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We provide updated estimates of the change of ocean heat content and the thermosteric component of sea level change of the 0–700 and 0–2000 m layers of the World Ocean for 1955–2010. Our estimates are based on historical data not previously available, additional modern data, and bathythermograph data corrected for instrumental biases. We have also used Argo data corrected by the Argo DAC if available and used uncorrected Argo data if no corrections were available at the time we downloaded the Argo data. The heat content of the World Ocean for the 0–2000 m layer increased by 24.0 ± 1.9 × 1022 J (±2S.E.) corresponding to a rate of 0.39 W m−2 (per unit area of the World Ocean) and a volume mean warming of 0.09°C. This warming corresponds to a rate of 0.27 W m−2 per unit area of earth's surface. The heat content of the World Ocean for the 0–700 m layer increased by 16.7 ± 1.6 × 1022 J corresponding to a rate of 0.27 W m−2(per unit area of the World Ocean) and a volume mean warming of 0.18°C. The World Ocean accounts for approximately 93% of the warming of the earth system that has occurred since 1955. The 700–2000 m ocean layer accounted for approximately one‐third of the warming of the 0–2000 m layer of the World Ocean. The thermosteric component of sea level trend was 0.54 ± .05 mm yr−1 for the 0–2000 m layer and 0.41 ± .04 mm yr−1 for the 0–700 m layer of the World Ocean for 1955–2010. Key Points A strong positive linear trend in exists in world ocean heat contentsince 1955 One third of the observed warming occurs in the 700‐2000 m layer of the ocean The warming can only be explained by the increase in atmospheric GHGs

ABSTRACT We have entered an era of massive data sets in astronomy. In particular, the number of supernova (SN) discoveries and classifications has substantially increased over the years from few tens to thousands per year. It is no longer the case that observations of a few prototypical events encapsulate most spectroscopic information about SNe, motivating the development of modern tools to collect, archive, organize, and distribute spectra in general and SN spectra in particular. For this reason, we have developed the Weizmann Interactive Supernova Data Repository (WISeREP)-an SQL-based database (DB) with an interactive Web-based graphical interface. The system serves as an archive of high-quality SN spectra, including both historical (legacy) data and data that are accumulated by ongoing modern programs. The archive provides information about objects, their spectra, and related metadata. Utilizing interactive plots, we provide a graphical interface to visualize data, perform line identification of the major relevant species, determine object redshifts, classify SNe, and measure expansion velocities. Guest users may view and download spectra or other data that have been placed in the public domain. Registered users may also view and download data that are proprietary to specific programs with which they are associated. The DB currently holds more than 8000 spectra, of which more than 5000 are public; the latter include published spectra from the Palomar Transient Factory (PTF), all of the SUSPECT (Supernova Spectrum) archive, the Caltech-Core-Collapse Program (CCCP), the CfA SN spectra archive, and published spectra from the University of California, Berkeley, SNDB repository. It offers an efficient and convenient way to archive data and share it with colleagues, and we expect that data stored in this way will be easy to access, increasing its visibility, usefulness, and scientific impact. We encourage the SN community worldwide to make use of the data and tools provided by WISeREP and to contribute data to be made globally available and archived for posterity.

A new empirical algorithm is proposed to estimate surface chlorophyll a (Chl) concentrations in the global ocean for Chl ≤ 0.25 mg m −3 (∼78% of the global ocean area). The algorithm is based on a color index (CI), defined as the difference between remote‐sensing reflectance ( R rs , sr −1 ) in the green and a reference formed linearly between R rs in the blue and red. For low‐Chl waters, in situ data showed a tighter (and therefore better) relationship between CI and Chl than between traditional band ratios and Chl, which was further validated using global data collected concurrently by ship‐borne and Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua instruments. Model simulations showed that for low‐Chl waters, compared with the band‐ratio algorithm, the CI‐based algorithm (CIA) was more tolerant to changes in chlorophyll‐specific backscattering coefficient and performed similarly for different relative contributions of nonphytoplankton absorption. Simulations using existing atmospheric correction approaches further demonstrated that the CIA was much less sensitive than band‐ratio algorithms to various errors induced by instrument noise and imperfect atmospheric correction (including sun glint and whitecap corrections). Image and time series analyses of SeaWiFS and MODIS/Aqua data also showed improved performance in terms of reduced image noise, more coherent spatial and temporal patterns, and better consistency between the two sensors. The reduction in noise and other errors is particularly useful to improve the detection of various ocean features such as eddies. Preliminary tests over Medium‐Resolution Imaging Spectrometer and Coastal Zone Color Scanner data indicate that the new approach should be generally applicable to all past, current, and future ocean color instruments. A completely novel algorithm and concept for remote sensing of ocean chlorophyll Significant improvement in ocean chlorophyll data quality Significant improvement in data consistency between SeaWiFS and MODIS

