Evidence for H2 dissociation and recombination heat transport in the atmosphere of KELT-9b

Astrophysical Journal Letters American Astronomical Society 888 (2020) L15

M Mansfield, JL Bean, KB Stevenson, TD Komacek, TJ Bell, X Tan, M Malik, TG Beatty, I Wong, NB Cowan, L Dang, J-M Désert, JJ Fortney, BS Gaudi, D Keating, L Kreidberg, EM-R Kempton, V Parmentier, KG Stassun

Patterns in Wall-Bounded Shear Flows

, 2020

LS Tuckerman, M Chantry, D Barkley

Seasonal forecasts of the 20th Century

Bulletin of the American Meteorological Society American Meteorological Society (2020) BAMS-D-19-0019.1

K Strømmen, C O’Reilly, D MacLeod, T Palmer, A Weisheimer, DJ Befort

<jats:p> Capsule Summary </jats:p><jats:p> New seasonal retrospective forecasts for 1901-2010 show that skill for predicting ENSO, NAO and PNA is reduced during mid-century periods compared to earlier and more recent high-skill decades. </jats:p>

An AeroCom/AeroSat study: Intercomparison of Satellite AOD Datasets for Aerosol Model Evaluation

Atmospheric Chemistry and Physics Discussions European Geosciences Union (2020)

N Schutgens, A Sayer, G de Leeuw, A Heckel, C Hsu, P Leonard, H Jethva, A Lyapustin, A Lipponen, R Levy, P North, C Poulson, L Sogacheva, V Sawyer, G Thomas, T Popp, M Schulz, S Kinne, O Torres, Y Wang, P STIER

Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz’96 Model

Journal of Advances in Modeling Earth Systems American Geophysical Union (AGU) (2020)

AC Subramanian, AH Monahan, HM Christensen, DJ Gagne

Ice, Fire, or Fizzle: The Climate Footprint of Earth's Supercontinental Cycles

Geochemistry, Geophysics, Geosystems (2020)

R PIERREHUMBERT, A Lenardic, M Jellinek

Diurnal cycle of the semi-direct effect from a persistent absorbing aerosol layer over marine stratocumulus in large-eddy simulations

Atmospheric Chemistry and Physics European Geosciences Union 20 (2020) 1317–1340-

E Highwood, N Bellouin, A Hill, R Herbert

<p>The rapid adjustment, or semi-direct effect, of marine stratocumulus clouds to elevated layers of absorbing aerosols may enhance or dampen the radiative effect of aerosol&ndash;radiation interactions. Here we use large-eddy simulations to investigate the sensitivity of stratocumulus clouds to the properties of an absorbing aerosol layer located above the inversion layer, with a focus on the location, timing, and strength of the radiative heat perturbation. The sign of the daily mean semi-direct effect depends on the properties and duration of the aerosol layer, the properties of the boundary layer, and the model setup. Our results suggest that the daily mean semi-direct effect is more elusive than previously assessed. We find that the daily mean semi-direct effect is dominated by the distance between the cloud and absorbing aerosol layer. Within the first 24&thinsp;h the semi-direct effect is positive but remains under 2&thinsp;W&thinsp;m<sup>&minus;2</sup>&nbsp;unless the aerosol layer is directly above the cloud. For longer durations, the daily mean semi-direct effect is consistently negative but weakens by 30&thinsp;%, 60&thinsp;%, and 95&thinsp;% when the distance between the cloud and aerosol layer is 100, 250, and 500&thinsp;m, respectively. Both the cloud response and semi-direct effect increase for thinner and denser layers of absorbing aerosol. Considerable diurnal variations in the cloud response mean that an instantaneous semi-direct effect is unrepresentative of the daily mean and that observational studies may underestimate or overestimate semi-direct effects depending on the observed time of day. The cloud response is particularly sensitive to the mixing state of the boundary layer: well-mixed boundary layers generally result in a negative daily mean semi-direct effect, and poorly mixed boundary layers result in a positive daily mean semi-direct effect. The properties of the boundary layer and model setup, particularly the sea surface temperature, precipitation, and properties of the air entrained from the free troposphere, also impact the magnitude of the semi-direct effect and the timescale of adjustment. These results suggest that the semi-direct effect simulated by coarse-resolution models may be erroneous because the cloud response is sensitive to small-scale processes, especially the sources and sinks of buoyancy.</p>

Surprising similarities in model and observational aerosol radiative forcing estimates

Atmospheric Chemistry and Physics Copernicus GmbH (2020)

H Wang, J Mülmenstädt, A Gettelman, E Gryspeerdt, M Wang, K Zhang, FF Malavelle, H Morrison, D Neubauer, PHILIP Stier, DG Partridge, T Takemura

