| 11 Nov 2025
The impact of Aeolus observations on wind and rainfall predictions
Abstract. Previous studies showed substantial improvements in upper-level wind and mass field forecasts from assimilating Aeolus wind observations. This study extends those analyses using the improved reprocessed Aeolus dataset (version B16) in experiments with the global ECMWF forecasting system spanning more than three years. Results show that zonal wind forecasts improve across the entire troposphere during the first forecast week, propagating gradually into the stratosphere, with average reductions in the Root Mean Square Error of about 0.5 %, reaching over 1.5 % in the tropical upper troposphere. These improvements lead to more accurate rainfall forecasts in some regions and seasons, as measured by the Fraction Skill Score (FSS) and the Stable Equitable Error in Probability Space (SEEPS). They are largest during the winter half-year in the extratropics, particularly in the Southern Hemisphere, and appear primarily at the grid scale. The largest FSS improvements, reaching several percent, occur for 5–10 day leads and heavy rainfall categories, while SEEPS indicates modest but consistent gains in categorical precipitation skill. These results suggest that assimilating Aeolus winds improves large-scale dynamics, such as jet streams and Rossby waves, leading to more accurate long-term predictions of cyclones and fronts, and ultimately better local wind and heavy rainfall forecasts.
Competing interests: Some authors are members of the editorial board of Weather and Climate Dynamics.
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Review of “The impact of Aeolus observations on wind and rainfall predictions”
I. General Assessment
This manuscript presents a comprehensive evaluation of the impact of Aeolus Doppler wind lidar observations (using the reprocessed Baseline 16 dataset) on global wind and precipitation forecasts. The authors have utilized the ECMWF Integrated Forecasting System over an impressively long evaluation period of more than three years. This long-term perspective is, in my view, the standout feature of the study, as it provides a level of statistical confidence often missing from shorter-term campaign evaluations.
The overall quality of the work is high. The experimental design is robust, and the improvements in wind forecasts—especially in the upper troposphere—are presented clearly and align well with our current understanding of the Aeolus mission's capabilities. While the paper is logically structured and the figures are informative, I believe the discussion regarding precipitation could be strengthened. My comments primarily focus on the interpretation of these results and some technical inconsistencies that need to be ironed out. I recommend publication after the following minor revisions are addressed.
II. Major Comments
1. Physical Mechanisms vs. Correlation: A recurring theme is the attribution of precipitation skill improvements to a better representation of large-scale dynamics (e.g., jet streams or Rossby waves). While this is a plausible physical explanation, the analysis remains essentially correlational. Since the causal chain isn't explicitly demonstrated through diagnostics, I suggest adopting a slightly more cautious tone, noting where physical causality is inferred based on spatial/temporal overlap.
2. Significance and Relevance: The improvements in SEEPS and FSS, while statistically significant, are quite small in absolute terms (often <1%). I recommend a more nuanced distinction between statistical significance and practical meteorological relevance. Additionally, acknowledging the scale-dependence of FSS would help ground the results.
3. The 12-hour Accumulation Window: Given that Aeolus provides "snapshots" in time, I wonder if the 12-hour precipitation accumulation window used for verification might be masking more immediate impacts on the convective cycle. Did the authors consider shorter windows (e.g., 6h) to see if the impact is more pronounced closer to the satellite overpass times?
4. Southern Hemisphere Signal: The pronounced wintertime signal in the Southern Hemisphere is a compelling finding but feels under-explored. Expanding the discussion to consider factors like baroclinic activity or the relative scarcity of other observations in that region would significantly enhance the scientific value of the paper.
5. Reference Dataset Transparency: Using ERA5 is standard, but it is worth explicitly stating for transparency that ERA5 is not a fully independent reference, as it shares the same underlying model physics as the forecasts being tested.
III. Minor and Technical Points
1. Interpretation of SEEPS (Figure 8): In Section 2.2.1, you define the change in SEEPS as -(EXP - CTRL) so that positive values indicate improvement. I appreciate this effort to make the results more intuitive. However, since SEEPS is traditionally negatively oriented, this "reversed" convention must be explicitly restated in the caption of Figure 8 to prevent confusion.
2. The "Tropical Disconnect": The fact that substantial wind improvements in the tropics don't translate into much precipitation skill is fascinating. Could this be a limitation of the verification products, or perhaps a result of how parameterized convection handles the corrected wind field? A brief comment on this would be very welcome.
3. "Entire Troposphere" Claim: In the abstract and conclusions, you mention improvements "across the entire troposphere." However, Figure 2 shows that in the lower troposphere at mid-latitudes, the impact is often negligible. I suggest a more precise phrasing.
4. Precipitation Regimes: Using "dry" vs "wet" as a proxy for lidar conditions is a useful approximation, but please clarify that "dry" surface conditions do not always equate to cloud-free profiles.
5. Terminology & Typos: