140 research outputs found
Impact of assimilating a merged sea-ice thickness from CryoSat-2 and SMOS in the Arctic reanalysis
Accurately
forecasting the sea-ice thickness (SIT) in the Arctic is a major challenge.
The new SIT product (referred to as CS2SMOS) merges measurements from the
CryoSat-2 and SMOS satellites on a weekly basis during the winter. The impact
of assimilating CS2SMOS data is tested for the TOPAZ4 system – the Arctic
component of the Copernicus Marine Environment Monitoring Services (CMEMS).
TOPAZ4 currently assimilates a large set of ocean and sea-ice observations
with the Deterministic Ensemble Kalman Filter (DEnKF).
Two parallel reanalyses are conducted without (Official run) and with (Test
run) assimilation of CS2SMOS data from 19 March 2014 to 31 March 2015. Since only mapping errors were provided in the CS2SMOS
observation, an arbitrary term was added to compensate for the missing
errors, but was found a posteriori too large. The SIT bias (too thin) is
reduced from 16 to 5 cm and the standard errors decrease from 53 to 38 cm (by 28 %) when compared to the assimilated SIT. When compared to
independent SIT observations, the error reduction is 24 % against the ice
mass balance (IMB) buoy 2013F and by 12.5 % against SIT data from the
IceBridge campaigns. The improvement of sea-ice volume persists through the
summer months in the absence of CS2SMOS data. Comparisons to sea-ice drift
from the satellites show that dynamical adjustments reduce the drift errors
around the North Pole by about 8 %–9 % in December 2014 and February 2015.
Finally, using the degrees of freedom for signal (DFS), we find that CS2SMOS
makes the prime source of information in the central Arctic and in the Kara
Sea. We therefore recommend the assimilation of C2SMOS for Arctic reanalyses
in order to improve the ice thickness and the ice drift.</p
An eddy resolving tidal-driven model of the South China Sea assimilating along-track SLA data using the EnOI
The upper ocean circulation in the South China Sea (SCS) is driven by the Asian monsoon, the Kuroshio intrusion through the Luzon Strait, strong tidal currents, and a complex topography. Here, we demonstrate the benefit of assimilating along-track altimeter data into a nested configuration of the HYbrid Coordinate Ocean Model that includes tides. Including tides in models is important because they interact with the main circulation. However, assimilation of altimetry data into a model including tides is challenging because tides and mesoscale features contribute to the elevation of ocean surface at different time scales and require different corrections. To address this issue, tides are filtered out of the model output and only the mesoscale variability is corrected with a computationally cheap data assimilation method: the Ensemble Optimal Interpolation (EnOI). This method uses a running selection of members to handle the seasonal variability and assimilates the track data asynchronously. The data assimilative system is tested for the period 1994–1995, during which time a large number of validation data are available. Data assimilation reduces the Root Mean Square Error of Sea Level Anomalies from 9.3 to 6.9 cm and improves the representation of the mesoscale features. With respect to the vertical temperature profiles, the data assimilation scheme reduces the errors quantitatively with an improvement at intermediate depth and deterioration at deeper depth. The comparison to surface drifters shows an improvement of surface current by approximately −9% in the Northern SCS and east of Vietnam. Results are improved compared to an assimilative system that does not include tides and a system that does not consider asynchronous assimilation
TOPAZ4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic
We present a detailed description of TOPAZ4, the latest version of TOPAZ – a coupled ocean-sea ice data assimilation system for the North Atlantic Ocean and Arctic. It is the only operational, large-scale ocean data assimilation system that uses the ensemble Kalman filter. This means that TOPAZ features a time-evolving, state-dependent estimate of the state error covariance. Based on results from the pilot MyOcean reanalysis for 2003–2008, we demonstrate that TOPAZ4 produces a realistic estimate of the ocean circulation in the North Atlantic and the sea-ice variability in the Arctic. We find that the ensemble spread for temperature and sea-level remains fairly constant throughout the reanalysis demonstrating that the data assimilation system is robust to ensemble collapse. Moreover, the ensemble spread for ice concentration is well correlated with