Stratospheric dynamics and midlatitude jets under geoengineering with space mirrors and sulfate and titania aerosols

The impact on the dynamics of the stratosphere of three approaches to geoengineering by solar radiation management is investigated using idealized simulations of a global climate model. The approaches are geoengineering with sulfate aerosols, titania aerosols, and reduction in total solar irradiance (representing mirrors placed in space). If it were possible to use stratospheric aerosols to counterbalance the surface warming produced by a quadrupling of atmospheric carbon dioxide concentrations, tropical lower stratospheric radiative heating would drive a thermal wind response which would intensify the stratospheric polar vortices. In the Northern Hemisphere this intensification results in strong dynamical cooling of the polar stratosphere. Northern Hemisphere stratospheric sudden warming events become rare (one and two in 65 years for sulfate and titania, respectively). The intensification of the polar vortices results in a poleward shift of the tropospheric midlatitude jets in winter. The aerosol radiative heating enhances the tropical upwelling in the lower stratosphere, influencing the strength of the Brewer-Dobson circulation. In contrast, solar dimming does not produce heating of the tropical lower stratosphere, and so there is little intensification of the polar vortex and no enhanced tropical upwelling. The dynamical response to titania aerosol is qualitatively similar to the response to sulfate

Intense Source of Slow Positrons

We describe a novel design for an intense source of slow positrons based on pair production with a beam of electrons from a 10 MeV accelerator hitting a thin target at a low incidence angle. The positrons are collected with a set of coils adapted to the large production angle. The collection system is designed to inject the positrons in a Greaves-Surko trap [1]. Such a source could be the basis for a series of experiments in fundamental and applied research and would also be a prototype source for industrial applications which concern the field of defect characterization in the nanometer scale.Comment: submitted to N.I.M.

Sub-seasonal forecasts of demand and wind power and solar power generation for 28 European countries

Electricity systems are becoming increasingly exposed to weather. The need for high-quality meteorological forecasts for managing risk across all timescales has therefore never been greater. This paper seeks to extend the uptake of meteorological data in the power systems modelling community to include probabilistic meteorological forecasts at sub-seasonal lead times. Such forecasts are growing in skill and are receiving considerable attention in power system risk management and energy trading. Despite this interest, these forecasts are rarely evaluated in power system terms, and technical barriers frequently prohibit use by non-meteorological specialists.This paper therefore presents data produced through a new EU climate services programme Subseasonal-to-seasonal forecasting for Energy (S2S4E). The data correspond to a suite of well-documented, easy-to-use, self-consistent daily and nationally aggregated time series for wind power, solar power and electricity demand across 28 European countries. The data are accessible from https://doi.org/10.17864/1947.275 (Gonzalez et al., 2020). The data include a set of daily ensemble reforecasts from two leading forecast systems spanning 20 years (ECMWF, an 11-member ensemble, with twice-weekly starts for 1996–2016, totalling 22 880 forecasts) and 11 years (NCEP, a 12-member lagged-ensemble, constructed to match the start dates from the ECMWF forecast from 1999–2010, totalling 14 976 forecasts). The reforecasts contain multiple plausible realisations of daily weather and power data for up to 6 weeks in the future.To the authors’ knowledge, this is the first time a fully calibrated and post-processed daily power system forecast set has been published, and this is the primary purpose of this paper. A brief review of forecast skill in each of the individual primary power system properties and a composite property is presented, focusing on the winter season. The forecast systems contain additional skill over climatological expectation for weekly-average forecasts at extended lead times, though this skill depends on the nature of the forecast metric considered. This highlights the need for greater collaboration between the energy and meteorological research communities to develop applications, and it is hoped that publishing these data and tools will support this

Associations between stratospheric variability and tropospheric blocking

There is widely believed to be a link between stratospheric flow variability and stationary, persistent “blocking” weather systems, but the precise nature of this link has proved elusive. Using data from the ERA-40 Reanalysis and an atmospheric general circulation model (GCM) with a well-resolved stratosphere (HadGAM), it is shown that there are in fact several different highly significant associations, with blocking in different regions being related to different patterns of stratospheric variability. This is true in both hemispheres and in both data sets. The associations in HadGAM are shown to be very similar to those in ERA-40, although the model has a tendency to underestimate both European blocking and the wave number 2 stratospheric variability to which this is related. Although the focus is on stratospheric variability in general, several of the blocking links are seen to occur in association with the major stratospheric sudden warmings. In general, the direction of influence appears to be upward, as blocking anomalies are shown to modify the planetary stationary waves, leading to an upward propagation of wave activity into the stratosphere. However, significant correlations are also apparent with the zonal mean flow in the stratosphere leading the occurrence of blocking at high latitudes. Finally, the underestimation of blocking is an enduring problem in GCMs, and an example has recently been given in which improving the resolution of the stratosphere improved the representation of blocking. Here, however, another example is given, in which increasing the stratospheric resolution unfortunately does not lead to an improvement in blocking

Meteorological source variability in atmospheric gravity wave parameters derived from a tropical infrasound station

