Estimating the seasonal impact of optically significant water constituents on surface heating rates in the Western Baltic Sea
Abstract. Heating rates induced by optically significant water constituents (OSCs), e.g. phytoplankton and coloured dissolved organic matter (CDOM), contribute to the seasonal modulation of thermal energy fluxes across the ocean-atmosphere interface in coastal and regional shelf seas. This is investigated in the Western Baltic Sea, a marginal sea characterised by considerable inputs of freshwater carrying nutrients and CDOM, and complex bio-optical and hydrodynamic processes. Using a coupled bio-optical-ocean model (ROMS-Bio-Optic), the inherent optical properties of different OSCs are modelled under varying environmental conditions and the underwater light field is spectrally-resolved in a dynamic ocean. We estimate the relative contribution of these OSCs to the divergence of the heat flux and heating rates and find that phytoplankton dominates the OSC contribution to heating in spring and summer, while CDOM dominates in summer and autumn. The study shows that seasonal and spatial changes in OSCs in the Western Baltic Sea have a small but noticeable impact on radiative heating in surface waters and consequences for the exchange of energy fluxes across the air-sea interface and the distribution of heat within the water column. In the Pomeranian Bight, where riverine influx of CDOM is strongest, water constituent-induced heating rates in surface waters in 2018 are estimated to be between 0.8 and 0.9 K m-1 d-1 in spring and summer, predominantly as a result of increased absorption by phytoplankton and CDOM. Further offshore, OSC-induced heating rates during the same periods are estimated to be between 0.4 and 0.8 K m-1 d-1. Warmer surface waters are balanced by cooler subsurface waters. Surface heat fluxes (latent, sensible and longwave) respond to warmer sea surface temperatures with a small increase in heat loss to the atmosphere of 5 Wm-2 during the period April to September. We find relatively good agreement between our modelled water constituent absorption, and in situ and satellite observations. More rigorous co-located heating rate calculations using an atmosphere-ocean radiative transfer model provide evidence of the suitability of the ROMS-Bio-Optic model for estimating heating rates.
Bronwyn E. Cahill et al.
Status: final response (author comments only)
RC1: 'Comment on egusphere-2022-1121', Anonymous Referee #1, 13 Dec 2022
- AC1: 'Reply on RC1', Bronwyn Cahill, 05 Mar 2023
RC2: 'Comment on egusphere-2022-1121', Svetlana Losa, 25 Jan 2023
- AC2: 'Reply on RC2', Bronwyn Cahill, 05 Mar 2023
Bronwyn E. Cahill et al.
Bronwyn E. Cahill et al.
Viewed (geographical distribution)
The paper “Estimating the seasonal impact of optically significant water constituents on surface heating rates in the Western Baltic Sea” by Cahill et al explores the impact of (dominantly) CDOM and phytoplankton on the upper ocean heating in the Baltic Sea. I find the paper a valuable contribution to the literature and mostly well written. I would be glad to recommend publication, subject to some fairly minor revisions. Please find my mostly minor comments below:
The introduction section 1 – 1.1:
-I would suggest to restructure this section to make it much more systematic, making sure the narrative flows coherently from the beginning until the end of the section. Perhaps the discussion can be simplified by presenting a process diagram showing the main optically active tracers, how they attenuate underwater light at different wave bands, how this feeds into biology (primary production), impacts the temperature gradients, which loop back into biology through reduced mixing and so on. A single Figure could replace here many lines of text. I would then start with describing the properties of the incoming irradiance in the different wavebands, how these are attenuated by clear sea water (invisible band) and OSCs in the visible band (essentially what is the paragraph on the lines 72 – 84), then I would list the main OSCs (phytoplankton, POM, CDOM, sediments..) and say something on how and where each of those OSCs impacts the light. Then I would stress the particular importance of CDOM in the western Baltic Sea and discuss its seasonal dynamics.. After describing the impact of OSCs on the underwater light field I would discuss their impact on the heating and stratification, and how that feeds back into the primary production. In all those instances I would refer to the schematic Figure..
-line 85: perhaps “characterized” is a little bit too strong word, maybe “influenced”?
