Abstract Reanalysis datasets provide spatially and temporally complete climate fields and are widely used as observational surrogates. Temperature trends from these datasets underpin numerous geoscience studies, yet the alignment of their directional trends with observations at the continental scale remains unclear. This study evaluates the sign of annual mean daily maximum (TMAX) and minimum (TMIN) temperature trends from three reanalysis data, viz. ERA5, MERRA-2, and NLDAS-2 against long-term Global Historical Climatology Network daily (GHCN) observations at 7059 (TMAX) and 6,983 (TMIN) stations across the continental United States (CONUS). We observe substantial trend misalignment between GHCN and reanalysis data, with ∼27%–31% of TMAX and ∼21%–30% of TMIN locations exhibiting discrepancies, mainly driven by false positive trends. Misalignment persists even for the longer records (⩾10–30 years) and is concentrated at stations with strong negative observed trends. Aggregating TMAX and TMIN trend agreement across different regions, including snow and rain-affected regions, western and eastern snow-dominated areas, urban and non-urban locations, and elevation classes, demonstrates that stations with trend misalignment prevail irrespective of the aggregation approach. NLDAS-2 dataset demonstrates a distinct behavior, with a greater percentage of stations exhibiting trend misalignment in snow-affected regions relative to rain-affected areas. Moreover, within the snow-affected domain, NLDAS-2 displays a contrasting spatial pattern, showing elevated misalignment across the western United States compared to other datasets. These findings call for caution while using reanalysis datasets for regional temperature trend analyses and derived applications.
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Recent Wind Stilling and Variability in Illinois
Abstract Wind energy is a growing component of energy production in Illinois (IL). However, uncertainty remains regarding future wind speed variability and trends and their potential impact on wind energy generation. Here, we assess recent (1992–2021) trends in monthly average wind speed and direction using data from the Illinois Climate Network (ICN), which consists of 18 weather stations across IL, supplemented by five IL stations from the Global Historical Climatology Network (GHCN) hourly dataset. We find decreases in mean annual wind speed at most ICN stations, ranging from −0.46% to −17.92% decade−1, and all five GHCN stations (from −1.53% to −6.53% decade−1). Decreasing wind speed trends are found in all seasons. In contrast, 10-m wind speed trends for IL in reanalysis data, a primary source of data for climate model validation and wind energy projection, are positive or show no trend in most grids that approximate IL station locations [1.28%–3.10% decade−1for ERA5, NASA MERRA-2, and NCEP North American Regional Reanalysis (NARR)]. Some IL stations also show a significant shift to more southerly winds, indicating a greater influence of air masses originating from the Gulf of Mexico. This trend is also not captured by reanalysis data, despite accurate wind direction climatologies. Thus, model validation of regional wind should be performed cautiously with reanalysis data, and reliance on reanalysis wind data may lead to an overestimation of future IL wind speeds and wind power generation. Significance StatementReanalysis data are used to validate climate models and for wind energy projection. The purpose of this study is to assess how well three widely used reanalysis products reproduce surface wind observations in Illinois, which ranks fifth in the country for wind power capacity. We found reanalysis data better reproduce wind direction than wind speed and tend to overestimate wind speeds. The station data show significant decreases in wind speeds and changes in wind direction, but those trends are not found in any of the reanalysis products studied here. This could lead to an overestimation of future wind energy generation and inaccuracies in wind in climate models. These results highlight the limitations of reanalysis data, which should be used cautiously.
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- Award ID(s):
- 2202919
- PAR ID:
- 10691041
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Journal of Applied Meteorology and Climatology
- Volume:
- 64
- Issue:
- 10
- ISSN:
- 1558-8424
- Page Range / eLocation ID:
- 1447 to 1465
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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