Baoqiang Xiang

We implemented in GFDL's global atmospheric model a parameterization for convective gravity waves, which explicitly describes the wave source based on the latent heating rates from the parameterized deep convection. The characteristics of the simulated Quasi‐Biennial Oscillation (QBO) in the equatorial stratosphere depend on the tunable parameters in the convective gravity wave scheme. In particular, a larger efficiency factor or a smaller convective area leads to a shorter QBO period. A less‐than‐one scaling factor for the convective heating depth, though unphysical, is necessary for the model to simulate a realistic QBO over the lower stratosphere. Furthermore, we relax the assumption of constant convective area and replace it with the prognostic convective area diagnosed from the convection scheme. While the model with a constant convective area simulates a similar QBO to that with variable convective area at the present‐day condition, it simulates a stronger reduction of the QBO period and the QBO amplitude in response to surface warming. Our results highlight the sensitivity of the simulated QBO in general circulation models to details of the parameterization for convective gravity waves.

Improving the subseasonal-to-seasonal (S2S) prediction of heatwaves is a critical scientific challenge due to their severe societal impacts and the limited predictability at these lead times. Here we show two dominant and physically distinct sources of S2S predictability for the weekly hot days across North America. The leading predictable mode, with its strongest loading over the southern U.S., reflects an ocean-forced mode associated with a Pacific Decadal Oscillation-like sea surface temperature pattern. In contrast, the second most predictable mode, with centers of action over northwestern and southeastern North America, is dominated by atmospheric internal variability associated with the summer Arctic Oscillation and summer North Atlantic Oscillation. Skillful week-3 forecasts of hot days are further characterized by quasi-stationary wave patterns coupled with regional soil moisture deficit, revealing dynamical and land-surface ‘windows of opportunity’ for extended S2S predictability. These findings identify the physical mechanisms governing North American heat extreme predictability and provide a scientific basis for improving extended-range early warnings of heat extremes.

Subseasonal prediction of extremes has emerged as a top forecast priority but remains a great challenge. In this work, we explored two physical modes controlling the subseasonal variation and prediction of land cold extremes over Eurasia: the so-called North Atlantic Oscillation (NAO) and the Eurasian Meridional Dipole mode (EMD). The ECMWF model has shown its skill in predicting the Eurasian land cold extremes 2-4 weeks in advance mainly because of the skillful prediction of NAO and EMD. Further, we separated these observed events into the good prediction and poor prediction groups for those two modes to reveal the potential factors influencing the subseasonal prediction of land cold extremes. It is found that the good prediction group has a stronger initial amplitude and longer persistence, while the poor prediction group has a relatively weaker initial amplitude but rapid intensification. For EMD, the predictability is mainly due to the skillful prediction of the Ural blocking which is further traced back to the stratospheric variations.

Heat extremes frequently hit different regions synchronously during boreal summer over the Eurasian continent. A remarkable coupling is first revealed between Eurasian heat extreme occurrence and individual extratropical intraseasonal oscillation (EISO). Further, the combined EISOs facilitate and largely increase the occurrence probabilities of synchronous Eurasian heat extremes. These dominant combined EISOs together contribute 20–45% to the total heat extreme days over the five Eurasian regions where the climatological heat extremes occur most frequently. A multi-model hindcast further shows that the subseasonal prediction exhibits higher skills for synchronous heat extremes over the combined-EISO hotspot regions when the associated combined EISOs are active, supporting the notion that the monitoring and prediction of EISOs are crucial for heat extremes’ early warning. Skillful prediction of EISOs opens a pathway for heat extremes’ prediction by extending it from the weather to the subseasonal timescales.

Atmospheric rivers (ARs) are characterized by intense lower tropospheric plumes of moisture transport that are frequently responsible for midlatitude wind and precipitation extremes. The prediction of ARs on subseasonal timescales is currently at a low level of skill, reflecting a need to improve our understanding of their underlying sources of predictability. Based on hindcast experiments from the Seamless System for Prediction and Earth System Research (SPEAR) at the Geophysical Fluid Dynamics Laboratory, we evaluate the global subseasonal prediction skill of wintertime AR statistics. Overall, the results from SPEAR are comparable to the European Centre for Medium-Range Weather Forecasts (ECMWF). Higher forecast skill is detected for strong AR activities than weak AR activities, despite that the occurrence frequency for weak ARs exceeds that of strong ARs. Importantly, we assess the sources of predictability and find that three most predictable modes of ARs in the North Pacific sector can be interpreted as arising from the influence of the El Niño–Southern Oscillation, the Pacific North American and the Arctic Oscillation patterns. Subseasonal AR forecast skill in western North America is modulated by different phases of these modes of large-scale seasonal variability highlighting the potential windows of opportunity for subseasonal AR forecasting.

