Bias correction of a novel European reanalysis data set for solar energy applications
暂无分享,去创建一个
Susanne Crewell | Andreas Hense | Jan D. Keller | Sabrina Wahl | Bernhard Pospichal | A. Hense | S. Crewell | J. Keller | B. Pospichal | Christopher Frank | S. Wahl | Christopher Frank | Sabrina Wahl
[1] M. Stone. Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .
[2] B. McArthur,et al. Baseline surface radiation network (BSRN/WCRP) New precision radiometry for climate research , 1998 .
[3] Christoph Schillings,et al. Long-term variability of solar direct and global radiation derived from ISCCP data and comparison with reanalysis data , 2006 .
[4] Sabine Van Huffel,et al. Overview of total least-squares methods , 2007, Signal Process..
[5] C. Gueymard,et al. Evaluation of conventional and high-performance routine solar radiation measurements for improved solar resource, climatological trends, and radiative modeling , 2009 .
[6] Martin Greiner,et al. Seasonal optimal mix of wind and solar power in a future, highly renewable Europe , 2010 .
[7] J. Thepaut,et al. The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .
[8] S. Schubert,et al. MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications , 2011 .
[9] Lucien Wald,et al. The HelioClim Project: Surface Solar Irradiance Data for Climate Applications , 2011, Remote. Sens..
[10] David Pozo-Vázquez,et al. Generation of synthetic daily global solar radiation data based on ERA-Interim reanalysis and artifi , 2011 .
[11] D. Lüthi,et al. Intercomparison of aerosol climatologies for use in a regional climate model over Europe , 2011 .
[12] Jörg Trentmann,et al. Remote sensing of solar surface radiation for climate monitoring — the CM-SAF retrieval in international comparison , 2012 .
[13] J. A. Ruiz-Arias,et al. Analysis of Spatiotemporal Balancing between Wind and Solar Energy Resources in the Southern Iberian Peninsula , 2012 .
[14] Jan Kleissl,et al. Solar Energy Forecasting and Resource Assessment , 2013 .
[15] Janet F. Barlow,et al. Exploring the role of reanalysis data in simulating regional wind generation variability over Northern Ireland , 2013 .
[16] Zhenghui Xie,et al. Evaluation of satellite and reanalysis products of downward surface solar radiation over East Asia: Spatial and seasonal variations , 2013 .
[17] Hazel E. Thornton,et al. European wind variability over 140 yr , 2013, 1301.4032.
[18] C. Frantzidis,et al. Response to Reviewers Reviewer #1 , 2010 .
[19] Fokko M. Mulder,et al. Implications of diurnal and seasonal variations in renewable energy generation for large scale energy storage , 2014 .
[20] Dirk J. Cannon,et al. Using reanalysis data to quantify extreme wind power generation statistics: A 33 year case study in Great Britain , 2015 .
[21] Jay Apt,et al. What can reanalysis data tell us about wind power , 2015 .
[22] Hilppa Gregow,et al. Comparison of regional and global reanalysis near-surface winds with station observations over Germany , 2015 .
[23] Susanne Crewell,et al. Towards a high‐resolution regional reanalysis for the European CORDEX domain , 2015 .
[24] Richard Müller,et al. Digging the METEOSAT Treasure - 3 Decades of Solar Surface Radiation , 2015, Remote. Sens..
[25] L. Wald,et al. Comparison between meteorological re-analyses from ERA-Interim and MERRA and measurements of daily solar irradiation at surface , 2015 .
[26] Martin Odening,et al. A New Approach to Assess Wind Energy Potential , 2015 .
[27] Hazel E. Thornton,et al. The climatological relationships between wind and solar energy supply in Britain , 2015, 1505.07071.
[28] F. Kaspar,et al. Wind speed variability between 10 and 116 m height from the regional reanalysis COSMO-REA6 compared to wind mast measurements over Northern Germany and the Netherlands , 2016 .
[29] S. Pfenninger,et al. Using bias-corrected reanalysis to simulate current and future wind power output , 2016 .
[30] Clemens Simmer,et al. HErZ: The German Hans-Ertel Centre for Weather Research , 2016 .
[31] S. Pfenninger,et al. Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data , 2016 .
[32] S. Pfenninger,et al. Balancing Europe’s wind power output through spatial deployment informed by weather regimes , 2017, Nature climate change.
[33] Susanne Crewell,et al. A novel convective-scale regional reanalysis COSMO-REA2: Improving the representation of precipitation;A novel convective-scale regional reanalysis COSMO-REA2: Improving the representation of precipitation , 2017 .
[34] Andreas Knaut,et al. The benefit of long-term high resolution wind data for electricity system analysis , 2018 .