The Palmer Drought Severity Index (PDSI) has been widely used to study aridity changes in modern and past climates. Efforts to address its major problems have led to new variants of the PDSI, such as the self‐calibrating PDSI (sc_PDSI) and PDSI using improved formulations for potential evapotranspiration (PE), such as the Penman‐Monteith equation (PE_pm) instead of the Thornthwaite equation (PE_th). Here I compare and evaluate four forms of the PDSI, namely, the PDSI with PE_th (PDSI_th) and PE_pm (PDSI_pm) and the sc_PDSI with PE_th (sc_PDSI_th) and PE_pm (sc_PDSI_pm) calculated using available climate data from 1850 to 2008. Our results confirm previous findings that the choice of the PE only has small effects on both the PDSI and sc_PDSI for the 20th century climate, and the self‐calibration reduces the value range slightly and makes the sc_PDSI more comparable spatially than the original PDSI. However, the histograms of the sc_PDSI are still non‐Gaussian at many locations, and all four forms of the PDSI show similar correlations with observed monthly soil moisture (r = 0.4–0.8) in North America and Eurasia, with historical yearly streamflow data (r = 0.4–0.9) over most of the world's largest river basins, and with GRACE (Gravity Recovery and Climate Experiment) satellite‐observed water storage changes (r = 0.4–0.8) over most land areas. All the four forms of the PDSI show widespread drying over Africa, East and South Asia, and other areas from 1950 to 2008, and most of this drying is due to recent warming. The global percentage of dry areas has increased by about 1.74% (of global land area) per decade from 1950 to 2008. The use of the Penman‐Monteith PE and self‐calibrating PDSI only slightly reduces the drying trend seen in the original PDSI. The percentages of dry and wet areas over the global land area and six select regions are anticorrelated (r = −0.5 to −0.7), but their long‐term trends during the 20th century do not cancel each other, with the trend for the dry area often predominating over that for the wet area, resulting in upward trends during the 20th century for the areas under extreme (i.e., dry or wet) conditions for the global land as a whole (∼1.27% per decade) and the United States, western Europe, Australia, Sahel, East Asia, and southern Africa. The recent drying trends are qualitatively consistent with other analyses and model predictions, which suggest more severe drying in the coming decades. Key Points Recent warming has caused widespread drying over land Use of different PE calculations does alter the above conclusion The drying trend may become more severe in coming decades

Arctic amplification (AA) – the observed enhanced warming in high northern latitudes relative to the northern hemisphere – is evident in lower‐tropospheric temperatures and in 1000‐to‐500 hPa thicknesses. Daily fields of 500 hPa heights from the National Centers for Environmental Prediction Reanalysis are analyzed over N. America and the N. Atlantic to assess changes in north‐south (Rossby) wave characteristics associated with AA and the relaxation of poleward thickness gradients. Two effects are identified that each contribute to a slower eastward progression of Rossby waves in the upper‐level flow: 1) weakened zonal winds, and 2) increased wave amplitude. These effects are particularly evident in autumn and winter consistent with sea‐ice loss, but are also apparent in summer, possibly related to earlier snow melt on high‐latitude land. Slower progression of upper‐level waves would cause associated weather patterns in mid‐latitudes to be more persistent, which may lead to an increased probability of extreme weather events that result from prolonged conditions, such as drought, flooding, cold spells, and heat waves. Key Points Enhanced Arctic warming reduces poleward temperature gradient Weaker gradient affects waves in upper‐level flow in two observable ways Both effects slow weather patterns, favoring extreme weather

The South Pole Telescope (SPT) is a 10 m diameter, wide-field, offset Gregorian telescope with a 966 pixel, multicolor, millimeter-wave, bolometer camera. It is located at the Amundsen-Scott South Pole station in Antarctica. The design of the SPT emphasizes careful control of spillover and scattering, to minimize noise and false signals due to ground pickup. The key initial project is a large-area survey at wavelengths of 3, 2, and 1.3 mm, to detect clusters of galaxies via the Sunyaev-Zel’dovich effect and to measure the small-scale angular power spectrum of the cosmic microwave background (CMB). The data will be used to characterize the primordial matter power spectrum and to place constraints on the equation of state of dark energy. A second-generation camera will measure the polarization of the CMB, potentially leading to constraints on the neutrino mass and the energy scale of inflation.

