Histone H1 is involved in chromatin compaction and dynamics. In human cells, the H1 complement is formed by different amounts of somatic H1 subtypes, H1.0‐H1.5 and H1X. The amount of each variant ...depends on the cell type, the cell cycle phase, and the time of development and can be altered in disease. However, the mechanisms regulating H1 protein levels have not been described. We have analyzed the contribution of the proteasome to the degradation of H1 subtypes in human cells using two different inhibitors: MG132 and bortezomib. H1 subtypes accumulate upon treatment with both drugs, indicating that the proteasome is involved in the regulation of H1 protein levels. Proteasome inhibition caused a global increase in cytoplasmatic H1, with slight changes in the composition of H1 bound to chromatin and chromatin accessibility and no alterations in the nucleosome repeat length. The analysis of the proteasome degradation pathway showed that H1 degradation is ubiquitin‐independent. The whole protein and its C‐terminal domain can be degraded directly by the 20S proteasome in vitro. Partial depletion of PA28γ revealed that this regulatory subunit contributes to H1 degradation within the cell. Our study shows that histone H1 protein levels are under tight regulation to prevent its accumulation in the nucleus. We revealed a new regulatory mechanism for histone H1 degradation, where the C‐terminal disordered domain is responsible for its targeting and degradation by the 20S proteasome, a process enhanced by the regulatory subunit PA28γ.
Sea level in the Mediterranean Sea over the period 1993–2011 is studied on the basis of altimetry, temperature, and salinity data and gravity measurements from Gravity Recovery and Climate Experiment ...(GRACE) (2002–2010). An observed increase in sea level corresponds to a linear sea level trend of 3.0 ± 0.5 mm/yr dominated by the increase in the oceanic mass in the basin. The increase in sea level does not, however, take place linearly but over two 2–3 year periods, each contributing 2–3 cm of sea level. Variability in the basin sea level and its mass component is dominated by the winter North Atlantic Oscillation (NAO). The NAO influence on sea level is primarily linked with atmospheric pressure changes and local wind field changes. However, neither the inverse barometer correction nor a barotropic sea level model forced by atmospheric pressure and wind can remove fully the NAO influence on the basin sea level. Thus, a third contributing mechanism linked with the NAO is suggested. During winter 2010, a low NAO index caused a basin sea level increase of 12 cm which was almost wholly due to mass changes and is evidenced by GRACE. About 8 cm of the observed sea level change can be accounted for as due to atmospheric pressure and wind changes. The residual 4 cm of sea level change is caused by the newly identified contribution. The physical mechanisms that may be responsible for this additional contribution are discussed.
Key points
Updated sea level trends for the Mediterranean Sea are provided
NAO contribution to atmospherically corrected sea level remains significant
Mass component interannual variability determine by the NAO
Observing the water transports through the Strait of Gibraltar is a difficult task. Here we present a methodology aimed to obtain the inflow, outflow and net transport of water from the limited set ...of available observations, currently consisting of an upward looking ADCP deployed at Espartel sill, two tide gauges located at each side of the Strait and radars monitoring the surface velocities. More precisely, we reconstruct the velocity field over a vertical section across the Strait using a reduced order optimal interpolation technique fed with the spatial covariance patterns deduced from high resolution numerical simulations. As a first step we carry out some sensitivity experiments with synthetic data that demonstrate the high potential of the approach. The reconstruction methodology can reproduce very satisfactorily the variability of the transports with estimated correlations for the inflow, outflow and net over 0.9 in all the cases and estimated RMS errors of 0.03, 0.08 and 0.05 Sv, respectively. However, we have also found that the reconstruction is sensible to bias problems, mostly due to the sensitivity of the method to the differences between the statistics of the actual and modeled velocity profiles. The sensitivity experiments have been used to tune the parameters of the method and a reconstruction of actual monthly transports has been performed for the period 2004–2010 along with an estimate of the associated uncertainty. This reconstruction provides for the first time a multiannual time series of the inflow and the net transports solely based on in situ observations. Therefore it can be used as an independent estimate for the validation of numerical models and surface freshwater fluxes in the Mediterranean.
Characterizing and understanding the basic functioning of the Mediterranean Sea in terms of heat and salt redistribution within the basin is a crucial issue to predict its evolution. Here we quantify ...and analyze the heat and salt transfers using a simple box model consisting of four layers in the vertical for each of the two (western and eastern) basins. Namely, we box-average 14 regional simulations of the Med-CORDEX ensemble plus a regional and a global reanalysis, computing for each of them the heat and salt exchanges between layers. First, we analyze in detail the mechanisms behind heat and salt redistribution at different time scales from the outputs of a single simulation (NEMOMED8). We show that in the western basin the transfer between layer 1 (0–150 m) and layer 2 (150–600 m) is upwards for most models both for heat and salt, while in the eastern basin both transfers are downwards. A feature common to both basins is that the transports are smaller in summer than in winter due to the enhanced stratification, which dampen the mixing between layers. From the comparison of the 16 simulations we observe that the spread between models is much larger than the ensemble average for the salt transfer and for the heat transfer between layer 1 and layer 2. At lower layers (below 600 m) there is a set of models showing a good agreement between them, while others are not correlated with any other. The mechanisms behind the ensemble spread are not straightforward. First, to have a coarse resolution prevents the model to correctly represent the heat and salt redistribution in the basin. Second, those models with a very different initial stratification also show a very different redistribution, especially at intermediate and deep layers. Finally, the assimilation of data seems to perturb the heat and salt redistribution. Besides this, the differences among regional models that share similar spatial resolution and initial conditions are induced by more subtle mechanisms which depend on the variable and process analyzed. In order to reduce the uncertainties in the Mediterranean regional climate projections further modelling studies and better observational datasets are needed to constrain the main sources of discrepancies among models. In the absence of those, an ensemble modelling approach as the one followed in the Med-CORDEX initiative seems to be the best solution to evaluate model uncertainties into the future climate projections.
