Spring bloom composition in the Baltic Sea, a partially ice‐covered brackish coastal waterbody, is shaped by winter‐spring weather conditions affecting the relative dominance of diatoms and a heterogeneous assemblage of cold‐water dinoflagellates, dominated by the chain‐forming Peridiniella catenata and a complex of at least three medium‐sized, single‐celled species: Biecheleria baltica, Gymnodinium corollarium, and Scrippsiella hangoei. During the last decades, the bloom community has dramatically changed in several basins. We analyze here a 30 yr time series of quantitative phytoplankton data, as predicted by hindcast modeled ice thickness and storminess for three distinct Baltic Sea localities, to verify climate‐driven mechanisms affecting the spring bloom composition. Thick (> 30 cm) and long‐lasting ice cover favored diatom‐dominated spring blooms, and mild winters, with storms and thin ice cover (10 to 20 cm), supported blooms of the B. baltica complex. Dispersal limitation plays an important role in the spatial extent of blooms of the B. baltica complex, caused by intricate interplay of local hydrodynamics and the dinoflagellate life cycle. Proportion peaks of key phytoplankton groups have shifted about 10 d earlier in the northwestern Baltic Sea (P. catenata and diatoms) and in the Gulf of Riga (P. catenata). The significant weather effects imply future shifts in spring bloom composition and consequent biogeochemical cycles, driven by the predicted changes in winter storminess and decrease in ice cover extent and duration in climate change models.
We describe a new ocean-sea ice-biogeochemical model, apply it to the Bothnian Bay in the northern Baltic Sea for the time period 1991-2007 and provide the first long-term mesoscale estimates of modelled sea-ice primary production in the northern Baltic Sea. After comparing the available physical and biogeochemical observations within the study area and the time period investigated with the model results, we show the modelled spatial, intra-and interannual variability in sea-ice physical and biogeochemical properties and consider the main factors limiting ice algal primary production. Sea-ice permeability in the studied area was low compared with the polar oceans, which appeared to be a major reason for the generally low primary production rates. Although the sea ice was less saline in the northernmost parts of the basin, these parts were characterized by sea ice with a larger amount of habitable space, higher levels of photosynthetically active radiation and increased macronutrient availability near the coast, which favoured higher algal growth rates. Other parts of the southern central basin were mostly co-limited by less favourable light conditions (i.e., earlier ice breakups associated with fewer sunlight hours) and lower seawater macronutrient concentrations than in the coastal zones. Although a change towards milder winters (i.e., reduced ice cover, thickness and length of the ice season) was previously detected on a half-century timescale and could partly be seen here, analysis of the temporal evolution of sea-icebiogeochemicalpropertiesshowednosignificanttrendsovertime,thoughthesepropertieswere characterized by large interannual variability.
Abstract. Ensemble sea ice forecasts of the Arctic Ocean conducted with the Korea Meteorological Administration's coupled global seasonal forecast system (GloSea5) is verified. To investigate the temporal and spatial characteristics of the seasonal projection of Arctic sea ice extent and thickness, a set of ensemble potential predictability is assessed. It shows significance for all lead months except anomalous around East Siberian Sea, Chukchi Sea and Beaufort Sea during summer months. However, during the radipdly thawing and freezing season, initial states lose its predictability and increase uncertainties in the prediction. The probability skill metrics show the summer sea ice prediction which strongly depends on the sea ice thickness interacting with the accuracy of the snow depth. We found the forecast skill is determined primarily by the timing of sea ice drift (i.e., Beaufort Gyre and Transpolar drift) and sea ice formation by freshwater flux in the East Siberian Sea. Therefore, capturing the sea ice thickness state effectively is the key process for skillful estimation of Arctic sea ice. In spite of the uncertainties in atmospheric conditions, this system provides skillful Arctic seasonal sea ice extent predictions up to six months.
