scholarly journals Surface salinity under transitioning ice cover in the Canada Basin: Climate model biases linked to vertical distribution of fresh water

2021 ◽  
Author(s):  
E. Rosenblum ◽  
R. Fajber ◽  
J. C. Stroeve ◽  
S. T. Gille ◽  
L. B. Tremblay ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Fresh Water ◽  
Climate Model ◽  
Ice Cover ◽  
Canada Basin ◽  
Surface Salinity ◽  
Model Biases

scholarly journals Surface salinity under transitioning ice cover in the Canada Basin: Climate model biases linked to vertical 2 distribution of freshwater

2021 ◽  
Author(s):  
Erica Rosenblum ◽  
Robert Fajber ◽  
Julienne Stroeve ◽  
Sarah Gille ◽  
Bruno Tremblay ◽  
...  
Keyword(s):  
Climate Model ◽  
Ice Cover ◽  
Canada Basin ◽  
Surface Salinity ◽  
Model Biases

Impacts cumulatifs du développement hydro-électrique sur le bilan d'eau douce de la baie d'Hudson

1994 ◽  
Vol 21 (2) ◽  
pp. 297-306 ◽  
Author(s):  
François Anctil ◽  
Richard Couture
Keyword(s):  
Water Balance ◽  
Fresh Water ◽  
Marine Environment ◽  
Mass Exchange ◽  
Spatial Scales ◽  
Ice Cover ◽  
Hudson Bay ◽  
Freezing And Thawing ◽  
Runoff Water ◽  
Hydroelectric Development

This paper discusses the consequences on the marine environment, more specifically on the fresh water balance, of the hydroelectric development of several tributaries of Hudson Bay, including James Bay and Foxe Basin. The fresh water balance is determined by identifying, at different scales, the modifications caused by each complex. The main inputs are the freezing and thawing of the ice cover, runoff water, and mass exchange at the air–water interface. Three spatial scales were used to obtain the resolution required to document the cumulative effects of fresh water balance modifications on the water surface layer: the Hudson Bay, the Hudson Strait, and the Labrador Sea. Finally, the addition of the proposed Grande-Baleine hydroelectric complex is examined from the available information and forecasts. Key words: hydroelectric development, impact, marine environment, fresh water balance, ice cover, runoff water, mass exchange.[Journal translation]

Historical changes in fresh water transport from sub-tropical to sub-polar oceans

2021 ◽  
Author(s):  
Taimoor Sohail ◽  
Jan Zika ◽  
Damien Irving ◽  
John Church
Keyword(s):  
Fresh Water ◽  
Climate Model ◽  
Water Cycle ◽  
Tropical Ocean ◽  
Freshwater Transport ◽  
Run Off ◽  
Polar Oceans ◽  
S Curve ◽  
Polar Ocean ◽  
Different Response

<p>Warming-induced global water cycle changes pose a significant threat to biodiversity and humanity.  The atmosphere transports freshwater from the sub-tropical ocean to the tropics and poles in two distinct branches. The resulting air-sea fluxes of fresh water and river run-off imprint on ocean salinity (S) at different temperatures (T), creating a characteristic `T-S curve' of mean salinity as a function of temperature. Using a novel tracer-percentile framework, we quantify changes in the observed T-S curve from 1970 to 2014.  The warming ocean has been characterised by freshening tropical and sub-polar oceans and salinifying sub-tropical oceans. Over the 44 year period investigated, a net poleward freshwater transport out of the sub-tropical ocean is quantified, implying an amplification of the net poleward atmospheric freshwater transport. Historical reconstructions from the 6th Climate Model Intercomparison Project (CMIP6) exhibit a different response, underestimating the peak salinification of the ocean by a factor of 4, and showing a weak freshwater transport <em>into</em> the sub-polar ocean. Results indicate this discrepancy between the observations and models may be attributed to consistently biased representations of evaporation and precipitation patterns, which lead to the the weaker amplification seen in CMIP6 models.</p>

Subpolar Gyre – AMOC – Atmosphere Interactions on Multidecadal Timescales in a Version of the Kiel Climate Model

2021 ◽  
Author(s):  
Jing Sun ◽  
Mojib Latif ◽  
Wonsun Park
Keyword(s):  
North Atlantic ◽  
Climate Model ◽  
Deep Convection ◽  
Meridional Overturning Circulation ◽  
Subpolar Gyre ◽  
Surface Salinity ◽  
The North ◽  
Ocean Coupling ◽  
Meridional Overturning ◽  
The North Atlantic

