ASSESSING ATMOSPHERIC STABILITY FROM GROUND-BASED MICROWAVE RADIOMETER OBSERVATIONS FOR WIND ENERGY APPLICATIONS

S. T. Nilo¹, D. Cimini^1,2, F. Di Paola¹, D. Gallucci¹, S. Gentile^1,2, E. Geraldi¹, S. Larosa¹, E. Ricciardelli¹, M. Viggiano¹, F. Romano¹, S. Fiedler³

¹National Research Council of Italy, Institute of Methodologies for Environmental Analysis (CNR-IMAA), Potenza, 85100, Italy, ²CETEMPS, University of L’Aquila, L’Aquila, 67100, Italy, ³Institute for Geophysics and Meteorology, University of Cologne, 50969 Cologne, Germany, now at: Institute of Environmental Physics, University Heidelberg, 69120 Heidelberg, Germany

Atmospheric stability is a critical factor influencing wind turbine performance by modulating the evolution of wakes and blockage effects. Typically, turbine output is enhanced under unstable or neutral conditions. Stability is commonly quantified via the vertical gradient of potential temperature, a metric derived from temperature profiles that can be measured by ground-based microwave radiometers (MWR), radiosondes and meteorological towers.

The ability to model and measure atmospheric stability was already evaluated in the previous project Radiometry and Atmospheric Profiling (RAP) funded by the Carbon Trust as part of the Offshore Wind Accelerator (OWA), using both onshore and offshore datasets and different scenarios [1]. Results show a MAE between MWR and radiosonde temperature (and potential temperature) gradients in the 50–300m vertical range going from 0.9 to 3.4Kkm^-1, while the RMS difference ranges from 1.2 to 5.1Kkm^-1. Considering this, the uncertainty of MWR for temperature and potential temperature gradients in the 50–300m vertical range is estimated between ∼ 0.5–4.3Kkm^-1. The considered datasets indicate that MWR in general can detect potential temperature gradients from −5 to +50Kkm^-1 at least.

A follow-up project has recently started: the MIcrowave RADiometer for the detection and assessment of Offshore wind Resources (MiRadOr). The Mirador project aims at quantifying the performance of MWR data for estimating stability indicators, assessing the quality of other MWR datasets from other campaigns, such as OBLEX-F1 [2] and FESSTVaL [3-4]. This presentation will show preliminary results and outcomes from the first phase of the Mirador project.

1. Cimini, D., Gandoin, R., Fiedler, S., Acquistapace, C., Balotti, A., Gentile, S., Geraldi, E., Knist, C., Martinet, P., Nilo, S. T., Pace, G., Pospichal, B., and Romano, F.: Atmospheric stability from numerical weather prediction models and microwave radiometer observations for onshore and offshore wind energy applications, Atmos. Meas. Tech., 18, 2041–2067, https://doi.org/10.5194/amt-18-2041-2025, 2025

2. Mostafa Bakhoday Paskyabi, Mean wind and stability time series at FINO1 between June and July 2015 (from OBLEX-F1). Zenodo, dic. 10, 2022. doi: 10.5281/zenodo.7422388.

3. Hohenegger, C., et al., 2023: FESSTVaL: The Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg. Bull. Amer. Meteor. Soc., 104, E1875–E1892, https://doi.org/10.1175/BAMS-D-21-0330.1.

4. Löhnert, Ulrich, Knist, Christine, Böck, Tobias, and Pospichal, Bernhard, “Microwave Radiometer Observations during FESSTVaL 2021”. 12-May-2022.