169 results found
Misios S, Kasoar M, Kasoar E, et al., 2021, Similar patterns of tropical precipitation and circulation changes under solar and greenhouse gas forcing, Environmental Research Letters, Vol: 16, Pages: 1-10, ISSN: 1748-9326
Theory and model evidence indicate a higher global hydrological sensitivity for the same amount of surface warming to solar as to greenhouse gas (GHG) forcing, but regional patterns are highly uncertain due to their dependence on circulation and dynamics. We analyse a multi-model ensemble of idealized experiments and a set of simulations of the last millennium and we demonstrate similar global signatures and patterns of forced response in the tropical Pacific, of higher sensitivity for the solar forcing. In the idealized simulations, both solar and GHG forcing warm the equatorial Pacific, enhance precipitation in the central Pacific, and weaken and shift the Walker circulation eastward. Centennial variations in the solar forcing over the last millennium cause similar patterns of enhanced equatorial precipitation and slowdown of the Walker circulation in response to periods with stronger solar forcing. Similar forced patterns albeit of considerably weaker magnitude are identified for variations in GHG concentrations over the 20th century, with the lower sensitivity explained by fast atmospheric adjustments. These findings differ from previous studies that have typically suggested divergent responses in tropical precipitation and circulation between the solar and GHG forcings. We conclude that tropical Walker circulation and precipitation might be more susceptible to solar variability rather than GHG variations during the last-millennium, assuming comparable global mean surface temperature changes.
Thomas C, Voulgarakis A, Lim G, et al., 2021, An unsupervised learning approach to identifying blocking events: the case of European summer, Weather and Climate Dynamics, Vol: 2, Pages: 581-608, ISSN: 2698-4016
Atmospheric blocking events are mid-latitude weather patterns, which obstruct the usual path of the polar jet streams. They are often associated with heat waves in summer and cold snaps in winter. Despite being central features of mid-latitude synoptic-scale weather, there is no well-defined historical dataset of blocking events. Various blocking indices (BIs) have thus been suggested for automatically identifying blocking events in observational and in climate model data. However, BIs show significant regional and seasonal differences so that several indices are typically applied in combination to ensure scientific robustness. Here, we introduce a new BI using self-organizing maps (SOMs), an unsupervised machine learning approach, and compare its detection skill to some of the most widely applied BIs. To enable this intercomparison, we first create a new ground truth time series classification of European blocking based on expert judgement. We then demonstrate that our method (SOM-BI) has several key advantages over previous BIs because it exploits all of the spatial information provided in the input data and reduces the dependence on arbitrary thresholds. Using ERA5 reanalysis data (1979–2019), we find that the SOM-BI identifies blocking events with a higher precision and recall than other BIs. In particular, SOM-BI already performs well using only around 20 years of training data so that observational records are long enough to train our new method. We present case studies of the 2003 and 2019 European heat waves and highlight that well-defined groups of SOM nodes can be an effective tool to diagnose such weather events, although the domain-based approach can still lead to errors in the identification of certain events in a fashion similar to the other BIs. We further test the red blocking detection skill of SOM-BI depending on the meteorological variable used to study blocking, including geopotential height, sea level pressure and four variables related to
Thomas C, Voulgarakis A, Lim G, et al., 2021, An unsupervised learning approach to identifying blocking events:the case of European summer, Weather and Climate Dynamics, Vol: 2, ISSN: 2698-4016
Atmospheric blocking events are mid-latitudeweather patterns, which obstruct the usual path of the polar jet streams. They are often associated with heat wavesin summer and cold snaps in winter. Despite being centralfeatures of mid-latitude synoptic-scale weather, there is nowell-defined historical dataset of blocking events. Variousblocking indices (BIs) have thus been suggested for automatically identifying blocking events in observational and inclimate model data. However, BIs show significant regionaland seasonal differences so that several indices are typicallyapplied in combination to ensure scientific robustness. Here,we introduce a new BI using self-organizing maps (SOMs),an unsupervised machine learning approach, and compare itsdetection skill to some of the most widely applied BIs. Toenable this intercomparison, we