Storm-track shifts under climate change: Toward a mechanistic understanding using baroclinic mean available potential energy

Journal of the Atmospheric Sciences 74 (2017) 93-110

C Mbengue, T Schneider

© 2017 American Meteorological Society.Zonal-mean storm-track shifts in response to perturbations in climate occur even in idealized simulations of dry atmospheres with axisymmetric forcing. Nonetheless, a generally accepted theory of the mechanisms controlling the storm-track shifts is still lacking. Here, mean available potential energy (MAPE), a general measure of baroclinicity that is proportional to the square of the Eady growth rate, is used to understand storm-track shifts. It is demonstrated that, in dry atmospheres, the eddy kinetic energy (EKE) in a storm track is linearly related to the mean available potential energy, relative to a local reference state, and that maxima of the two are generally collocated in latitude. Changes in MAPE with climate are then decomposed into components. It is shown that in simulations of dry atmospheres, changes in the latitude of maximum MAPE are dominated by changes in near-surface meridional temperature gradients. By contrast, changes in the magnitude of MAPE are primarily determined by changes in static stability and in the depth of the troposphere. A theory of storm-track shifts may build upon these findings and primarily needs to explain changes in near-surface meridional temperature gradients. The terminus of the Hadley circulation often shifts in tandem with storm tracks and is hypothesized to play an important role in triggering the storm-track shifts seen in this idealized dry context, especially in simulations where increases only in the convective static stability in the deep tropics suffice to shift storm tracks poleward.

Report on the SPARC QBO Workshop: The QBO and its Global Influence - Past, Present and Future

(2017) 48

J Anstey, SM Osprey, N Butchart, K Hamilton, L Gray, M Baldwin

The 11-year solar cycle - Climate Influencer.


MJ Brown, L Gray

Impacts of stratospheric sulfate geoengineering on global solar photovoltaic and concentrating solar power resource

Journal of Applied Meteorology and Climatology 56 (2017) 1483-1497

CJ Smith, JA Crook, R Crook, LS Jackson, SM Osprey, PM Forster

© 2017 American Meteorological Society.In recent years, the idea of geoengineering, artificially modifying the climate to reduce global temperatures, has received increasing attention because of the lack of progress in reducing global greenhouse gas emissions. Stratospheric sulfate injection (SSI) is a geoengineering method proposed to reduce planetary warming by reflecting a proportion of solar radiation back into space that would otherwise warm the surface and lower atmosphere. The authors analyze results from the Met Office Hadley Centre Global Environment Model, version 2, Carbon Cycle Stratosphere (HadGEM2-CCS) climate model with stratospheric emissions of 10 Tg yr-1 of SO2, designed to offset global temperature rise by around 1°C. A reduction in concentrating solar power output of 5.9% on average over land is shown under SSI relative to a baseline future climate change scenario (RCP4.5) caused by a decrease in direct radiation. Solar photovoltaic energy is generally less affected as it can use diffuse radiation, which increases under SSI, at the expense of direct radiation. The results from HadGEM2-CCS are compared with the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) from the Geoengineering Model Intercomparison Project (GeoMIP), with 5 Tg yr-1 emission of SO2. In many regions, the differences predicted in solar energy output between the SSI and RCP4.5 simulations are robust, as the sign of the changes for both HadGEM2-CCS and GEOSCCM agree. Furthermore, the sign of the total and direct annual mean radiation changes evaluated by HadGEM2-CCS agrees with the sign of the multimodel mean changes of an ensemble of GeoMIP models over the majority of the world.

