Archived information

My personal archive - A list of useful links for work

    To read

    C3RDM data management, EU wind-and-other-co2-free-assets-replacing-coal-2030, the-many-faces-of-the-nao, van der Wiel A protocol for probabilistic extreme event attribution analyses, Data Analysis: A Bayesian Tutorial sivia john skilling
  1. Tools: Connected papers, Research rabbit,

  2. Data

  3. Courses

    Data assimilation ECMWF, AI4ES summer school will be held virtually June 22-26, 2020 by the National Center for Atmospheric Research (Boulder, Colorado, USA). ECMWF Data assimilation EUMESAT training: EUMETRAIN, SatManu, Synoptic course 2018 Weather briefings, Summer schools in Europe, FLAGSHIP floating offshore wind,
  4. Relevant institutions US renewable energy laboratory Amesoc seminar HErZ Koeln-Bonn website (my responsibity) Login: add wp-admin after the URL. Wordpress website
  5. Data European countries Wind power onshore Offshore What wind turbine is that (Germany)? Turbinemap Radiation model Forecast-uChicago
  6. Observations:
    JOYCE cloud website
    Precipitation data satellite Germany Jülich JOYCE
    Bonn website

    Aerosol aerosol net
  7. Zoom Earth and Weather map DWD precipitation and satellitefilm; Windy weather radar in Germany and Vietnam
  8. Python course - Numpy and python3 tutorial quick tips for reducing dimention, pyam package similar to dplyr Plotly - python Colorspace: manipulating and assessing colours and palettes Huyen Chip Just pandas things

  9. Tips for plotting


    Matplotlib samples from DKRZ source code and PyNGL from NCAR; Beautiful colors, Colour scheme for oceanography Cartopy advanced, projections, Gallery, ECMWF inspiration, based on xarray, Metview Metpy,
  10. Documentation: netCDF4 package, CDO wiki, documentation, DKRZ examples eHighway2050 https://docs.entsoe.eu/baltic-conf/bites/www.e-highway2050.eu/results/
    HErZ: Literature list on COSMO Website HErZ website https://www.herz.uni-bonn.de/wordpress/
    grib: wgrib, wgrib2, wgrib2 tricks
    Jupyter: jupyter notebook tricks 10 practical tips to personalize jupyter notebook
  11. Weather regime classification wetterlagen from DWD,
    12. MetOffice weather regimes,

Interesting articles to read

  1. from Raul Pacheco-Vega
      Reading techniques
    • Abstract. AIC story telling -> Put a question (when read title/abstract) and read the paper whether to answer it
    • Introduction: the context, what’s been done, BUT the problem is, hence the paper, will solve using method
    • Conclusion: summary of what’s been done and how (In this paper), additional context and insight
    • Short summary (rhetorical precis) each sentence: 1. (Authors, date, title) & Verb (assert, argue, deny, refute, suggest, prove, disprove, explain, etc.) & Major claim (thesis statement), 2. How the authors develop and support the claim, 3 Authors’ purpose (in order to), 4. Intended audience
  2. Towards data science 5 pro tips to grow your python skills for data scientists or machine learning engineer
  3. Xarray Jit
Useful command lines
  1. Animation from png files (Melanie)
    ffmpeg -framerate 3 -pattern_type glob -i '*.png' -c:v libx264 -r 30 -pix_fmt yuv420p out.mp4
  2. wgrib -h cutoffs/cutoff_2007.2d.grb | grep "var156" > out.txt
    wget -b
    wget https://opendata.dwd.de/climate_environment/REA/COSMO_REA6/daily/2D/T_2M/T_2M.2D.2010{01..12}.DayMean.grb cat infile1.grb infile2.grb > out.grb grep -r --after-context=2 --before-context=2 'shapefile' * (-r: search also inside sub-directory) cat *.tar.bz2 | tar -ixjv # multiple file tar -xf file.tar.bz2 # one file SCREEN screen -ls screen -r 5647 Ctrl a d -> detach screen -XS 20411 quit --> or Ctrl a k, then y (not sure) screen -x -d 368297
  3. Listen to what ports are used: netstat -tulpn | grep LISTEN
  4. cdo pardes/showname ifile.grb/nc? (list of variables) 
    
			cdo -timmean ifile.nc file.nc
			cdo -timmean -selmon,01,02,12 ifile.nc ofile.nc
			cdo -timmean -selyear,2000/2010 file …
			For mon in 01 02 ..
			do
			cdo …
			done
			cdo selday,01/15 ifile ofile_April1-15.nc
			cdo selday,16/30 file ofile_April16-end.nc
			cdo mergetime ifle1_dec ifile_01 ofile_winterGWL.nc
			cdo -r -f nc copy ifile.grb file.nc
			cdo daymean -cat '/data/etcc/cosmo-rea6/15min/SWDIRS_RAD.2D/2007/*/*.grb' mean.grb
    cdo info -selmon,01 -daymean -ifthen SWDIRS_RAD.2D.201001.grb SWDIRS_RAD.2D.201001.grb - Info outputs results on the screen (remove and put and ofile name at the end, if you want to write it to a file, include -r -f nc behind cdo to output netCDF directly) - Selmon removes the NaN from the fist time step for month 02 - Daymean computes the mean for each day - Ifthen determines areas where the value is greater than 0 from ifile1 and than selects the values from these areas in ifile2 (here the same file, hence the file is named twice) This gives us one value per day and the middle of the averaging period is written to file/screen as the time stamp. = repetitive???? cdo info -selmon,01 -daymean -ifthen SWDIRS_RAD.2D.201001.grb SWDIRS_RAD.2D.201001.grb - Info outputs results on the screen (remove and put and ofile name at the end, if you want to write it to a file, include -r -f nc behind cdo to output netCDF directly) - Selmon removes the NaN from the fist time step for month 02 - Daymean computes the mean for each day - Ifthen determines areas where the value is greater than 0 from ifile1 and than selects the values from these areas in ifile2 (here the same file, hence the file is named twice) This gives us one value per day and the middle of the averaging period is written to file/screen as the time stamp. cdo -s showyear file1.nc | xargs -n1 > times_file1 cdo -s showyear file2.nc | xargs -n1 > times_file2 comm -23 times_file1 times_file2 > missing_times Get the missing timestep {#tsteps[@]}-1: syntax error: operand expected (error token is "{#tsteps[@]}-1")
Others
  1. Hiking: Hiking planning,
  2. Organise your trip: tricount How to listen to clasical music Insidethescore App: Menti (polls, word …), mural (white board everyone) AGU sketch your science My Blog - website