Atmospheric rivers (ARs) exert significant socioeconomic impacts in western North America, where 30% of the annual precipitation is determined by ARs that occur in less than 15% of wintertime. ARs are thus beneficial to water supply but can produce extreme precipitation hazards when making landfall. While most prevailing research has focused on the subseasonal (<5 weeks) prediction of ARs, only limited efforts have been made for AR forecasts on multiseasonal timescales (>3 months) that are crucial for water resource management and disaster preparedness. Through the analysis of reanalysis data and retrospective predictions from a new seasonal-to-decadal forecast system, this research shows the existing potential of multiseasonal AR frequency forecasts with predictive skills 9 months in advance. Additional analysis explores the dominant predictability sources and challenges for multiseasonal AR prediction.
Climate models often show errors in simulating and predicting tropical cyclone (TC) activity, but the sources of these errors are not well understood. This study proposes an evaluation framework and analyzes three sets of experiments conducted using a seasonal prediction model developed at the Geophysical Fluid Dynamics Laboratory (GFDL). These experiments apply the nudging technique to the model integration and/or initialization to estimate possible improvements from nearly perfect model conditions. The results suggest that reducing sea surface temperature (SST) errors remains important for better predicting TC activity at long forecast leads—even in a flux-adjusted model with reduced climatological biases. Other error sources also contribute to biases in simulated TC activity, with notable manifestations on regional scales. A novel finding is that the coupling and initialization of the land and atmosphere components can affect seasonal TC prediction skill. Simulated year-to-year variations in June land conditions over North America show a significant lead correlation with the North Atlantic large-scale environment and TC activity. Improved land–atmosphere initialization appears to improve the Atlantic TC predictions initialized in some summer months. For short-lead predictions initialized in June, the potential skill improvements attributable to land–atmosphere initialization might be comparable to those achievable with perfect SST predictions. Overall, this study delineates the SST and non-oceanic error sources in predicting TC activity and highlights avenues for improving predictions. The nudging-based evaluation framework can be applied to other models and help improve predictions of other weather extremes.
Wang, Zhuo, Gan Zhang, Timothy J Dunkerton, and Fei-Fei Jin, September 2020: Summertime stationary waves integrate tropical and extratropical impacts on tropical cyclone activity. Proceedings of the National Academy of Sciences, 117(37), DOI:10.1073/pnas.201054711722720-22726. Abstract
Tropical cyclones (TC) are one of the most severe storm systems on Earth and cause significant loss of life and property upon landfall in coastal areas. A better understanding of their variability mechanisms will help improve the TC seasonal prediction skill and mitigate the destructive impacts of the storms. Early studies focused primarily on tropical processes in regulating the variability of TC activity, while recent studies suggest also some long-range impacts of extratropical processes, such as lateral transport of dry air and potential vorticity by large-scale waves. Here we show that stationary waves in the Northern Hemisphere integrate tropical and extratropical impacts on TC activity in July through October. In particular, tropical upper-tropospheric troughs (TUTTs), as part of the summertime stationary waves, are associated with the variability of large-scale environmental conditions in the tropical North Atlantic and North Pacific and significantly correlated to the variability of TC activity in these basins. TUTTs are subject to the modulation of diabatic heating in various regions and are the preferred locations for extratropical Rossby wave breaking (RWB). A strong TUTT in a basin is associated with enhanced RWB and tropical−extratropical stirring in that basin, and the resultant changes in the tropical atmospheric conditions modulate TC activity. In addition, the anticorrelation of TUTTs between the North Atlantic and North Pacific makes the TC activity indices over the two basins compensate each other, rendering the global TC activity less variable than otherwise would be the case if TUTTs were independent.
The locally accumulated damage by tropical cyclones (TCs) can intensify substantially when these cyclones move more slowly. While some observational evidence suggests that TC motion might have slowed significantly since the mid-20th century (1), the robustness of the observed trend and its relation to anthropogenic warming have not been firmly established (2–4). Using large-ensemble simulations that directly simulate TC activity, we show that future anthropogenic warming can lead to a robust slowing of TC motion, particularly in the midlatitudes. The slowdown there is related to a poleward shift of the midlatitude westerlies, which has been projected by various climate models. Although the model’s simulation of historical TC motion trends suggests that the attribution of the observed trends of TC motion to anthropogenic forcings remains uncertain, our findings suggest that 21st-century anthropogenic warming could decelerate TC motion near populated midlatitude regions in Asia and North America, potentially compounding future TC-related damages.
Improving the seasonal prediction of tropical cyclone (TC) activity demands a robust analysis of the prediction skill and the inherent predictability of TC activity. Using the resampling technique, this study analyzes a state‐of‐the‐art prediction system and offers a robust assessment of when and where the seasonal prediction of TC activity is skillful. We found that uncertainties of initial conditions affect the predictions and the skill evaluation significantly. The sensitivity of predictions to initial conditions also suggests that landfall and high‐latitude activity are inherently harder to predict. The lower predictability is consistent with the relatively low prediction skill in these regions. Additionally, the lower predictability is largely related to the atmospheric environment rather than the sea surface temperature, at least for the predictions initialized shortly before the hurricane season. These findings suggest the potential for improving the seasonal TC prediction and will help the development of the next‐generation prediction systems.
