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Published By American Meteorological Society

1520-0442, 0894-8755

2022 ◽  
pp. 1-59
Author(s):  
Paul J. Kushner ◽  
Russell Blackport ◽  
Kelly E. McCusker ◽  
Thomas Oudar ◽  
Lantao Sun ◽  
...  

Abstract Analyzing a multi-model ensemble of coupled climate model simulations forced with Arctic sea-ice loss using a two-parameter pattern-scaling technique to remove the cross-coupling between low- and high-latitude responses, the sensitivity to high-latitude sea-ice loss is isolated and contrasted to the sensitivity to low-latitude warming. In spite of some differences in experimental design, the Northern Hemisphere near-surface atmospheric sensitivity to sea-ice loss is found to be robust across models in the cold season; however, a larger inter-model spread is found at the surface in boreal summer, and in the free tropospheric circulation. In contrast, the sensitivity to low-latitude warming is most robust in the free troposphere and in the warm season, with more inter-model spread in the surface ocean and surface heat flux over the Northern Hemisphere. The robust signals associated with sea-ice loss include upward turbulent and longwave heat fluxes where sea-ice is lost, warming and freshening of the Arctic ocean, warming of the eastern North Pacific relative to the western North Pacific with upward turbulent heat fluxes in the Kuroshio extension, and salinification of the shallow shelf seas of the Arctic Ocean alongside freshening in the subpolar North Atlantic. In contrast, the robust signals associated with low-latitude warming include intensified ocean warming and upward latent heat fluxes near the western boundary currents, freshening of the Pacific Ocean, salinification of the North Atlantic, and downward sensible and longwave fluxes over the ocean.


2022 ◽  
pp. 1-41

Abstract The interannual variation of springtime extreme precipitation (SEP) days in North China (NC) and their reliance on atmospheric circulation patterns are studied by using the continuous daily record of 396 rain gauges and the fifth generation of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis during 1979–2019. The SEP days are defined as the days when at least 10% of rain gauges in NC record daily precipitation no less than 10.5 mm. Results show that the number of SEP days shows large interannual variability but no significant trend in the study period. Using the objective classification method of the obliquely rotated principal analysis in T-mode, we classify the atmospheric circulation into five different patterns based on the geopotential height at 700 hPa. Three circulation patterns all have fronts and are associated with strong southerly wind, leading to 88% of SEP days in NC. The strong southerly wind may provide moisture and dynamic forcing for the frontal precipitation. The interannual variation of SEP days is related with the number of the three above-mentioned dominant circulation patterns. Further analysis shows that the West Pacific pattern could be one of the possible climate variability modes related to SEP days. This study reveals that the daily circulation pattern may be the linkage between SEP days and climate variability modes in NC.


2022 ◽  
pp. 1-59
Author(s):  
Ying Lu ◽  
Xianan Jiang ◽  
Philip J. Klotzbach ◽  
Liguang Wu ◽  
Jian Cao

Abstract A L2 regularized logistic regression model is developed in this study to predict weekly tropical cyclone (TC) genesis over the western North Pacific (WNP) and sub-regions of the WNP including the South China Sea (SCS), the western WNP (WWNP), and the eastern WNP (EWNP). The potential predictors for the TC genesis model include a time-varying TC genesis climatology, the Madden-Julian oscillation (MJO), the quasi-biweekly oscillation (QBWO), and ENSO. The relative importance of the predictors in a constructed L2 regression model is justified by a forward stepwise selection procedure for each region from a 0-week to a 7-week lead. Cross-validated hindcasts are then generated for the corresponding prediction schemes out to a 7-week lead. The TC genesis climatology generally improves the regional model skill, while the importance of intra-seasonal oscillations and ENSO are regionally dependent. Over the WNP, there is increased model skill over the time-varying climatology in predicting weekly TC genesis out to a 4-week lead by including the MJO and QBWO, while ENSO has a limited impact. On a regional scale, ENSO and then the MJO and QBWO respectively, are the two most important predictors over the EWNP and WWNP after the TC genesis climatology. The MJO is found to be the most important predictor over the SCS. The logistic regression model is shown to have comparable reliability and forecast skill scores to the ECMWF dynamical model on intra-seasonal time scales.


