The impact of volcanic aerosols on recent global tropical cyclone (TC) activity is examined in observations, reanalysis, and models (the Coupled Model Intercomparison Project phase 5 - CMIP5 multi-model, and one single model large ensemble). In observations, we find a reduction of TC activity only in the North Atlantic following the last three strong volcanic eruptions; that signal, however, cannot be clearly attributed to volcanoes, as all three eruptions were simultaneous with El Niño events. In reanalyses, we find no robust impact of volcanic eruptions on potential intensity (PI) and genesis indices. In models, we find a reduction in PI after volcanic eruptions in the historical simulations, but this effect is significantly reduced when differences between the model environment and observations are accounted for. Morever, the CMIP5 multi-model historical ensemble shows no effect of volcanic eruptions on a TC genesis index. Finally, there is no robust and consistent reduction in recent TC activity following recent volcanic eruptions in a large set of synthetic TCs downscaled from these simulations. Taken together, these results show that in recent eruptions volcanic aerosols did not reduce global TC activity.
It has been widely recognized that tropical cyclone (TC) genesis requires favorable large‐scale environmental conditions. Based on these linkages, numerous efforts have been made to establish an empirical relationship between seasonal TC activities and large‐scale environmental favorability in a quantitative way, which lead to conceptual functions such as the TC genesis index. However, due to the limited amount of reliable TC observations and complexity of the climate system, a simple analytic function may not be an accurate portrait of the empirical relationship between TCs and their ambiences. In this research, we use convolution neural networks (CNNs) to disentangle this complex relationship. To circumvent the limited amount of seasonal TC observation records, we implement transfer‐learning technique to train ensemble of CNNs first on suites of high‐resolution climate model simulations with realistic seasonal TC activities and large‐scale environmental conditions, and then on a state‐of‐the‐art reanalysis from 1950 to 2019. The trained CNNs can well reproduce the historical TC records and yields significant seasonal prediction skills when the large‐scale environmental inputs are provided by operational climate forecasts. Furthermore, by inputting the ensemble CNNs with 20th century reanalysis products and Phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations, we investigated TC variability and its changes in the past and future climates. Specifically, our ensemble CNNs project a decreasing trend of global mean TC activity in the future warming scenario, which is consistent with our future projections using high‐resolution climate model.
more » « less- Award ID(s):
- 2231237
- PAR ID:
- 10492379
- Publisher / Repository:
- AGU
- Date Published:
- Journal Name:
- Journal of Advances in Modeling Earth Systems
- Volume:
- 15
- Issue:
- 10
- ISSN:
- 1942-2466
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract El Niño–Southern Oscillation (ENSO) influences seasonal Atlantic tropical cyclone (TC) activity by impacting environmental conditions important for TC genesis. However, the influence of future climate change on the teleconnection between ENSO and Atlantic TCs is uncertain, as climate change is expected to impact both ENSO and the mean climate state. We used the Weather Research and Forecasting Model on a tropical channel domain to simulate 5-member ensembles of Atlantic TC seasons in historical and future climates under different ENSO conditions. Experiments were forced with idealized sea surface temperature configurations based on the Community Earth System Model (CESM) Large Ensemble representing: a monthly varying climatology, eastern Pacific El Niño, central Pacific El Niño, and La Niña. The historical simulations produced fewer Atlantic TCs during eastern Pacific El Niño compared to central Pacific El Niño, consistent with observations and other modeling studies. For each ENSO state, the future simulations produced a similar teleconnection with Atlantic TCs as in the historical simulations. Specifically, La Niña continues to enhance Atlantic TC activity, and El Niño continues to suppress Atlantic TCs, with greater suppression during eastern Pacific El Niño compared to central Pacific El Niño. In addition, we found a decrease in the Atlantic TC frequency in the future relative to historical regardless of ENSO state, which was associated with a future increase in northern tropical Atlantic vertical wind shear and a future decrease in the zonal tropical Pacific sea surface temperature (SST) gradient, corresponding to a more El Niño–like mean climate state. Our results indicate that ENSO will remain useful for seasonal Atlantic TC prediction in the future.