first create a new groundtruth time series classification of European blocking basedon expert judgement. We then demonstrate that our method(SOM-BI) has several key advantages over previous BIs because it exploits all of the spatial information provided in theinput data and reduces the dependence on arbitrary thresholds. Using ERA5 reanalysis data (1979–2019), we find thatthe SOM-BI identifies blocking events with a higher precision and recall than other BIs. In particular, SOM-BI alreadyperforms well using only around 20 years of training data sothat observational records are long enough to train our newmethod. We present case studies of the 2003 and 2019 European heat waves and highlight that well-defined groups ofSOM nodes can be an effective tool to diagnose such weatherevents, although the domain-based approach can still lead toerrors in the identification of certain events in a fashion similar to the other BIs. We further test the red blocking detectionskill of SOM-BI depending on the meteorological variableused to study blocking, including geopotential height, sealevel pressure and four variables related to potential vorticity,and t
Gibbins G, Haigh JD, 2021, Comments on "global and regional entropy production by radiation Estimated from satellite observations", Journal of Climate, Vol: 34, Pages: 3721-3728, ISSN: 0894-8755
A recent paper by Kato and Rose reports a negative correlation between the annual mean entropy production rate of the climate and the absorption of solar radiation in the CERES SYN1deg dataset, using the simplifying assumption that the system is steady in time. It is shown here, however, that when the nonsteady interannual storage of entropy is accounted for, the dataset instead implies a positive correlation; that is, global entropy production rates increase with solar absorption. Furthermore, this increase is consistent with the response demonstrated by an energy balance model and a radiative–convective model. To motivate this updated analysis, a detailed discussion of the conceptual relationship between entropy production, entropy storage, and entropy flows is provided. The storage-corrected estimate for the mean global rate of entropy production in the CERES dataset from all irreversible transfer processes is 81.9 mW m−2 K−1 and from only nonradiative processes is 55.2 mW m−2 K−1 (observations from March 2000 to February 2018).
Thomas C, Voulgarakis A, Lim G, et al., 2021, An unsupervised learning approach to identifying blocking events: the case of European summer
<jats:p>&lt;p&gt;Atmospheric blocking events are mid-latitude weather patterns, which obstruct the usual path of the polar jet stream. Several blocking indices (BIs) have been developed to study blocking patterns and their associated trends, but these show significant seasonal and regional differences. Despite being central features of mid-latitude synoptic-scale weather, there is no well-defined historical dataset of blocking events. Here, we introduce a new blocking index using self-organizing maps (SOMs), an unsupervised machine learning approach, and compare its detection skill to some of the most widely applied BIs. To enable this intercomparison, we first create a new ground truth time series classification of European blocking based on expert judgement. We then demonstrate that our method (SOM-BI) has several key advantages over previous BIs because it exploits all the spatial information provided in the input data and avoids the need for arbitrary thresholds. Using ERA5 reanalysis data (1979-2019), we find that the SOM-BI identifies blocking events with a higher precision and recall than other BIs. We present a case study of the 2003 European heat wave and highlight that well-defined groups of SOM nodes can be an effective tool to reliably and accurately diagnose such weather events. This contrasts with the way SOMs are commonly used, where an individual SOM node can be wrongly assumed to represent a weather pattern. We also evaluate the SOM-BI performance on about 100 years of climate model data from a preindustrial simulation with the new UK Earth System Model (UK-ESM1). For the model data, all blocking detection methods have lower skill than for the ERA5 reanalysis, but SOM-BI performs significantly better than the conventional indices. This shows that our method can be effectively applied to climate models to develop our understanding of how climate change will affect regional blocking characteristics. Overall, our results demonstra
Malik A, Nowack PJ, Haigh JD, et al., 2020, Tropical Pacific climate variability under solar geoengineering: impacts on ENSO extremes, ATMOSPHERIC CHEMISTRY AND PHYSICS, Vol: 20, Pages: 15461-15485, ISSN: 1680-7316
Gibbins G, Haigh JD, 2020, Entropy production rates of the climate, Journal of the Atmospheric Sciences, ISSN: 0022-4928