Synchronisation of the equatorial QBO by the annual cycle in tropical upwelling in a warming climate


K Rajendran, IM Moroz, PL Read, SM Osprey

Oceanic stochastic parameterizations in a seasonal forecast system

Monthly Weather Review 144 (2016) 1867-1875

M Andrejczuk, FC Cooper, S Juricke, TN Palmer, A Weisheimer, L Zanna

© 2016 American Meteorological Society.Stochastic parameterization provides a methodology for representing model uncertainty in ensemble forecasts. Here the impact on forecast reliability over seasonal time scales of three existing stochastic parameterizations in the ocean component of a coupled model is studied. The relative impacts of these schemes upon the ocean mean state and ensemble spread are analyzed. The oceanic variability induced by the atmospheric forcing of the coupled system is, in most regions, the major source of ensemble spread. The largest impact on spread and bias came from the stochastically perturbed parameterization tendency (SPPT) scheme, which has proven particularly effective in the atmosphere. The key regions affected are eddy-active regions, namely, the western boundary currents and the Southern Ocean where ensemble spread is increased. However, unlike its impact in the atmosphere, SPPT in the ocean did not result in a significant decrease in forecast error on seasonal time scales. While there are good grounds for implementing stochastic schemes in ocean models, the results suggest that they will have to be more sophisticated. Some suggestions for next-generation stochastic schemes are made.

The NuMI neutrino beam


P Adamson, K Andersonc, M Andrewsc, R Andrewsc, I Anghel, D Augustinec, A Aurisanob, S Avvakumov, DS Ayres, B Baller, B Barish, G Barr, WL Barrett, RH Bernstein, J Biggs, M Bishai, A Blake, V Bocean, GJ Bock, DJ Boehnlein, D Bogert, K Bourkland, SV Cao, CM Castromonte, S Childress, BC Choudhary, JAB Coelho, JH Cobb, L Corwin, D Crane, JP Cravens, D Cronin-Hennessy, RJ Ducar, JK De Jong, AV Devan, NE Devenish, MV Diwan, AR Erwin, D Crane, JP Cravens, D Cronin-Hennessy, RJ Ducar, JK De Jong, AV Devan, NE Devenish, MV Diwan, AR Erwin, CO Escobar, JJ Evans, E Falk, GJ Feldman, TH Fields, R Ford, MV Frohne, HR Gallagher, V Garkushak, RA Gomes, MC Goodman, P Gouffon, N Graf, R Gran, N Grossman, K Grzelak, A Habig, SR Hahn, D Harding, D Harris, PG Harris, J Hartnell, R Hatcher, S Hays, K Heller, A Holin, J Huang, J Hylen, A Ibrahim, D Indurthy, GM Irwin, Z Isvan, DE Jaffe, C James, D Jensen, J Johnstone, T Kafka, SMS Kasahara, G Koizumi, S Kopp, M Kordosky, A Kreymer, K Lang, C Laughton, G Lefeuvre, J Ling, PJ Litchfield, L Loiacono, P Lucas, WA Mann, A Marchionni, ML Marshak, N Mayer, C McGivern, MM Medeiros, R Mehdiyey, JR Meier, MD Messier, DG Michael, RH Milburn, JL Miller, WH Miller, SR Mishra, SM Sherc, CD Moore, J Morfin, L Mualem, S Mufson, S Murgia, M Murtagh, J Musser, D Naples, JK Nelson, HB Newman, RJ Nichol, JA Nowak, J O'Connor, WP Oliver, M Olsen, M Orchanian, S Osprey, RB Pahlka, J Paley, A Para, RB Patterson, T Patzak, Z Pavlovic, G Pawloski, A Perch, EA Peterson, DA Petyt, MM Pfuetzner, S Phan-Budd, RK Plunkett, N Poonthottathil, P Prieto, D Pushka, X Qiu, A Radovic, RA Rameika, J Ratchford, B Rebel, R Reilly, C Rosenfeld, HA Rubin, K Ruddick, MC Sanchez, N Saoulidou, L Sauer, J Schneps, D Schoo, A Schreckenberger, P Schreiner, P Shanahan, R Sharma, W Smart, C Smith, A Sousa, A Stefanik, N Tagg, RL Talaga, G Tassotto, J Thomas, J Thompson, MA Thomson, X Tian, A Timmons, D Tinsley, SC Tognini, R Toner, D Torretta, I Trostin, G Tzanakos, J Urheim, P Vahle, K Vaziri, E Villegas, B Viren, G Vogel, RC Webber, A Weber, RC Webb, A Wehmann, C White, L Whitehead, LH Whitehead, SG Wojcicki, ML Wong-Squires, T Yang, FX Yumiceva, V Zarucheisky, R Zwaska