Zhang, Gan, and Z Wang, July 2019: North Atlantic Rossby Wave Breaking during the Hurricane Season: Association with Tropical and Extratropical Variability. Journal of Climate, 32(13), DOI:10.1175/JCLI-D-18-0299.1. Abstract
This study explores the connection of Rossby wave breaking (RWB) with tropical and extratropical variability during the Atlantic hurricane season. The exploration emphasizes subtropical anticyclonic RWB events over the western North Atlantic, which strongly affect tropical cyclone (TC) activity. The first part of the study investigates the link between RWB and tropical sea surface temperature (SST) variability. Tropical SST variability affects tropical precipitation and modulates the large-scale atmospheric circulation over the subtropical Atlantic, which influences the behaviors of Rossby waves and the frequency of RWB occurrence. Meanwhile, RWB regulates surface heat fluxes and helps to sustain SST anomalies in the western North Atlantic. The second part of the study explores the connections between RWB and extratropical atmosphere variability by leveraging weather regime analysis. The weather regimes over the North Atlantic are closely associated with RWB over the eastern North Atlantic and western Europe, but show weak associations with RWB over the western North Atlantic. Instead, RWB over the western basin is closely related to the weather regimes in the North Pacific–North America sector. The finding helps clarify why the correlation between the Atlantic TC activity and the summertime North Atlantic Oscillation is tenuous. The relations between the extratropical weather regimes and tropical climate modes are also discussed. The findings suggest that both tropical and extratropical variability are important for understanding variations of RWB events and their impacts on Atlantic TC activity.
Zhang, Gan, Thomas R Knutson, and Stephen T Garner, December 2019: Impacts of Extratropical Weather Perturbations on Tropical Cyclone Activity: Idealized Sensitivity Experiments with a Regional Atmospheric Model. Geophysical Research Letters, 46(23), DOI:10.1029/2019GL085398. Abstract
Extratropical weather perturbations have been linked to Atlantic tropical cyclones (TC) activity in observations. However, modeling studies of the extratropical impact are scarce and disagree about its importance and climate implications. Using a non‐hydrostatic regional atmospheric model, we explore the extratropical impact by artificially suppressing extratropical weather perturbations at the tropical–extratropical interface. Our 22‐year simulations of August–October suggest that the extratropical suppression adds ~3.7 Atlantic TCs per season on average, although the response varies among individual years. The TC response mainly appears within 30°N–40°N, where tropical cyclogenesis frequency quadruples compared to control simulations. This increased cyclogenesis, accompanied by a strong increase of mid‐tropospheric relative humidity, arises as the perturbation suppression reduces the extratropical interference of TC development. The suppression of extratropical perturbations is highly idealized but may suggest mechanisms by which extratropical atmospheric variability potentially influences TC activity in past or future altered climate states.
Li, Weiwei, Z Wang, Gan Zhang, M S Peng, S G Benjamin, and Ming Zhao, December 2018: Subseasonal Variability of Rossby Wave Breaking and Impacts on Tropical Cyclones during the North Atlantic Warm Season. Journal of Climate, 31(23), DOI:10.1175/JCLI-D-17-0880.1. Abstract
This study investigates the subseasonal variability of anticyclonic Rossby wave breaking (AWB) and its impacts on atmospheric circulations and tropical cyclones (TCs) over the North Atlantic in the warm season from 1985 to 2013. Significant anomalies in sea level pressure, tropospheric wind and humidity fields are found over the tropical-subtropical Atlantic within 8 days of an AWB activity peak. Such anomalies may lead to suppressed TC activity on the subseasonal timescale, but a significant negative correlation between the subseasonal variability of AWB and Atlantic basin-wide TC activity does not exist every year, likely due to the modulation of TCs by other factors. It is also found that AWB occurrence may be modulated by the Madden-Julian Oscillation (MJO). In particular, AWB occurrence over the tropical-subtropical West Atlantic is reduced in phases 2 and 3 and enhanced in phases 6 and 7 based on the Real-time Multivariate MJO Index (RMM).
The impacts of AWB on the predictive skill of Atlantic TCs are examined using the Global Ensemble Forecasting System (GEFS) reforecasts with the forecast lead time up to 2 weeks. The hit rate of tropical cyclogenesis during active AWB episodes is lower than the long-term mean hit rate, and the GEFS is less skillful in capturing the variations of weekly TC activity during the years of enhanced AWB activity. The lower predictability of TCs is consistent with the lower predictability of environmental variables (such as vertical wind shear, moisture, and low-level vorticity) under the extratropical influence.
The hindcasts of the Geophysical Fluid Dynamics Laboratory (GFDL) High-Resolution Atmospheric Model (HiRAM), which skillfully predicted the interannual variability of Atlantic tropical cyclone (TC) frequency, were analyzed to investigate what key circulation systems a model must capture in order to skillfully predict TCs. The HiRAM reproduced the leading EOF mode (M1) of the interannual variability of the Atlantic Hadley circulation and its impacts on environmental conditions. M1 represents the variability of the ITCZ intensity and width, and the predictability of Atlantic TCs can be explained by the lag correlation between M1 and SST in preceding months. Although the ITCZ displacement was not well predicted by the HiRAM, it does not affect the prediction of the basin-wide hurricane count. The analyses suggest that the leading mode of the variability of the regional Hadley circulation can serve as a useful metric to evaluate the performance of global models in TC seasonal prediction.
