the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 13 Feb 2026
Convection-permitting projections of North American low-level jets and their mechanistic responses to climate change
Abstract. This study investigates the response of North American Low-Level Jets (LLJs) to climate warming using a high-resolution (4 km) convection-permitting Weather Research and Forecasting (WRF) simulation driven by the Pseudo-Global Warming (PGW) approach. The simulation reveals that the response of LLJs is highly heterogeneous across seasons and regions. Among the various LLJ systems over North America, the most robust and dynamically distinct responses to climate warming are identified in the Great Plains southerly LLJ and the California coastal northerly LLJ. For the Great Plains southerly LLJ, the research identifies a robust intensification in spring but a muted response in summer. Mechanism analysis indicates that the spring strengthening is driven by a steepened zonal thermal gradient and enhanced nocturnal stability, which amplifies the inertial oscillation. In contrast, increased nocturnal instability in summer suppresses this decoupling mechanism, preventing significant strengthening. Regarding the California coastal northerly LLJ, the simulation projects a weakening trend in summer. This is attributed to a reconfiguration of the land-sea thermal contrast, where enhanced local sea-breeze circulations disrupt the coastal baroclinicity that sustains the jet. These results highlight the necessity of convection-permitting scales in capturing the fine-scale thermodynamic and dynamic adjustments governing future LLJ evolution. The projected seasonal shifts in jet intensity and vertical structure have important implications for other interdisciplinary fields.
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Status: open (until 19 Aug 2026)
- RC1: 'Comment on egusphere-2026-360', Anonymous Referee #1, 12 Jul 2026 reply
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RC2: 'Comment on egusphere-2026-360', Anonymous Referee #2, 12 Aug 2026
reply
This manuscript is an extension of an earlier paper by the authors published in 2024 in Atmospheric Chemistry and Physics (Ma, X., Y. Li, Z. Li, and F. Huo, 2024, Investigation of the characteristics of low-level jets over North America in a convection-permitting weather research and forecasting simulation, Atmospheric Chemistry and Physics, 24, 12013–12030, doi:10.5194/acp-24-12013-2024). In preparation for this review, I read both the current manuscript and the earlier publication.
In the 2024 publication, the authors analyzed high-resolution (4 km) convection-permitting Weather Research and Forecasting (WRF) simulations for 2000-2013 to investigate the frequency of low-level jets across North America using the classic Bonner (1968) definition of a low-level wind maximum. The uniqueness of that paper was the high spatial (i.e., horizontal) resolution of the simulations and the inclusion of the convection-permitting scheme compared to previous studies that used coarser resolution observations and/or reanalysis fields. In the manuscript currently under review, the authors extend their analyses to explore the potential impact of climate change on the characteristics of low-level jets.
One issue is that some of figures from the 2024 publication are reproduced in the current manuscript without any indication that they were previously published. This is not appropriate, and the authors must provide proper attribution. The figures include: a) The first four panels of Figure 2 in the current manuscript make up Figure 4 in the 2024 publication, and b) The first four panels of Figure 5 in the current manuscript make up Figure 3 in the 2024 publication.
Another concern is that the authors do not discuss the limitations of their future climate simulations. The authors used a Pseudo-Global Warming experiment where “deltas” (i.e., differences) were calculated at ERA-Interim gridpoint locations between the composite values of a 19-member GCM ensemble for 2071-2100 and 1976-2005, with the deltas simply added to the 2000-2013 ERA-Interim data which then served as input to WRF. While this approach substantially reduces computational requirements, it also has serious limitations including the inability to capture large-scale circulation changes and interannual and internal climate variability. The authors do not acknowledge these limitations, nor do they consider how their approach may have influenced their findings. Also, by using the PGW method and one mesoscale model (i.e., WRF), the authors have only a single future projection and no estimate of uncertainty. Also, the authors statement that “Crucially, the PGW approach obviates the need for extended simulations; it allows for centennial-scale projections to be derived from just 13 years of data through equivalent climate perturbations” is questionable, and it is unclear what they mean by “equivalent” climate projections. The use of only a 13-year period for the control and future simulations is another weakness of the manuscript, and the use of composite values for a single 30-year period at the end of the century is hardly “centennial-scale” as it ignores the evolution of the climate during the century. A data-related concern also raised in the reviews of the 2024 publication is that the WRF simulations are driven by the older ERA-Interim reanalysis rather than the more recent ERA 5 reanalysis.
