Wie genau sind universelle Funktionen bei stark stabiler Schichtung?

<p>Der Datensatz des <em>Surface Heat Budget of the Arctic Ocean (SHEBA) </em>Experimentes 1997/98 wird häufig für die Berechnung von universellen Funktionen für stabile Schichtung herangezogen. Für eine nicht-iterative Modellierung (Louis-Ansatz) können diese Funktionen neu berechnet werden. Allerdings haben diese Funktionen viele empirische Faktoren, die sich aus der Anpassung an den ursprünglichen Datensatz ergeben. Ein interessantes Ergebnis bei der Analyse der Daten des SHEBA-Experimentes ist, dass die Daten für die oberen Messpunkte des Experiments einer lokalen Skalierung mit den klassischen universellen Funktionen folgen, während die Daten der unteren Messpunkte eine große Streuung aufweisen. Somit könnten für den oberen Teil des Profils ein allgemein üblicher Louis-Ansatz verwendet werden. Es ist davon auszugehen, dass unter besonderen Bedingungen der untere Teil des Profils vom oberen Teil entkoppelt ist, wie es bei anderen Experimenten bereits gezeigt werden konnte. Ein einfacher Test für die Entkopplung durch Vergleich der experimentellen Daten mit einem hydrodynamischen Modellansatzes wird in der Präsentation gezeigt. Es wird daher empfohlen, den SHEBA Datensatz auf Entkopplung zu testen und eine wahrscheinlich viel einfachere universelle Funktion zu erstellen. Allerdings ist der Umgang mit entkoppelten Situationen noch im Bereich der Forschung. Es ist allerdings für die meisten Fälle zu erwarten, dass bei Berücksichtigung der Entkopplung kleinere Flüsse bestimmt würden.</p>

Meltwater sources and sinks for multiyear Arctic sea ice in summer

On Arctic sea ice, the melt of snow and sea ice generate a summertime flux of fresh water to the upper ocean. The partitioning of this meltwater to storage in melt ponds and deposition in the ocean has consequences for the surface heat budget, the sea ice mass balance, and primary productivity. Synthesizing results from the 1997–1998 SHEBA field experiment, we calculate the sources and sinks of meltwater produced on a multiyear floe during summer melt. The total meltwater input to the system from snowmelt, ice melt, and precipitation from 1 June to 9 August was equivalent to a layer of water 80 cm thick over the ice-covered and open ocean. A total of 85 % of this meltwater was deposited in the ocean, and only 15 % of this meltwater was stored in ponds. The cumulative contributions of meltwater input to the ocean from drainage from the ice surface and bottom melting were roughly equal.

Solidification effects of snowfall on sea-ice freeze-up: results from an onsite experimental study

Although the effects of snow during sea-ice growth have been investigated for sea ice which is thick enough to accommodate dry snow, those for thin sea ice have not been paid much attention due to the difficulty in observing them. Observations are complicated by the presence of slush and its subsequent freeze-up, and the surface heat budget might be sensitive to the additional ice thickness. An onsite short-term land fast sea-ice freeze-up experiment in the Saroma-ko Lagoon, Hokkaido, Japan was carried out to examine the effects of snowfall on the structure and surface heat budget of thin sea ice, based on observational results and a 1-D thermodynamic model. We found that snowfall contributes to the solidification of the surface slush layer, contributing ice thickness that is comparable to the snowfall amount and affecting the crystal texture significantly. On the other hand, the basal ice growth rate and turbulent heat flux were not significantly affected, being <3.1 × 10−8 m s−1 and 3 W m−2, respectively. This finding may validate the omission in past studies of snow effect in estimating ice production rates in polynyas and has implications about the reconstruction of growth history from sample analysis.

Evaluating the impact of atmospheric forcing and air–sea coupling on near-coastal regional ocean prediction

Atmospheric forcing applied as ocean model boundary conditions can have a critical impact on the quality of ocean forecasts. This paper assesses the sensitivity of an eddy-resolving (1.5 km resolution) regional ocean model of the north-west European Shelf (NWS) to the choice of atmospheric forcing and atmosphere–ocean coupling. The analysis is focused on a month-long simulation experiment for July 2014 and evaluation of simulated sea surface temperature (SST) in a shallow near-coastal region to the south-west of the UK (Celtic Sea and western English Channel). Observations of the ocean and atmosphere are used to evaluate model results, with a particular focus on the L4 ocean buoy from the Western Channel Observatory as a rare example of co-located data above and below the sea surface. The impacts of differences in the atmospheric forcing are illustrated by comparing results from an ocean model run in forcing mode using operational global-scale numerical weather prediction (NWP) data with an ocean model run forced by a convective-scale regional atmosphere model. The value of dynamically representing feedbacks between the atmosphere and ocean state is assessed via the use of these model components within a fully coupled ocean–wave–atmosphere system. Simulated SSTs show considerable sensitivity to atmospheric forcing and to the impact of model coupling in near-coastal areas. A warm ocean bias relative to in situ observations in the simulation forced by global-scale NWP (0.7 K in the model domain) is shown to be reduced (to 0.4 K) via the use of the 1.5 km resolution regional atmospheric forcing. When simulated in coupled mode, this bias is further reduced (by 0.2 K). Results demonstrate much greater variability of both the surface heat budget terms and the near-surface winds in the convective-scale atmosphere model data, as might be expected. Assessment of the surface heat budget and wind forcing over the ocean is challenging due to a scarcity of observations. However, it can be demonstrated that the wind speed over the ocean simulated by the convective-scale atmosphere did not agree as well with the limited number of observations as the global-scale NWP data did. Further partially coupled experiments are discussed to better understand why the degraded wind forcing does not detrimentally impact on SST results.

Surface Heat Budget over the North Sea in Climate Change Simulations

An ensemble of regional climate change scenarios for the North Sea is validated and analyzed. Five Coupled Model Intercomparison Project Phase 5 (CMIP5) General Circulation Models (GCMs) using three different Representative Concentration Pathways (RCPs) have been downscaled with the coupled atmosphere–ice–ocean model RCA4-NEMO. Validation of sea surface temperature (SST) against different datasets suggests that the model results are well within the spread of observational datasets. The ensemble mean SST with a bias of less than 1 ∘ C is the solution that fits the observations best and underlines the importance of ensemble modeling. The exchange of momentum, heat, and freshwater between atmosphere and ocean in the regional, coupled model compares well with available datasets. The climatological seasonal cycles of these fluxes are within the 95% confidence limits of the datasets. Towards the end of the 21st century the projected North Sea SST increases by 1.5 ∘ C (RCP 2.6), 2 ∘ C (RCP 4.5), and 4 ∘ C (RCP 8.5), respectively. Under this change the North Sea develops a specific pattern of the climate change signal for the air–sea temperature difference and latent heat flux in the RCP 4.5 and 8.5 scenarios. In the RCP 8.5 scenario the amplitude of the spatial heat flux anomaly increases to 5 W/m 2 at the end of the century. Different hypotheses are discussed that could contribute to the spatially non-uniform change in air–sea interaction. The most likely cause for an increased latent heat loss in the central western North Sea is a drier atmosphere towards the end of the century. Drier air in the lee of the British Isles affects the balance of the surface heat budget of the North Sea. This effect is an example of how regional characteristics modulate global climate change. For climate change projections on regional scales it is important to resolve processes and feedbacks at regional scales.