiles agree well with the airborne measurements, showing a mean bias error (MBE) and a mean absolute bias error (MABE) of 0.3 µm3/cm3 (12%) and 5.8 µm3/cm3 (25%), respectively. The differences between retrieved VC and airborne in-situ measurements are within the uncertainty of GRASP retrievals. In addition, the retrieved VC at 2500 m a.s.l. is shown and compared with in-situ measurements obtained during summer 2016 at a high-atitude mountain station in the framework of the SLOPE I campaign (Sierra Nevada Lidar AerOsol Profiling Experiment). VC from GRASP presents high correlation (r=0.91) with the in-situ measurements, but overestimates them, MBE and MABE being equal to 23% and 43%.This work was supported by the Andalusia Regional Government (project P12-RNM-2409) and by the “Consejería de Educación” of “Junta de Castilla y León” (project VA100U14); the Spanish Ministry of Economy and Competitiveness under the projects, CMT2015-66742-R, CGL2016-81092-R and “Juan de la Cierva-Formación” program (FJCI-2014-22052); and the European Union's Horizon 2020 research and innovation programme through project ACTRIS-2 (grant agreement no 654109) and the Marie Curie Rise action GRASP-ACE (grant agreement no 778349). The authors thankfully acknowledge the FEDER program for the instrumentation used in this work. COST Action TOPROF (ES1303), supported by COST (European Cooperation in Science and Technology), is also acknowledged

Extinction-related Angström exponent characterization of submicrometric volume fraction in atmospheric aerosol particles

The AEAOD– ΔAEAOD grid proposed by Gobbi et al. (2007) is a graphical method used to visually represent the spectral characterization of aerosol optical depth (AOD), i.e. Angström exponent (AE) and its curvature, in order to infer the fine mode contribution (η) to the total AOD and the size of the fine mode aerosol particles. Perrone et al. (2014) applied this method for the wavelengths widely used in lidar measurements. However, in neither case does the method allow for a direct relationship between η and the fine mode fraction contribution to the total aerosol population. Some discussions are made regarding the effect of shape and composition to the classical AE-ΔAE plot. The potential use of particle backscatter measurements, widely used in aerosol characterization methods together with extinction measurements, is also discussed in the AE-ΔAE grid context. A modification is proposed that yields the submicron contribution to the total volume concentration by using particle extinction data, and a comparison to experimental measurements is made. Our results indicate that the use of a modified AE-ΔAE grid plot to directly obtain submicrometric and micrometric mode fraction to the total aerosol population is feasible if a volume-based bimodal particle size distribution is used instead of a number-based one.Andalusia Regional Government through project P12-RNM-2409Spanish Ministry of Sciences, Innovation and Universities (CGL2016-81092 and CGL2017 -90884 - REDT