There is ongoing interest in the global entropy production rate as a climate diagnostic and predictor, but progress has been limited by ambiguities in its definition; different conceptual boundaries of the climate system give rise to different internal production rates. Three viable options are described, estimated and investigated here, two of which -- the material and the total radiative (here `planetary') entropy production rates -- are well-established and a third which has only recently been considered but appears very promising. This new option is labelled the `transfer' entropy production rate and includes all irreversible processes that transfer heat within the climate, radiative and material, but not those involved in the exchange of radiation with space. Estimates in three model climates put the material rate in the range 27-48 mW/m^2K, the transfer rate 67-76mW/m^2K, and the planetary rate 1279-1312 mW/m^2K. The climate-relevance of each rate is probed by calculating their responses to climate changes in a simple radiative-convective model. An increased greenhouse effect causes a significant increase in the material and transfer entropy production rates but has no direct impact on the planetary rate. When the same surface temperature increase is forced by changing the albedo instead, the material and transfer entropy production rates increase less dramatically and the planetary rate also registers an increase. This is pertinent to solar radiation management as it demonstrates the difficulty of reversing greenhouse gas-mediated climate changes by albedo alterations. It is argued that the transfer perspective has particular significance in the climate system and warrants increased prominence.
Nowack P, Runge J, Eyring V, et al., 2020, Causal networks for climate model evaluation and constrained projections, Nature Communications, Vol: 11, ISSN: 2041-1723
Global climate models are central tools for understanding past and future climate change. The assessment of model skill, in turn, can benefit from modern data science approaches. Here we apply causal discovery algorithms to sea level pressure data from a large set of climate model simulations and, as a proxy for observations, meteorological reanalyses. We demonstrate how the resulting causal networks (fingerprints) offer an objective pathway for process-oriented model evaluation. Models with fingerprints closer to observations better reproduce important precipitation patterns over highly populated areas such as the Indian subcontinent, Africa, East Asia, Europe and North America. We further identify expected model interdependencies due to shared development backgrounds. Finally, our network metrics provide stronger relationships for constraining precipitation projections under climate change as compared to traditional evaluation metrics for storm tracks or precipitation itself. Such emergent relationships highlight the potential of causal networks to constrain longstanding uncertainties in climate change projections.
Nowack P, Ong QYE, Braesicke P, et al., 2019, Machine learning parameterizations for ozone: climate model transferability, https://sites.google.com/view/climateinformatics2019/proceedings, 9th International Workshop on Climate Informatics, Publisher: UCAR, Pages: 263-268
Many climate modeling studies have demon-strated the importance of two-way interactions betweenozone and atmospheric dynamics. However, atmosphericchemistry models needed for calculating changes in ozoneare computationally expensive. Nowack et al.  high-lighted the potential of machine learning-based ozoneparameterizations in constant climate forcing simulations,with ozone being predicted as a function of the atmo-spheric temperature state. Here we investigate the roleof additional time-lagged temperature information underpreindustrial forcing conditions. In particular, we testif the use of Long Short-Term Memory (LSTM) neuralnetworks can significantly improve the predictive skill ofthe parameterization. We then introduce a novel workflowto transfer the regression model to the new UK EarthSystem Model (UKESM). For this, we show for the firsttime how machine learning parameterizations could betransferred between climate models, a pivotal step tomaking any such parameterization widely applicable inclimate science. Our results imply that ozone parame-terizations could have much-extended scope as they arenot bound to individual climate models but, once trained,could be used in a number of different models. We hope tostimulate similar transferability tests regarding machinelearning parameterizations developed for other Earthsystem model components such as ocean eddy modeling,convection, clouds, or carbon cycle schemes.
Pancost R, Rogelj J, Scoones I, et al., 2019, The pathway toward a net-zero-emissions future, One Earth, Vol: 1, Pages: 18-20, ISSN: 2590-3322
The UK government recently committed to achieving net-zero carbon emissions by 2050. We asked a selection of UK-based experts to reflect upon this commitment, the challenges ahead, and the actions required to make it a reality.