2022 ◽  
pp. 1-44

Abstract Atlantic Multidecadal Variability (AMV) impacts temperature, precipitation, and extreme events on both sides of the Atlantic basin. Previous studies with climate models have suggested that when external radiative forcing is held constant, the large-scale ocean and atmosphere circulation are associated with sea-surface temperature anomalies that have similar characteristics to the observed AMV. However, there is an active debate as to whether these internal fluctuations driven by coupled atmosphere-ocean variability remain influential to the AMV on multidecadal timescales in our modern, anthropogenically-forced climate. Here we provide evidence from multiple large ensembles of climate models, paleo reconstructions, and instrumental observations of a growing role for external forcing in the AMV. Prior to 1850, external forcing, primarily from volcanoes, explains about one third of AMV variance. Between 1850 and 1950, there is a transitional period, where external forcing explains half of AMV variance, but volcanic forcing only accounts for about 10% of that. After 1950, external forcing explains three quarters of AMV variance. That is, the role for external forcing in the AMV grows as the variations in external forcing grow, even if the forcing is from different sources. When forcing is relatively stable, as in earlier modeling studies, a higher percentage of AMV variations are internally generated.


2022 ◽  
pp. 1-49

Abstract In this study, we examine the wintertime environmental precursors of summer anticyclonic wave breaking (AWB) over the North Atlantic region and assess the applicability of these precursors in predicting AWB impacts on seasonal tropical cyclone (TC) activity. We show that predictors representing the environmental impacts of subtropical AWB on seasonal TC activity improve the skill of extended-range seasonal forecasts of TC activity. There is a significant correlation between boreal winter and boreal summer AWB activity via AWB-forced phases of the quasi-stationary North Atlantic Oscillation (NAO). Years with above-normal boreal summer AWB activity over the North Atlantic region also show above-normal AWB activity in the preceding boreal winter that tends to force a positive phase of the NAO that persists through the spring. These conditions are sustained by continued AWB throughout the year, particularly when El Niño-Southern Oscillation plays less of a role at forcing the large-scale circulation. While individual AWB events are synoptic and nonlinear with little predictability beyond 8-10 days, the strong dynamical connection between winter and summer wave breaking lends enough persistence to AWB activity to enable predictability of its potential impacts on TC activity. We find that the winter-summer relationship improves the skill of extended-range seasonal forecasts from as early as an April lead time, particularly for years when wave breaking has played a crucial role in suppressing TC development.


2022 ◽  
pp. 1-31

Abstract Projections of relative sea-level change (RSLC) are commonly reported at an annual mean basis. The seasonality of RSLC is often not considered, even though it may modulate the impacts of annual mean RSLC. Here, we study seasonal differences in 21st-century ocean dynamic sea-level change (DSLC, 2081-2100 minus 1995-2014) on the Northwestern European Shelf (NWES) and their drivers, using an ensemble of 33 CMIP6 models complemented with experiments performed with a regional ocean model. For the high-end emissions scenario SSP5-8.5, we find substantial seasonal differences in ensemble mean DSLC, especially in the southeastern North Sea. For example, at Esbjerg (Denmark), winter mean DSLC is on average 8.4 cm higher than summer mean DSLC. Along all coasts on the NWES, DSLC is higher in winter and spring than in summer and autumn. For the low-end emissions scenario SSP1-2.6, these seasonal differences are smaller. Our experiments indicate that the changes in winter and summer sea-level anomalies are mainly driven by regional changes in wind-stress anomalies, which are generally southwesterly and east-northeasterly over the NWES, respectively. In spring and autumn, regional wind-stress changes play a smaller role. We also show that CMIP6 models not resolving currents through the English Channel cannot accurately simulate the effect of seasonal wind-stress changes on he NWES. Our results imply that using projections of annual mean RSLC may underestimate the projected changes in extreme coastal sea levels in spring and winter. Additionally, changes in the seasonal sea-level cycle may affect groundwater dynamics and the inundation characteristics of intertidal ecosystems.