Gravity waves are an important part of the momentum budget of the atmosphere. Despite this, parameterizations of gravity wave spectra in atmospheric models are poorly constrained. Gravity waves are formed by jet streams, flow over topography and convection, all of which produce pressure perturbations as they propagate over the Earth’s surface, detectable by microbarometer arrays used for sensing infrasound. In this study, observations of gravity waves between 2007 and 2011 at an infrasound station in the Ivory Coast, West Africa are combined with meteorological data to calculate parameters such as intrinsic phase speed and wavenumber. Through spectral analysis, the seasonal and daily variations in all gravity wave parameters are examined. The gravity wave back azimuth varies with the migration of the Inter-Tropical Convergence Zone, a region of intense convection, supporting previous studies. Daily variations in gravity wave arrivals at the station can be linked to two distinct convective cycles over the land and ocean. This was achieved by combining the gravity wave parameters with lightning strikes detected by the Met Office’s Arrival Time Difference lightning detection system. Noise generated by turbulence in the middle of the day was found to attenuate smaller pressure amplitude gravity waves, artificially amplifying the daily variations in some gravity wave parameters. Detection of daily and seasonal variations in gravity wave parameters has the potential be used to improve the representation of gravity wave spectra in atmospheric models

Wintertime North American weather regimes and the Arctic stratospheric polar vortex

The impact of the Arctic stratospheric polar vortex on persistent weather regimes over North America is so far under-explored. Here we show the relationship between four wintertime North American weather regimes and the stratospheric vortex strength using reanalysis data. We find that the strength of the vortex significantly affects the behavior of the regimes. Whilst a regime associated with Greenland blocking is strongly favored following weak vortex events, it is not the primary regime associated with a widespread, elevated risk of extreme cold in North America. Instead, we find that the regime most strongly associated with widespread extremely cold weather does not show a strong dependency on the strength of the lower-stratospheric zonal-mean zonal winds. We also suggest that stratospheric vortex morphology may be particularly important for cold air outbreaks during this regime

Chilean wildfires: probabilistic prediction, emergency response and public communication

The 2016/17 wildfire season in Chile was the worst on record, burning more than 600,000 hectares. Whilst wildfires are an important natural process in some areas of Chile supporting its diverse ecosystems, wildfires are also one of the biggest threats to Chile’s unique biodiversity and it’s timber and wine industries. They also pose a danger to human life and property due to the sharp wildland-urban interface that exists in many Chilean towns and cities. Wildfires are however difficult to predict due to the combination of physical (meteorology, vegetation and fuel condition), and human (population density and awareness level) factors. Most Chilean wildfires are started due to accidental ignition by humans. This accidental ignition could be minimized if an effective wildfire warning system alerted the population to the heightened danger of wildfires in certain locations and meteorological conditions. Here we demonstrate the design of a novel probabilistic wildfire prediction system. The system uses ensemble forecast meteorological data together with a longtime series of fire products derived from Earth Observation to predict not only fire occurrence, but in addition, how intense wildfires could be. The system provides wildfire risk estimation and associated uncertainty for up to 6 days in advance, and communicates it to a variety of end users. The advantage of this probabilistic wildfire warning system over deterministic systems is that it allows users to assess the confidence of a forecast and thus make more informed decisions regarding resource allocation and forest management. The approach used in this study could easily be adapted to communicate other probabilistic forecasts of natural hazards

The potential to narrow uncertainty in projections of stratospheric ozone over the 21st century

Future stratospheric ozone concentrations will be determined both by changes in the concentration of ozone depleting substances (ODSs) and by changes in stratospheric and tropospheric climate, including those caused by changes in anthropogenic greenhouse gases (GHGs). Since future economic development pathways and resultant emissions of GHGs are uncertain, anthropogenic climate change could be a significant source of uncertainty for future projections of stratospheric ozone. In this pilot study, using an "ensemble of opportunity" of chemistry-climate model (CCM) simulations, the contribution of scenario uncertainty from different plausible emissions pathways for ODSs and GHGs to future ozone projections is quantified relative to the contribution from model uncertainty and internal variability of the chemistry-climate system. For both the global, annual mean ozone concentration and for ozone in specific geographical regions, differences between CCMs are the dominant source of uncertainty for the first two-thirds of the 21st century, up-to and after the time when ozone concentrations return to 1980 values. In the last third of the 21st century, dependent upon the set of greenhouse gas scenarios used, scenario uncertainty can be the dominant contributor. This result suggests that investment in chemistry-climate modelling is likely to continue to refine projections of stratospheric ozone and estimates of the return of stratospheric ozone concentrations to pre-1980 levels

The predictability of the extratropical stratosphere on monthly time-scales and its impact on the skill of tropospheric forecasts

This is the final version of the article. Available from Wiley via the DOI in this record.Extreme variability of the winter- and spring-time stratospheric polar vortex has been shown to affect extratropical tropospheric weather. Therefore, reducing stratospheric forecast error may be one way to improve the skill of tropospheric weather forecasts. In this review, the basis for this idea is examined. A range of studies of different stratospheric extreme vortex events shows that they can be skilfully forecasted beyond 5 days and into the sub-seasonal range (0–30 days) in some cases. Separate studies show that typical errors in forecasting a stratospheric extreme vortex event can alter tropospheric forecast skill by 5–7% in the extratropics on sub-seasonal time-scales. Thus understanding what limits stratospheric predictability is of significant interest to operational forecasting centres. Both limitations in forecasting tropospheric planetary waves and stratospheric model biases have been shown to be important in this context.This work is supported by the Natural Environmental Research Council (NERC) funded project Stratospheric Network for the Assessment of Predictability (SNAP) (Grant H5147600) and partially supported by the SPARC. ACP and RGH acknowledge funding through the EU ARISE project (Grant 284387) (EU-FP7). We also acknowledge Steven Pawson and Lawrence Coy from NASA for providing Figure 1. We wish to thank Lorenzo Polvani from Columbia University for providing Figure 4 and Amy Butler from NOAA for her contribution to Figure 5. We thank Adrian Simmons of ECMWF for his insightful review and two anonymous reviewers for their comments and suggestions that improved the quality of the manuscript