I have reservations regarding the monthly analyses of jet frequency and speed in Section 3.5 of the manuscript. For the Great Plains LLJ, the authors summed (for frequency) or averaged (for speed) gridpoint values by month for a large area extending from southern Texas to the border between the Dakotas. However, a number of previous studies have shown that the location of frequent S-LLJs in the Great Plains shifts northward from the south Texas in spring to the central plains in summer and autumn. This shift can be seen in the monthly plots of S-LLJ frequency in Doubler et al. (2015), although other authors have documented similar spatial displacements. The monthly values in the bar charts shown in Figure 4 mask the intra-annual spatial variability in jet locations. Moreover, S-LLJs in the Great Plains can form under very different large-scale circulations, which Igau and Nielsen-Gammon (1998) broadly labeled as “active” and “quiescent” patterns, depending on location and season. Consequently, it is not clear how these spatially-averaged monthly values of frequency and jet speed should be interpreted. Similar large seasonal shifts in jet location are not seen for the California coastal N-LLJ, although the spatial extent of the area of frequent N-LLJs expands in the warm season (see the N-LLJ monthly plots in Doubler et al. 2015). These differences complicate comparison of the monthly values between the two jet types. Why not instead show monthly maps of PGW-CTRL for frequency and speed, similar to what was done by season? That way any spatial variations in the monthly differences are evident. Also, because the units for jet frequency (i.e., percent frequency) and jet speed (meters per second) differ, any comparisons of the relative impact of climate change on these two parameters requires that their units be converted to the same scale (i.e., percent change -- (PGW-CTRL)/CTRL). Without a uniform scale, statements such as “Compared with occurrence frequency, the monthly variability of core wind speed for the California coastal N-LLJJ is considerably weaker” or “These results suggest that, for the California coastal N-LLJ, future changes are dominated by a redistribution of occurrence on the monthly scale, whereas modifications to individual event intensity are secondary and largely confined to the midsummer period.”
In section 4, the authors state “this study selects two representative jet core locations (refer to Points A and B in Fig. 1) to conduct a targeted diagnosis of the low-level wind structure under the CTRL and PGW scenarios”, however what is labeled “A” and “B” in Figure 1 are transects rather than points. There are no “points” on the map. Also, how is the jet core height defined for the inertial oscillation analysis? Is the jet core height allowed to vary between May and August? The authors refer to Figure 11 as a “meridional cross-section”, however meridional cross sections run along a line of longitude, in other words they run north-south. However, the cross section in Figure 11 runs west-east, or in other words along a line of latitude (depending on the map projection). The authors refer to “from the valley to the highlands”, but isn’t the lower elevations on these plots the plains (not necessarily a valley)? The authors focus on differences between PGW and CTRL in the inertial oscillation (for Great Plains LLJ) and the background geostrophic wind (for the California coastal jets), but other factors also contribute to jet formation such as synoptic-scale forcing for Great Plains jets (see Burrows et al, 2019, Journal of Climate, doi:10.1175/JCLI-D-18-0891.1) and the elevation of the marine boundary layer for the coastal jets (see Beardsley et al., 1987, Journal of Geophysical Research).
In Section 5 (Conclusions), the authors need to elaborate on their key findings and discuss the limitations of their analysis. For example, is the projected springtime increase in Great Plains S-LLJ frequency and speed not only a function in changes in boundary-layer forcing but also a function of changes in synoptic forcing in the future? How do the authors know that the difference between their findings and those of Tang et al. (2017) are due to the authors’ use of convection-permitting simulations rather than their use of the PGW approach to drive the simulations compared to individual GCMs? Or perhaps the differences are a combination of both? In addition to Tang et al., several previous studies have investigated potential future changes in the Great Plains LLJ. How do the authors’ findings compare to those studies? The authors also need to cite other studies when appropriate. For example, citations are needed for the authors’ statement “This behaviour contrasts with large-scale or coarse-resolution projections that primarily emphasize monotonic changes in coastal wind strength and indicates that future coastal LLJ responses are governed not simply by background circulation changes, but by a reorganization of coastal boundary-layer structure and sea-breeze–baroclinicity interactions that can only be captured at convection-permitting scales.” What previous studies are the authors referring to here? I also remind the authors that in neither this manuscript or the 2024 publication did they compare simulations at the same spatial resolution and for the same time period but with and without a convection-permitting scheme, thus they can only infer rather than directly evaluate the contribution of the convection-permitting scheme in simulating LLJs and to understanding the mechanisms responsible for their formation. Other factors such as horizontal resolution and choice of mesoscale model may also contribute to differences with previous studies. Another limitation is the authors’ use of only one mesoscale model and only one driving future scenario. Consequently, the authors are unable to provide an estimate of the uncertainty surrounding their future projections.
I did a quick scan of the references and found at least one misspelled author name, citations in the text that are not in the reference list, and one article that is listed twice in the reference section. The authors need to carefully check the references for accuracy.
Citation: https://doi.org/10.5194/egusphere-2026-360-RC2
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I am recommending that this paper not be accepted. There are several major issues. First, the paper uses RCP8.5, which is now considered highly improbable and unrealistic. Second, the approach uses a pseudo-global warming technique that is not appropriate since the driving synoptic systems could well change as the planet warms (e.g., changes in the summer offshore high pressure). Finally, the signal is very small (a few percent) and within natural variability.