-lines 89-91 I would be more careful with stating that the increased stratification has automatically positive impact on phytoplankton growth. This would be indeed true for specific times and locations, when/where phytoplankton is light limited. However, whenever phytoplankton becomes nutrient-limited, increased stratification will have the opposite effect and reduce its growth. Indeed it is widely expected that increased stratification due to global warming will lower primary production and not the other way round..
-lines 128-130: why there is lack of mentioning detritus and its impact on the light attenuation?
-lines 109-148: there is some discussion of spectral resolution here, but why there isn’t discussion of directional resolution of incoming irradiance? E.g resolving light in two streams diffuse/direct is quite common, e.g Dutkiewitz et al, 2015, or the OASIM model in Gregg & Rousseaux (2016). It has been shown that resolving diffuse light has particularly important impact on biogeochemistry in the higher latitudes (Gregg & Rousseaux, 2016). Also why the section doesn’t discuss finer spectral resolution than VIS/IR, or R/G/B within VIS? E.g OASIM model of Gregg & Casey (2009) resolves irradiance in 33 wavebands.. Some words on how the incoming surface irradiance is usually calculated for the biogeochemistry model (using atmospheric models) would be valuable here as well...
-line 186: maybe the text below can be put in a separate section describing what has been done in the paper?
The methods section:
-Figure 1: a really minor comment, but I find the colorscale a little non-intuitive (blue where it’s shallow and green where it is deep), maybe you can consider changing it, but really up to you..
-section 2.3.1: maybe you can consider to put some of the information on the atmospheric model/OSCs/spectral resolution in a Table? Just like the schematic diagram, it always makes life easier for the reader… Also can you please provide information on where the data on clouds, aerosols and water vapour (lines 303-304) are taken from? I assume you use spectrally resolved (up to 5nm) absorption, backscattering coefficients, where are their values taken from? It would be maybe good to get some extra detail on how the surface E_d is calculated from the atmospheric data, not just the Gregg&Carder (1990) reference. Some more information on all this is needed…
-section 2.3.2, lines 324-325: maybe you want to explicitly say already from the start that MOMO is used to validate the more approximate model? It makes the reader start to wonder why you are describing MOMO here..
-Table 1: in the model grid section I believe the “1nm” should be “1.8km”?
-Sections 2.5.1 are there no observations on other important OCSs, such as phytoplankton chlorophyll/even carbon? Why you did not try to validate phytoplankton (concentration/attenuation), only CDOM absorption?
- Figure 3: there are missing labels on the x-axes marking the time of the simulation. What is the white rectangle in the Arkone Sea temperature plot? Also can you explain the dip in the temperature at Arkona Sea at about 20m depth? It’s quite unusual that temperature grows with depth (i.e in the stratified period?), which is what happens at certain times in the 20-40m range…
-Table 2: it is missing the significant details in the caption – it needs to explicitly say that what is shown is temperature and what are the units for RMSE, bias (I assume K/C)
-lines 469-481: I think it would be also worth to show Figures directly for the phytoplankton, CDOM, detritus concentrations, not just on their spectral absorption.. E.g on their seasonality at the surface and comparing it with in situ/satellite data.
-Line 488: has the irradiance been validated with observations?
-Line 540: should be section 3.2, not 3.3?
-Lines 575 – 583: this is nice and exactly what I would expect. However the storyline is not entirely clear to me.. What is the exact role of light here vs the role of temperature in stimulating growth? Why I can’t say that the increase of light in spring supports the growth, increasing the surface temperature (due to both water and phytoplankton absorption), stratifying the water column and preventing phytoplankton of being mixed into the deeper darker waters, which further stimulates growth… Btw to support your statements why don’t you re-do the Fig.9 as Hovmoller diagrams, rather than showing different curves for different times? It would be a much better way how to package the information (!) Also, is there any change to phytoplankton seasonality patterns/phenology between biofeed and nonbiofeed? E.g to the timing of the bloom peak and it’s magnitude?
-Fig.10: again caption needs better description, what are the left-hand panels and what the right-hand panels? Also in the buildup to the Figure can you explain why you chose the Bornholm Basin?