Eleven-year solar cycle signal in the NAO and Atlantic/European blocking

Quarterly Journal of the Royal Meteorological Society 142 (2016) 1890-1903

LJ Gray, TJ Woollings, M Andrews, J Knight

© 2016 The Authors. Quarterly Journal of the Royal Meteorological Society published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society.The 11-year solar cycle signal in December–January–February (DJF) averaged mean-sea-level pressure (SLP) and Atlantic/European blocking frequency is examined using multilinear regression with indices to represent variability associated with the solar cycle, volcanic eruptions, the El Niño–Southern Oscillation (ENSO) and the Atlantic Multidecadal Oscillation (AMO). Results from a previous 11-year solar cycle signal study of the period 1870–2010 (140 years; ∼13 solar cycles) that suggested a 3–4 year lagged signal in SLP over the Atlantic are confirmed by analysis of a much longer reconstructed dataset for the period 1660–2010 (350 years; ∼32 solar cycles). Apparent discrepancies between earlier studies are resolved and stem primarily from the lagged nature of the response and differences between early- and late-winter responses. Analysis of the separate winter months provide supporting evidence for two mechanisms of influence, one operating via the atmosphere that maximises in late winter at 0–2 year lags and one via the mixed-layer ocean that maximises in early winter at 3–4 year lags. Corresponding analysis of DJF-averaged Atlantic/European blocking frequency shows a highly statistically significant signal at ∼1-year lag that originates primarily from the late winter response. The 11-year solar signal in DJF blocking frequency is compared with other known influences from ENSO and the AMO and found to be as large in amplitude and have a larger region of statistical significance.

The Use of Remotely Sensed Rainfall for Managing Drought Risk: A Case Study of Weather Index Insurance in Zambia

Remote Sensing 8 (2016) 342-342

E Black, E Tarnavsky, R Maidment, H Greatrex, A Mookerjee, T Quaife, M Brown

Managing drought risk in Africa


E Black, E Tarnavsky, R Maidment, H Greatrex, MJ Brown

A new system for predicting agricultural drought


MJ Brown, E Black, T Quaife, F Otu-Larbi

The 11-year solar cycle – mechanisms for surface impact.


MJ Brown, L Gray

The land surface memory - a drought prediction tool


MJ Brown, E Black, T Quaife, F Otu-Larbi

Food security in Africa is a major problem. Approximately 886mil lion people in Africa rely on agriculture as their main means of survival. They are therefore susceptible to changes in seasonal rains from year to year that can result in agricul tural drought. Agricultural drought is determined by low soil moisture content. Soil moisture res ponds to rainfall, but also depends on many other factors including the soil characteristic s and, crucially, on the past soil moisture. Seasonal rainfall forecasts are thus of limited us e when attempting to predict agricultural drought because they do not predict the soil moi sture, nor take account of the current and past values. Here we demonstrate that predictive skill can be gained from kno wledge of the current state of the land surface – how wet or dry the soil is – as the growing season evolves. This skill arises from the land surface memory - the soil moistur e content at a particular time depends to a large extent on the historical soil moisture. Reversing this, the state of t he soil moisture at a point in the future must depend somewhat on the st ate of the soil moisture now . By forcing a land surface model with observed data up to a present day and then repeatedly with historical data (to represent the range of poss ible future conditions) we show that it is possible to be confident of an ensuing ag ricultural drought 50 days ahead of the end of the growing season. This can be achieved without any rainfall forecast information, but requires the modelled soil moisture to be accu rate. The basic premise of the system is that after a certain date we can be confident of an ensuing drought because, no matter how much it rains, the soil moisture will not r ecover quickly enough to avoid one before the end of the growing season. We also present results from a current operational trial of a forecast system using this method for an undisclosed location in Northern Ghana.

