Global water cycle amplifying at less than the Clausius-Clapeyron rate

A change in the cycle of water from dry to wet regions of the globe would have far reaching impact on humanity. As air warms, its capacity to hold water increases at the Clausius-Clapeyron rate (CC, approximately 7% °C−1). Surface ocean salinity observations have suggested the water cycle has amplified at close to CC following recent global warming, a result that was found to be at odds with state-of the art climate models. Here we employ a method based on water mass transformation theory for inferring changes in the water cycle from changes in three-dimensional salinity. Using full depth salinity observations we infer a water cycle amplification of 3.0 ± 1.6% °C−1 over 1950–2010. Climate models agree with observations in terms of a water cycle amplification (4.3 ± 2.0% °C−1) substantially less than CC adding confidence to projections of total water cycle change under greenhouse gas emission scenarios

Operational ocean forecasting in the Eastern Mediterranean: implementation and evaluation

The Cyprus Coastal Ocean Forecasting and Observing System (CYCOFOS) has been producing operational flow forecasts of the northeastern Levantine Basin since 2002 and has been substantially improved in 2005. CYCOFOS uses the POM flow model, and recently, within the frame of the MFSTEP project, the flow model was upgraded to use the hourly SKIRON atmospheric forcing, and its resolution was increased from 2.5 km to 1.8 km. The CYCOFOS model is now nested in the ALERMO regional model from the University of Athens, which is nested within the MFS basin model. The Variational Initialization and FOrcing Platform (VIFOP) has been implemented to reduce the numerical transient processes following initialization. Moreover, a five-day forecast is repeated every day, providing more detailed and more accurate information. Forecast results are posted on the web page http://www.oceanography.ucy.ac.cy/cycofos. The new, daily, high-resolution forecasts agree well with the ALERMO regional model. The agreement is better and results more reasonable when VIFOP is used. Active and slave experiments suggest that a four-week active period produces realistic results with more small-scale features. For runs in September 2004, biases with remote sensing sea surface temperature are less than 0.6°C with similar expressions of the flow field present in both. Remotely-observed coastal upwelling south of Cyprus and advection of cool water from the Rhodes Gyre to the southern shores of Cyprus are also modeled. In situ observed hydrographic data from south of Cyprus are similar to the corresponding forecast fields. Both indicate the relatively fresh subsurface Atlantic Water and a near-surface anticyclone south of Cyprus for August/September of 2004 and September 2005. Plans for further model improvement include assimilation of observed XBT temperature profiles, CTD profiles from drifters and gliders, and CT data from the CYCOFOS ocean observatory

Maintenance and broadening of the ocean’s salinity distribution by the water cycle

The global water cycle leaves an imprint on ocean salinity through evaporation and precipitation. It has been proposed that observed changes in salinity can be used to infer changes in the water cycle. Here salinity is characterized by the distribution of water masses in salinity coordinates. Only mixing and sources and sinks of freshwater and salt can modify this distribution. Mixing acts to collapse the distribution, making saline waters fresher and fresh waters more saline. Hence, in steady state, there must be net precipitation over fresh waters and net evaporation over saline waters. A simple model is developed to describe the relationship between the breadth of the distribution, the water cycle, and mixing—the latter being characterized by an e-folding time scale. In both observations and a state-of-the-art ocean model, the water cycle maintains a salinity distribution in steady state with a mixing time scale of the order of 50 yr. The same simple model predicts the response of the salinity distribution to a change in the water cycle. This study suggests that observations of changes in ocean salinity could be used to infer changes in the hydrological cycle

Mediterranean Sea response to climate change in an ensemble of twenty first century scenarios

The Mediterranean climate is expected to become warmer and drier during the twenty-first century. Mediterranean Sea response to climate change could be modulated by the choice of the socio-economic scenario as well as the choice of the boundary conditions mainly the Atlantic hydrography, the river runoff and the atmospheric fluxes. To assess and quantify the sensitivity of the Mediterranean Sea to the twenty-first century climate change, a set of numerical experiments was carried out with the regional ocean model NEMOMED8 set up for the Mediterranean Sea. The model is forced by air–sea fluxes derived from the regional climate model ARPEGE-Climate at a 50-km horizontal resolution. Historical simulations representing the climate of the period 1961–2000 were run to obtain a reference state. From this baseline, various sensitivity experiments were performed for the period 2001–2099, following different socio-economic scenarios based on the Special Report on Emissions Scenarios. For the A2 scenario, the main three boundary forcings (river runoff, near-Atlantic water hydrography and air–sea fluxes) were changed one by one to better identify the role of each forcing in the way the ocean responds to climate change. In two additional simulations (A1B, B1), the scenario is changed, allowing to quantify the socio-economic uncertainty. Our 6-member scenario simulations display a warming and saltening of the Mediterranean. For the 2070–2099 period compared to 1961–1990, the sea surface temperature anomalies range from +1.73 to +2.97 °C and the SSS anomalies spread from +0.48 to +0.89. In most of the cases, we found that the future Mediterranean thermohaline circulation (MTHC) tends to reach a situation similar to the eastern Mediterranean Transient. However, this response is varying depending on the chosen boundary conditions and socio-economic scenarios. Our numerical experiments suggest that the choice of the near-Atlantic surface water evolution, which is very uncertain in General Circulation Models, has the largest impact on the evolution of the Mediterranean water masses, followed by the choice of the socio-economic scenario. The choice of river runoff and atmospheric forcing both have a smaller impact. The state of the MTHC during the historical period is found to have a large influence on the transfer of surface anomalies toward depth. Besides, subsurface currents are substantially modified in the Ionian Sea and the Balearic region. Finally, the response of thermosteric sea level ranges from +34 to +49 cm (2070–2099 vs. 1961–1990), mainly depending on the Atlantic forcing

