the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 15 Jul 2025
Evaluating Precipitation Behavior in CESM2 Using Nudging Technique
Abstract. Persistent precipitation biases in coupled general circulation models (CGCMs) are often linked to deficiencies in moist physics parameterizations and their interactions with large-scale dynamics. However, disentangling these effects is challenging due to the coupling between precipitation and the large-scale environment. Nudging—a simulation technique that forces model variables toward a target state—offers a means to isolate parameterization errors. This study explores and improves the nudging implementation in the Community Earth System Model (CESM) version 2.2.2, and evaluates the performance of precipitation by nudging horizontal wind, moisture, and/or temperature toward reanalysis. We identify a limitation in the default nudging sequence, where separating the computation and application of nudging tendencies by moist processes leads to artificial precipitation biases. A revised implementation significantly reduces these errors, establishing a more robust framework for parameterization evaluation. Using this optimized setup, we show that forcing model with observed horizontal wind improves mean precipitation by enhancing low-level convergence in the Pacific warm pool and ITCZ, while reducing the wet bias in the subtropics. Nonetheless, the model continues to produce excessive drizzle and insufficient heavy precipitation, with rainy-hour relative humidity exceeding reanalysis values. Nudging temperature or specific humidity offers limited additional improvement. These results reveal an intrinsic inefficiency in converting moisture into heavy precipitation—independent of large-scale state errors—highlighting a fundamental weakness in the model's parameterizations. This study also underscores the value of nudging for isolating parameterization deficiencies in model evaluation.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-2684', Anonymous Referee #1, 18 Oct 2025
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RC2: 'Comment on egusphere-2025-2684', Anonymous Referee #2, 22 Oct 2025
This manuscript tackles a scientifically significant and pertinent topic: assessing and refining the nudging technique in CESM2.2.2—a method that artificially relaxes model variables (like winds, temperature, and humidity) toward reanalysis data at targeted vertical levels to constrain large-scale dynamics—aimed at isolating errors in moist-physics parameterizations and their effects on precipitation. The authors state that this approach of disentangling parameterization deficiencies from large-scale state biases via these focused nudging experiments is insightful and holds strong promise for advancing model development. Nonetheless, the nudging approach itself is known to have fundamental limitations for improving climate models, as it suppresses intrinsically generated variability and internal feedbacks—precisely the processes that moist physics must correctly parameterize in free-running simulations—potentially leading to misleading diagnoses of parameterization errors that do not translate to unconstrained model behavior.
The manuscript is challenging to navigate. The experimental setup and nudging implementation lack clear, structured explanations; experiment names are confusing; and several core findings and interpretations lack robust quantitative backing. Figures require better presentation, and the explanations of physical processes need greater clarity and substantiation. The simulation length is also too short for robust climate modeling, failing to adequately sample precipitation variability, rare extreme events, and climatological means essential for meaningful moist physics evaluation.Additionally, the comparison with IMERG is highly problematic, as the authors fail to address how IMERG is constructed—through merging of microwave estimates with IR data and calibrated by gauge data with significant regional gaps—overlooking key biases such as: (1) systematic underestimation of warm rain processes due to microwave insensitivity to low-level liquid hydrometeors; (2) underestimation of orographic precipitation from shallow, terrain-forced ascent that falls below microwave detection thresholds; (3) overestimation in deep convective regions from parallax errors where microwave footprints are misaligned with actual precipitation columns; (4) scale-dependent sampling uncertainties where 0.1° gridbox averages smooth out sub-grid variability that dominates precipitation statistics; (5) gauge calibration biases that overcorrect arid regions with sparse stations while undercorrecting data-rich areas; and (6) temporal sampling gaps from satellite overpass limitations that miss peak diurnal precipitation cycles, particularly over land. These biases can confound model evaluation, particularly over land and complex terrain. Overall, considering IMERG as 'the truth' is highly problematic, methodologically speaking.
Finally, the authors ignore well-known caveats in using precipitation to validate climate models, including its intermittency, extreme sensitivity to resolution and subgrid processes, mismatch between model grid-box means and point observations, and the inability of raw precipitation fields to robustly constrain underlying dynamical or thermodynamic errors.I do not recommend publication in its current form. Major changes are required to address these fundamental methodological flaws, provide adequate quantitative support for claims, clarify the experimental design, extend simulation lengths, critically evaluate observational uncertainties, and fundamentally reconsider the nudging methodology's applicability to free-running climate model improvement. Without these substantial changes, beyond the scope of a major revision, the conclusions cannot be trusted and would mislead the community regarding moist physics deficiencies in CESM2.2.2.Citation: https://doi.org/10.5194/egusphere-2025-2684-RC2 -
EC1: 'Editorial Decision - no publication', Juan Antonio Añel, 30 Oct 2025
After reviewing the reviewers' reports, and unless the authors can point out something fundamentally wrong with them, I do not envisage publication of this manuscript in Geoscientific Model Development.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2025-2684-EC1 -
AC1: 'Reply on EC1', Fucheng Yang, 31 Oct 2025
Dear Editor,
Thank you for the prompt evaluation of our manuscript. I have carefully revised the manuscript in accordance with all suggestions and provide detailed, point-by-point responses in this document. In the revised manuscript, I have demonstrated the effectiveness of nudging simulations and the robustness of our findings by either extending the simulation lengths or incorporating additional quantitative analyses. I will upload the final revised manuscript and response letter once all co-authors have approved.
Although the first reviewer recognized the scientific significance of our study and provided supportive and constructive feedback, the second reviewer raised several concerns that appear to stem from misunderstandings of our methodology and objectives. Before providing a formal, detailed response, I would like to briefly clarify these key points.
In this study, the suppression of internally generated variability and feedbacks through nudging is an intended advantage, as it allows us to isolate and evaluate the behavior of the model’s moist-physics parameterizations under ideal large-scale input, rather than a methodological limitation. If the moist physics can not produce reasonable precipitation when the large-scale environment is constrained to near-observed conditions at each timestep, it raises a fundamental question: how can we expect the model to generate realistic precipitation in free-running simulations? This purpose was clearly stated in the Introduction of the original manuscript, though it appears the reviewer may have overlooked it. Regarding the potential biases in IMERG precipitation, we also compared the model results with precipitation from other datasets, including ERA5 and GPCP (Fig. B4 in the original manuscript), which the reviewer likewise may not have noted. Moreover, these potential IMERG biases do not weaken our conclusions but instead reinforce them, as they suggest that the model’s deficiencies in reproducing heavy precipitation events are likely even more severe than indicated. These points will be further addressed in the detailed responses.
Sincerely,
Fucheng Yang
Citation: https://doi.org/10.5194/egusphere-2025-2684-AC1
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AC1: 'Reply on EC1', Fucheng Yang, 31 Oct 2025
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This manuscript addresses a scientifically meaningful and technically relevant topic: evaluating and improving the implementation of the nudging technique in CESM2.2.2 to isolate moist-physics parameterization errors and their impacts on precipitation. The idea of disentangling parameterization deficiencies from large-scale state errors through targeted nudging experiments is valuable and has clear potential to inform model development.
However, in its current form, the manuscript is rather difficult to follow. The model design and nudging implementation are not clearly or systematically described, the naming of experiments is confusing, and some key results and interpretations are not well supported by quantitative evidence. The presentation of figures and the discussion of physical mechanisms also require clarification and stronger justification.
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Minor / Technical Comments