denis-bz

Windspeeds across Bayern at 175m in 2016 from CERRA

Keywords: wind-power Bayern CERRA capacity-factor renewable-energy open-data python

CERRA has open data on windspeeds across Europe, 3-hour averages on a 5.5 km grid.
See CERRA, the Copernicus European Regional Reanalysis system Ridal et al., 2024, 27p.
This map of average windspeeds in 2016 was made from CERRA data, using python and numpy:

denis-bz

EEG für Windräder: Je weniger Wind, desto mehr Geld

Keywords: wind-power low-wind Germany Bayern renewable-energy EEG Erneuerbare-Energie

Was, Bayern ist schwachwindig ? Kein Problem, Söder und Aiwanger holen einen ordentlichen Extrazuschlag raus:

Wer bestimmt denn den Gütefaktor an einem Standort?

denis-bz

Windspeeds at 175m in Germany, COSMO-REA6 and NEWA

Keywords: wind-speed COSMO-REA6 NEWA Germany neweuropeanwindatlas reanalysis open-data python

I'm interested in windspeeds at 175m, the turbine height of many new wind turbines in Germany, Two sources of windspeed data in EUrope are

1. https://opendata.DWD.de/.../COSMO_REA6: hourly, 1995 to 2018, 6 x 6 km grid
2. NEWA, the New European Wind Atlas, 3 x 3 km grid.

What are good places to compare the two ?

denis-bz

Fourier upsamplng a spike: why is odd n so big ?

Keywords: resample upsample interpolate frequency-domain Fourier scipy

The problem:

from scipy.signal import resample # in Fourier space

denis-bz

TSH levels of 111 hypothyroid people over 70: 26 % have TSH $\geq$ 4.0

TSH, Thyroid-stimulating_hormone, is measured in blood to determine a suitable dosage of L-thyroxine.

Is TSH 4.0 high ?

Wikipedia TSH gives "reference ranges" of $0.4 - 4.0$ μIU/mL.

denis-bz

Callback to track and stop scipy solve_ivp

Keywords: scipy solve_ivp callback ODE ordinary-differential-equation IVP initial-value-problem python

Purpose

add a callback function to the scipy ODE solver solve_ivp, so that you can

• print progress at each timestep
• tell the solver to stop if h is too small, or KeyboardInterrupt, or ... and return the sol so far.

denis-bz

Cosmopy: clip and regrid COSMO_REA6 wind data to python numpy

Keywords: Cosmo_rea6 DWD wind-data python numpy

Purpose: DWD, the German Meteorological Service, has wind data for Europe on a 6 x 6 km grid, from 1995 to August 2019, hourly, at heights 10 100 .. 200m. These are in 2 gigabyte files like
https://opendata.dwd.de/climate_environment/REA/COSMO_REA6/converted/hourly/2D/WS_100m.2D.201908.nc4
-- windspeed data at 100m for 2019 August.

denis-bz

Old mst.py with Kruskal's algorithm

mst.py is simple old (2011) code for MSTs using Kruskal's algorithm -- see the animation there.

Kleinberg-Tardos:

single-link k-clustering == MST k-1 most expensive edges

but min( max spacing ), Theorem 1, may be wrong or at least odd for k-clustering ?

denis-bz

Windspeeds in Bayern, COSMO_REA6 vs. ERA5

Here are plots of average windspeeds in Bayern in January 2018 at 100m,
COSMO_REA6 on its ~ 6 × 6 km grid
ERA5 on its 0.25° × 0.25° grid.
We see big differences over the Alps in the south and over hilly areas in north Bayern.

denis-bz

Wind speeds at 100m in Bayern, ERA5 vs. globalwindatlas

Keywords: wind power, Germany, python, ERA5, globalwindatlas

Purpose: look at windspeed estimates at 100m in Bayern from two different sources:
ERA5: https://confluence.ecmwf.int/display/CKB/ERA5
GWA: https://globalwindatlas.info/area/Germany/Bayern