<jats:p>Abstract. The radiative forcing from aerosols (particularly through their interaction with clouds) remains one of the most uncertain components of the human forcing of the climate. Observation-based studies have typically found a smaller aerosol effective radiative forcing than in model simulations and were given preferential weighting in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). With their own sources of uncertainty, it is not clear that observation-based estimates are more reliable. Understanding the source of the model and observational differences is thus vital to reduce uncertainty in the impact of aerosols on the climate. These reported discrepancies arise from the different methods of separating the components of aerosol forcing used in model and observational studies. Applying the observational decomposition to global climate model (GCM) output, the two different lines of evidence are surprisingly similar, with a much better agreement on the magnitude of aerosol impacts on cloud properties. Cloud adjustments remain a significant source of uncertainty, particularly for ice clouds. However, they are consistent with the uncertainty from observation-based methods, with the liquid water path adjustment usually enhancing the Twomey effect by less than 50 %. Depending on different sets of assumptions, this work suggests that model and observation-based estimates could be more equally weighted in future synthesis studies. </jats:p>

Uncertainty in the response of sudden stratospheric warmings and stratosphere-troposphere coupling to quadrupled CO2 concentrations in CMIP6 models

Journal of Geophysical Research: Atmospheres American Geophysical Union (AGU) (2020) e2019JD032345-e2019JD032345

AJ Charlton-Perez, B Ayarzagüena, S Watanabe, EM Volodin, P Hitchcock, IR Simpson, LM Polvani, N Butchart, AH Butler, EP Gerber, P Lin, B Hassler, L Gray, S Osprey, E Manzini, R Mizuta, C Orbe, F Lott, D Saint-Martin, M Sigmond, M Taguchi

Go-around detection using crowd-sourced ADS-B position data

Aerospace 7 (2020)

SR Proud

© 2020 by the author. The decision of a flight crew to undertake a go-around, aborting a landing attempt, is primarily to ensure the safe conduct of a flight. Although go-arounds are rare, they do cause air traffic disruption, especially in busy airspace, due to the need to accommodate an aircraft in an unusual position, and a go-around can also result in knock-on delays due to the time taken for the aircraft to re-position, fit into the landing sequence and execute a successful landing. Therefore, it is important to understand and alleviate the factors that can result in a go-around. In this paper, I present a new method for automatically detecting go-around events in aircraft position data, such as that sent via the ADS-B system, and apply the method to one year of approach data for Chhatrapati Shivaji Maharaj International Airport (VABB) in Mumbai, India. I show that the method is significantly more accurate than other methods, detecting go-arounds with very few false positives or negatives. Finally, I use the new method to reveal that while there is no one cause for go-arounds at this airport, the majority can be attributed to weather and/or an unstable approach. I also show that one runway (14/32) has a significantly higher proportion of go-arounds than the other (09/27).

QBO changes in CMIP6 climate projections

Geophysical Research Letters American Geophysical Union (AGU) (2020)

N Butchart, Y Kawatani, JA Anstey, SM Osprey, JH Richter, T Wu

The physics of numerical analysis: a climate modelling case study.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences 378 (2020) 20190058-

TN Palmer

The case is made for a much closer synergy between climate science, numerical analysis and computer science. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'.

Up to two billion times acceleration of scientific simulations with deep neural architecture search

CoRR abs/2001.08055 (2020)

MF Kasim, D Watson-Parris, L Deaconu, S Oliver, S Khatiwala, P Hatfield, DH Froula, G Gregori, M Jarvis, J Topp-Mugglestone, J Korenaga, E Viezzer, SM Vinko

Computer simulations are invaluable tools for scientific discovery. However, accurate simulations are often slow to execute, which limits their applicability to extensive parameter exploration, large-scale data analysis, and uncertainty quantification. A promising route to accelerate simulations by building fast emulators with machine learning requires large training datasets, which can be prohibitively expensive to obtain with slow simulations. Here we present a method based on neural architecture search to build accurate emulators even with a limited number of training data. The method successfully accelerates simulations by up to 2 billion times in 10 scientific cases including astrophysics, climate science, biogeochemistry, high energy density physics, fusion energy, and seismology, using the same super-architecture, algorithm, and hyperparameters. Our approach also inherently provides emulator uncertainty estimation, adding further confidence in their use. We anticipate this work will accelerate research involving expensive simulations, allow more extensive parameters exploration, and enable new, previously unfeasible computational discovery.

A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing

Atmospheric Measurement Techniques European Geosciences Union 13 (2020) 373–404-

A Povey, A Lipponen, T Mielonen, Y Govaerts, F Patadia, ML Witek, AM Sayer, T Popp, M Luffarelli, P Kolmonen, K Stebel

