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:

AbstractWe investigate the response of winter precipitation and storm activity in the North Atlantic–European–Mediterranean region (NAEM) to the Indian Ocean Dipole (IOD) from 1979 to 2024. We observe a positive NAO‐like pattern over NAEM, which appears in December and shifts eastward through February. IOD further modulates precipitation by inducing changes in total precipitation, event frequency, and wet spell duration. The strength of the observed teleconnection is primarily significant in December. Additionally, we observe a reduction in cyclone activity in December over the East Atlantic and Western Mediterranean. These changes in cyclone track density are primarily driven by variations in the Eady Growth Rate, which are linked to enhanced vertical wind shear associated with a strengthened meridional temperature gradient over the NAEM. The results underscore a significant remote impact of the IOD on early winter hydro‐climate variability over the NAEM region, offering a potential value for improving sub‐seasonal to seasonal prediction.

Abstract:

While it is widely believed that the intense rainfall in summer 2022 over Pakistan was substantially exacerbated by anthropogenic climate change1, 2, climate models struggled to confirm this3, 4. Using a high-resolution operational seasonal forecasting system that successfully predicted the extreme wet conditions, we perform counterfactual experiments simulating pre-industrial and future conditions. Both experiments also exhibit strong anomalous rainfall, indicating a limited role of CO2-induced forcing. We attribute 10% of the total rainfall to historical increases in CO2 and ocean temperature. However, further increases in the future suggest a weak mean precipitation reduction but with increased variability. By decomposing rainfall and large-scale circulation into CO2 and SST-related signals, we illustrate a tendency for these signals to compensate each other in future scenarios. This suggests that historical CO2 impacts may not reliably predict future responses. Accurately capturing local dynamics is therefore essential for regional climate adaptation planning and for informing loss and damage discussions.