Changes in upper ocean stratification during the second half of the 21st century, relative to the second half of the 20th century, are examined in ten of the CMIP3 climate models according to the SRES‐A2 scenario. The upper ocean stratification, defined here as the density difference between 200 m and the surface, is larger everywhere during the second half of the 21st century, indicative of an increasing degree of decoupling between the surface and the deeper oceans, with important consequences for many biogeochemical processes. The areas characterized by the largest stratification changes include the Arctic, the tropics, the North Atlantic, and the northeast Pacific. The increase in stratification is primarily due to the increase in surface temperature, whose influence upon density is largest in the tropical regions, and decreases with increasing latitude. The influence of salinity upon the stratification changes, while not as spatially extensive as that of temperature, is very large in the Arctic, North Atlantic and Northeast Pacific. Salinity also significantly contributes to the density decrease near the surface in the western tropical Pacific, but counteracts the negative influence of temperature upon density in the tropical Atlantic. Key Points Changes in SST and SSS lead to changes in stratification Increasing temperatures reduce surface density Salinity can have a large influence on density in specific regions

A recent global compilation of the thermal structure of subduction zones is used to predict the metamorphic facies and H2O content of downgoing slabs. Our calculations indicate that mineralogically bound water can pass efficiently through old and fast subduction zones (e.g., in the western Pacific), whereas hot subduction zones such as Cascadia see nearly complete dehydration of the subducting slab. The top of the slab is sufficiently hot in all subduction zones that the upper crust, including sediments and volcanic rocks, is predicted to dehydrate significantly. The degree and depth of dehydration in the deeper crust and uppermost mantle are highly diverse and depend strongly on composition (gabbro versus peridotite) and local pressure and temperature conditions. The upper mantle dehydrates at intermediate depths in all but the coldest subduction zones. On average, about one third of the bound H2O subducted globally in slabs reaches 240 km depth, carried principally and roughly equally in the gabbro and peridotite sections. The predicted global flux of H2O to the deep mantle is smaller than previous estimates but still amounts to about one ocean mass over the age of the Earth. At this rate, the overall mantle H2O content increases by 0.037 wt % (370 ppm) over the age of the Earth. This is qualitatively consistent with inferred H2O concentrations in the Earth's mantle assuming that secular cooling of the Earth has increased the efficiency of volatile recycling over time.

The turbulent mixing in thin ocean surface boundary layers (OSBL), which occupy the upper 100 m or so of the ocean, control the exchange of heat and trace gases between the atmosphere and ocean. Here we show that current parameterizations of this turbulent mixing lead to systematic and substantial errors in the depth of the OSBL in global climate models, which then leads to biases in sea surface temperature. One reason, we argue, is that current parameterizations are missing key surface‐wave processes that force Langmuir turbulence that deepens the OSBL more rapidly than steady wind forcing. Scaling arguments are presented to identify two dimensionless parameters that measure the importance of wave forcing against wind forcing, and against buoyancy forcing. A global perspective on the occurrence of wave‐forced turbulence is developed using re‐analysis data to compute these parameters globally. The diagnostic study developed here suggests that turbulent energy available for mixing the OSBL is under‐estimated without forcing by surface waves. Wave‐forcing and hence Langmuir turbulence could be important over wide areas of the ocean and in all seasons in the Southern Ocean. We conclude that surface‐wave‐forced Langmuir turbulence is an important process in the OSBL that requires parameterization. Key Points Climate models have biases in the depth of the ocean surface boundary layer Langmuir turbulence is a key process mixing the ocean surface boundary layer Langmuir turbulence deepens the layer more quickly than wind‐forced turbulence

ABSTRACT Kepler provides light curves of 156,000 stars with unprecedented precision. However, the raw data as they come from the spacecraft contain significant systematic and stochastic errors. These errors, which include discontinuities, systematic trends, and outliers, obscure the astrophysical signals in the light curves. To correct these errors is the task of the Presearch Data Conditioning (PDC) module of the Kepler data analysis pipeline. The original version of PDC in Kepler did not meet the extremely high performance requirements for the detection of miniscule planet transits or highly accurate analysis of stellar activity and rotation. One particular deficiency was that astrophysical features were often removed as a side effect of the removal of errors. In this article we introduce the completely new and significantly improved version of PDC which was implemented in Kepler SOC version 8.0. This new PDC version, which utilizes a Bayesian approach for removal of systematics, reliably corrects errors in the light curves while at the same time preserving planet transits and other astrophysically interesting signals. We describe the architecture and the algorithms of this new PDC module, show typical errors encountered in Kepler data, and illustrate the corrections using real light curve examples.