the actual errors. This indicates that the ensemble statistics provide reliable state-dependent error estimates – a feature that is unique to ensemble-based data assimilation systems. We demonstrate that the quality of the reanalysis changes when different sea surface temperature products are assimilated, or when in-situ profiles below the ice in the Arctic Ocean are assimilated. We find that data assimilation improves the match to independent observations compared to a free model. Improvements are particularly noticeable for ice thickness, salinity in the Arctic, and temperature in the Fram Strait, but not for transport estimates or underwater temperature. At the same time, the pilot reanalysis has revealed several flaws in the system that have degraded its performance. Finally, we show that a simple bias estimation scheme can effectively detect the seasonal or constant bias in temperature and sea-level
Teaching new dogs old tricks: membrane biophysical properties in drug delivery and resistance
"How do drugs cross the plasma membrane?" this may seem like a trivial question. This question is often over-looked to focus primarily on the different complex macro-molecular aspects involved in drug delivery or drug resistance. However, recent studies have highlighted the theme that to be fully understood, more knowledge of the underlying biology of the most complex biological processes involved in the delivery and resistance to drugs is needed. After all, why would a drug interact with a transporter then subsequently be excluded from P-glycoprotein (P-gp) expressing drug resistant cells? What are the determinants of this transition in behavior? Full consideration of the physical biology of drug delivery has allowed a better understanding of the reasons why specific membrane proteins are upregulated or overexpressed in drug resistant cells. This, in turn, allows us to identify new targets for drug chemicals. Better yet, it increases the significance of recents patents and underlines their importance in multi drug resistance
Seasonal-to-decadal predictions with the ensemble Kalman filter and the Norwegian Earth System Model: a twin experiment
Here, we firstly demonstrate the potential of an advanced flow dependent data assimilation method for performing seasonal-to-decadal prediction and secondly, reassess the use of sea surface temperature (SST) for initialisation of these forecasts. We use the Norwegian Climate Prediction Model (NorCPM), which is based on the Norwegian Earth System Model (NorESM) and uses the deterministic ensemble Kalman filter to assimilate observations. NorESM is a fully coupled system based on the Community Earth System Model version 1, which includes an ocean, an atmosphere, a sea ice and a land model. A numerically efficient coarse resolution version of NorESM is used. We employ a twin experiment methodology to provide an upper estimate of predictability in our model framework (i.e. without considering model bias) of NorCPM that assimilates synthetic monthly SST data (EnKF-SST). The accuracy of EnKF-SST is compared to an unconstrained ensemble run (FREE) and ensemble predictions made with near perfect (i.e. microscopic SST perturbation) initial conditions (PERFECT). We perform 10 cycles, each consisting of a 10-yr assimilation phase, followed by a 10-yr prediction. The results indicate that EnKF-SST improves sea level, ice concentration, 2 m atmospheric temperature, precipitation and 3-D hydrography compared to FREE. Improvements for the hydrography are largest near the surface and are retained for longer periods at depth. Benefits in salinity are retained for longer periods compared to temperature. Near-surface improvements are largest in the tropics, while improvements at intermediate depths are found in regions of large-scale currents, regions of deep convection, and at the Mediterranean Sea outflow. However, the benefits are often small compared to PERFECT, in particular, at depth suggesting that more observations should be assimilated in addition to SST. The EnKF-SST system is also tested for standard ocean circulation indices and demonstrates decadal predictability for Atlantic overturning and sub-polar gyre circulations, and heat content in the Nordic Seas. The system beats persistence forecast and shows skill for heat content in the Nordic Seas that is close to PERFECT
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Advances in reconstructing the AMOC using sea surface observations of salinity
