Dr Scott Osprey FRMetS

Abstract:

The World Climate Research Programme (WCRP) envisions a world “that uses sound, relevant, and timely climate science to ensure a more resilient present and sustainable future for humankind.” This bold vision requires the climate science community to provide actionable scientific information that meets the evolving needs of societies all over the world. To realize its vision, WCRP has created five Lighthouse Activities to generate international commitment and support to tackle some of the most pressing challenges in climate science today. The overarching goal of the Lighthouse Activity on Explaining and Predicting Earth System Change is to develop an integrated capability to understand, attribute, and predict annual to decadal changes in the Earth system, including capabilities for early warning of potential high impact changes and events. This article provides an overview of both the scientific challenges that must be addressed, and the research and other activities required to achieve this goal. The work is organized in three thematic areas: (i) monitoring and modeling Earth system change; (ii) integrated attribution, prediction, and projection; and (iii) assessment of current and future hazards. Also discussed are the benefits that the new capability will deliver. These include improved capabilities for early warning of impactful changes in the Earth system, more reliable assessments of meteorological hazard risks, and quantitative attribution statements to support the Global Annual to Decadal Climate Update and State of the Climate reports issued by the World Meteorological Organization.

Abstract:

Multi-annual to decadal changes in climate are accompanied by changes in extreme events that cause major impacts on society and severe challenges for adaptation. Early warnings of such changes are now potentially possible through operational decadal predictions. However, improved understanding of the causes of regional changes in climate on these timescales is needed both to attribute recent events and to gain further confidence in forecasts. Here we document the Large Ensemble Single Forcing Model Intercomparison Project that will address this need through coordinated model experiments enabling the impacts of different external drivers to be isolated. We highlight the need to account for model errors and propose an attribution approach that exploits differences between models to diagnose the real-world situation and overcomes potential errors in atmospheric circulation changes. The experiments and analysis proposed here will provide substantial improvements to our ability to understand near-term changes in climate and will support the World Climate Research Program Lighthouse Activity on Explaining and Predicting Earth System Change.

Abstract:

The influence of the quasi-biennial oscillation (QBO) on tropical climate is demonstrated using 500-year pre-industrial control simulations from the Met Office Hadley Centre model. Robust precipitation responses to the phase of the QBO are diagnosed in the model, which show zonally asymmetric patterns that resemble the El Niño–Southern Oscillation (ENSO) impacts. These patterns are found because the frequency of ENSO events for each QBO phase is significantly different in these simulations, with more El Niño events found under the westerly phase of the QBO (QBOW) and more La Niña events for the easterly phase (QBOE). The QBO–ENSO relationship is non-stationary and subject to decadal variability in both models and observations. In addition, regression analysis shows that there is a QBO signal in precipitation that is independent of ENSO. No evidence is found to suggest that these QBO–ENSO relationships are caused by ENSO modulating the QBO in the simulations. A relationship between the QBO and a dipole of precipitation in the Indian Ocean is also found in models and observations in boreal fall, characterised by a wetter western Indian Ocean and drier conditions in the eastern part for QBOW and the opposite under QBOE conditions. The Walker circulation is significantly weaker during QBOW compared to QBOE, which could explain the observed and simulated zonally asymmetric precipitation responses at equatorial latitudes, as well as the more frequent El Niño events during QBOW. Further work, including targeted model experiments, is required to better understand the mechanisms causing these relationships between the QBO and tropical convection.

Abstract:

Observations show that the seasonal cycle of precipitation in parts of southern Mexico and Central America exhibits a bimodal signal, known as the Midsummer drought (MSD), but there is no consensus on which processes are most relevant for the two-peak structure of the rainy season. This paper evaluates three hypotheses that could explain the MSD: the SST cloud-radiative feedback, the solar declination angle and the Caribbean Low-Level Jet (CLLJ) moisture transport hypotheses. Model experiments produced by the Met Office Hadley Centre (MOHC) for CMIP6 as well as ERA5 reanalysis data are used to critically assess the predictions of each hypothesis. The simulations capture the double peak signal of precipitation well and reasonably simulate the spatial and temporal variations of the MSD and other relevant climate features such as the CLLJ. Evidence from our analysis suggests that the Eastern Pacific SSTs do not increase in late summer in ERA5 data and only slightly increase in the simulations. More importantly, the Eastern Pacific SST variability in ERA5 and in the model experiments cannot explain the differences in the seasonality of precipitation. The net shortwave radiation at the surface shows a two-peak seasonal cycle; however, this behaviour appears to result from a strong anti-correlation of the incoming shortwave and convective activity due to cloud radiative-effects. There was no evidence found by this study of a causal link in which absorption of shortwave energy forces precipitation variations, as suggested by the solar declination angle hypothesis. The moisture convergence, CLLJ and the precipitable water vapor variations best explain the characteristics of the observed and simulated MSD, particularly for the onset of the MSD. The diagnosed variations of moisture convergence, which are synchronous with the timing of the MSD, point to a dynamic mechanism in which the low-level inflow from the Caribbean is more important for the MSD than other radiative mechanisms.

Abstract:

The processes occurring in the tropical tropopause layer (TTL) are of great importance for stratosphere–troposphere exchanges and the variability of the Earth's climate. Previous studies demonstrated the increasing ability of atmospheric general circulation models (AGCMs) in simulating the TTL, depending on factors such as the horizontal and vertical resolution, with the major role for physical parametrizations. In this work we assess the mean state and variability of the tropical upper troposphere and lower stratosphere simulated by 13 AGCMs of the Stratosphere–troposphere Processes And their Role in Climate Quasi-Biennial Oscillation initiative (QBOi) for the historical period. As these models internally generate quasi-biennial oscillations (QBOs) of the stratospheric zonal wind, we can analyse the simulated QBO influence on the TTL on interannual time-scales. We find that model biases in temperature near the tropopause are strongly related to water vapour concentrations in the lower stratosphere. A source of intermodel spread derives from stratospheric aerosols, as the responses to eruptions differ between those models prescribing volcanic aerosol forcing. The QBO influence on the thermal structure is generally realistic in the equatorial region, but the subtropical response is weak compared with the reanalysis. This is associated with a limited downward penetration of QBO winds, generally smaller QBO meridional widths, and weaker temperature anomalies, which disappear above the tropopause for most models. We discuss the QBO impacts on tropopause pressure and precipitation, characterized by large uncertainties due to the small signal in the observational records and sampling uncertainty. Realistic QBO connection with the troposphere in some models suggests that the underlying physical processes can be correctly simulated. Overall, we find that the QBOi models have limited ability to reproduce the observed modulation of the TTL processes, which is consistent with biases in the vertical and latitudinal extent of the simulated QBOs degrading this connection.