Uncertainty in Signals of Large-Scale Climate Variations in Radiosonde and Satellite Upper-Air Temperature Datasets

There is no single reference dataset of long-term global upper-air temperature observations, although several groups have developed datasets from radiosonde and satellite observations for climate-monitoring purposes. The existence of multiple data products allows for exploration of the uncertainty in signals of climate variations and change. This paper examines eight upper-air temperature datasets and quantifies the magnitude and uncertainty of various climate signals, including stratospheric quasi-biennial oscillation (QBO) and tropospheric ENSO signals, stratospheric warming following three major volcanic eruptions, the abrupt tropospheric warming of 1976–77, and multidecadal temperature trends. Uncertainty estimates are based both on the spread of signal estimates from the different observational datasets and on the inherent statistical uncertainties of the signal in any individual dataset. The large spread among trend estimates suggests that using multiple datasets to characterize large-scale upperair temperature trends gives a more complete characterization of their uncertainty than reliance on a single dataset. For other climate signals, there is value in using more than one dataset, because signal strengths vary. However, the purely statistical uncertainty of the signal in individual datasets is large enough to effectively encompass the spread among datasets. This result supports the notion of an 11th climate-monitoring principle, augmenting the 10 principles that have now been generally accepted (although not generally implemented) by the climate community. This 11th principle calls for monitoring key climate variables with multiple, independent observing systems for measuring the variable, and multiple, independent groups analyzing the data

The International Pulsar Timing Array: First data release

International audienceThe highly stable spin of neutron stars can be exploited for a variety of (astro)physical investigations. In particular, arrays of pulsars with rotational periods of the order of milliseconds can be used to detect correlated signals such as those caused by gravitational waves. Three such 'pulsar timing arrays' (PTAs) have been set up around the world over the past decades and collectively form the 'International' PTA (IPTA). In this paper, we describe the first joint analysis of the data from the three regional PTAs, i.e. of the first IPTA data set. We describe the available PTA data, the approach presently followed for its combination and suggest improvements for future PTA research. Particular attention is paid to subtle details (such as underestimation of measurement uncertainty and long-period noise) that have often been ignored but which become important in this unprecedentedly large and inhomogeneous data set. We identify and describe in detail several factors that complicate IPTA research and provide recommendations for future pulsar timing efforts. The first IPTA data release presented here (and available on-line) is used to demonstrate the IPTA's potential of improving upon gravitational-wave limit

Building a tuberculosis-free world: The Lancet Commission on tuberculosis

___Key messages___ The Commission recommends five priority investments to achieve a tuberculosis-free world within a generation. These investments are designed to fulfil the mandate of the UN High Level Meeting on tuberculosis. In addition, they answer

Uncertainty in Signals of Large-Scale Climate Variations in Radiosonde and Satellite Upper-Air Temperature Datasets

There is no single reference dataset of long-term global upper-air temperature observations, although several groups have developed datasets from radiosonde and satellite observations for climate-monitoring purposes. The existence of multiple data products allows for exploration of the uncertainty in signals of climate variations and change. This paper examines eight upper-air temperature datasets and quantifies the magnitude and uncertainty of various climate signals, including stratospheric quasi-biennial oscillation (QBO) and tropospheric ENSO signals, stratospheric warming following three major volcanic eruptions, the abrupt tropospheric warming of 1976–77, and multidecadal temperature trends. Uncertainty estimates are based both on the spread of signal estimates from the different observational datasets and on the inherent statistical uncertainties of the signal in any individual dataset. The large spread among trend estimates suggests that using multiple datasets to characterize large-scale upperair temperature trends gives a more complete characterization of their uncertainty than reliance on a single dataset. For other climate signals, there is value in using more than one dataset, because signal strengths vary. However, the purely statistical uncertainty of the signal in individual datasets is large enough to effectively encompass the spread among datasets. This result supports the notion of an 11th climate-monitoring principle, augmenting the 10 principles that have now been generally accepted (although not generally implemented) by the climate community. This 11th principle calls for monitoring key climate variables with multiple, independent observing systems for measuring the variable, and multiple, independent groups analyzing the data

