Cold pools are a key element in the organization of precipitating convective systems, yet knowledge of their typical surface characteristics is largely anecdotal. To help to alleviate this situation, cold pools from 39 mesoscale convective system (MCS) events are sampled using Oklahoma Mesonet surface observations. In total, 1389 time series of surface observations are used to determine typical rises in surface pressure and decreases in temperature, potential temperature, and equivalent potential temperature associated with the cold pool, and the maximum wind speeds in the cold pool. The data are separated into one of four convective system life cycle stages: first storms, MCS initiation, mature MCS, and MCS dissipation. Results indicate that the mean surface pressure rises associated with cold pools increase from 3.2 hPa for the first storms' life cycle stage to 4.5 hPa for the mature MCS stage before dropping to 3.3 hPa for the dissipation stage. In contrast, the mean temperature (potential temperature) deficits associated with cold pools decrease from 9.5 (9.8) to 5.4 K (5.6 K) from the first storms to the dissipation stage, with a decrease of approximately 1 K associated with each advance in the life cycle stage. However, the daytime and early evening observations show mean temperature deficits over 11 K. A comparison of these observed cold pool characteristics with results from idealized numerical simulations of MCSs suggests that observed cold pools likely are stronger than those found in model simulations, particularly when ice processes are neglected in the microphysics parameterization. The mean deficits in equivalent potential temperature also decrease with the MCS life cycle stage, starting at 21.6 K for first storms and dropping to 13.9 K for dissipation. Mean wind gusts are above 15 m s Ϫ1 for all life cycle stages. These results should help numerical modelers to determine whether the cold pools in high-resolution models are in reasonable agreement with the observed characteristics found herein. Thunderstorm simulations and forecasts with thin model layers near the surface are also needed to obtain better representations of cold pool surface characteristics that can be compared with observations.

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Separating global horizontal irradiance measurements into direct and diffuse components has been vigorously discussed over the past half-century of solar radiation research leading to the creation of many models which attempt to compute these components with varying degrees of success. However, over the course of this discussion, nearly all studies have focused on hourly values, with no studies that have proposed a model for minute-level values of irradiance. As data-logging technologies have become much more prolific and their storage capabilities much larger, solar radiation monitoring sites are more commonly logging data at intervals much less than one hour, but no models exists that are designed to separate these measurements into direct and diffuse components. In Australia, the Australian Bureau of Meteorology and the Australian Solar Institute have compiled a dataset of tens of millions of one-minute global, direct and diffuse solar irradiance observations, comprising data from regions all around Australia. This dataset provides a unique opportunity to investigate the relationships between global irradiance and its direct and diffuse components at higher resolution than has previously been possible. Herein, the largest and most complete diffuse fraction model analysis yet undertaken for Australian solar radiation data, and the first ever to focus on minute resolution data is reported. Nine of the most prominent diffuse fraction, or "separation", models are tested against minute resolution radiation data from three datasets. The first removed cloud enhancement events in accordance with practices undertaken by the majority of studies in the literature. The second retains these events in order to assess which model would be best suited for operational purposes. The third consisted of only clear sky observations, in order to assess the performance of diffuse fraction models under clear skies. Through the course of this study only the Perez model was found to perform satisfactorily for minute resolution data at sites in southeastern Australia. Three new diffuse models proposed in this study, one trained for each of the three datasets, were found to greatly exceed the performance of existing modeling techniques, with slight improvements over

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There have been many validation studies of clear sky solar radiation models, however, to date, no such analysis has been completed for Australia. Clear sky models are essential for estimating the generation potential of various solar energy technologies, the basic calibration of radiation measuring equipment, quality control of solar radiation datasets, engineering design (e.g. heating and cooling of buildings) and in agricultural and biological sciences (e.g. forestry). All of these areas are of considerable interest to the Australian economy and will benefit from an assessment of clear sky radiation models. With the recent provision of one-minute interval radiation data by the Australian Bureau of Meteorology for 20 sites across Australia, such a study can now be undertaken at a level not previously possible. Using up to ten years of data from each of 14 of these sites, clear sky periods are extracted through an automated detection algorithm. With these clear sky periods identified, nine of the most prominent beam and global clear sky radiation models are assessed using the relative Mean Bias Error, relative Root Mean Square Error and Coefficient of Determination as metrics. Further testing assessed model performance as a function of solar zenith angle and apparent solar time. Results show that for global clear sky simulations, the Solis, Esra and REST2 approaches perform best, while the Iqbal, Esra and REST2 methods are the most proficient clear sky beam models.

Knowledge of PV system characteristics is needed in different regional PV modelling approaches. It is the aim of this paper to provide that knowledge by a twofold method that focuses on (1) metadata (tilt and azimuth of modules, installed capacity and specific annual yield) as well as (2) the impact of shading. Metadata from 2,802,797 PV systems located in Europe, USA, Japan and Australia, representing a total capacity of 59 GWp (14.8% of installed capacity worldwide), is analysed. Visually striking interdependencies of the installed capacity and the geographic location to the other parameters tilt, azimuth and specific annual yield motivated a clustering on a country level and between systems sizes. For an eased future utilisation of the analysed metadata, each parameter in a cluster was approximated by a distribution function. Results show strong characteristics unique to each cluster, however, there are some commonalities across all clusters. Mean tilt values were reported in a range between 16.1 • (Australia) and 35.6 • (Belgium), average specific annual yield values occur between 786 kWh/kWp (Denmark) and 1,426 kWh/kWp (USA South). The region with smallest median capacity was the UK (2.94 kWp) and the largest was Germany (8.96 kWp). Almost all countries had a mean azimuth angle facing the equator. PV system shading was considered by deriving viewsheds for ≈ 48,000 buildings in Uppsala, Sweden (all ranges of solar angles were explored). From these viewsheds, two empirical equations were derived related to irradiance losses on roofs due to shading. The first expresses the loss of beam irradiance as a function of the solar elevation angle. The second determines the view factor as a function of the roof tilt including the impact from shading and can be used to estimate the losses of diffuse and reflected irradiance.