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Tropical Cyclones (Hurricanes) - AR4 WGI Chapter Global Climate Projections

Alexander Grohsjean. Andreas W. Boyang Liu. Shinsuke Inuki. Marc Hutchby. Behrouz Touri. Jonathan M. Jaroslav Haas. Julia Poncela Casasnovas. Matthew Joseph Mottram. Andres de Bustos Molina. Animations showing the development and evolution of hurricane activity in the model are available here. Turning to future climate projections, current climate models suggest that tropical Atlantic SSTs will warm dramatically during the 21st century, and that upper tropospheric temperatures will warm even more than SSTs.

Furthermore, most of the CMIP3 models project increasing levels of vertical wind shear over parts of the western tropical Atlantic see Vecchi and Soden Both the increased warming of the upper troposphere relative to the surface and the increased vertical wind shear are detrimental factors for hurricane development and intensification, while warmer SSTs favor development and intensification.


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Our regional model projects that Atlantic hurricane and tropical storms are substantially reduced in number , for the average 21st century climate change projected by current models, but have higher rainfall rates , particularly near the storm center. The average intensity of the storms that do occur increases by a few percent Figure 6 , in general agreement with previous studies using other relatively high resolution models, as well as with hurricane potential intensity theory Emanuel Such sensitivity estimates have considerable uncertainty, as a subsequent assessment of multiple studies Knutson et al.

Wright et al. A review of existing studies, including the ones cited above, lead us to conclude that: it is likely that greenhouse warming will cause hurricanes in the coming century to be more intense globally and have higher rainfall rates than present-day hurricanes. Turning now to the question of the frequency of very intense hurricanes, the regional model of Knutson et al. Furthermore, the idealized study of Knutson and Tuleya assumed the existence of hurricanes and then simulated how intense they would become.

Thus, that study could not address the important question of the frequency of intense hurricanes. In a series of Atlantic basin-specific dynamical downscaling studies Bender et al. The GFDL hurricane model with a grid spacing as fine as 9 km is able to simulate the frequency, intensity, and structure of the more intense hurricanes, such as category storms, much more realistically than the regional 18 km grid model.

Global Warming and Hurricanes

Using this additional downscaling step, the GFDL hurricane model reproduces some important historical characteristics of very intense Atlantic hurricanes, including the wind speed distribution and the change of this distribution between active and inactive decadal periods of hurricane activity Fig. The Bender et al. That study also downscaled ten individual CMIP3 models in addition to the multi-model ensemble, and found that three of ten models produced a significant increase in category 4 and 5 storms, and four of the ten models produced at least a nominal decrease.

While multi-model ensemble results are probably more reliable than individual model results, each of the individual model results can be viewed as at least plausible at this time. Based on Knutson et al. Returning to the issue of future projections of aggregate activity PDI, as in Fig. As noted above, there is some indication from high resolution models of substantial increases in the numbers of the most intense hurricanes even if the overall number of tropical storms or hurricanes decreases.

Finally, one can ask when a large increase in Category hurricanes, as projected by our earlier Bender et al. Apart from greenhouse warming, other human influences conceivably could have contributed to recent observed increases in Atlantic hurricanes. For example, Mann and Emanuel hypothesize that a reduction in aerosol-induced cooling over the Atlantic in recent decades may have contributed to the enhanced warming of the tropical North Atlantic, relative to global mean temperature. However, the cause or causes of the recent enhanced warming of the Atlantic, relative to other tropical basins, and its effect on Atlantic tropical cyclones, remains highly uncertain e.

A number of anthropogenic and natural factors e.

IPCC AR5 concluded that there is medium confidence that reduced aerosol forcing contributed to the observed increase in Atlantic tropical cyclone activity since the s, but does not state any estimate of the magnitude of contribution. They also conclude that it remains uncertain whether there are any detectable changes in past tropical cyclone activity. Sea level rise must also be considered as a way in which human-caused climate change can impact Atlantic hurricane climate—or at least the impacts of the hurricanes at the coast.

Tropical cyclone forecast model

The vulnerability of coastal regions to storm-surge flooding is expected to increase with future sea-level rise and coastal development, although this vulnerability will also depend upon future storm characteristics, as discussed above. All else equal, coastal inundation levels associated with tropical cyclones should increase with sea level rise. There are large ranges in the 21st century projections for both Atlantic hurricane characteristics and for the magnitude of regional sea level rise along the U.

