Evaluation of Global Reanalysis Land Surface Wind Speed Trends to Support Wind Energy Development Using In Situ Observations

Abstract

Global reanalysis products are important tools across disciplines to study past meteorological changes and are especially useful for wind energy resource evaluations. Studies of observed wind speed show that land surface wind speed declined globally since the 1960s (known as global terrestrial stilling), but reversed with a turning point around 2010. Whether the declining trend and the turning point have been captured by reanalysis products remains unknown so far. To fill this research gap, a systematic assessment of climatological winds and trends in five reanalysis products (ERA5, ERA-Interim, MERRA-2, JRA-55 and CFSv2) was conducted by comparing grid cell timeseries of 10 m wind speed with observational data from 1,439 in-situ meteorological stations for the period 1989-2018. Overall, ERA5 is the closest to the observations according to the evaluation of climatological winds. However, substantial discrepancies were found between observations and simulated wind speeds. No reanalysis product showed similar change to that of the global observations, though some showed regional agreement. This discrepancy between observed and reanalysis land surface wind speed indicates the need for prudence when using reanalysis products for the evaluation and prediction of winds. The possible reasons for the inconsistent wind speed trends between reanalysis products and observations are analyzed. The results show that wind energy production should select different products for different regions to minimize the discrepancy with observations.

Weaknesses in dust emission modelling hidden by tuning to dust in the atmosphere

“…Here, we use the latest version of ERA5-Land wind (at 10 m height) data at a reasonably fine (11 km) resolution. It is evident that U10 is over-estimated in some regions (Fan et al, 2021). However, there appears to be no systematic bias that would lead to the over-estimation of dust emission frequency.…”

“…The use of these data does not imply priority over any other data. We recognize that there are different qualities to different model data as evident in their wind fields (Fan et al, 2021). Where applicable, we used the same data in both TEM and AEM to consider the relative differences.…”

Evaluating dust emission model performance using dichotomous satellite observations of dust emission

“…Figure 4a shows that neither of these conditions are frequently identified in the AEM, with P<0.2 during observed events. These small P values very likely arise from the use of ERA-5 global wind field data (11 km pixels), like most global modelled wind field data, will struggle to describe episodic, mesoscale events such as LLJs and cold pooling (Fan et al, 2020). Instead, these wind data describe a single spatial mean value per 11 km pixel, which is subsequently used to form us* and compared to u*ts (at the grain scale without adjustment).…”

What can surface wind observations tell us about interannual variation in wind energy output?

“…Wind speed observations that are measured at altitude (modern tower heights average ~90 m) at actual wind plant sites are typically held as private data and not made publicly available 4 . Meanwhile, various reanalysis datasets that are based on global meteorological models are publicly available and do offer complete temporal and geographical coverage (and at various altitudes), but their modeled long‐term trends in surface wind speeds can differ from one another, as well as from observed trends 5–8 . As such, researchers hoping to maintain a focus on observed rather than modeled wind trends must make use of publicly available data from surface meteorological stations.…”