398 research outputs found
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Rapid liquid AP-MALDI MS profiling of lipids and proteins from goat and sheep milk for speciation and colostrum analysis
No full textDataset of liquid AP-MALDI MS profiling of lipids and proteins from goat and sheep milk for speciation and colostrum analysis. The dataset supports the article by Piras et al. 2020, 'Rapid machine learning-liquid AP-MALDI MS profiling of lipids and proteins from goat and sheep milk for speciation and colostrum analysis'. The dataset contains mass spectrometry data, multivariate models and validation reports
ERA5 derived time series of European country-aggregate electricity demand, wind power generation and solar power generation: hourly data from 1979-2019
No full textThe ERA5 reanalysis data (1979-2019) has been used to calculate the hourly country aggregated wind and solar power generation for 28 European countries based on a distribution of wind and solar farms which is considered to be representative of the 2017 situation. In addition a corresponding daily time series of nationally aggregated electricity demand is provided. The datasets have been produced to investigate the inter-annual variability of the three weather-dependent power system components.
When citing this dataset please refer to the publication: Sub-seasonal forecasts of demand, wind power and solar power generation for 28 European countries (see Related CentAUR publications)
MERRA2 derived time series of European country-aggregate electricity demand, wind power generation and solar power generation
No full textThe MERRA2 reanalysis data (1980-2018) has been used to calculate the hourly, country aggregated wind and solar power generation for 28 European countries based on a distribution of wind and solar farms which is considered to be representative of the current situation (2017). In addition a corresponding daily time series of nationally aggregated electricity demand is provided. The data sets have been produced to investigate the inter-annual variability of the three weather-dependent power system components
Improved method for rapid calculation of halocarbon radiative forcing
No full textThe model described in Pinnock et al. (Journal of Geophysical Research 1995 10.1029/95JD02323) permits the rapid and accurate calculation of the radiative forcing of halocarbons using the absorption cross-sections of those halocarbons (which could be derived from laboratory observations or quantum-chemical calculations). The provided values are an update to those given in Hodnebrog et al. (Reviews of Geophysics 2013 10.1002/rog.20013) and include, for the first time, an explicit wavenumber-dependent correction for the effect of stratospheric temperature adjustment. The revised method is detailed in Shine and Myhre (Journal of Advances in Modeling Earth Systems 2020 10.1029/2019MS001951)
Dataset for 'Consistent dust electrification from Arabian Gulf sea breezes'
No full textThis dataset contains atmospheric electric field, visibility and ceilometer data contained within the paper 'Consistent dust electrification from Arabian Gulf sea breezes' by K.A. Nicoll, R.G. Harrison, G.M. Marlton and M.W. Airey, submitted to Environmental Research Letters (2020). The measurements were obtained at Al Ain airport (24°15' N, 55°37' E), United Arab Emirates (UAE) in the year 2018. The data has been used within this paper to study the electrification of dust lofted by sea breeze events
ERA5 derived time series of European country-aggregate electricity demand, wind power generation and solar power generation
No full textThe ERA5 reanalysis data (1979-2018) has been used to calculate the three-hourly country aggregated wind and solar power generation for 28 European countries based on a distribution of wind and solar farms which is considered to be representative of the current situation (2017). In addition a corresponding daily time series of nationally aggregated electricity demand is provided. The datasets have been produced to investigate the inter-annual variability of the three weather-dependent power system components.
** This is an update on the previous version of the data where there were issues with the timestamps in the 3-hourly wind and solar power data. *
Reconstructions of the radiation fluxes at the top of the atmosphere and net surface energy flux over 1985-2017 - DEEP-C Version 4.0
No full textIn order to study the energy flow in the climate system, the radiative fluxes (OLR, ASR and NET) at the top of atmosphere (TOA) prior to the CERES period have been reconstructed using satellite observations of CERES v4.1 and ERBS WFOF v3.0, atmospheric reanalysis (ERA5) and AMIP6 model simulations. The new approach using the mass-corrected atmospheric energy divergencies (transports) and consistent enthalpy treatment of water substances is employed to estimate the net surface energy fluxes.
This is the version 4.0 of DEEP-C dataset created in September 2020. CERES version 4.1 and ERBS WFOV version 3.0 are used. The TOA flux anomaly is constrained by WFOV anomaly in each 10 degree x 10 degree grid box.
The atmospheric energy transport is based on the new enthalpy treatment of water substances (Mayer et al. 2017)
Outputs from a volcanic ash transport and dispersion model (NAME), source inversion system (InTEM) and SEVIRI satellite retrievals for the 2011 Grímsvötn eruption.
No full textThis dataset contains (1) the output of a volcanic ash transport and dispersion model (Numerical Atmospheric-dispersion Modelling Environment - NAME) simulations of the 2011 Grímsvötn eruption used in the UK Met Office volcanic ash source inversion system (InTEM), (2) SEVIRI satellite retrievals provided by kind permission of the UK Met Office that were used in InTEM inversion system, (3) output from the InTEM system for the Grímsvötn eruption, (4) output of volcanic ash transport and dispersion model simulations used for comparison to satellite retrievals and to produce ash hazard risk maps. The use of this data is outlined in Natalie Harvey et al. (2020): The impact of ensemble meteorology on inverse modeling estimates of volcano emissions and ash dispersion forecasts: Grímsvötn 2011
Sub-seasonal forecasts of European electricity demand, wind power and solar power generation
No full textSub-seasonal forecasts of daily country-level European electricity demand, wind power and solar power generation, along with the driving meteorological variables, from two sub-seasonal to seasonal prediction systems and lead times extending to 44 days. The matching ERA5-derived variables are also provided to facilitate verification analyses.
When citing this dataset please refer to the publication: Sub-seasonal forecasts of demand, wind power and solar power generation for 28 European countries (see Related CentAUR publications)
Skillful spatial scales and representativity of seasonal rainfall forecasts over Africa
No full textThis dataset contains gridded estimates of the skillful spatial scales of seasonal rainfall forecasts (tercile probabilities) over Africa and a measure of how representative these skillful spatial scales are for anticipating local rainfall conditions (as described by terciles). The skillful spatial scales presented apply to tercile probability hindcasts (re-forecasts) of seasonal total rainfall derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting System 5 (SEAS5). The SEAS5 hindcasts analysed here are initialised at a lead time of 1 month ahead of the start of a given season. The representativity of the SEAS5 skillful spatial scales is computed using observed seasonal rainfall terciles from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) version 2.0 dataset. The skillful spatial scales and representativity data are combined to delineate regions where the SEAS5 seasonal hindcasts are both skillful and representative for anticipating local seasonal rainfall conditions. Note that the these data are specific to tercile probabilities derived from the SEAS5 hindcasts and different skillful scales and representativity results are likely to be found when applying this methodology to other dynamical weather forecasting systems and event/quantile categories.
A subset of this dataset is presented in Figure 6 of
Young, M., Heinrich, V., Black, E., and Asfaw, D., 2020: Optimal spatial scales for seasonal forecasts over Africa, Environmental Research Letters. In press https://doi.org/10.1088/1748-9326/ab94e9