Uncertainty in Signals of Large-Scale Climate Variations in Radiosonde and Satellite Upper-Air Temperature Datasets

There is no single reference dataset of long-term global upper-air temperature observations, although several groups have developed datasets from radiosonde and satellite observations for climate-monitoring purposes. The existence of multiple data products allows for exploration of the uncertainty in signals of climate variations and change. This paper examines eight upper-air temperature datasets and quantifies the magnitude and uncertainty of various climate signals, including stratospheric quasi-biennial oscillation (QBO) and tropospheric ENSO signals, stratospheric warming following three major volcanic eruptions, the abrupt tropospheric warming of 1976–77, and multidecadal temperature trends. Uncertainty estimates are based both on the spread of signal estimates from the different observational datasets and on the inherent statistical uncertainties of the signal in any individual dataset. The large spread among trend estimates suggests that using multiple datasets to characterize large-scale upperair temperature trends gives a more complete characterization of their uncertainty than reliance on a single dataset. For other climate signals, there is value in using more than one dataset, because signal strengths vary. However, the purely statistical uncertainty of the signal in individual datasets is large enough to effectively encompass the spread among datasets. This result supports the notion of an 11th climate-monitoring principle, augmenting the 10 principles that have now been generally accepted (although not generally implemented) by the climate community. This 11th principle calls for monitoring key climate variables with multiple, independent observing systems for measuring the variable, and multiple, independent groups analyzing the data

Response to Comment on “Rapid cooling and cold storage in a silicic magma reservoir recorded in individual crystals”

In a recent paper, we used Li concentration profiles and U-Th ages to constrain the thermal conditions of magma storage. Wilson and co-authors argue that the data instead reflect control of Li behavior by charge balance during partitioning and not by experimentally determined diffusion rates. Their arguments are based on (i) a coupled diffusion mechanism for Li, which has been postulated but has not been documented to occur, and (ii) poorly constrained zircon growth rates combined with the assumption of continuous zircon crystallization

Rapid cooling and cold storage in a silicic magma reservoir recorded in individual crystals

© 2017 The Authors. Silicic volcanic eruptions pose considerable hazards, yet the processes leading to these eruptions remain poorly known. A missing link is knowledge of the thermal history of magma feeding such eruptions, which largely controls crystallinity and therefore eruptability. We have determined the thermal history of individual zircon crystals from an eruption of the Taupo Volcanic Zone, New Zealand. Results show that although zircons resided in the magmatic system for 103 to 105 years, they experienced temperatures \u3e 650° to 750°C for only years to centuries. This implies near-solidus long-term crystal storage, punctuated by rapid heating and cooling. Reconciling these data with existing models of magma storage requires considering multiple small intrusions and multiple spatial scales, and our approach can help to quantify heat input to and output from magma reservoirs

Flow regime and deposition pattern of evaporating binary mixture droplet suspended with particles

The flow regimes and the deposition pattern have been investigated by changing the ethanol concentration in a water-based binary mixture droplet suspended with alumina nanoparticles. To visualize the flow patterns, Particle Image Velocimetry (PIV) has been applied in the binary liquid droplet containing the fluorescent microspheres. Three distinct flow regimes have been revealed in the evaporation. In Regime I, the vortices and chaotic flows are found to carry the particles to the liquid-vapor interface and to promote the formation of particle aggregation. The aggregates move inwards in Regime II as induced by the Marangoni flow along the droplet free surface. Regime III is dominated by the drying of the left water and the capillary flow driving particles radially outward is observed. The relative weightings of Regimes I and II, which are enhanced with an increasing load of ethanol, determine the motion of the nanoparticles and the formation of the final drying pattern