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15,232 result(s) for "Tropical cyclones"
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On the Spirality of the Asymmetric Rain Field of Tropical Cyclones Under Vertical Wind Shear
The downshear‐left enhancement of tropical cyclone rainfall has been demonstrated previously, but the radial dependence of this effect was not analyzed in detail. This study quantifies the progressive upwind shift of the wavenumber‐1 maximum rain position with radius relative to the vertical wind shear direction. This shift is visualized as a distinctive upwind spiral of the maximum. It is shown that this spiral pattern is generally observed across various storm intensities, shear strength, and ocean basins. Detailed examination revealed that the maximum downwind deflection angle of the wavenumber‐1 rain maximum relative to the shear direction is smaller for tropical storms than hurricanes, but insensitive to hurricane intensity. It is proposed that the spirality is produced by a continuous decline in angular advection of air parcels with radius. The stability of the deflection angle in hurricanes may be accounted for by a corresponding increase in vertical ascent under strengthening angular flow. Plain Language Summary Tropical cyclones (TCs) can produce torrential rainfall that generates floods, causing significant socio‐economic losses. Understanding the spatial structure of the TC rain field is crucial for improving disaster preparedness. The TC rain field can be thought of as the combination of a symmetric and an asymmetric part. By using a technique called Fourier decomposition, we can break down the asymmetric part into individual wavenumber components. The first component, wavenumber‐1 (WN‐1), is dominant and tends to be larger in the downshear quadrants under vertical wind shear. Using 21 years of global WN‐1 rain fields, we produced composite images aligned with the shear direction. We discovered that the positions at which the WN‐1 maximum occurs progressively shift upwind with increasing distance from the TC center, forming a spiral. We provided the first quantification of the observed spirals and showed that this is a general pattern that exists across different TC intensities, shear strength, and ocean basins. We also identified detailed changes in the pattern with storm intensity and introduced simple models as a first attempt to comprehend these changes. The findings can improve weather forecasts and risk predictions, making us better prepared for hazards associated with TC rainfall. Key Points There exists a general and progressive upwind shift in the wavenumber‐1 maximum with radius in global shear‐relative rainfall composites Maximum downwind deflection of the wavenumber‐1 maxima rises with storm intensity up to Category 1 on the Saffir–Simpson Hurricane Scale Linearity between the angular velocity and the vertical velocity of the storm may stabilize the downwind deflection beyond Category 1
Global increase in major tropical cyclone exceedance probability over the past four decades
Theoretical understanding of the thermodynamic controls on tropical cyclone (TC) wind intensity, as well as numerical simulations, implies a positive trend in TC intensity in a warming world. The global instrumental record of TC intensity, however, is known to be heterogeneous in both space and time and is generally unsuitable for global trend analysis. To address this, a homogenized data record based on satellite data was previously created for the period 1982–2009. The 28-y homogenized record exhibited increasing global TC intensity trends, but they were not statistically significant at the 95% confidence level. Based on observed trends in the thermodynamic mean state of the tropical environment during this period, however, it was argued that the 28-y period was likely close to, but shorter than, the time required for a statistically significant positive global TC intensity trend to appear. Here the homogenized global TC intensity record is extended to the 39-y period 1979–2017, and statistically significant (at the 95% confidence level) increases are identified. Increases and trends are found in the exceedance probability and proportion of major (Saffir–Simpson categories 3 to 5) TC intensities, which is consistent with expectations based on theoretical understanding and trends identified in numerical simulations in warming scenarios. Major TCs pose, by far, the greatest threat to lives and property. Between the early and latter halves of the time period, the major TC exceedance probability increases by about 8% per decade, with a 95% CI of 2 to 15% per decade.
