Turbulent flux and meteorological measurements during ARCTEX-2006 campaign

This dataset present result from the DFG- funded Arctic-Turbulence-Experiment (ARCTEX-2006) performed by the University of Bayreuth on the island of Svalbard, Norway, during the winter/spring transition 2006. From May 5 to May 19, 2006 turbulent flux and meteorological measurements were performed on the monitoring field near Ny-Ålesund, at 78°55'24'' N, 11°55'15'' E Kongsfjord, Svalbard (Spitsbergen), Norway. The ARCTEX-2006 campaign site was located about 200 m southeast of the settlement on flat snow covered tundra, 11 m to 14 m above sea level. The permanent sites used for this study consisted of the 10 m meteorological tower of the Alfred Wegener Institute for Polar- and Marine Research (AWI), the international standardized radiation measurement site of the Baseline Surface Radiation Network (BSRN), the radiosonde launch site and the AWI tethered balloon launch sites. The temporary sites - set up by the University of Bayreuth - were a 6 m meteorological gradient tower, an eddy-flux measurement complex (EF), and a laser-scintillometer section (SLS). A quality assessment and data correction was applied to detect and eliminate specific measurement errors common at a high arctic landscape. In addition, the quality checked sensible heat flux measurements are compared with bulk aerodynamic formulas that are widely used in atmosphere-ocean/land-ice models for polar regions as described in Ebert and Curry (1993, doi:10.1029/93JC00656) and Launiainen and Cheng (1995). These parameterization approaches easily allow estimation of the turbulent surface fluxes from routine meteorological measurements. The data show: - the role of the intermittency of the turbulent atmospheric fluctuation of momentum and scalars, - the existence of a disturbed vertical temperature profile (sharp inversion layer) close to the surface, - the relevance of possible free convection events for the snow or ice melt in the Arctic spring at Svalbard, and - the relevance of meso-scale atmospheric circulation pattern and air-mass advection for the near-surface turbulent heat exchange in the Arctic spring at Svalbard. Recommendations and improvements regarding the interpretation of eddy-flux and laser-scintillometer data as well as the arrangement of the instrumentation under polar distinct exchange conditions and (extreme) weather situations could be derived.

Meteorological records from the Vernagtferner basin - Gletschermitte Station, for the years 1968 to 1987

The first meteorological station in the Vernagtferner basin, called 'Gletschermitte' was run from 1968 to 1987. It was positioned on a small rock in the western part of the glacier at an elevation of 3078 m a.s.l. The coordinates were 46.868939° N (Latitude) and 10.802986° E (Longitude). The following parameters were recorded mainly during the summer months: Wind speed and wind direction, air temperature and humidity of the air and precipitation. The records of the first four parameters comprise hourly values from 1968 to 1986 /1987, daily sums of precipitation run from 1977 to 1987. All quantities were recorded on paper chart, i.e. 'Woelfle-Windschreiber' for the wind components, mechanically driven thermo-hygrographs (1968 to 1975) and 'BTW-Langzeit-Thermo-Hygrograph' (1977 to 1987) for temperature and humidity, Belfort analogue weighing gauge for precipitation. In 1976, air temperature was recorded on a Schenk paper chart recorder. In addition, photographs of the eastern part of Vernagtferner were taken once a day in summer between 1981 and 1986.

Meteorological observations and eddy covariance raw data from polygonal tundra in the Lena River Delta, Siberia

We present the first ecosystem-scale methane flux data from a northern Siberian tundra ecosystem covering the entire snow-free period from spring thaw until initial freeze-back. Eddy covariance measurements of methane emission were carried out from the beginning of June until the end of September in the southern central part of the Lena River Delta (72°22' N, 126°30' E). The study site is located in the zone of continuous permafrost and is characterized by Arctic continental climate with very low precipitation and a mean annual temperature of -14.7°C. We found relatively low fluxes of on average 18.7 mg/m**2/d, which we consider to be because of (1) extremely cold permafrost, (2) substrate limitation of the methanogenic archaea, and (3) a relatively high surface coverage of noninundated, moderately moist areas. Near-surface turbulence as measured by the eddy covariance system in 4 m above the ground surface was identified as the most important control on ecosystem-scale methane emission and explained about 60% of the variance in emissions, while soil temperature explained only 8%. In addition, atmospheric pressure was found to significantly improve an exponential model based on turbulence and soil temperature. Ebullition from waterlogged areas triggered by decreasing atmospheric pressure and near-surface turbulence is thought to be an important pathway that warrants more attention in future studies. The close coupling of methane fluxes and atmospheric parameters demonstrated here raises questions regarding the reliability of enclosure-based measurements, which inherently exclude these parameters.

A probabilistic approach to the estimation of regional photovoltaic power generation using meteorological data

In Germany the upscaling algorithm is currently the standard approach for evaluating the PV power produced in a region. This method involves spatially interpolating the normalized power of a set of reference PV plants to estimate the power production by another set of unknown plants. As little information on the performances of this method could be found in the literature, the first goal of this thesis is to conduct an analysis of the uncertainty associated to this method. It was found that this method can lead to large errors when the set of reference plants has different characteristics or weather conditions than the set of unknown plants and when the set of reference plants is small. Based on these preliminary findings, an alternative method is proposed for calculating the aggregate power production of a set of PV plants. A probabilistic approach has been chosen by which a power production is calculated at each PV plant from corresponding weather data. The probabilistic approach consists of evaluating the power for each frequently occurring value of the parameters and estimating the most probable value by averaging these power values weighted by their frequency of occurrence. Most frequent parameter sets (e.g. module azimuth and tilt angle) and their frequency of occurrence have been assessed on the basis of a statistical analysis of parameters of approx. 35 000 PV plants. It has been found that the plant parameters are statistically dependent on the size and location of the PV plants. Accordingly, separate statistical values have been assessed for 14 classes of nominal capacity and 95 regions in Germany (two-digit zip-code areas). The performances of the upscaling and probabilistic approaches have been compared on the basis of 15 min power measurements from 715 PV plants provided by the German distribution system operator LEW Verteilnetz. It was found that the error of the probabilistic method is smaller than that of the upscaling method when the number of reference plants is sufficiently large (>100 reference plants in the case study considered in this chapter). When the number of reference plants is limited (<50 reference plants for the considered case study), it was found that the proposed approach provides a noticeable gain in accuracy with respect to the upscaling method.

Cross-correlations between weather variables in Australia

The information on climate variations is essential for the research of many subjects, such as the performance of buildings and agricultural production. However, recorded meteorological data are often incomplete. There may be a limited number of locations recorded, while the number of recorded climatic variables and the time intervals can also be inadequate. Therefore, the hourly data of key weather parameters as required by many building simulation programmes are typically not readily available. To overcome this gap in measured information, several empirical methods and weather data generators have been developed. They generally employ statistical analysis techniques to model the variations of individual climatic variables, while the possible interactions between different weather parameters are largely ignored. Based on a statistical analysis of 10 years historical hourly climatic data over all capital cities in Australia, this paper reports on the finding of strong correlations between several specific weather variables. It is found that there are strong linear correlations between the hourly variations of global solar irradiation (GSI) and dry bulb temperature (DBT), and between the hourly variations of DBT and relative humidity (RH). With an increase in GSI, DBT would generally increase, while the RH tends to decrease. However, no such a clear correlation can be found between the DBT and atmospheric pressure (P), and between the DBT and wind speed. These findings will be useful for the research and practice in building performance simulation.