Misios S, Gray LJ, Knudsen MF, et al., 2019, Slowdown of the Walker circulation at solar cycle maximum, Proceedings of the National Academy of Sciences of USA, Vol: 116, Pages: 7186-7191, ISSN: 0027-8424
The Pacific Walker Circulation (PWC) fluctuates on interannual and multidecadal timescales under the influence of internal variability and external forcings. Here, we provide observational evidence that the 11-y solar cycle (SC) affects the PWC on decadal timescales. We observe a robust reduction of east-west sea-level pressure gradients over the Indo-Pacific Ocean during solar maxima and the following 1-2 y. This reduction is associated with westerly wind anomalies at the surface and throughout the equatorial troposphere in the western/central Pacific paired with an eastward shift of convective precipitation that brings more rainfall to the central Pacific. We show that this is initiated by a thermodynamical response of the global hydrological cycle to surface warming, further amplified by atmosphere-ocean coupling, leading to larger positive ocean temperature anomalies in the equatorial Pacific than expected from simple radiative forcing considerations. The observed solar modulation of the PWC is supported by a set of coupled ocean-atmosphere climate model simulations forced only by SC irradiance variations. We highlight the importance of a muted hydrology mechanism that acts to weaken the PWC. Demonstration of this mechanism acting on the 11-y SC timescale adds confidence in model predictions that the same mechanism also weakens the PWC under increasing greenhouse gas forcing.
Ball WT, Rozanov EV, Alsing J, et al., 2019, The upper stratospheric solar cycle ozone response, Geophysical Research Letters, Vol: 46, Pages: 1831-1841, ISSN: 0094-8276
The solar cycle (SC) stratospheric ozone response is thought to influence surface weather and climate. To understand the chain of processes and ensure climate models adequately represent them, it is important to detect and quantify an accurate SC ozone response from observations. Chemistry climate models (CCMs) and observations display a range of upper stratosphere (1–10 hPa) zonally averaged spatial responses; this and the recommended data set for comparison remains disputed. Recent data-merging advancements have led to more robust observational data. Using these data, we show that the observed SC signal exhibits an upper stratosphere U-shaped spatial structure with lobes emanating from the tropics (5–10 hPa) to high altitudes at midlatitudes (1–3 hPa). We confirm this using two independent chemistry climate models in specified dynamics mode and an idealized timeslice experiment. We recommend the BASIC v2 ozone composite to best represent historical upper stratospheric solar variability, and that those based on SBUV alone should not be used.
Malik A, Nowack PJ, Haigh JD, et al., 2019, Tropical Pacific Climate Variability under Solar Geoengineering: Impacts on ENSO Extremes
<jats:p>Abstract. Many modelling studies suggest that the El Niño Southern Oscillation (ENSO), in interaction with the tropical Pacific background climate, will change under rising atmospheric greenhouse gas concentrations. Solar geoengineering (reducing the solar flux from outer space) has been proposed as a means to counteract anthropogenic greenhouse-induced changes in climate. Effectiveness of solar geoengineering is uncertain. Robust results are particularly difficult to obtain for ENSO because existing geoengineering simulations are too short (typically ~ 50 years) to detect statistically significant changes in the highly variable tropical Pacific background climate. We here present results from a 1000-year sunshade geoengineering simulation, G1, carried out with the coupled atmosphere-ocean general circulation model HadCM3L. In agreement with previous studies, reducing the shortwave solar flux more than compensates the warming in the tropical Pacific that develops in the 4×CO2 scenario: we observe an overcooling of 0.3 °C (5 %) and 0.23-mm day−1 (5 %) reduction in mean rainfall relative to preindustrial conditions in the G1 simulation. This is due to the different latitudinal distributions of the shortwave (solar) and longwave (CO2) forcings.The location of the Intertropical Convergence Zone (ITCZ) located north of equator in the tropical Pacific, which moved 7.5° southwards under 4×CO2, is also restored to its preindustrial location. However, other aspects of the tropical Pacific mean climate are not reset as effectively. Relative to preindustrial conditions, in G1 the zonal wind stress, zonal sea surface temperature (SST) gradient, and meridional SST gradient are reduced by 10 %, 11 %, and 9 %, respectively, and the Pacific Walker Circulation (PWC) is consistently weakened. The overall amplitude of ENSO strengthens by 5–8 %, but there is a 65 % reduct