<p>There is a controversy about the nature of multidecadal climate variability in the North Atlantic (NA) region, concerning the roles of ocean circulation and atmosphere-ocean coupling. Here we describe NA multidecadal variability from a version of the Kiel Climate Model, in which both subpolar gyre (SPG)-Atlantic Meridional Overturning Circulation (AMOC) and atmosphere-ocean coupling are essential. The oceanic barotropic streamfuntions, meridional overturning streamfunctions, and sea level pressure are jointly analyzed to derive the leading mode of Atlantic variability. This mode accounting for about 23.7 % of the total combined variance is oscillatory with an irregular periodicity of 25-50 years and an e-folding time of about a decade. SPG and AMOC mutually influence each other and together provide the delayed negative feedback necessary for maintaining the oscillation. An anomalously strong SPG, for example, drives higher surface salinity and density in the NA’s sinking region. In response, oceanic deep convection and AMOC intensify, which, with a time delay of about a decade, reduces SPG strength by enhancing upper-ocean heat content. The weaker gyre circulation leads to lower surface salinity and density in the sinking region, which eventually reduces deep convection and AMOC strength. There is a positive ocean-atmosphere feedback between the sea surface temperature and low-level atmospheric circulation over the Southern Greenland area, with related wind stress changes reinforcing SPG changes, thereby maintaining the (damped) multidecadal oscillation against dissipation. Stochastic surface heat-flux forcing associated with the North Atlantic Oscillation drives the eigenmode.</p>

Ocean Salinity Aspects of the Ningaloo Niño

2021 ◽  
pp. 1
Author(s):  
Yaru Guo ◽  
Yuanlong Li ◽  
Fan Wang ◽  
Yuntao Wei
Keyword(s):  
Fresh Water ◽  
Large Scale ◽  
Southern Oscillation ◽  
Regional Climate ◽  
Ocean Model ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Near Surface ◽  
Ocean Salinity

AbstractNingaloo Niño – the interannually occurring warming episode in the southeast Indian Ocean (SEIO) – has strong signatures in ocean temperature and circulation and exerts profound impacts on regional climate and marine biosystems. Analysis of observational data and eddy-resolving regional ocean model simulations reveals that the Ningaloo Niño/Niña can also induce pronounced variability in ocean salinity, causing large-scale sea surface salinity (SSS) freshening of 0.15–0.20 psu in the SEIO during its warm phase. Model experiments are performed to understand the underlying processes. This SSS freshening is mutually caused by the increased local precipitation (~68%) and enhanced fresh-water transport of the Indonesian Throughflow (ITF; ~28%) during Ningaloo Niño events. The effects of other processes, such as local winds and evaporation, are secondary (~18%). The ITF enhances the southward fresh-water advection near the eastern boundary, which is critical in causing the strong freshening (> 0.20 psu) near the Western Australian coast. Owing to the strong modulation effect of the ITF, SSS near the coast bears a higher correlation with the El Niño-Southern Oscillation (0.57, 0.77, and 0.70 with Niño-3, Niño-4, and Niño-3.4 indices, respectively) than sea surface temperature (-0.27, -0.42, and -0.35) during 1993-2016. Yet, an idealized model experiment with artificial damping for salinity anomaly indicates that ocean salinity has limited impact on ocean near-surface stratification and thus minimal feedback effect on the warming of Ningaloo Niño.

Climate Model Biases and Modification of the Climate Change Signal by Intensity-Dependent Bias Correction

2018 ◽  
Vol 31 (16) ◽  
pp. 6591-6610 ◽  
Author(s):  
Martin Aleksandrov Ivanov ◽  
Jürg Luterbacher ◽  
Sven Kotlarski
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Daily Precipitation ◽  
Analytical Description ◽  
Analytical Theory ◽  
Climate Change Signal ◽  
Future Research ◽  
Model Biases

Climate change impact research and risk assessment require accurate estimates of the climate change signal (CCS). Raw climate model data include systematic biases that affect the CCS of high-impact variables such as daily precipitation and wind speed. This paper presents a novel, general, and extensible analytical theory of the effect of these biases on the CCS of the distribution mean and quantiles. The theory reveals that misrepresented model intensities and probability of nonzero (positive) events have the potential to distort raw model CCS estimates. We test the analytical description in a challenging application of bias correction and downscaling to daily precipitation over alpine terrain, where the output of 15 regional climate models (RCMs) is reduced to local weather stations. The theoretically predicted CCS modification well approximates the modification by the bias correction method, even for the station–RCM combinations with the largest absolute modifications. These results demonstrate that the CCS modification by bias correction is a direct consequence of removing model biases. Therefore, provided that application of intensity-dependent bias correction is scientifically appropriate, the CCS modification should be a desirable effect. The analytical theory can be used as a tool to 1) detect model biases with high potential to distort the CCS and 2) efficiently generate novel, improved CCS datasets. The latter are highly relevant for the development of appropriate climate change adaptation, mitigation, and resilience strategies. Future research needs to focus on developing process-based bias corrections that depend on simulated intensities rather than preserving the raw model CCS.

Detection of Internal Inhomogeneities in a Fresh-Water Ice Cover Using Passive Radio Location

2014 ◽  
Vol 56 (9) ◽  
pp. 1013-1017
Author(s):  
A. A. Gurulev ◽  
S. V. Tsyrenzhapov ◽  
A. O. Orlov
Keyword(s):  
Fresh Water ◽  
Ice Cover ◽  
Water Ice ◽  
Radio Location
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