Observations of wind ramps generated by thunderstorm outflows

Abraham, Aliza; Bodini, Nicola; Hamilton, Nicholas; Hirth, Brian; Schroeder, John; Moriarty, Patrick

doi:10.5194/wes-2026-82

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https://doi.org/10.5194/wes-2026-82

Preprints

08 May 2026

| 08 May 2026

Status: this preprint is currently under review for the journal WES.

Observations of wind ramps generated by thunderstorm outflows

Aliza Abraham, Nicola Bodini, Nicholas Hamilton, Brian Hirth, John Schroeder, and Patrick Moriarty

Abstract. Thunderstorms occur frequently in regions with strong wind resources, such as the U.S. Great Plains. The outflows from these storms generate wind ramps, where the wind speed and direction change dramatically over a short period. Wind turbines are designed to withstand wind ramps such as the "extreme coherent gust with direction change" (ECD) defined by the International Electrotechnical Commission (IEC), but this depiction is highly simplified and based on point measurements. In the current investigation, we characterize the wind ramps generated by six thunderstorm outflows observed in northern Oklahoma using dual-Doppler X-band radar measurements covering a 160 km³ volume, and compare their properties with the IEC-defined ECD. We show that, while the observed wind ramps exhibit wind speed and direction changes with similar magnitudes to the ECD, the observed rise times are an order of magnitude longer. Furthermore, the observed events are more complex than the idealized ECD profile, displaying spatial and temporal variations that cause significant variability in wind turbine power generation.

Received: 30 Apr 2026 – Discussion started: 08 May 2026

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Aliza Abraham, Nicola Bodini, Nicholas Hamilton, Brian Hirth, John Schroeder, and Patrick Moriarty

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RC1:
'Comment on wes-2026-82', Anonymous Referee #1, 06 Jul 2026 reply
General comments

The manuscript proposes a novel method using remote sensing technology to determine Extreme Coherent Gust with Direction change (ECD) parameters. The manuscript provides adequate background and derives standardized parameters based on lidar, SCADA, and in-situ measurements. The proposed methodology and procedures are generally sound and well-described. The findings reveal the spatial variability of this type of complex flow and demonstrate how these events deviate from the IEC standard, posing unique challenges for wind farm power generation. We recommend this manuscript for publication following the adaptations listed below.

Specific comments

Because the manuscript relies on data from a large field campaign, detailed information regarding data treatment is essential. While the authors describe the filter thresholds adopted for the lidars, the manuscript lacks information on data filtering for the in-situ measurements (3.3), turbine anemometers (3.4) and, more importantly, the radars. As the radar measurements exhibit some data vacancies (shown already in Fig. 4), we suggest elaborating on the filtering and rejection criteria, as well as any interpolation methods if used. Please give more details than line 94.

Section 4 notes that 26 wind ramp events were identified but only 6 are analyzed in detail, with the selection based on concurrent precipitation observations and sufficient dual-Doppler radar coverage. While the authors acknowledge this is not a frequency assessment, we would like to suggest the authors briefly discuss whether this selection criterion could bias the reported ramp characteristics and clarify how many events were excluded due to radar data quality (see comment 1) versus the non-precipitation atmosphere.

There appear to be several Dual-Doppler radar synthesis techniques available, while the manuscript only briefly mentions that radial wind speeds are interpolated onto a three-dimensional Cartesian grid (lines 95–99). Extending from Comment 1, more elaboration should be appended here. Each individual radar generates radial wind speeds that are not uniform in spatial resolution. The further the measurement is from the radar, the greater the spacing between adjacent measurement points. The 0.5 degree across-beam resolution (line 91), the azimuthal spacing at the far edge of the ~30 km range is approximately 260 m (~ 5 times coarser than the 50 m horizontal grid resolution). Is it true that the synthesis data have a regular horizontal resolution of 50 m and a vertical resolution of 25 m across the full radar domain? How representative is a 50 m grid at far ranges? We suggest the authors elaborate on how the synthesis process accounts for this range-dependent resolution effect, and clarify whether the effective spatial resolution varies across the domain.