Malik A, Nowack PJ, Haigh JD, et al., 2019, Supplementary material to &quot;Tropical Pacific Climate Variability under Solar Geoengineering: Impacts on ENSO Extremes&quot;
Nowack P, Ong QYE, Braesicke P, et al., 2019, Machine learning parameterizations for ozone in climate sensitivity simulations, Kurzfassungen der Meteorologentagung DACH
Gewin V, Keith D, Haigh J, et al., 2018, Tackling harassment, NATURE, Vol: 562, Pages: 449-450, ISSN: 0028-0836
Nowack PJ, Braesicke P, Haigh J, et al., 2018, Using machine learning to build temperature-based ozone parameterizations for climate sensitivity simulations, Environmental Research Letters, Vol: 13, ISSN: 1748-9326
A number of studies have demonstrated the importance of ozone in climate change simulations, for example concerning global warming projections and atmospheric dynamics. However, fully interactive atmospheric chemistry schemes needed for calculating changes in ozone are computationally expensive. Climate modelers therefore often use climatological ozone fields, which are typically neither consistent with the actual climate state simulated by each model nor with the specific climate change scenario. This limitation applies in particular to standard modeling experiments such as preindustrial control or abrupt 4xCO2 climate sensitivity simulations. Here we suggest a novel method using a simple linear machine learning regression algorithm to predict ozone distributions for preindustrial and abrupt 4xCO2 simulations. Using the atmospheric temperature field as the only input, the regression reliably predicts three-dimensional ozone distributions at monthly to daily time intervals. In particular, the representation of stratospheric ozone variability is much improved compared with a fixed climatology, which is important for interactions with dynamical phenomena such as the polar vortices and the Quasi-Biennial Oscillation. Our method requires training data covering only a fraction of the usual length of simulations and thus promises to be an important stepping stone towards a range of new computationally efficient methods to consider ozone changes in long climate simulations. We highlight key development steps to further improve and extend the scope of machine learning-based ozone parameterizations.
Ball WT, Alsing J, Mortlock DJ, et al., 2018, Evidence for a continuous decline in lower stratospheric ozone offsetting ozone layer recovery, Atmospheric Chemistry and Physics, Vol: 18, Pages: 1379-1394, ISSN: 1680-7316
Ozone forms in the Earth's atmosphere from the photodissociation of molecular oxygen, primarily in the tropical stratosphere. It is then transported to the extratropics by the Brewer–Dobson circulation (BDC), forming a protective "ozone layer" around the globe. Human emissions of halogen-containing ozone-depleting substances (hODSs) led to a decline in stratospheric ozone until they were banned by the Montreal Protocol, and since 1998 ozone in the upper stratosphere is rising again, likely the recovery from halogen-induced losses. Total column measurements of ozone between the Earth's surface and the top of the atmosphere indicate that the ozone layer has stopped declining across the globe, but no clear increase has been observed at latitudes between 60° S and 60° N outside the polar regions (60–90°). Here we report evidence from multiple satellite measurements that ozone in the lower stratosphere between 60° S and 60° N has indeed continued to decline since 1998. We find that, even though upper stratospheric ozone is recovering, the continuing downward trend in the lower stratosphere prevails, resulting in a downward trend in stratospheric column ozone between 60° S and 60° N. We find that total column ozone between 60° S and 60° N appears not to have decreased only because of increases in tropospheric column ozone that compensate for the stratospheric decreases. The reasons for the continued reduction of lower stratospheric ozone are not clear; models do not reproduce these trends, and thus the causes now urgently need to be established.