Recent years have seen the increasing inclusion of per-retrieval prognostic (predictive) uncertainty estimates within satellite aerosol optical depth (AOD) data sets, providing users with quantitative tools to assist in the optimal use of these data. Prognostic estimates contrast with diagnostic (i.e. relative to some external truth) ones, which are typically obtained using sensitivity and/or validation analyses. Up to now, however, the quality of these uncertainty estimates has not been routinely assessed. This study presents a review of existing prognostic and diagnostic approaches for quantifying uncertainty in satellite AOD retrievals, and it presents a general framework to evaluate them based on the expected statistical properties of ensembles of estimated uncertainties and actual retrieval errors. It is hoped that this framework will be adopted as a complement to existing AOD validation exercises; it is not restricted to AOD and can in principle be applied to other quantities for which a reference validation data set is available. This framework is then applied to assess the uncertainties provided by several satellite data sets (seven over land, five over water), which draw on methods from the empirical to sensitivity analyses to formal error propagation, at 12 Aerosol Robotic Network (AERONET) sites. The AERONET sites are divided into those for which it is expected that the techniques will perform well and those for which some complexity about the site may provide a more severe test. Overall, all techniques show some skill in that larger estimated uncertainties are generally associated with larger observed errors, although they are sometimes poorly calibrated (i.e. too small or too large in magnitude). No technique uniformly performs best. For powerful formal uncertainty propagation approaches such as optimal estimation, the results illustrate some of the difficulties in appropriate population of the covariance matrices required by the technique. When the data sets are confronted by a situation strongly counter to the retrieval forward model (e.g. potentially mixed land–water surfaces or aerosol optical properties outside the family of assumptions), some algorithms fail to provide a retrieval, while others do but with a quantitatively unreliable uncertainty estimate. The discussion suggests paths forward for the refinement of these techniques.

On the Role of Rossby Wave Breaking in the Quasi-Biennial Modulation of the Stratospheric Polar Vortex during Boreal Winter

Quarterly Journal of the Royal Meteorological Society Wiley (2020)

H Lu, SM Osprey, MH Hitchman, JA Anstey, LJ Gray

Modelling binary alloy solidification with adaptive mesh refinement

Journal of Computational Physics: X 5 (2020)

JRG Parkinson, DF Martin, AJ Wells, RF Katz

© 2019 The solidification of a binary alloy results in the formation of a porous mushy layer, within which spontaneous localisation of fluid flow can lead to the emergence of features over a range of spatial scales. We describe a finite volume method for simulating binary alloy solidification in two dimensions with local mesh refinement in space and time. The coupled heat, solute, and mass transport is described using an enthalpy method with flow described by a Darcy-Brinkman equation for flow across porous and liquid regions. The resulting equations are solved on a hierarchy of block-structured adaptive grids. A projection method is used to compute the fluid velocity, whilst the viscous and nonlinear diffusive terms are calculated using a semi-implicit scheme. A series of synchronization steps ensure that the scheme is flux-conservative and correct for errors that arise at the boundaries between different levels of refinement. We also develop a corresponding method using Darcy's law for flow in a porous medium/narrow Hele-Shaw cell. We demonstrate the accuracy and efficiency of our method using established benchmarks for solidification without flow and convection in a fixed porous medium, along with convergence tests for the fully coupled code. Finally, we demonstrate the ability of our method to simulate transient mushy layer growth with narrow liquid channels which evolve over time.

Sensitivity of deep ocean mixing to local internal tide breaking and mixing efficiency

Geophysical Research Letters Wiley (2019)

L Cimoli, CP Caulfield, HL Johnson, DP Marshall, A Mashayek, AC Naveira Garabato, C Vic

The impact of a stochastic parameterization scheme on climate sensitivity in EC‐Earth

Journal of Geophysical Research: Atmospheres American Geophysical Union (2019)

K Strommen, PAG Watson, TN Palmer

Stochastic schemes, designed to represent unresolved sub-grid scale variability, are frequently used in short and medium-range weather forecasts, where they are found to improve several aspects of the model. In recent years, the impact of stochastic physics has also been found to be beneficial for the model's long term climate. In this paper, we demonstrate for the first time that the inclusion of a stochastic physics scheme can notably affect a model's projection of global warming, as well as its historical climatological global temperature. Specifically, we find that when including the 'stochastically perturbed parametrisation tendencies' scheme (SPPT) in the fully coupled climate model EC-Earth v3.1, the predicted level of global warming between 1850 and 2100 is reduced by 10% under an RCP8.5 forcing scenario. We link this reduction in climate sensitivity to a change in the cloud feedbacks with SPPT. In particular, the scheme appears to reduce the positive low cloud cover feedback, and increase the negative cloud optical feedback. A key role is played by a robust, rapid increase in cloud liquid water with SPPT, which we speculate is due to the scheme's non-linear interaction with condensation.

The scientific challenge of understanding and estimating climate change.

Proceedings of the National Academy of Sciences of the United States of America 116 (2019) 24390-24395

T Palmer, B Stevens

Given the slow unfolding of what may become catastrophic changes to Earth's climate, many are understandably distraught by failures of public policy to rise to the magnitude of the challenge. Few in the science community would think to question the scientific response to the unfolding changes. However, is the science community continuing to do its part to the best of its ability? In the domains where we can have the greatest influence, is the scientific community articulating a vision commensurate with the challenges posed by climate change? We think not.

The Impact of a Stochastic Parameterization Scheme on Climate Sensitivity in EC-Earth


K Strommen, PAG Watson, TN Palmer