2022 ◽  
pp. 1-61
Author(s):  
Marcia B. Baker

Abstract We analyze observations and develop a hierarchy of models to understand heat waves – long-lived, high temperature anomalies – and extremely high daily temperatures during summertime in the continental extratropics. Throughout the extratropics, the number of extremely hot days found in the three hottest months is much greater than expected from a random, single-process model. Furthermore, in many locations the temperature skewness switches from negative on daily timescales to positive on monthly timescales (or shifts from positive on daily timescales to higher positive values on monthly timescales) in ways that cannot be explained by averaging alone. These observations motivate a hierarchy of models of the surface energy and moisture budgets that we use to illuminate the physics responsible for daily and monthly averaged temperature variability. Shortwave radiation fluctuations drive much of the variance and the negative skewness found in daily temperature observations. On longer timescales, precipitation-induced soil moisture anomalies are important for temperature variability and account for the shift toward positive skewness in monthly averaged temperature. Our results demonstrate that long-lived heat waves are due to (i) the residence time of soil moisture anomalies and (ii) a nonlinear feedback between temperature and evapotranspiration via the impact of temperature on vapor pressure deficit. For most climates, these two processes give rise to infrequent, long-lived heat waves in response to randomly distributed precipitation forcing. Combined with our results concerning high-frequency variability, extremely hot days are seen to be state-independent filigree driven by shortwave variability acting on top of longer-lived, moisture driven heat waves.


2022 ◽  
pp. 1-52

Abstract This study investigates the impact of the Indian and East Asian summer monsoons on the diurnal temperature range (DTR) in the low-latitude highlands of China (CLLH) based on in-situ DTR observations, ERA5 reanalysis data, and numerical simulations. Diagnoses indicate that the DTR in the CLLH shows a significant positive correlation with the Indian summer monsoon (ISM), while a negative correlation with the East Asian summer monsoon (EASM). When a strengthened ISM occurs with a weakened EASM, an anomalous anticyclonic circulation with downward motion is excited over the CLLH. This anomalous circulation pattern increases the DTR in the rainy season by reducing the medium and high cloud cover in the CLLH. When a weakened ISM with a strengthened EASM decreases the DTR over the CLLH in the rainy season. Numerical experiments help to verify this crucial physical process linking the variability of the ISM and EASM with the DTR in the CLLH. The model results further indicate that the covariability of ISM and EASM contributes most to the variability of the rainy season DTR in the CLLH, followed by the individual variability of the EASM, and the smallest contribution to the rainy season DTR in the CLLH is the individual variability of the ISM.


2022 ◽  
pp. 1-39

Abstract Uncertainty in climate projections is large as shown by the likely uncertainty ranges in Equilibrium Climate Sensitivity (ECS) of 2.5-4K and in the Transient Climate Response (TCR) of 1.4-2.2K. Uncertainty in model projections could arise from the way in which unresolved processes are represented, the parameter values used, or the targets for model calibration. We show that, in two climate model ensembles which were objectively calibrated to minimise differences from observed large scale atmospheric climatology, uncertainties in ECS and TCR are about two to six times smaller than in the CMIP5 or CMIP6 multi-model ensemble. We also find that projected uncertainties in surface temperature, precipitation and annual extremes are relatively small. Residual uncertainty largely arises from unconstrained sea-ice feedbacks. The 20+ year old HadAM3 standard model configuration simulates observed hemispheric scale observations and pre-industrial surface temperatures about as well as the median CMIP5 and CMIP6 ensembles while the optimised configurations simulates these better than almost all the CMIP5 and CMIP6 models. Hemispheric scale observations and pre-industrial temperatures are not systematically better simulated in CMIP6 than in CMIP5 though the CMIP6 ensemble seems to better simulate patterns of large-scale observations than the CMIP5 ensemble and the optimised HadAM3 configurations. Our results suggest that most CMIP models could be improved in their simulation of large scale observations by systematic calibration. However, the uncertainty in climate projections (for a given scenario) likely largely arises from the choice of parametrisation schemes for unresolved processes (“structural uncertainty”), with different tuning targets another possible contributor.


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