The Changing-Atmosphere Infra-Red Tomography Explorer (CAIRT) Earth Explorer 11 candidate mission

(2024)

Authors:

Bernd Funke, Martyn Chipperfield, Quentin Errera, Felix Friedl-Vallon, Sophie Godin-Beekmann, Michael Hoepfner, Alex Hoffmann, Alizee Malavart, Scott Osprey, Inna Polichtchouk, Peter Preusse, Piera Raspollini, Björn-Martin Sinnhuber, Pekka Verronen, Kaley Walker

Abstract:

The Changing-Atmosphere Infra-Red Tomography Explorer (CAIRT) is currently in Phase A as one of two final candidates for ESA’s Earth Explorer 11. As a Fourier transform infrared limb imager, CAIRT will observe simultaneously from the middle troposphere to the lower thermosphere at high spectral resolution and with unprecedented horizontal and vertical resolution. With this, CAIRT will provide critical information on (a) atmospheric gravity waves, circulation and mixing, (b) coupling with the upper atmosphere, solar variability and space weather and, (c) aerosols and pollutants in the upper troposphere and  lower stratosphere. In this presentation we will give an overview of CAIRT’s science goals and the expected mission performance, based on latest results from feasibility studies performed during Phase 0. 

Improving and Assessing Organized Convection Parameterization in the Unified Model

(2024)

Authors:

Zhixiao Zhang, Hannah Christensen, Mark Muetzelfeldt, Tim Woollings, Bob Plant, Alison Stirling, Michael Whitall, Mitchell Moncrieff, Chih-Chieh Chen

Abstract:

Improving weather and climate prediction cannot avoid accurately representing organized convection, as its convective and stratiform components distinctly reshape large-scale circulations via redistributing momentum and heat. For latent heating, the stratiform heating in organized convection shifts to higher altitudes compared to convective regions, presenting a significant challenge for representation in models across scales. The Multiscale Coherent Structural Parameterization (MCSP), introduced by Moncrieff et al. (2017), offers a promising solution by generating the top-heavy profile from convective heating in slantwise layer overturning scenarios. As part of the MCS: PRIME project, the PRIME-MCSP implementation by Zhang et al. (submitted, 2024) couples MCSP with the CoMorph-A convection scheme in the UK Met Office Unified Model with the following improvements: 1) CoMorph permits unstable air to rise from any height, diverging from the conventional CAPE trigger for deep convection, thereby enhancing continuity and facilitating storm tracking. 2) We activate MCSP selectively for deep mixed-phase clouds, recognizing the limited ability of shallow clouds to produce a stratiform component. 3) We configure the global model runs to include both a fixed convective-stratiform heating fraction and a fraction proportional to cloud top temperature. MCS tracks in ensembles of weather runs show that PRIME-MCSP suppresses cloud deepening and reduces precipitation areas by dampening low-level updrafts. 20-year climate simulations show that PRIME-MCSP improves the precipitation seasonal cycle over the Indian Ocean, while increasing the warm-season wet bias over the Western Pacific. Additionally, PRIME-MCSP intensifies the Madden Julian Oscillation (MJO). The model run using a variable convective-stratiform fraction more accurately represents the MJO frequency and aligns better with reanalysis. Future plans focus on the stochastic representation of stratiform effects, steered by insights from data assimilation increments.

Response of winter climate and extreme weather to projected Arctic sea-ice loss in very large-ensemble climate model simulations 

(2024)

Authors:

Kunhui Ye, Tim Woollings, Sarah Sparrow, Peter Watson, James Screen

Abstract:

Arctic sea-ice loss and amplified Arctic warming have been one striking signature of climate change, which have important impacts on climate variability in the Arctic and mid-low latitudes. Climate modeling including the Polar Amplification Model Intercomparison Project (PAMIP) has been a powerful tool for investigating the effects of Arctic sea-ice loss in a changing climate. However, existing climate model simulations including individual climate models from the multi-model/ensemble PAMIP project have relatively small ensemble sizes that may not allow a robust separation of forced response, particularly the response of extremes, to Arctic sea-ice loss from internal variability. Therefore, our confidence in the response to projected Arctic sea-ice loss in climate change is reduced. This has led to two unanswered important questions: (1) what ensemble sizes are needed for robust detection of extremes, as well as seasonal-mean responses to projected Arctic sea-ice loss? and (2) is the response dependent on resolution? To address the challenge, we have performed very large (~2000 members) initial-condition ensemble climate simulations, using both low (~90 km) and high (~60 km) resolutions, with prescribed boundary conditions (i.e., sea surface temperature and sea-ice concentration) taken from the PAMIP project, to advance understanding of mean climate and extreme weather responses to projected Arctic sea-ice loss under 2°C global warming above preindustrial levels. We have run these simulations with the Met Office Hadley Centre global atmospheric model Version 4 on the University of Oxford’s innovative distributed computing project (Climateprediction.net). These simulations better sample internal atmospheric variability and extremes for each model compared to those from the PAMIP, and also allow studying the resolution-dependence of the response to projected Arctic sea-ice using a larger ensemble. Analysis of these simulations suggests that the mean climate response is mostly consistent with that from the PAMIP multi-model ensemble, including tropospheric warming, reduced midlatitude westerlies and storm track activity, an equatorward shift of the eddy-driven jet and increased mid-to-high latitude blocking. The response of temperature and precipitation extremes largely follows the seasonal-mean response. However, East Asia is a notable exception in showing an increase in severe cold temperature extremes in response to the projected Arctic sea-ice loss. Two resolutions of the same model exhibit significant differences in the stratospheric circulation. This does suggest resolution-dependence of the response but we consider that the difference in the stratospheric response weakly modulates the tropospheric response. We highlight that our very large-ensemble simulations have allowed rigorous sub-sampling to address the challenge of obtaining a robust forced response to projected Arctic sea-ice loss. The sub-sampling confirms that large ensembles (e.g. >=400) are needed to robustly estimate the seasonal-mean large-scale circulation response, and very large ensembles (e.g., >=1000) for regional climate and extremes. The reduction in uncertainty of the response with ensemble size is very well predicted by standard error analysis, guiding the design of future large ensembles. 

Global Chemical Transport on Hot Jupiters: Insights from the 2D VULCAN Photochemical Model

The Astrophysical Journal American Astronomical Society 963:1 (2024) 41

Authors:

Shang-Min Tsai, Vivien Parmentier, João M Mendonça, Xianyu Tan, Russell Deitrick, Mark Hammond, Arjun B Savel, Xi Zhang, Raymond T Pierrehumbert, Edward W Schwieterman

Aeolus wind lidar observations of the 2019/2020 quasi-biennial oscillation disruption with comparison to radiosondes and reanalysis

Atmospheric Chemistry and Physics European Geosciences Union 24:4 (2024) 2465-2490

Authors:

Timothy P Banyard, Corwin J Wright, Scott M Osprey, Neil P Hindley, Gemma Halloran, Lawrence Coy, Paul A Newman, Neal Butchart, Martina Bramberger, M Joan Alexander

Abstract:

The quasi-biennial oscillation (QBO) was unexpectedly disrupted for only the second time in the historical record during the 2019/2020 boreal winter. As the dominant mode of atmospheric variability in the tropical stratosphere and a significant source of seasonal predictability globally, understanding the drivers behind this unusual behaviour is very important. Here, novel data from Aeolus, the first Doppler wind lidar (DWL) in space, are used to observe the 2019/2020 QBO disruption. Aeolus is the first satellite able to observe winds at high resolution on a global scale, and it is therefore a uniquely capable platform for studying the evolution of the disruption and the broader circulation changes triggered by it. This study therefore contains the first direct wind observations of the QBO from space, and it exploits measurements from a special Aeolus scanning mode, implemented to observe this disruption as it happened. Aeolus observes easterly winds of up to 20 m s−1 in the core of the disruption jet during July 2020. By co-locating with radiosonde measurements from Singapore and the ERA5 reanalysis, comparisons of the observed wind structures in the tropical stratosphere are produced, showing differences in equatorial wave activity during the disruption period. Local zonal wind biases are found in both Aeolus and ERA5 around the tropopause, and the average Aeolus-ERA5 Rayleigh horizontal line-of-sight random error is found to be 7.58 m s−1. The onset of the QBO disruption easterly jet occurs 5 d earlier in Aeolus observations compared with the reanalysis. This discrepancy is linked to Kelvin wave variances that are 3 to 6 m2 s−2 higher in Aeolus compared with ERA5, centred on regions of maximum vertical wind shear in the tropical tropopause layer that are up to twice as sharp. The enhanced lower-stratospheric westerly winds which are known to help disrupt the QBO, perhaps with increasing frequency as the climate changes, are also stronger in Aeolus observations, with important implications for the future predictability of such disruptions. An investigation into differences in the equivalent depth of the most dominant Kelvin waves suggests that slower, shorter-vertical-wavelength waves break more readily in Aeolus observations compared with the reanalysis. This analysis therefore highlights how Aeolus and future DWL satellites can deepen our understanding of the QBO, its disruptions and the tropical upper-troposphere lower-stratosphere region more generally.