Solar signals in CMIP-5 simulations: Effects of atmosphere-ocean coupling

Quarterly Journal of the Royal Meteorological Society 142 (2016) 928-941

S Misios, DM Mitchell, LJ Gray, K Tourpali, K Matthes, L Hood, H Schmidt, G Chiodo, R Thiéblemont, E Rozanov, A Krivolutsky

© 2016 Royal Meteorological Society.The surface response to the 11 year solar cycle is assessed in ensemble simulations of the twentieth century climate performed in the framework of the fifth phase of the Coupled Model Inter-Comparison Project (CMIP5). A lead/lag multiple linear regression analysis identifies a multi-model mean (MMM) global mean surface warming of about 0.07 K, lagging the solar cycle by 1-2 years on average. The anomalous warming penetrates to approximately the first 80-100 m depth in the ocean. Solar signals in the troposphere show a similar time lag of 1-2 years and the strongest MMM warming is simulated in the Tropics above 300 hPa. At the surface, the MMM response in a subset of models that show statistically significant global mean warming (CMIP5-SIG95) is characterized by an anomalous warming in the west equatorial Pacific Ocean and the Arctic, at 1-2 years after solar maximum. The Arctic warming is twice as strong as the global mean response and appears in the winter months only. The surface warming in the equatorial Pacific Ocean is related to dynamical/thermodynamical processes. Different increase rates of global mean precipitation and atmospheric water vapour in response to a warmer surface lead to a weaker Walker circulation and anomalous westerly winds over the equatorial Pacific in the years following the solar maximum. Owing to atmosphere-ocean coupling, the anomalous westerly winds cool the subsurface and warm the surface in the western equatorial Pacific by ∼0.14 K. The CMIP5-SIG95 MMM surface warming in the equatorial Pacific and Arctic is weak but qualitatively similar compared with solar signals in the HadCRUT4 dataset.

An unexpected disruption of the atmospheric quasi-biennial oscillation.

Science (New York, N.Y.) (2016)

SM Osprey, N Butchart, JR Knight, AA Scaife, K Hamilton, JA Anstey, V Schenzinger, C Zhang

One of the most repeatable phenomena seen in the atmosphere, the quasi-biennial oscillation (QBO) between prevailing eastward and westward wind-jets in the equatorial stratosphere (~16-50 km altitude), was unexpectedly disrupted in February 2016. An unprecedented westward jet formed within the eastward phase in the lower stratosphere and cannot be accounted for by the standard QBO paradigm based on vertical momentum transport. Instead the primary cause was waves transporting momentum from the Northern Hemisphere. Seasonal forecasts did not predict the disruption but analogous QBO disruptions are seen very occasionally in some climate simulations. A return to more typical QBO behavior within the next year is forecast, though the possibility of more frequent occurrences of similar disruptions is projected for a warming climate.

Signatures of naturally induced variability in the atmosphere using multiple reanalysis datasets


DM Mitchell, LJ Gray, M Fujiwara, T Hibino, JA Anstey, W Ebisuzaki, Y Harada, C Long, S Misios, PA Stott, D Tan

A dynamical systems explanation of the Hurst effect and atmospheric low-frequency variability.

Scientific reports 5 (2015) 9068-

CL Franzke, SM Osprey, P Davini, NW Watkins

The Hurst effect plays an important role in many areas such as physics, climate and finance. It describes the anomalous growth of range and constrains the behavior and predictability of these systems. The Hurst effect is frequently taken to be synonymous with Long-Range Dependence (LRD) and is typically assumed to be produced by a stationary stochastic process which has infinite memory. However, infinite memory appears to be at odds with the Markovian nature of most physical laws while the stationarity assumption lacks robustness. Here we use Lorenz's paradigmatic chaotic model to show that regime behavior can also cause the Hurst effect. By giving an alternative, parsimonious, explanation using nonstationary Markovian dynamics, our results question the common belief that the Hurst effect necessarily implies a stationary infinite memory process. We also demonstrate that our results can explain atmospheric variability without the infinite memory previously thought necessary and are consistent with climate model simulations.

