Predictability of weather and climate

Abstract:

Posit numbers, a recently proposed alternative to floating-point numbers, claim to have smaller arithmetic rounding errors in many applications. By studying weather and climate models of low and medium complexity (the Lorenz system and a shallow water model) we present benefits of posits compared to floats at 16 bit. As a standardised posit processor does not exist yet, we emulate posit arithmetic on a conventional CPU. Using a shallow water model, forecasts based on 16-bit posits with 1 or 2 exponent bits are clearly more accurate than half precision floats. We therefore propose 16 bit with 2 exponent bits as a standard posit format, as its wide dynamic range of 32 orders of magnitude provides a great potential for many weather and climate models. Although the focus is on geophysical fluid simulations, the results are also meaningful and promising for reduced precision posit arithmetic in the wider field of computational fluid dynamics.

Abstract:

Abstract Storm Eunice was a severe windstorm that impacted Central Europe in February 2022. The meteorology and synoptic dynamics of Eunice have been studied in depth in several studies examining features of the storm such as its sting jet. The contribution of climate change to the storm dynamics and severity was examined in previous work, which found that in counterfactual weather forecasts - given an identical initial synoptic setup - climate change had measurably increased the severity of the storm. Here we move beyond meteorological attribution and quantify the role of climate change in the insured losses incurred during Eunice in, to the best of our knowledge, the first impact attribution of its kind for a European windstorm event. We combine the same counterfactual weather forecasts with three loss models, including two state-of-the-art commercial models, finding that the increases in meteorological severity do translate through to significant increases in estimated loss. We estimate a conditional increase in insured loss of nearly €2 bn between pre-industrial and present-day climates. Of particular note is the existence of several members within the forecast ensembles whose losses are far greater than what unfolded in reality. This includes one realisation, simulated in a warmer “future” climate, in which the estimated loss could reach over 10x the realised loss during Eunice. The plausible existence of such a catastrophic loss is of considerable relevance to a wide variety of stakeholders across adaptation planning and the financial sector. We suggest that our results practically demonstrate not only the utility of counterfactual weather forecasts in quantifying impacts attributable to climate change, but also the value of academic - private partnerships in which the two sectors are able to bring different areas of expertise.

Abstract:

Abstract. The teleconnections of the Quasi-Biennial Oscillation are revisited using ∼65 000 years of model output contributed by four modeling centers to the Large Ensemble Single Forcing Model Intercomparison Project (LESFMIP). The large ensemble size (at least 10, and in many cases 50) allows isolation of weak signals that are usually hidden by internal variability, as well as better quantification of the role of internal variability in possible model–observation discrepancies in the magnitude of the signals. All four models simulate a Holton–Tan effect, and two of the models also simulate a subtropical downward arching wind horseshoe teleconnection that is most prominent in the Pacific sector. The magnitudes of these teleconnections are statistically indistinguishable from those observed in two of the models but not in the other two; this is a notable improvement from previous work that analyzed small ensembles. These large-scale teleconnections lead to surface temperature and precipitation anomalies over the mid-latitude continents, including an impact on western North America surface temperature which appears to have not been noted before. Furthermore, all models show impacts of the QBO on tropical surface temperature and precipitation, however the nature of these responses differs across the models due, in part, to qualitatively different interactions with El Niño. Remarkably, one of the models simulates a connection between the QBO and the Madden Julian Oscillation that mimics observations, although it remains too weak. Finally, the LESFMIP simulations allow an exploration of external forcings impacting the magnitude of teleconnections. Among these experiments, greenhouse gas forcing is seen to significantly strengthen the subtropical wind horseshoe of the QBO.