Predictability of weather and climate

Abstract:

Abstract The Earth’s middle atmosphere spans the deep region from the upper troposphere/lower stratosphere at around 10 km altitude to the mesosphere/lower thermosphere at around 100 km altitude. It is being increasingly recognized for its role in driving extreme surface weather and regional climate change. Climate models predict large ongoing and future changes in the middle atmosphere composition and circulation. However, the observations needed to detect, attribute and understand these changes and their impacts, to test predictions, and thereby to improve our models, are lacking. Here we show the capacity of infrared limb-imaging tomography to provide the needed observations. This evaluation is based on studies performed within a recent satellite mission concept – the Changing-Atmosphere Infrared Tomography Explorer, CAIRT. Observing thermal infrared emissions simultaneously from the middle troposphere at about 4 km up to the lower thermosphere at about 115 km altitude this technique provides observations of temperature and an extensive range of trace gases with unprecedented spatial resolution of about 50 by 50 km horizontally and about 1 km vertically. We show how these observations would (a) help to quantify the changing atmospheric circulation, (b) allow characterization and quantification of the gravity waves that are critical in driving this circulation, (c) reveal how variability in solar radiation and energetic particles propagate downward to affect regional climate at the surface, (d) detect how volcanic eruptions and wildfires impact the middle atmosphere and climate, and (e) resolve how stratosphere-troposphere exchange affects ozone and water vapor in the crucial and climate-relevant tropopause region.

Abstract:

Sea ice ensemble forecasts can be highly underdispersive, meaning that the ensemble spread is notably lower than the average forecast error. One common strategy to address underdispersion is to add stochastic perturbations to the forecasts. We detail the implementation of a stochastically perturbed parameterisation (SPP) scheme for SI³, the sea ice component used by the Integrated Forecast System (IFS), the forecast model used and developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). We then evaluate its impact on seasonal forecasts of Northern Hemisphere summer and winter. The inclusion of SPP is found to enhance ensemble spread for sea ice concentration (SIC) and sea ice thickness (SIT) forecasts by around 10 % relative to a forecast with no SPP, which results in a better calibrated probabilistic forecast. Some small but robust changes to the mean state are also found, including a general decrease in the mean SIC and a redistribution of the winter ice from the central Arctic to the ice edge. These changes reduce or increase the mean bias depending on the region. Changes to the mean and spread of the sea ice result in changes to the mean and spread of air temperature up to at least 850 hPa, altering the mean air temperature biases of the model. An apparent consequence of this is a significant increase in the anomaly correlation coefficients of 500 hPa geopotential height (Z500) over the Euro-Atlantic domain in winter, which partially projects onto the North Atlantic Oscillation. We conclude that sea ice stochastic perturbations can be a valuable contribution to increased reliability of seasonal forecasts of the sea ice itself and can impact seasonal forecasts of the atmosphere at high and mid latitudes.

Abstract:

Southern Hemisphere (SH) circulation and surface climate changes are emerging in recent decades. For example, in most seasons, the SH Hadley cell edge and the eddy‐driven jet stream have shifted polewards, and the Southern Annular Mode (SAM) has trended towards its positive phase. However, attributing these changes to specific external forcings, such as greenhouse gas (GHG) increases or stratospheric ozone depletion, has been hindered by small ensemble sizes and lack of coherent forcing methodology across multiple models. In this study, we analyzed simulations from 10 models within the Large Ensemble Single Forcing Model Intercomparison Project (LESFMIP) to isolate the long‐term (1850–2014) SH climate response to individual forcings (GHGs, aerosols, and ozone). We found that long‐term SH climate trends are dominated by GHGs across all seasons. Over this time period, stratospheric ozone depletion exerts an influence comparable to GHGs but is restricted to austral spring and summer. Although anthropogenic aerosols show weaker effects on climate trends that oppose those induced by GHG forcing and ozone depletion, they have a noticeable impact. Notably, ozone recovery following the Montreal Protocol is currently weakening or reversing spring and summer trends in key circulation metrics. Finally, we quantify the degree to which the observed sea surface cooling of the Southern Ocean and Antarctic sea ice increase from 1980 to 2014 fall outside the models' ensemble spread. Our results highlight the need to better understand the roles of different forcings, model differences, and discrepancies between models and observations to constrain projections of future Southern Hemisphere climate change. Atmospheric and oceanic circulation changes are emerging in the Southern Hemisphere (SH). To better understand the drivers of these changes, in this study we use a new multi‐model large ensemble data set to look at how specific factors (forcings) have individually influenced the long‐term SH climate trends from 1850 to 2014. We find that greenhouse gases are the main driver of long‐term changes in the SH since the preindustrial era. The impact of stratospheric ozone depletion is comparable to greenhouse gases, but only during austral spring and summer. On the other hand, anthropogenic aerosols partially counteract greenhouse gas effects on the circulation. The models are able to simulate the recent weakening or even reversal of some of the trends in key atmospheric circulation metrics due to the recovery of the ozone layer following the enactment of the Montreal Protocol and its amendments. However, the disagreement between model simulations and real‐world observations for recent trends in Southern Ocean sea surface temperatures and Antarctic sea ice highlights the need for more research to reliably project future climate change in this crucial region. Greenhouse gases drive Southern Hemisphere circulation changes year‐round, while ozone is a key driver during austral spring and summer Although weaker, anthropogenic aerosol effects are substantial and should be accounted for in attribution studies Persistent model‐observational discrepancies exist for recent trends in Southern Ocean sea surface temperature and sea ice extent Greenhouse gases drive Southern Hemisphere circulation changes year‐round, while ozone is a key driver during austral spring and summer Although weaker, anthropogenic aerosol effects are substantial and should be accounted for in attribution studies Persistent model‐observational discrepancies exist for recent trends in Southern Ocean sea surface temperature and sea ice extent

Abstract:

Early winter (October-December; OND) precipitation is critical for Pakistan’s water resources, agriculture and socio-economic stability, yet the large-scale drivers and physical mechanism driving its interannual variability remains poorly understood. Using in-situ observations and ERA5 reanalysis for 1981–2023, we have investigated the dominant mode of early winter precipitation variability over Pakistan and its associated atmospheric teleconnections. The leading Empirical Orthogonal Function (EOF1) explains approximately 60% of the total variance, with the maximum interannual variability centered over northern Pakistan, including the Upper Indus Basin. A Pakistan Precipitation Index (PRI) is developed over this core precipitation region. Regression analysis demonstrates that positive PRI anomalies are associated with anomalous upper-level divergence over central-eastern equatorial Pacific and western Indian Ocean, compensated by convergence over Maritime Continent. A quasi-stationary Rossby wave train excites from tropical pacific and propagates eastward along the subtropical westerly jet into Eurasia producing an anomalous upper-level trough over southwest Asia including Pakistan. This favors enhanced ascent and cyclonic circulation anomalies along with moisture transport from western Indian Ocean and Bay of Bengal, resulting in above normal precipitation over Pakistan. The PRI is significantly correlated (r = 0.5) with the warm central-eastern equatorial Sea Surface Temperature (SST) anomalies (i.e., Niño3.4 index), indicating the El Niño-Southern Oscillation (ENSO) as a dominant mode of early winter precipitation variability. During El Niño, the warm SST anomalies in central-eastern equatorial Pacific enhance upper-level divergence, excite stationary Rossby wave and shift the subtropical westerly jet southward. At same time, the enhanced moisture transport and wave activity from the western Indian Ocean, favors convergence over Pakistan. In contrast, La Niña produces the opposite response. This shows ENSO along with the Indian Ocean strongly influences Pakistan precipitation variability in early winter. These findings provide valuable basis for seasonal prediction and support water resource management, agriculture and climate resilient planning across Pakistan.