Ball WT, Alsing J, Mortlock DJ, et al., 2018, Continuous decline in lower stratospheric ozone offsets ozone layer recovery, Atmospheric Chemistry and Physics Discussions, Vol: 18, Pages: 1379-1394, ISSN: 1680-7367
Ozone forms in the Earth's atmosphere from the photodissociation of molecular oxygen, primarily in the tropical stratosphere. It is then transported to the extratropics by the Brewer–Dobson circulation (BDC), forming a protective "ozone layer" around the globe. Human emissions of halogen-containing ozone-depleting substances (hODSs) led to a decline in stratospheric ozone until they were banned by the Montreal Protocol, and since 1998 ozone in the upper stratosphere is rising again, likely the recovery from halogen-induced losses. Total column measurements of ozone between the Earth's surface and the top of the atmosphere indicate that the ozone layer has stopped declining across the globe, but no clear increase has been observed at latitudes between 60°S and 60°N outside the polar regions (60–90°). Here we report evidence from multiple satellite measurements that ozone in the lower stratosphere between 60°S and 60°N has indeed continued to decline since 1998. We find that, even though upper stratospheric ozone is recovering, the continuing downward trend in the lower stratosphere prevails, resulting in a downward trend in stratospheric column ozone between 60°S and 60°N. We find that total column ozone between 60°S and 60°N appears not to have decreased only because of increases in tropospheric column ozone that compensate for the stratospheric decreases. The reasons for the continued reduction of lower stratospheric ozone are not clear; models do not reproduce these trends, and thus the causes now urgently need to be established.
Ball WT, Alsing J, Mortlock DJ, et al., 2017, Reconciling differences in stratospheric ozone composites, Atmospheric Chemistry and Physics, Vol: 17, Pages: 12269-12302, ISSN: 1680-7316
Observations of stratospheric ozone from multipleinstruments now span three decades; combining these intocomposite datasets allows long-term ozone trends to be estimated.Recently, several ozone composites have been published,but trends disagree by latitude and altitude, even betweencomposites built upon the same instrument data. Weconfirm that the main causes of differences in decadal trendestimates lie in (i) steps in the composite time series when theinstrument source data changes and (ii) artificial sub-decadaltrends in the underlying instrument data. These artefacts introducefeatures that can alias with regressors in multiple linearregression (MLR) analysis; both can lead to inaccuratetrend estimates. Here, we aim to remove these artefacts usingBayesian methods to infer the underlying ozone time seriesfrom a set of composites by building a joint-likelihoodfunction using a Gaussian-mixture density to model outliersintroduced by data artefacts, together with a data-driven prioron ozone variability that incorporates knowledge of problemsduring instrument operation. We apply this Bayesianself-calibration approach to stratospheric ozone in 10◦ bandsfrom 60◦ S to 60◦ N and from 46 to 1 hPa (∼ 21–48 km) for1985–2012. There are two main outcomes: (i) we independentlyidentify and confirm many of the data problems previouslyidentified, but which remain unaccounted for in existingcomposites; (ii) we construct an ozone composite, withuncertainties, that is free from most of these problems – wecall this the BAyeSian Integrated and Consolidated (BASIC)composite. To analyse the new BASIC composite, we usedynamical linear modelling (DLM), which provides a morerobust estimate of long-term changes through Bayesian inferencethan MLR. BASIC and DLM, together, provide astep forward in improving estimates of decadal trends. Ourresults indicate a significant recovery of ozone since 1998 inthe upper stratosphere, of both northern and southern midlatitudes,in all f
Haigh JD, 2017, acp-2017-477, Atmospheric Chemistry and Physics, ISSN: 1680-7316
Geen R, Czaja A, Haigh JD, 2016, The effects of increasing humidity on heat transport by extratropical waves, Geophysical Research Letters, Vol: 43, Pages: 8314-8321, ISSN: 1944-8007
This study emphasizes the separate contributions of the warm and cold sectors of extratropical cyclones to poleward heat transport. Aquaplanet simulations are performed with an intermediate complexity climate model in which the response of the atmosphere to a range of values of saturation vapor pressure is assessed. These simulations reveal stronger poleward transport of latent heat in the warm sector as saturation vapor pressure is increased and an unexpected increase in poleward sensible heat transport in the cold sector. The latter results nearly equally from changes in the background stability of the atmosphere at low levels and changes in the temporal correlation between wind and temperature fields throughout the troposphere. Increased stability at low level reduces the likelihood that movement of cooler air over warmer water results in an absolutely unstable temperature profile, leading to less asymmetric damping of temperature and meridional velocity anomalies in cold and warm sectors.
