| 24 Feb 2026
Phenology and Surface Energy Balance Changes Across Northern Lands
Abstract. Plant phenological shifts—notably earlier start (SOS) and later end (EOS) of the growing season—affect surface albedo, latent and sensible heat fluxes, and ultimately the surface temperature. The magnitude and spatial variability of these effects remain uncertain. Using Earth observation and reanalysis data (2001–2021), we quantify the sensitivity of surface energy fluxes to SOS and EOS changes across northern lands (> 30° N), and we report uncertainties and convergence across multiple independent datasets. Spatially-aggregated results show that an earlier SOS is generally associated with decreased albedo by up to 0.004 day−1 (needleleaf forests and tundra), and increased latent heat fluxes by 0.46 W m−2 day−1 (spatial median), ranging from 0.17 W m−2 day−1 (croplands) to 0.68 W m−2 day−1 (mixed forests). Delays in EOS are also associated with decreases in albedo, though much smaller in magnitude, and with increases in latent heat flux—up to 0.13 W m−2 day−1 in mixed forests—with weaker and more variable responses across other land-cover types. Datasets reveal large spatial variability and discrepancies in the responses of the sensible heat fluxes and thus evaporative fraction. These findings demonstrate phenology-driven impacts on evaporative cooling and indicate a negative feedback loop that may partially dampen surface warming.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Biogeosciences.
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This manuscript quantifies sensitivities of surface energy balance variables to phenological shifts (SOS/EOS) across northern lands using multiple datasets for 2001–2021. The latent heat results are the clearest contribution and are largely consistent across datasets. However, several methodological concerns need to be addressed before the paper is ready for publication.
Major Comments:
1. SOS and EOS are defined using a single threshold of 30% of annual maximum LAI across all vegetation types and latitudes (L78–80). For tundra or deciduous forests with strong seasonal amplitude this may work reasonably well, but for evergreen needleleaf forests — where intra-annual LAI variation is small — the same threshold likely captures noise rather than a real phenological transition. PFT-specific biases in phenological detection could plausibly explain part of the spatial heterogeneity the authors observe in energy balance sensitivities, but this possibility is never examined. A sensitivity test with alternative thresholds (e.g., 20% and 40%) would help, or at minimum the authors should acknowledge this as a source of spatially-structured uncertainty.
2. The partial correlation analysis uses ERA5 surface temperature as a covariate to control for confounding (L125–128). When ERA5 LE and H are the response variables, this is problematic because ERA5 skin temperature and ERA5 turbulent fluxes are products of the same land surface model, where energy balance closure is imposed — they are not independent. The issue is most acute in Section 3.4 where ERA5 LST serves as both the response variable (Figure 6) and the partial correlation covariate. The authors should acknowledge this explicitly and note that ERA5-based partial correlations need to be interpreted carefully. Results from FLUXCOM and GLEAM provide a more independent basis for inference here.
Minor Comments
1. (L10–12): The abstract states the findings "indicate a negative feedback loop that may partially dampen surface warming." The paper itself acknowledges (L239–242) that causal attribution is not possible from these observations. The abstract should reflect that — something like "are consistent with" would be more accurate.
2. (L60–65): The paper describes using "daily temporal resolution data," but MODIS and FLUXCOM are 8-daily. The interpolation from 8-day to daily for GLASS LAI (L74–75) produces smoothed estimates that are not independent observations. This matters for how precisely SOS/EOS dates are actually being constrained, and should be noted.
3. (L120–124): The ±20-day fixed window around mean SOS/EOS does not account for inter-annual variation in transition duration. Some justification for this choice, or a brief check of sensitivity to window width, would be helpful.
4. (L180–185): "Back-of-the-envelope" is a bit informal for a methods section. Reframe as a first-order estimate, and state the assumptions more explicitly.
5. (L254–255): Winkler et al. (2026) is a companion preprint with overlapping authorship, cited here as supporting evidence for the feedback mechanism. This should be flagged clearly as a companion paper under review rather than independent supporting literature.
6. (L260–264): The SOS–EOS interaction is mentioned as a limitation too briefly. An earlier SOS may deplete summer soil moisture and directly affect autumn energy balance — this is not just a gap for future work, it could be actively confounding the EOS–LE results. Worth a few more sentences in Section 3.2 or 3.4.