<p>The Arctic Ocean is globally important for the weather and climate and has a unique environment. Therefore accurate prediction of the Arctic sea ice remains crucial in most numerical models. It is because small changes within the atmosphere or the ocean can cause major changes in the areal extent and thickness of the sea ice. Such changes, in turn, will have pronounced effects on the ocean and atmosphere through modification of the albedo, the ocean-atmosphere heat and momentum exchanges, and the ocean-ice heat and salt fluxes. The focus of this study is on the impact of such coupling on sea ice and upper ocean properties and the halostad related sea ice variations and inflows from Oceans. To assess the impact of the vertical mixing, we perform a set of sensitivity experiments with a global oceanic configuration at 1/4&#176; resolution based on the version 4.0 of NEMO (Nucleus for European Modelling of the Ocean). In particular we examine the spatio-temporal distributions of Pacific and Eastern Arctic origin waters in the Chukchi Sea using 2016-2018 hydrographic data. Overall, the model agrees well with observations in terms of sea ice extent in spite of inaccurate vertical stratification of the water column. We conclude that beyond seasonal time scale forecast accuracy could be improved by more accurate representation of the structure of water masses.</p>
<p class="p1"><span class="s1">In recent years, coastal disasters have been frequently caused by typhoons and storm surges accompanied by high waves due to global warming and the changing marine environment. In addition, the development of coastal areas in Korea has also led to suffering great damage to society every year.&#160;</span></p> <p class="p1"><span class="s1">To cope with this issue, we have developed a new storm-surge prediction system based on the NEMO model for improving the predictability both the tide and the surge. This new regional tide-surge prediction system (RTSM) is constructed with a two-dimensional barotropic sigma coordinates and has a 1/12 degrees horizontal resolution. To find optimal coefficients of this model, several sensitivity experiments were conducted and verified with tide gauge measurements from the KHOA (Korea Hydrographic and Oceanographic Agency). Finally, we selected a bathymetry from SRTM (Shuttle Radar Topography Mission), Charnock coefficient as a constant value of 0.275 and the reference pressure for the inverse barometric effect as the domain mean. As the result of comparing surge-height predictions with the currently operating model (OPER-RTSM), the new system (RTSM) showed roughly 30% higher in forecast accuracy than the previous OPER-RTSM.</span></p>
Journal: TC Title: Seasonal sea ice forecast skills and predictability of the KMA's GloSea5 Author(s): Byoung Woong An et al. MS No.: tc-2018-217 MS Type: Research articleWe would like to thank the reviewers for careful and thorough reading of this manuscript and for the thoughtful comments and constructive suggestions, which help to improve the quality of this manuscript. Our response follows.Response to RC1: Comments from Referee: However, concepts, ideas, tools and data do not appear novel. For example, it is not clear how the GloSea5 system operated by KMA differs from the developed at the UK Met Office. This shortcoming makes the C1 TCD Interactive commentPrinter-friendly version Discussion paper description of experiments and calculations insufficiently complete and precise, and therefore do not allow their reproduction by fellow scientists. Also, if the KMA version is close to the UK Met Office one, seems strange that the UK Met Office seasonal sea-ice forecasters are not involved in this study, and that their work is not credited and cited. In general, it seems likely that some key literature are missing in the paper as I point out next. Importantly, the results presented in the abstract and conclusions do not appear substantial. The authors state that the sea-ice prediction was improved by implementing sea-ice thickness initial conditions and that sea-ice thickness is a key parameter for skillful prediction. But this has already been shown in many earlier studies, for example by Day et al. (2014). The specific results related to the GloSea5 system have also already been shown by Peterson et al. (2014), who are strangely is not cited in this paper, using the GloSea4 system, the predecessor of GloSea5. For example, the authors find that GloSea5 provides skillful Arctic seasonal sea-ice extent predictions up to six months and that the GloSea5 sea-ice concentration forecast skill better from October to March than from January to June. These results can also be found in Peterson et al. (2014). Moreover, the authors find that GloSea5 has a good sea-ice concentration predictability, except in summer. This finding seem to match the one by Peterson et al. (2014), who found that the GloSea4 sea-ice prediction skill for September decreases after early April due to thinning of sea ice at the start of the melt season. In summary, it is difficult to find original and important results in this paper. Although the overall presentation follows well the general structure of a scientific paper as divided to sections, the text at the paragraph level is often very hard to read and sentence-to-sentence logic often impossible to follow, for example in Introduction. These problems arise partly because the language is not fluent and precise. Therefore the text should be inspected, rewritten and clarified. The paper is also too long (over 12 pages) for a research article in the Cryosphere and should be shortened. Because of these shortcomings I suggest that the manuscript is rejected and recommend that the authors could submit a ...
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