Dhomse SS, Chipperfield MP, Damadeo RP, et al., 2016, On the ambiguous nature of the 11 year solar cycle signal in upper stratospheric ozone, Geophysical Research Letters, Vol: 43, Pages: 7241-7249, ISSN: 1944-8007
Up to now our understanding of the 11 year ozone solar cycle signal (SCS) in the upper stratosphere has been largely based on the Stratospheric Aerosol and Gas Experiment (SAGE) II (v6.2) data record, which indicated a large positive signal which could not be reproduced by models, calling into question our understanding of the chemistry of the upper stratosphere. Here we present an analysis of new v7.0 SAGE II data which shows a smaller upper stratosphere ozone SCS, due to a more realistic ozone-temperature anticorrelation. New simulations from a state-of-art 3-D chemical transport model show a small SCS in the upper stratosphere, which is in agreement with SAGE v7.0 data and the shorter Halogen Occultation Experiment and Microwave Limb Sounder records. However, despite these improvements in the SAGE II data, there are still large uncertainties in current observational and meteorological reanalysis data sets, so accurate quantification of the influence of solar flux variability on the climate system remains an open scientific question.
Sukhodolov T, Rozanov E, Ball WT, et al., 2016, Evaluation of simulated photolysis rates and their response to solar irradiance variability, JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, Vol: 121, Pages: 6066-6084, ISSN: 2169-897X
The state of the stratospheric ozone layer and the temperature structure of the atmosphere are largely controlled by the solar spectral irradiance (SSI) through its influence on heating and photolysis rates. This study focuses on the uncertainties in the photolysis rate response to solar irradiance variability related to the choice of SSI data set and to the performance of the photolysis codes used in global chemistry-climate models. To estimate the impact of SSI uncertainties, we compared several photolysis rates calculated with the radiative transfer model libRadtran, using SSI calculated with two models and observed during the Solar Radiation and Climate Experiment (SORCE) satellite mission. The importance of the calculated differences in the photolysis rate response for ozone and temperature changes has been estimated using 1-D a radiative-convective-photochemical model. We demonstrate that the main photolysis reactions, responsible for the solar signal in the stratosphere, are highly sensitive to the spectral distribution of SSI variations. Accordingly, the ozone changes and related ozone-temperature feedback are shown to depend substantially on the SSI data set being used, which highlights the necessity of obtaining accurate SSI variations. To evaluate the performance of photolysis codes, we compared the results of eight, widely used, photolysis codes against two reference schemes. We show that, in most cases, absolute values of the photolysis rates and their response to applied SSI changes agree within 30%. However, larger errors may appear in specific atmospheric regions because of differences, for instance, in the treatment of Rayleigh scattering, quantum yields, or absorption cross sections.