During 2010 to 2020, Northeast Pacific (NEP) sea surface temperature (SST) experienced the warmest decade ever recorded, manifested in several extreme marine heatwaves, referred to as “warm blob” events, which severely affect marine ecosystems and extreme weather along the west coast of North America. While year-to-year internal climate variability has been suggested as a cause of individual events, the causes of the continuous dramatic NEP SST warming remain elusive. Here, we show that other than the greenhouse gas (GHG) forcing, rapid aerosol abatement in China over the period likely plays an important role. Anomalous tropospheric warming induced by declining aerosols in China generated atmospheric teleconnections from East Asia to the NEP, featuring an intensified and southward-shifted Aleutian Low. The associated atmospheric circulation anomaly weakens the climatological westerlies in the NEP and warms the SST there by suppressing the evaporative cooling. The aerosol-induced mean warming of the NEP SST, along with internal climate variability and the GHG-induced warming, made the warm blob events more frequent and intense during 2010 to 2020. As anthropogenic aerosol emissions continue to decrease, there is likely to be an increase in NEP warm blob events, disproportionately large beyond the direct radiative effects.

Boreal summer intraseasonal oscillation (BSISO) is a primary source of predictability for summertime weather and climate on the subseasonal-to-seasonal (S2S) time scale. Using the GFDL SPEAR S2S prediction system, we evaluate the BSISO prediction skills based on 20-yr (2000–19) hindcast experiments with initializations from May to October. It is revealed that the overall BSISO prediction skill using all hindcasts reaches out to 22 days as measured by BSISO indices before the bivariate anomalous correlation coefficient (ACC) drops below 0.5. Results also show that the northeastward-propagating canonical BSISO (CB) event has a higher prediction skill than the northward dipole BSISO (DB) event (28 vs 23 days). This is attributed to CB’s more periodic nature, resulting in its longer persistence, while DB events are more episodic accompanied by a rapid demise after reaching maximum enhanced convection over the equatorial Indian Ocean. From a forecaster’s perspective, a precursory strong Kelvin wave component in the equatorial western Pacific signifies the subsequent development of a CB event, which is likely more predictable. Investigation of individual CB events shows a large interevent spread in terms of their prediction skills. For CB, the events with weaker and fluctuating amplitude during their lifetime have relatively lower prediction skills likely linked to their weaker convection–circulation coupling. Interestingly, the prediction skills of individual CB events tend to be relatively higher and less scattered during late summer (August–October) than those in early summer (May–July), suggestive of the seasonal modulation on the evolution and predictability of BSISO. Significance Statement: The advance of subseasonal-to-seasonal (S2S) prediction largely depends on dynamical models’ ability to predict some major intrinsic modes in the climate system, including the boreal summer intraseasonal oscillation (BSISO). Using a newly developed S2S prediction system, we thoroughly evaluated its performance in predicting BSISO, and revealed the skill dependence on the BSISO propagation diversity. Here we provide physical explanations of what influences the BSISO predictions and identify different precursory signals for two types of BSISO, which have important implications for operational forecasts.

This study investigates how climate sensitivity depends upon the spatial pattern of radiative forcing. Sensitivity experiments using a coupled ocean‐atmosphere model were conducted by adding anomalous incoming solar radiation over the entire globe, Northern Hemisphere mid‐latitudes, Southern Ocean, and tropics. The varied forcing patterns led to highly divergent climate sensitivities. Specifically, the climate is nearly twice as sensitive to Southern Ocean forcing as tropical forcing. Strong coupling between the surface and free troposphere in the tropics increases the inversion strength, leading to smaller cloud feedback in the tropical forcing experiments. In contrast, the extratropics exhibit weaker coupling, a decrease or near‐zero change in the inversion strength, and strong positive cloud feedback. These results contrast with the conventional SST‐pattern effect in which tropical surface temperature changes regulate climate sensitivity. They also have important implications for other potentially asymmetric forcings, such as those from geoengineering, volcanic eruptions, and paleoclimatic changes.