Academic Rebuttal Letter
Academic Rebuttal Letter
Dear Dr. Smith and Esteemed Reviewers,
We sincerely thank you for reviewing our manuscript titled “Artificial Intelligence in Climate Prediction: Challenges and Innovations.” We greatly appreciate your constructive feedback, which has been invaluable in enhancing the clarity and quality of our work. Below, we provide detailed responses to each comment. All revisions are highlighted in the updated manuscript and noted by page and line numbers.
Reviewer 1:
Comment 1:
“The introduction lacks a clear discussion of how your proposed method compares to existing AI models in the literature (e.g., Smith et al., 2045).”
Response:
Thank you for pointing this out. We have revised the introduction to include a comparison of our model with the state-of-the-art AI methods, as outlined in Smith et al. (2045) and Jones et al. (2047). This discussion can now be found on page 2, lines 45–60. We believe this addition clarifies the novelty and relevance of our approach.
Comment 2:
“Please provide more information on the training dataset used for your model. The dataset size and selection criteria are unclear.”
Response:
We have expanded the Methods section to include detailed information about the training dataset. Specifically, we now describe the dataset size (15 TB of climate simulation data), time range (2020–2048), and geographic coverage (global, with a resolution of 0.5°). These details are on page 5, lines 125–140. Additionally, we outline the selection criteria to ensure reproducibility.
Reviewer 2:
Comment 1:
“The results section does not adequately discuss potential limitations of the proposed model, particularly in extreme weather prediction.”
Response:
We appreciate this valuable observation. A new subsection, “Limitations and Future Work,” has been added on page 10, lines 300–320. This section discusses challenges in extreme weather prediction, including underrepresentation of rare events in the training data and computational limitations in high-resolution simulations.
Comment 2:
“The figures could be improved for clarity, particularly Figure 4, where the legend is hard to read.”
Response:
We have updated Figure 4 to include a larger font size for the legend and improved the color scheme for better visibility. The revised figure appears on page 12, and we believe it is now much clearer.
Reviewer 3:
Comment 1:
“The manuscript would benefit from a broader discussion of ethical implications, particularly concerning AI biases in climate modeling.”
Response:
Thank you for this suggestion. We have added a new paragraph to the Discussion section, on page 14, lines 400–415, addressing potential biases in AI models, including underrepresentation of data from low-resource regions. We also suggest ethical guidelines for mitigating such biases in future work.
Closing Remarks
We once again express our gratitude for the reviewers’ insightful feedback. The revisions have addressed all comments, and we believe they significantly enhance the manuscript. Please let us know if there are any remaining concerns or additional suggestions.
We look forward to your feedback and hope this revised version meets the journal’s standards.
Sincerely,
Dr. [Your Name]
Lead Author, Department of Climate Sciences
[Your Company Name], 2050
[Your Email]