The Atlantic meridional overturning circulation (AMOC) is one of the main drivers of climate variability at decadal and longer time scales. As there are no direct multi-decadal observations of this key circulation, the reconstruction of past AMOC variations is essential. This work presents a step forward in reconstructing the AMOC using climate models and time-varying surface nudging of salinity and temperature data, for which independent multi-decadal observed series are available. A number of nudging protocols are explored in a perfect model framework to best reproduce the AMOC variability accommodating to the characteristics of SST and SSS available products. As reference SST products with sufficient space and time coverage are available, we here choose to focus on the limitations associated to SSS products with the goal of providing protocols using independent salinity products. We consider a global gridded dataset and, additionally, a coarser SSS dataset restricted to the Atlantic and with a quite low spatial resolution (order of 10 degrees vs. 2 for the model grid). We show how, using the latter, we can improve the efficiency of the nudging on the AMOC reconstruction by adding a high-resolution annual cycle to the coarse resolution SSS product as well as a spatial downscaling to account for SSS gradient. The final protocol retained for the coarse SSS data is able to reconstruct a 100-year long AMOC period (average of 10.18 Sv and a standard deviation of 1.39 Sv), with a correlation of 0.76 to the target and a RMSE of 0.99 Sv. These values can be respectively compared to 0.85 and 0.75 Sv when using the global salinity surface observations. This work provides a first step towards understanding the limitations and prospects of historical AMOC reconstructions using different sea surface salinity datasets for the surface nudging
Cytostatic potential of novel agents that inhibit the regulation of intracellular pH
Cells within the acidic extracellular environment of solid tumours maintain their intracellular pH (pHi) through the activity of membrane-based ion exchange mechanisms including the Na+/H+ antiport and the Na+-dependent Cl−/HCO3− exchanger. Inhibition of these regulatory mechanisms has been proposed as an approach to tumour therapy. Previously available inhibitors of these exchangers were toxic (e.g. 4,4-diisothiocyanstilbene-2,2-disulphonic acid), and/or non-specific (e.g. 5-N-ethyl-N-isopropyl amiloride). Using two human (MCF7, MDA-MB231) and one murine (EMT6) breast cancer cell lines, we evaluated the influence of two new agents, cariporide (an inhibitor of the Na+/H+ antiport) and S3705 (an inhibitor of the Na+-dependent Cl−/HCO3− exchanger) on the regulation of intracellular pH (pHi). The cytotoxicity of the two agents was assessed by using clonogenic assays. Our results suggest that cariporide has similar efficacy and potency to 5-N-ethyl-N-isopropyl amiloride for inhibition of Na+/H+ exchange while S3705 is more potent and efficient than 4,4-diisothiocyanstilbene-2,2-disulphonic acid in inhibiting Na+-dependent Cl−/HCO3− exchange. The agents inhibited the growth of tumour cells when they were incubated at low pHe (7.0–6.8), but were non-toxic to cells grown at doses that inhibited the regulation of pHi. Our results indicate that cariporide and S3705 are selective cytostatic agents under in vitro conditions that reflect the slightly acidic microenvironment found in solid tumours
The Naturally Processed CD95L Elicits a c-Yes/Calcium/PI3K-Driven Cell Migration Pathway
Patients affected by chronic inflammatory disorders display high amounts of soluble CD95L. This homotrimeric ligand arises from the cleavage by metalloproteases of its membrane-bound counterpart, a strong apoptotic inducer. In contrast, the naturally processed CD95L is viewed as an apoptotic antagonist competing with its membrane counterpart for binding to CD95. Recent reports pinpointed that activation of CD95 may attract myeloid and tumoral cells, which display resistance to the CD95-mediated apoptotic signal. However, all these studies were performed using chimeric CD95Ls (oligomerized forms), which behave as the membrane-bound ligand and not as the naturally processed CD95L. Herein, we examine the biological effects of the metalloprotease-cleaved CD95L on CD95-sensitive activated T-lymphocytes. We demonstrate that cleaved CD95L (cl-CD95L), found increased in sera of systemic lupus erythematosus (SLE) patients as compared to that of healthy individuals, promotes the formation of migrating pseudopods at the leading edge of which the death receptor CD95 is capped (confocal microscopy). Using different migration assays (wound healing/Boyden Chamber/endothelial transmigration), we uncover that cl-CD95L promotes cell migration through a c-yes/Ca2+/PI3K-driven signaling pathway, which relies on the formation of a CD95-containing complex designated the MISC for Motility-Inducing Signaling Complex. These findings revisit the role of the metalloprotease-cleaved CD95L and emphasize that the increase in cl-CD95L observed in patients affected by chronic inflammatory disorders may fuel the local or systemic tissue damage by promoting tissue-filtration of immune cells
