Prediction of the quasi鈥恇iennial oscillation with a multi鈥恗odel ensemble of QBO鈥恟esolving models
Quarterly Journal of the Royal Meteorological Society Wiley 148:744A (2020) 1519-1540
Abstract:
A multi鈥恗odel study is carried out to investigate the ability of models to predict the evolution of the quasi鈥恇iennial oscillation (QBO) up to 12鈥塵onths in advance. All models are initialised from common reanalysis data, and forecasts run for a common set of 30 start dates over 15鈥墆ears. All models have high skill in predicting the phase evolution of the QBO at 20鈥30鈥塰Pa, with slightly more variable results at higher and lower levels. Other aspects of the predicted QBO are of variable quality, and in some cases are consistently poor. QBO easterlies are too weak in all models at 20鈥50鈥塰Pa, while westerlies can be either too strong or too weak. This results in both a reduced amplitude of the QBO and a westerly bias in zonal鈥恗ean winds, notably at 30鈥塰Pa. At 70鈥塰Pa models tend to have reduced QBO amplitude and an easterly bias. Despite these failings, a multi鈥恗odel ensemble of bias鈥 and variance鈥恈orrected forecasts can be used to give accurate and reliable QBO forecasts up to at least a year ahead. Analysis of the zonal momentum budget during the first month of the forecast shows that large鈥恠cale forcing from Eliassen鈥揚alm flux divergence and vertical advection are handled fairly well by the models, although vertical advection terms tend to be weaker than reanalysis estimates. Total tendencies show common errors, suggesting common failings in gravity鈥恮ave drag treatments. Teleconnections from the QBO to Northern Hemisphere winter circulation are also examined, and do not appear to be realistic beyond the first month. Analysis of initialised forecasts is a powerful tool for diagnosing the accuracy of model processes driving the QBO.Number formats, error mitigation, and scope for 16鈥恇it arithmetics in weather and climate modeling analyzed with a shallow water model
Journal of Advances in Modeling Earth Systems American Geophysical Union 12:10 (2020) e2020MS002246
Abstract:
The need for high鈥恜recision calculations with 64鈥恇it or 32鈥恇it floating鈥恜oint arithmetic for weather and climate models is questioned. Lower鈥恜recision numbers can accelerate simulations and are increasingly 91探花ed by modern computing hardware. This paper investigates the potential of 16鈥恇it arithmetic when applied within a shallow water model that serves as a medium complexity weather or climate application. There are several 16鈥恇it number formats that can potentially be used (IEEE half precision, BFloat16, posits, integer, and fixed鈥恜oint). It is evident that a simple change to 16鈥恇it arithmetic will not be possible for complex weather and climate applications as it will degrade model results by intolerable rounding errors that cause a stalling of model dynamics or model instabilities. However, if the posit number format is used as an alternative to the standard floating鈥恜oint numbers, the model degradation can be significantly reduced. Furthermore, mitigation methods, such as rescaling, reordering, and mixed precision, are available to make model simulations resilient against a precision reduction. If mitigation methods are applied, 16鈥恇it floating鈥恜oint arithmetic can be used successfully within the shallow water model. The results show the potential of 16鈥恇it formats for at least parts of complex weather and climate models where rounding errors would be entirely masked by initial condition, model, or discretization error.Responses of Precipitation and Runoff to Climate Warming and Implications for Future Drought Changes in China
Earth S Future 8:10 (2020)
Abstract:
The Clausius-Clapeyron relationship holds that the atmospheric water vapor content enhances with warming temperatures, suggesting intensifications of precipitable water and also altering runoff generation. Drought conditions are determined by variations in water fluxes such as precipitation and runoff, which tightly connect with temperature scaling characteristics. However, whether and how water fluxes' scaling with temperatures may affect the evolution of droughts under climate change has not yet been systematically investigated. This study develops a cascade modeling chain consisting of the climate model ensemble, bias correction technique, and hydrological models to investigate the precipitation and runoff scaling relationships with warming temperatures under the current (1961鈥2005) and future periods (2011鈥2055 and 2056鈥2100), as well as their implications on future drought changes across 151 catchments in China. The results show that (1) precipitation (runoff) scaling relationships with temperatures are stable during different time periods; (2) return level analysis indicates drought risks are projected to become (1鈥10 times) more severe across central and southern catchments, where the precipitation (runoff) strengthens with rising temperatures up to a peak point and then decline in a hotter environment. The northeastern and western catchments, where a monotonic increasing scaling type dominated, are accompanied by drought mitigations for two future periods; (3) future changes in hydrological droughts relative to the baseline are (1鈥5 times) larger than those in meteorological droughts. These results imply that changes in future drought risks are highly dependent on the present precipitation (runoff)-temperature relationships, suggesting a meaningful implication of scaling types for future drought prediction.Tropical Indian Ocean Mediates ENSO Influence Over Central Southwest Asia During the Wet Season
Geophysical Research Letters American Geophysical Union (AGU) 47:18 (2020)
Tropospheric forcing of the 2019 Antarctic sudden stratospheric warming
Geophysical Research Letters American Geophysical Union 47:20 (2020) e2020GL089343