Improved estimates of water cycle change from ocean salinity: the key role of ocean warming

Changes in the global water cycle critically impact environmental, agricultural, and energy systems relied upon by humanity (Jiménez Cisneros et al 2014 Climate Change 2014: Impacts, Adaptation, and Vulnerability (Cambridge: Cambridge University Press)). Understanding recent water cycle change is essential in constraining future projections. Warming-induced water cycle change is expected to amplify the pattern of sea surface salinity (Durack et al 2012 Science 336 455–8). A puzzle has, however, emerged. The surface salinity pattern has amplified by 5%–8% since the 1950s (Durack et al 2012 Science 336 455–8, Skliris et al 2014 Clim. Dyn. 43 709–36) while the water cycle is thought to have amplified at close to half that rate (Durack et al 2012 Science 336 455–8, Skliris et al 2016 Sci. Rep. 6 752). This discrepancy is also replicated in climate projections of the 21st century (Durack et al 2012 Science 336 455–8). Using targeted numerical ocean model experiments we find that, while surface water fluxes due to water cycle change and ice mass loss amplify the surface salinity pattern, ocean warming exerts a substantial influence. Warming increases near-surface stratification, inhibiting the decay of existing salinity contrasts and further amplifying surface salinity patterns. Observed ocean warming can explain approximately half of observed surface salinity pattern changes from 1957–2016 with ice mass loss playing a minor role. Water cycle change of 3.6% ± 2.1% per degree Celsius of surface air temperature change is sufficient to explain the remaining observed salinity pattern change

Challenges in quantifying changes in the global water cycle

Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes

Fibronectin rescues estrogen receptor α from lysosomal degradation in breast cancer cells

Estrogen receptor α (ERα) is expressed in tissues as diverse as brains and mammary glands. In breast cancer, ERα is a key regulator of tumor progression. Therefore, understanding what activates ERα is critical for cancer treatment in particular and cell biology in general. Using biochemical approaches and superresolution microscopy, we show that estrogen drives membrane ERα into endosomes in breast cancer cells and that its fate is determined by the presence of fibronectin (FN) in the extracellular matrix; it is trafficked to lysosomes in the absence of FN and avoids the lysosomal compartment in its presence. In this context, FN prolongs ERα half-life and strengthens its transcriptional activity. We show that ERα is associated with β1-integrin at the membrane, and this integrin follows the same endocytosis and subcellular trafficking pathway triggered by estrogen. Moreover, ERα+ vesicles are present within human breast tissues, and colocalization with β1-integrin is detected primarily in tumors. Our work unravels a key, clinically relevant mechanism of microenvironmental regulation of ERα signaling.Fil: Sampayo, Rocío Guadalupe. Universidad Nacional de San Martin. Instituto de Nanosistemas; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Oncología "Ángel H. Roffo"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Toscani, Andrés Martin. Universidad Nacional de Luján; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Rubashkin, Matthew G.. University of California; Estados UnidosFil: Thi, Kate. Lawrence Berkeley National Laboratory; Estados UnidosFil: Masullo, Luciano Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Violi, Ianina Lucila. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias "Elizabeth Jares Erijman"; ArgentinaFil: Lakins, Jonathon N.. University of California; Estados UnidosFil: Caceres, Alfredo Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra. Universidad Nacional de Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra; ArgentinaFil: Hines, William C.. Lawrence Berkeley National Laboratory; Estados UnidosFil: Coluccio Leskow, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina. Universidad Nacional de Luján; ArgentinaFil: Stefani, Fernando Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Chialvo, Dante Renato. Universidad de Buenos Aires; Argentina. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología. Centro Internacional de Estudios Avanzados; ArgentinaFil: Bissell, Mina J.. Lawrence Berkeley National Laboratory; Estados UnidosFil: Weaver, Valerie M.. University of California; Estados UnidosFil: Simian, Marina. Universidad Nacional de San Martin. Instituto de Nanosistemas; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Oncología "Ángel H. Roffo"; Argentin