Reconstructing extreme AMOC events through nudging of the ocean surface: a perfect model approach
While the Atlantic Meridional Overturning Circulation (AMOC) is thought to be a crucial component of the North Atlantic climate, past changes in its strength are challenging to quantify, and only limited information is available. In this study, we use a perfect model approach with the IPSL-CM5A-LR model to assess the performance of several surface nudging techniques in reconstructing the variability of the AMOC. Special attention is given to the reproducibility of an extreme positive AMOC peak from a preindustrial control simulation. Nudging includes standard relaxation techniques towards the sea surface temperature and salinity anomalies of this target control simulation, and/or the prescription of the wind-stress fields.
Surface nudging approaches using standard fixed restoring terms succeed in reproducing most of the target AMOC variability, including the timing of the extreme event, but systematically underestimate its amplitude. A detailed analysis of the AMOC variability mechanisms reveals that the underestimation of the extreme AMOC maximum comes from a deficit in the formation of the dense water masses in the main convection region, located south of Iceland in the model. This issue is largely corrected after introducing a novel surface nudging approach, which uses a varying restoring coefficient that is proportional to the simulated mixed layer depth, which, in essence, keeps the restoring time scale constant. This new technique substantially improves water mass transformation in the regions of convection, and in particular, the formation of the densest waters, which are key for the representation of the AMOC extreme. It is therefore a promising strategy that may help to better constrain the AMOC variability and other ocean features in the models. As this restoring technique only uses surface data, for which better and longer observations are available, it opens up opportunities for improved reconstructions of the AMOC over the last few decades
Lactic Acidosis Triggers Starvation Response with Paradoxical Induction of TXNIP through MondoA
Although lactic acidosis is a prominent feature of solid tumors, we still have limited understanding of the mechanisms by which lactic acidosis influences metabolic phenotypes of cancer cells. We compared global transcriptional responses of breast cancer cells in response to three distinct tumor microenvironmental stresses: lactic acidosis, glucose deprivation, and hypoxia. We found that lactic acidosis and glucose deprivation trigger highly similar transcriptional responses, each inducing features of starvation response. In contrast to their comparable effects on gene expression, lactic acidosis and glucose deprivation have opposing effects on glucose uptake. This divergence of metabolic responses in the context of highly similar transcriptional responses allows the identification of a small subset of genes that are regulated in opposite directions by these two conditions. Among these selected genes, TXNIP and its paralogue ARRDC4 are both induced under lactic acidosis and repressed with glucose deprivation. This induction of TXNIP under lactic acidosis is caused by the activation of the glucose-sensing helix-loop-helix transcriptional complex MondoA:Mlx, which is usually triggered upon glucose exposure. Therefore, the upregulation of TXNIP significantly contributes to inhibition of tumor glycolytic phenotypes under lactic acidosis. Expression levels of TXNIP and ARRDC4 in human cancers are also highly correlated with predicted lactic acidosis pathway activities and associated with favorable clinical outcomes. Lactic acidosis triggers features of starvation response while activating the glucose-sensing MondoA-TXNIP pathways and contributing to the “anti-Warburg” metabolic effects and anti-tumor properties of cancer cells. These results stem from integrative analysis of transcriptome and metabolic response data under various tumor microenvironmental stresses and open new paths to explore how these stresses influence phenotypic and metabolic adaptations in human cancers
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