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Abstract Subseasonal tropical cyclone (TC) reforecasts from the Community Earth System Model version 2 (CAM6) subseasonal prediction system are examined in this study. We evaluate the modeled TC climatology and the probabilistic forecast skill of basin‐wide TC genesis at weekly temporal resolution. Prediction skill is calculated using the Brier skill score relative to a constant annual mean climatology and to a monthly varying seasonal climatology during TC season. The model captures the observed basin‐wide climatological TC seasonality and spatial distributions at weeks 1–6, but TC genesis is largely underestimated from Week 2 onward. For some basins and lead times, the predicted TC genesis is primarily controlled by the number of TC “seeds” and the mean‐state climate condition. The model has good prediction skill relative to the constant climatology across all the basins and lead times, but is only skillful in the eastern Pacific, North Indian Ocean, and Southern Hemisphere at Week 1 when compared to the seasonal climatology, indicating limited skill in predicting deviations from the seasonal cycle. We find strong modulations of the predicted TC genesis at up to 3 weeks of forecast lead time by the Madden‐Julian Oscillation. The interannual variability of predicted TC genesis and accumulated cyclone energy are skillfully predicted in the North Atlantic and the Northwestern Pacific, with a strong modulation by the El Nino‐Southern Oscillation.
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Abstract The small sample size of tropical cyclone (TC) genesis in the observations prevents us from fully characterizing its spatiotemporal variations. Here we take advantage of a large ensemble of 60-km-resolution atmospheric simulations to address this issue over the northwest Pacific (NWP) during 1951–2010. The variations in annual TC genesis density are explored separately on interannual and decadal time scales. The interannual variability is dominated by two leading modes. One is characterized by a dipole pattern, and its temporal evolution is closely linked to the developing ENSO. The other mode features high loadings in the central part of the basin, with out-of-phase changes near the equator and date line, and tends to occur during ENSO decay years. On decadal time scales, TC genesis density variability is primarily controlled by one mode, which exhibits an east–west dipole pattern with strong signals confined to south of 20°N and is tied to the interdecadal Pacific oscillation–like sea surface temperature anomalies. Further, we investigate the seasonal evolution of the ENSO effect on TC genesis density. The results highlight the distinct impacts of the two types of ENSO (i.e., eastern Pacific vs central Pacific) on TC genesis density in the NWP during a specific season and show the strong seasonal dependency of the TC genesis response to ENSO. Although the results from the observations are not as prominent as those from the simulations because of the small sample size, the high consistency between them demonstrates the fidelity of the model in reproducing TC statistics and variability in the observations.
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Abstract There is currently no theory for the rate of tropical cyclone (TC) formation given a particular climate, so our understanding of the relationship between TC frequency and large‐scale environmental factors is largely empirical. Here, we explore the sensitivity of TC formation and intensification rates to climate warming in a series of highly idealized cloud‐permitting simulations, in which TCs form spontaneously from a base state of rest on an
f ‐plane. The simulations reveal a nonmonotonic relationship between the time taken for a TC precursor disturbance (a “seed”) to form and the prescribed sea surface temperature (SST), with moderately long seed emergence times at both ends of the SST range tested (292 and 304 K) and a shorter seed emergence time at the middle value of SST (298 K). Genesis potential indices (GPIs) exhibit a different response to warming: either a monotonic increase if the potential intensity and midtropospheric relative humidity are used or relatively little sensitivity if the saturation deficit is used as the humidity variable. The sensitivity of elapsed time between a TC seed disturbance and TC genesis to surface warming is, however, generally well captured by GPIs, especially those that depend on the saturation deficit. The maximum intensification rate of TCs increases strongly with warming, particularly during the second half of the intensification process. Notably, storms intensify much more rapidly with increasing temperature than is predicted by extant theory based on potential intensity, suggesting that TCs in a warmer climate may intensify even more rapidly than recent studies suggest.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1029/2022MS003596