Ball WT, Haigh JD, Rozanov EV, et al., 2016, High solar cycle spectral variations inconsistent with stratospheric ozone observations, Nature Geoscience, Vol: 9, Pages: 206-209, ISSN: 1752-0894
Haigh JD, 2016, Blue Sky; Mirages, haloes and sundogs; Rainbows; Space Weather; Sunshine; Sunspots and Climate, 30-Second Meteorology: The 50 Most Significant Events and Phenomena, Each Explained in Half a Minute, Editors: Scaife, ISBN: 978-1-7824-0310-4
Tinetti G, Drossart P, Eccleston P, et al., 2015, The EChO science case, Experimental Astronomy, Vol: 40, Pages: 329-391, ISSN: 1572-9508
The discovery of almost two thousand exoplanets has revealed an unexpectedlydiverse planet population. We see gas giants in few-day orbits, whole multi-planet systemswithin the orbit of Mercury, and new populations of planets with masses between that of theEarth and Neptune—all unknown in the Solar System. Observations to date have shown thatour Solar System is certainly not representative of the general population of planets in ourMilky Way. The key science questions that urgently need addressing are therefore: What areexoplanets made of? Why are planets as they are? How do planetary systems work and whatcauses the exceptional diversity observed as compared to the Solar System? The EChO(Exoplanet Characterisation Observatory) space mission was conceived to take up thechallenge to explain this diversity in terms of formation, evolution, internal structure andplanet and atmospheric composition. This requires in-depth spectroscopic knowledge of theatmospheres of a large and well-defined planet sample for which precise physical, chemicaland dynamical information can be obtained. In order to fulfil this ambitious scientificprogram, EChO was designed as a dedicated survey mission for transit and eclipsespectroscopy capable of observing a large, diverse and well-defined planet sample withinits 4-year mission lifetime. The transit and eclipse spectroscopy method, whereby the signalfrom the star and planet are differentiated using knowledge of the planetary ephemerides,allows us to measure atmospheric signals from the planet at levels of at least 10−4 relative tothe star. This can only be achieved in conjunction with a carefully designed stable payloadand satellite platform. It is also necessary to provide broad instantaneous wavelengthcoverage to detect as many molecular species as possible, to probe the thermal structureof the planetary atmospheres and to correct for the contaminating effects of the stellarphotosphere. This requires wavelength coverage of at l
Haigh JD, Matthes K, Hanslmeier A, 2015, The Impact of Solar Variability on Climate., Earth’s climate response to a changing Sun, Editors: Lilensten, Dudok de Wit, Matthes, ISBN: 978-2-7598-1733-7
Haigh JD, Cargill P, 2015, The Sun's Influence on Climate, ISBN: 9780691153841
"--Peter Pilewskie, University of Colorado Boulder "This succinct volume will be invaluable to scientists and general readers who want to learn more about the Sun and its effects on our climate system.
Ball WT, Krivova NA, Unruh YC, et al., 2014, A new SATIRE-S spectral solar irradiance reconstruction for solar cycles 21-23 and its implications for stratospheric Ozone, Journal of the Atmospheric Sciences, Vol: 71, Pages: 4086-4101, ISSN: 0022-4928
The authors present a revised and extended total and spectral solar irradiance (SSI) reconstruction, which includes a wavelength-dependent uncertainty estimate, spanning the last three solar cycles using the Spectral and Total Irradiance Reconstruction—Satellite era (SATIRE-S) model. The SSI reconstruction covers wavelengths between 115 and 160 000 nm and all dates between August 1974 and October 2009. This represents the first full-wavelength SATIRE-S reconstruction to cover the last three solar cycles without data gaps and with an uncertainty estimate. SATIRE-S is compared with the Naval Research Laboratory Spectral Solar Irradiance (NRLSSI) model and ultraviolet (UV) observations from the Solar Radiation and Climate Experiment (SORCE) Solar Stellar Irradiance Comparison Experiment (SOLSTICE). SATIRE-S displays similar cycle behavior to NRLSSI for wavelengths below 242 nm and almost twice the variability between 242 and 310 nm. During the decline of the last solar cycle, between 2003 and 2008, the SSI from SORCE SOLSTICE versions 12 and 10 typically displays more than 3 times the variability of SATIRE-S between 200 and 300 nm. All three datasets are used to model changes in stratospheric ozone within a 2D atmospheric model for a decline from high solar activity to solar minimum. The different flux changes result in different modeled ozone trends. Using NRLSSI leads to a decline in mesospheric ozone, while SATIRE-S and SORCE SOLSTICE result in an increase. Recent publications have highlighted increases in mesospheric ozone when considering version 10 SORCE SOLSTICE irradiances. The recalibrated SORCE SOLSTICE version 12 irradiances result in a much smaller mesospheric ozone response than that of version 10, and this smaller mesospheric ozone response is similar in magnitude to that of SATIRE-S. This shows that current knowledge of variations in spectral irradiance is not sufficient to warrant robust conclusions concerning the impact of solar variability on th
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