However, according to the IPCC AR5 , the average rate of global sea level rise over the 21st Century will very likely exceed that observed during for a range of future emission scenarios. In summary, neither our model projections for the 21st century nor our analyses of trends in Atlantic hurricane and tropical storm activity support the notion that greenhouse gas-induced warming leads to large increases in either tropical storm or overall hurricane numbers in the Atlantic.


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  7. These climate change detection results for rapid intensification metrics are suggestive but not definitive, and more research is needed for more confident conclusions. Therefore, we conclude that it is premature to conclude with high confidence that human activity—and particularly greenhouse warming—has already caused a detectable change in Atlantic hurricane activity.

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    However, human activity may have already caused some some changes that are not yet confidently detectable due to the small magnitude of the changes or observation limitations, or due to limitations in modeling and physical understanding e. We also conclude that it is likely that climate warming will cause Atlantic hurricanes in the coming century have higher rainfall rates than present-day hurricanes, and medium confidence that they will be more intense higher peak winds and lower central pressures on average.

    In our view, it is uncertain how the annual number of Atlantic tropical storms will change over the 21st century. Dynamical models were not developed until the s and the s, with earlier efforts focused on the storm surge problem. Track models did not show forecast skill when compared to statistical models until the s.

    Tropical Cyclones and Climate Change

    Statistical-dynamical models were used from the s into the s. Early models use data from previous model runs while late models produce output after the official hurricane forecast has been sent.

    The use of consensus, ensemble, and superensemble forecasts lowers errors more than any individual forecast model. Both consensus and superensemble forecasts can use the guidance of global and regional models runs to improve the performance more than any of their respective components. Techniques used at the Joint Typhoon Warning Center indicate that superensemble forecasts are a very powerful tool for track forecasting.

    It used the newly developed North Atlantic tropical cyclone database to find storms with similar tracks. It then shifted their tracks through the storm's current path, and used location, direction and speed of motion, and the date to find suitable analogs. The method did well with storms south of the 25th parallel which had not yet turned northward, but poorly with systems near or after recurvature. In the era of skillful dynamical forecasts, CLIPER is now being used as the baseline to show model and forecaster skill.

    In regards to intensity forecasting, the Statistical Hurricane Intensity Prediction Scheme SHIPS utilizes relationships between environmental conditions from the Global Forecast System GFS such as vertical wind shear and sea surface temperatures , climatology, and persistence storm behavior via multiple regression techniques to come up with an intensity forecast for systems in the northern Atlantic and northeastern Pacific oceans.

    It has been operational since Once it was determined that it could show skill in hurricane prediction, a multi-year transition transformed the research model into an operational model which could be used by the National Weather Service for both track and intensity forecasting in The Beta Advection Model BAM has been used operationally since using steering winds averaged through the hPa to hPa layer and the Beta effect which causes a storm to drift northwest due to differences in the coriolis effect across the tropical cyclone.

    If the forecast from the three versions is similar, then the forecaster can conclude that there is minimal uncertainty, but if the versions vary by a great deal, then the forecaster has less confidence in the track predicted due to the greater uncertainty. Tested in and , The Vic Ooyama Barotropic VICBAR model used a cubic-B spline representation of variables for the objective analysis of observations and solutions to the shallow-water prediction equations on nested domains, with the boundary conditions defined as the global forecast model.

    These models are interpolated to the current storm position for use in the following forecast cycle — for example, GFDI, the interpolated version of the GFDL model. Using a consensus of forecast models reduces forecast error. For the season, and until model verification can occur, it is not being utilized in the development of any consensus forecasts. No model is ever perfectly accurate because it is impossible to learn exactly everything about the atmosphere in a timely enough manner, and atmospheric measurements that are taken are not completely accurate.

    It uses a lower resolution version with larger grid spacing of its GSM, with ten perturbed members and one non-perturbed member. The Florida State Super Ensemble FSSE is produced from a suite of models which then uses statistical regression equations developed over a training phase to reduce their biases, which produces forecasts better than the member models or their mean solution. It shows significant skill in track, intensity, and rainfall predictions of tropical cyclones.

    All the models improved during SAFA's five-year history and removing erroneous forecasts proved difficult to do in operations. A report correlates low sunspot activity with high hurricane activity. In June , the hurricanes predictors in the US were not using this information. The accuracy of hurricane forecast models can vary significantly from storm to storm. For some storms the factors affecting the hurricane track are relatively straightforward, and the models are not only accurate but they produce similar forecasts, while for other storms the factors affecting the hurricane track are more complex and different models produce very different forecasts.

    From Wikipedia, the free encyclopedia. See also: History of numerical weather prediction. Tropical cyclones portal. National Oceanic and Atmospheric Administration. Retrieved 26 February