Predictability of weather and climate

Abstract:

The impact of the quasi-biennial oscillation (QBO) on tropical convection and precipitation is investigated through nudging experiments using the UK Met Office Hadley Center Unified Model. The model control simulations show robust links between the internally generated QBO and tropical precipitation and circulation. The model zonal wind in the tropical stratosphere was nudged above 90 hPa in atmosphere-only and coupled ocean-atmosphere configurations. The convection and precipitation in the atmosphere-only simulations do not differ between the experiments with and without nudging, which may indicate that SST-convection coupling is needed for any QBO influence on the tropical lower troposphere and surface. In the coupled experiments, the precipitation and sea-surface temperature relationships with the QBO phase disappear when nudging is applied. Imposing a realistic QBO-driven static stability anomaly in the upper-troposphere lower-stratosphere is not sufficient to simulate tropical surface impacts. The nudging reduced the influence of the lower troposphere on the upper branch of the Walker circulation, irrespective of the QBO, indicating that the upper tropospheric zonal circulation has been decoupled from the surface by the nudging. These results suggest that grid-point nudging mutes relevant feedback processes occurring at the tropopause level, including high cloud radiative effects and wave mean flow interactions, which may play a key role in stratospheric-tropospheric coupling.

Abstract:

Land cover changes have been proposed to play a significant role, alongside emission reductions, in achieving the temperature goals agreed upon under the Paris Agreement. Such changes carry both global implications, pertaining to the biogeochemical effects of land cover change and thus the global carbon budget, and regional or local implications, pertaining to the biogeophysical effects arising within the immediate area of land cover change. Biogeophysical effects of land cover change are of high relevance to national policy and decision makers, and accounting for them is essential for effective deployment of land cover practices that optimise between global and regional impacts. To this end, Earth system model (ESM) outputs that isolate the biogeophysical responses of climate to land cover changes are key in informing impact assessments and supporting scenario development exercises. However, generating multiple such ESM outputs in a manner that allows comprehensive exploration of all plausible land cover scenarios is computationally untenable. This study proposes a framework to explore in an agile manner the local biogeophysical responses of climate under customised tree cover change scenarios by means of a computationally inexpensive emulator, the Tree cover change clIMate Biophysical responses EmulatoR (TIMBER) v0.1. The emulator is novel in that it solely represents the biogeophysical responses of climate to tree cover changes, and it can be used as either a standalone device or as a supplement to existing climate model emulators that represent the climate responses from greenhouse gas (GHG) or global mean temperature (GMT) forcings. We start off by modelling local minimum, mean, and maximum surface temperature responses to tree cover changes by means of a month- and Earth system model (ESM)-specific generalised additive model (GAM) trained over the whole globe; 2 m air temperature responses are then diagnosed from the modelled minimum and maximum surface temperature responses using observationally derived relationships. Such a two-step procedure accounts for the different physical representations of surface temperature responses to tree cover changes under different ESMs whilst respecting a definition of 2 m air temperature that is more consistent across ESMs and with observational datasets. In exploring new tree cover change scenarios, we employ a parametric bootstrap sampling method to generate multiple possible temperature responses, such that the parametric uncertainty within the GAM is also quantified. The output of the final emulator is demonstrated for the Shared Socioeconomic Pathway (SSP) 1-2.6 and 3-7.0 scenarios. Relevant temperature responses are identified as those displaying a clear signal in relation to their surrounding parametric uncertainty, calculated as the signal-to-noise ratio between the sample set mean and sample set variability. The emulator framework developed in this study thus provides a first step towards bridging the information gap surrounding biogeophysical implications of land cover changes, allowing for smarter land use decision making.