This manuscript systematically evaluated the effects of different climate factors (temperature, precipitation) on crop yield before and during the growing season, focusing on winter and spring cereal yields in Sweden from 1965 to 2020. Using county-level yield data and a range of physiologically relevant climate indictors for growth stages, the study found that warmer temperatures only benefit yields if accompanied by increased growing-season precipitation. This study, aligned with the focus of Biogeosciences on climate-ecosystem interactions, and provides recommendations for yield management in the context of climate warming in Sweden's high latitudes. However, the manuscript requires further improvement in its variable selection strategy, model specification, and reproducibility of the results. The article's structure and language should also be refined.

Specific Comments:

1. Table 1: Nearly all the selected climate indicators represent frequency of short-term or extreme events, omitting intensity metrics that are known to influence crop yields. Please justify this choice or include intensity-based indicators in Section 2.2.1.
2. Model formulation:

• Why the Best formula can only include two main climate variables?
• Pre-growing: why only consider DI, what about other indicators?
• Rather than fitting pre- and post-flowering variables separately, perform LASSO selection on the full set of seasonal indicators simultaneously (as iZhu et al. The critical benefits of snowpack insulation and snowmelt for winter wheat productivity. Nat. Clim. Chang. 12, 485–490 (2022)), then interpret the selected variables. Also you can try to put the average & short-term indicators together.
• Many climate-crop studies use log-transformed yield as the dependent variable. Please clarify why raw yield Y was chosen. Will the result change if you use log(Y)?

1. The potential role of snowfall on soil moisture and yield is also important in high latitudes regions. Please discuss or analyze snowfall indicators.
2. Section 2.2.2 Periods of interest: how to estimate the date of flowering and maturity. Now you only explain the beginning of growing-season. Uncertainty analyses of estimated phenological dates are also needed (e.g. shift the phenological dates forward or backward by equal intervals of days)
3. Line300: here you indicated the yield maximizing DI, but for people who are not familiar with DI definition, they do not know what’s the meaning of this DI value. What’s the threshold of DI that represents drought? It should be clear in Methods.
4. The current Discussion part repeats to many results and lacks logical flow. Please rewrite this part following a more clear structure and only remain main results.

Technical Corrections:

1. Figure 1b-c: The spatial map in panels b and c do not march the extent of panels a and d. The geographical boundaries should be the same as others.
2. Figure 2: the inclusion of too many indicators obscures the main information. Consider focusing on the most influential metrics. And the Spearman correlation coefficients were calculated from variables in which period? Please specify the period.
3. Figure 3: add the explanation of each indicator in the caption (like what’s short-term).
4. Table 2: relocate it to the Supplement and reference it appropriately in the main text.
5. The current equations now only include fixed effects, random effects (e.g. site, year) also should be shown in the equation.
6. Line275-280: “Yields increased between 0.2 ton·ha-1 per decade for spring crops and 0.5 ton·ha-1 per decade for winter wheat (Table 2), i.e., 7% to 10% of the long-term average”. The location of this paragraph is a bit abrupt.

This paper explores the meteorological drivers of observed variability in crop yields in Sweden, investigating statistical relationships between key weather / climate indices and the yields of the four most commonly grown crops in the country over 55 years (1965-2020). Given the common assertion that anthropogenic climate change is beneficial for crops in higher latitudes, the conclusion that the potential benefits of warming may be limited by lack of increased precipitation is a very important one. There are also a number of extremely useful insights in the manuscript regarding the relative explanatory power of different variables, so overall I am supportive of this work.

I note that the manuscript has already received a review from a referee and also a community review, to which the authors have already responded. Here I will focus on two additional points that appear to have been overlooked, which I recommend are addressed in a revised manuscript.

1. As the authors note, climate change is expected to increase the length of the growing season, and indeed this has already happened. eg. in southern Sweden, the meteorologically-defined growing season length has been starting earlier by between 2 and 4 days per decade between 1950 and 2022 (Miś and Tomczyk, 2025 https://doi.org/10.1007/s00704-025-05382-6). So, over the period analysed in the current study, the growing season may have lengthened by over 20 days in some places. However, the authors conduct their analysis using an average growing season length over the study period. Is there a risk that the results may have been affected by including events or averaging periods outside of the growing season in the earlier part of the study period but excluding some within the growing season in the later part? This seems particularly pertinent in the context of the authors remark at lines 317-320: “We surmise this low performance is in part due to the infrequent occurrence of short-term potentially damaging conditions (e.g., few occurrences of days with average temperatures 320 above 25 °C, or frost during sensitive developmental stages)”. I would be reassured if the authors could demonstrate that their conclusions are not sensitive to the use of an average growing season length over a period when the length has changed by a non-trivial amount.
2. The authors do not mention the potential impact of rising atmospheric CO2 concentrations on photosynthesis, transpiration and yield - see, for example, Rezaie et al (2023 https://doi.org/10.1038/s43017-023-00491-0) for a recent review. If this is already having an influence then it will be included within the continuous variable representing the combined effects of time elapsed in since 1965 (as described in lines 197-200) so I don’t think it will alter the findings regarding the relative importance of the different meteorological drivers during the period of observations. However, given the potential non-linear effects of CO2 effects in the future, especially in how they may affect crop responses to drought and high temperatures, the existence of these influences and their implications should be highlighted as an outstanding uncertainty in relation to the results here. Eg. it should be mentioned in line 199 alongside climate change and technological improvements, and also discussed in section 4.4 (Implications under climate change).