The skills of 5 observational networks are explored in the context of the monitoring of climate signals in the Mediterranean Sea. Namely we explore the capabilities of hydrographic surveys and ships ...of opportunity, of Argo buoys, of a (virtual) regularly distributed mooring network, of the present-day observational system (which makes use of the 3 kinds of observations) and of a targeted future system. The skills of each observational network are quantified as follows: first, the output of a realistic regional circulation model (considered here as the virtual truth) is sampled at the same time and location of the actual observations gathered by each observational network. An objective analysis scheme based on Optimal Statistical Interpolation is then applied to the pseudo-observations to obtain gridded products, which are compared to the model output in order to infer the capability of each sampling to capture the true fields. We do it for different periods (for 1962−2000 and for the whole 21st century) and for different parameters (temperature, salinity and the rate of deep water formation in the Western Mediterranean). Results indicate that the skills to reproduce large scale climatic signals depend on the depth and variable, ranging from >90% of explained monthly variance and <5% relative trend errors for the upper (0−100 m) and intermediate layer (100−400 m) temperature fields, to <60% of variance and 30% relative trend errors for the upper layer salinity field. When averaging temperature and salinity over the whole basin volume, both annual values and long term trends are properly captured by all the networks, though the deep water formation rate in the Western Mediterranean is largely overestimated. Conversely, regional features are missed by all the sampling networks, since none of them has an adequate spatial distribution to capture small scale processes.
The distribution of sea level in the Mediterranean Sea is recovered for the period 1945–2000 by using a reduced space optimal interpolation analysis. The method involves estimating empirical ...orthogonal functions from satellite altimeter data spanning the period 1993–2005 that are then combined with tide gauge data to recover sea level fields over the period 1945–2000. The reconstruction technique is discussed and its robustness is checked through different tests. For the altimetric period (1993–2000) the prediction skill is quantified over the whole domain by comparing the reconstructed fields with satellite altimeter observations. For past times the skill can only be tested locally, by validating the reconstruction against independent tide gauge records. The reconstructed distribution of sea level trends for the period 1945–2000 shows a positive peak in the Ionian Sea (up to 1.5 mm yr
−
1
) and a negative peak of −
0.5 mm yr
−
1
in a small area to the south-east of Crete. Positive trends are found nearly everywhere, being larger in the western Mediterranean (between 0.5 and 1 mm yr
−
1
) than in the eastern Mediterranean (between 0 and 0.5 mm yr
−
1
). The estimated rate of mean sea level rise for the period 1945–2000 is 0.7
±
0.2 mm yr
−
1
, i.e. about a half of the rate estimated for global mean sea level. These overall results do not appear to be very sensitive to the distribution of tide gauges. The poorest results are obtained in open-sea regions with intense mesoscale variability not correlated with any tide gauge station, such as the Algerian Basin.
The mass contribution to Mediterranean Sea level variability is estimated from steric-corrected altimetry and from GRACE observations for the period August 2002 to December 2006. The two signals are ...highly correlated (0.8) and display coherent trends, provided that a proper spatial averaging kernel is used to extract the gravity signal from GRACE coefficients (the same filter is applied to all fields in order to obtain consistent and comparable signals). The good agreement between GRACE observations and steric-corrected altimetry supports the quantification of the long-term mass contribution in terms of non-steric sea level in the Mediterranean. For the past decades, total sea level fields are reconstructed using a reduced-space optimal interpolation of altimetry and tide gauge data. The steric component is evaluated from hydrographic observations available for the same period for the upper 700
m. The errors associated with total sea level and the steric component are evaluated in order to obtain the uncertainty of non-steric sea level. Results indicate that the mass content of the Mediterranean basin has increased at a rate of 0.8
±
0.1
mm/yr for the period 1948–2000. When the effect of the atmospheric pressure is removed, the trend of the mass component increases up to 1.2
±
0.2
mm/yr.
We compare the results of three baroclinic models with the aim of evaluating their skills in reproducing Mediterranean long‐term sea level variability. The models are an ocean‐ice coupled forced ...global model (ORCA), a regional forced ocean model (OM8) and a regional coupled atmosphere‐ocean model (MITgcm). Model results are compared for the period 1961–2000 against hydrographic observations for water mass properties and steric sea level, and against satellite altimetry data and a reconstruction for sea level. All models represent the temperature variability of the upper layers reasonably well, but exhibit a considerable positive drift in the temperature of the deep layers due to an imbalance between the surface heat flux and the heat flux through Gibraltar. OM8 and MITgcm simulate the process of dense water formation better than ORCA thanks to their higher resolution in the model grid and in the atmospheric forcings. Concerning sea level variability, MITgcm is the only model that simulates well the inter‐annual sea level variability associated with the Eastern Mediterranean Transient. However, none of the models is able to reproduce other features that have clear signatures on sea level. The inter‐annual variability of Mediterranean mean sea level is better reproduced by the ORCA model because it is the only one considering the mass contribution from the Atlantic. The lack of that component in the regional models is a major shortcoming to reproduce Mediterranean sea level variability. Finally, mean sea level trends are overestimated by all models due to the spurious warming drift in the deep layers.
Key Points
All three models exhibit a temperature drift
The lack of the mass component in the regional models is a major shortcoming
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