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The Forbio Climate Data Set for Climate Analyses : Volume 12, Issu...

By: M. Journée; C. Bertrand; C. Delvaux

Description: Royal Meteorological Institute of Belgium, Brussels, Belgium. In the framework of the interdisciplinary FORBIO Climate research project, the Royal Meteorological Institute of Belgium is in charge of providing high resolution gridded past climate data (i.e. temperature and precipitation). This climate data set will be linked to the measurements on seedlings, saplings and mature trees to assess the effects of climate variation on tree performance. This pa...

Aguilar, E., Auer, I., Brunet, M., Peterson, T., and Wieringa, J.: Guidelines on climate metadata and homogenization, World Climate Programme Data and Monitoring WCDMP-No. 53, WMO-TD No. 1186, World Meteorological Organization, Geneva, 2003.; Bolstad, P. V., Swift, L., Collins, F., and Régnière, J.: Measured and predicted air temperatures at basin to regional scales in the southern Appalachian mountains, Agr. Forest Meteorol., 91, 161–176, 1998.; Bossard, M. and Feranec,...

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Advanced Information Criterion for Environmental Data Quality Assu...

By: A. Hense; A. Düsterhus

Description: Meteorological Institute of the University of Bonn, Auf dem Hügel 20, 53121 Bonn, Germany. A new method for testing time series of environmental data for internal inconsistencies is presented. The method divides the dataset into several disjunct blocks. By means of a comparison of the blocks' estimated probability density distributions, each block is compared with the others. In order to judge the differences, four different measures are used and compare...

Ducr{é}-Robitaille, J.-F., Vincent, L. A., and Boulet, G.: Comparison of techniques for detection of discontinuities in temperature series, Int. J. Climatol., 23, 1087–1101, 2003.; Durre, I., Menne, M. J., Gleason, B. E., Houston, T. G., and Vose, R. S.: Comprehensive Automated Quality Assurance of Daily Surface Observations, J. Appl. Meteorol. Clim., 49, 1615–1633, 2010.; Endres, D. M. and Schindelin, J. E.: A new metric for probability distributions, IEEE T. Inform. Th...

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Forecasting Wind Power Production from a Wind Farm Using the Rams ...

By: A. M. Sempreviva; R. C. Torcasio; S. Montesanti; C. Transerici; L. Tiriolo; S. Federico; C. R. Calidonna

Description: Institute of Atmospheric Sciences and Climate of the Italian National Council of Research, ISAC-CNR, UOS of Lamezia Terme, zona Industriale Comparto 15, 88046 Lamezia Terme, Italy. The importance of wind power forecast is commonly recognized because it represents a useful tool for grid integration and facilitates the energy trading.

This work considers an example of power forecast for a wind farm in the Apennines in Central Italy. The orography...

Alessandrini, S., Sperati, S., and Pinson, P.: A comparison between the ECMWF and COSMO Ensemble Prediction Systems applied to short-term wind power forecasting on real data, Appl. Energy, 107, 271–280, 2013.; Cotton, W. R., Pielke Sr., R. A., Walko, R. L., Liston, G. E., Tremback, C. J., Jiang, H., McAnelly, R. L., Harrington, J. Y., Nicholls, M. E., Carrio, G. G., and McFadden, J. P. : RAMS 2001: Current satus and future directions, Meteor. Atmos., 82, 5–29, 2003.; Dur...

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Atmospheric Boundary Layer Wind Profile at a Flat Coastal Site – W...

By: S.-e. Gryning; E. Batchvarova; A. N. Hahmann; T. Mikkelsen; R. Floors; A. Peña

Description: Wind Energy Division, Risø National Laboratory for Sustainable Energy, Technical University of Denmark, P.O. Box 49, 4000 Roskilde, Denmark. Wind profiles up to 600 m height are investigated. Measurements of mean wind speed profiles were obtained from a novel wind lidar and compared to model simulations from a mesoscale model (WRF-ARW v3.1). It is found that WRF is able to predict the mean wind profile rather well and typically within 1–2 m s−1

Blackadar, A.: The vertical distribution of wind and turbulent exchange in a neutral atmosphere, J. Geophys. Res., 67, 3095–3102, 1962.; Chen, F. and Dudhia, J.: Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity, Mon. Weather Rev., 129, 569–585, 2001.; Draxl, C., Hahmann, A., Pe{ñ}a, A., Nissen, J., and Giebel, G.: Validation of boundary-layer winds from WRF mesoscale forecasts wit...

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The Effect of Weather and Its Changes on Emotional State – Individ...

By: Z. Spasova

Description: National Center of Public Health and Analyses, Sofia, Bulgaria. Given the proven effects of weather on the human organism, an attempt to examine its effects on a psychological and emotional level has been made. Emotions affect the bio tone, working ability, and concentration; hence their significance in various domains of economic life such as health care, education, transportation, and tourism.

The present pilot study was conducted in Sofia, ...

Auliciems, A.: Mood dependency on low intensity atmospheric variability, Int. J. Biometeorol., 22, 20–32, 1978.; Baibakova, E., Butyeva, I., Ilyicheva, E., and Nevraev, G.: Weather change and its assessment for the medical characterization of climate. Issues of culturology, physiotherapy and medical physical exercise, 145–150, 1966.; Barnston, A.: The effect of weather on mood, productivity, and frequency of emotional crisis in a temperate continental climate, Int. J. Bi...

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