As noted in the manuscript line 100, the dual-Doppler radars are not synchronized and perform relatively slow scans, introducing a temporal ambiguity of 2 to 4 minutes. In the context of gust propagation, this time lag is not trivial (a gust moving at 15 m/s travels 1.9 km within this time period). While the naturally longer rise times observed make physical sense, calculating the rise time by combining a fit-derived spatial rise distance (Sect. 6.2) with an ensemble-averaged boundary propagation speed (Sect. 6.1) introduces uncertainty. We recommend adding a discussion paragraph to address these uncertainties or providing error estimates, particularly when comparing these space-time converted results to the standard IEC temporal method. In this regard, we note that the propagation speed is itself derived from volume-to- volume boundary displacements during this 2 to 4 minute interval (Sect. 6.1, lines 180–185). The temporal resolution limitation is therefore still present, as it is directly inherited through propagation into all reported rise time values in Table 2. Furthermore, propagation speed is computed as an averaged quantity while boundary displacement is a local measurement, applying a single mean propagation speed across the entire boundary implicitly assumes spatially uniform flow. More elaboration on this limitation and how it enters the resultant rise time should be given/quantified.

In Fig. 10(i), several bins exhibit near-zero Δt_{θ} values, which appear physically implausible given the spatial resolution and propagation speeds. The manuscript does not describe any quality control applied to the curve-fitting results such as goodness-of-fit thresholds or lower rejection bounds. It is unclear whether these near-zero values represent genuine sharp wind direction transitions, degraded fitting quality, or artifacts of using the wind speed boundary to define the perpendicular cross-section direction in a case where the wind speed and direction boundaries are non-coincident (as is the case for 2023-06-16, line 164). The authors should clarify the curve-fitting acceptance criteria and discuss whether these values are physically meaningful or should be excluded.

As a general comment for the methodology used, Fig. 8 and Fig. 10 (f)(g)(h)(i) demonstrate large variability in radar-derived ramp parameters along the outflow boundary. The manuscript attributes some of this variability to inhomogeneous flow features (lines 327–329), no metrics are provided to distinguish physically driven variability from methodological ones , such as the range-dependent increase in effective radar volume (noted in Comment 2) and the absence of quality control of the curve-fitting procedure (Sect. 6.2). We suggest the authors provide fitting quality metrics or discuss how these methodological factors may contribute to the observed variability.

The radar-based method extends gust quantification into the spatial domain, and it is clear this approach is not expected to compare one-on-one to the standard point measurement method. To strengthen the paper's practical impact, we suggest explicitly outlining the operational advantages of using this proposed spatial method (predictive wind farm control…etc.) alongside a discussion of its limitations regarding space-time volume averaging.

Technical corrections

Line 57: “Section 2” is inconsistent with “Sect. X” used in other texts.

Equation (3): should use smaller or equal (<=) for the first condition. Otherwise, 4 m/s has not been included in either condition.

Line 129 states that events are identified when the wind speed changes "at least 4 m/s" between adjacent 10-minute periods, while the Figure 3 caption describes a "ramp with wind speed change greater than 5 m/s". We suggest aligning these thresholds.

Line 164: … propagate (south) eastward…: need a space, or south-eastward

Line 190: “the 2024-05-24 (case study?) exhibits the largest deceleration”. This sentence seems to miss a word.

Fig. 10 captions: Site C1a and Site D seem to be inconsistent

Line 352-353: Suggest using standard terminology “cut-out” instead of cut-off.

Line 405 to 457: Several references have twice https://doi.org.

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Citation: https://doi.org/10.5194/wes-2026-82-RC1

Aliza Abraham, Nicola Bodini, Nicholas Hamilton, Brian Hirth, John Schroeder, and Patrick Moriarty

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Short summary

Thunderstorms can cause sudden changes in wind speed and direction called "wind ramps". While wind turbines are designed to withstand simplified versions of such wind ramps, this paper shows that real wind ramps are much more variable and complex than those prescribed in the design standard. This variability makes it difficult for wind farm operators to predict the conditions that each wind turbine will experience, adding uncertainty to the prediction of wind farm power.


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