The stratospheric wintertime response to applied extratropical torques and its relationship with the annular mode

CLIMATE DYNAMICS 44 (2015) 2513-2537

PAG Watson, LJ Gray

Solar signals in CMIP-5 simulations: The ozone response

Quarterly Journal of the Royal Meteorological Society 141 (2015) 2670-2689

LL Hood, S Misios, DM Mitchell, E Rozanov, LJ Gray, K Tourpali, K Matthes, H Schmidt, G Chiodo, R Thiéblemont, D Shindell, A Krivolutsky

© 2015 Royal Meteorological Society.A multiple linear regression statistical method is applied to model data taken from the Coupled Model Intercomparison Project, phase 5 (CMIP-5) to estimate the 11-year solar cycle responses of stratospheric ozone, temperature, and zonal wind during the 1979-2005 period. The analysis is limited to the six CMIP-5 models which resolve the stratosphere (high-top models) and which include interactive ozone chemistry. All simulations assumed a conservative 11-year solar spectral irradiance (SSI) variation based on the Naval Research Laboratory model. These model responses are then compared to corresponding observational estimates derived from two independent satellite ozone profile datasets and from ERA-Interim reanalysis meteorological data. The models exhibit a range of 11-year responses with three models (CESM1-WACCM, MIROC-ESM-CHEM and MRI-ESM1) yielding substantial solar-induced ozone changes in the upper stratosphere which compare favourably with available observations. The remaining three models do not, apparently because of differences in the details of their radiation and photolysis rate codes. During winter in both hemispheres, the three models with stronger upper-stratospheric ozone responses produce relatively strong latitudinal gradients of ozone and temperature in the upper stratosphere which are associated with accelerations of the polar night jet under solar maximum conditions. This behaviour is similar to that found in the satellite ozone and ERA-Interim data, except that the latitudinal gradients tend to occur at somewhat higher latitudes in the models. The sharp ozone gradients are dynamical in origin and assist in radiatively enhancing the temperature gradients, leading to a stronger zonal wind response. These results suggest that simulation of a realistic solar-induced variation of upper-stratospheric ozone, temperature and zonal wind in winter is possible for at least some coupled climate models even if a conservative SSI variation is adopted.

Solar signals in CMIP-5 simulations: The stratospheric pathway

Quarterly Journal of the Royal Meteorological Society 141 (2015) 2390-2403

DM Mitchell, S Misios, LJ Gray, K Tourpali, K Matthes, L Hood, H Schmidt, G Chiodo, R Thiéblemont, E Rozanov, D Shindell, A Krivolutsky

© 2015 Royal Meteorological Society.The 11 year solar-cycle component of climate variability is assessed in historical simulations of models taken from the Coupled Model Intercomparison Project, phase 5 (CMIP-5). Multiple linear regression is applied to estimate the zonal temperature, wind and annular mode responses to a typical solar cycle, with a focus on both the stratosphere and the stratospheric influence on the surface over the period ~1850-2005. The analysis is performed on all CMIP-5 models but focuses on the 13 CMIP-5 models that resolve the stratosphere (high-top models) and compares the simulated solar cycle signature with reanalysis data. The 11 year solar cycle component of climate variability is found to be weaker in terms of magnitude and latitudinal gradient around the stratopause in the models than in the reanalysis. The peak in temperature in the lower equatorial stratosphere (~70 hPa) reported in some studies is found in the models to depend on the length of the analysis period, with the last 30 years yielding the strongest response. A modification of the Polar Jet Oscillation (PJO) in response to the 11 year solar cycle is not robust across all models, but is more apparent in models with high spectral resolution in the short-wave region. The PJO evolution is slower in these models, leading to a stronger response during February, whereas observations indicate it to be weaker. In early winter, the magnitude of the modelled response is more consistent with observations when only data from 1979-2005 are considered. The observed North Pacific high-pressure surface response during the solar maximum is only simulated in some models, for which there are no distinguishing model characteristics. The lagged North Atlantic surface response is reproduced in both high- and low-top models, but is more prevalent in the former. In both cases, the magnitude of the response is generally lower than in observations.