Understanding of the Effect of Climate Change on Tropical Cyclone Intensity: A Review
The effect of climate change on tropical cyclone intensity has been an important scientific issue for a few decades. Although theory and modeling suggest the intensification of tropical cyclones in a warming climate, there are uncertainties in the assessed and projected responses of tropical cyclone intensity to climate change. While a few comprehensive reviews have already provided an assessment of the effect of climate change on tropical cyclone activity including tropical cyclone intensity, this review focuses mainly on the understanding of the effect of climate change on basin-wide tropical cyclone intensity, including indices for basin-wide tropical cyclone intensity, historical datasets used for intensity trend detection, environmental control of tropical cyclone intensity, detection and simulation of tropical cyclone intensity change, and some issues on the assessment of the effect of climate change on tropical cyclone intensity. In addition to the uncertainty in the historical datasets, intertwined natural variabilities, the considerable model bias in the projected large-scale environment, and poorly simulated inner-core structures of tropical cyclones, it is suggested that factors controlling the basin-wide intensity can be different from individual tropical cyclones since the assessment of the effect of climate change treats tropical cyclones in a basin as a whole.
Recent Progress in Tropical Cyclone Intensity Forecasting at the National Hurricane Center
It has been well documented that the National Hurricane Center (NHC) has made significant improvements in Atlantic basin tropical cyclone (TC) track forecasting during the past half century. In contrast, NHC’s TC intensity forecast errors changed little from the 1970s to the early 2000s. Recently, however, there has been a notable decrease in TC intensity forecast error and an increase in intensity forecast skill. This study documents these trends and discusses the advancements in TC intensity guidance that have led to the improvements in NHC’s intensity forecasts in the Atlantic basin. We conclude with a brief projection of future capabilities.
Are Forecasts of the Tropical Cyclone Radius of Maximum Wind Skillful?
The radius of maximum wind (RMW) defines the location of the maximum winds in a tropical cyclone and is critical to understanding intensity change as well as hazard impacts. A comparison between the Hurricane Analysis and Forecast System (HAFS) models and two statistical models based off the National Hurricane Center official forecast is conducted relative to a new baseline climatology to better understand whether models have skill in forecasting the RMW of North Atlantic tropical cyclones. On average, the HAFS models are less skillful than the climatology and persistence baseline and two statistically derived RMW estimates. The performance of the HAFS models is dependent on intensity with better skill for stronger tropical cyclones compared to weaker tropical cyclones. To further improve guidance of tropical cyclone hazards, more work needs to be done to improve forecasts of tropical cyclone structure. Plain Language Summary The radius of maximum wind (RMW) is a key structural parameter of tropical cyclones that describes how far the strongest winds are from the storm's center. The RMW is closely tied to significant hazards such as wind, storm surge, and rainfall. However, little forecast guidance is provided for the RMW resulting in forecasters using climatological estimates to help communicate hazard risk. In order to better forecast the RMW, we need to understand the performance of the few guidance techniques available. We compare RMW forecasts from the Hurricane Analysis and Forecast System (HAFS) to two statistical models and a climatological estimate. Forecasts of the RMW from HAFS are not competitive with statistical derivations of the RMW with marginally better to comparable skill for stronger tropical cyclones. The results indicate that there is a strong need for future improvements to better predict tropical cyclone structure in addition to track and intensity. Key Points Forecasting the radius of maximum wind (RMW) is important for forecasting tropical cyclone hazards A RMW climatology and persistence model is created to determine forecast skill Statistical RMW forecasts are skillful and outperform dynamical model guidance
Response of Global Tropical Cyclone Activity to Increasing CO2: Results from Downscaling CMIP6 Models
Global models comprising the sixth-generation Coupled Climate Model Intercomparison Project (CMIP6) are downscaled using a very high-resolution but simplified coupled atmosphere–ocean tropical cyclone model, as a means of estimating the response of global tropical cyclone activity to increasing greenhouse gases. As with a previous downscaling of CMIP5 models, the results show an increase in both the frequency and severity of tropical cyclones, robust across the models downscaled, in response to increasing greenhouse gases. The increase is strongly weighted to the Northern Hemisphere, and especially noteworthy is a large increase in the higher latitudes of the North Atlantic. Changes are insignificant in the South Pacific across metrics. Although the largest increases in track density are far from land, substantial increases in global landfalling power dissipation are indicated. The incidence of rapid intensification increases rapidly with warming, as predicted by existing theory. Measures of robustness across downscaled climate models are presented, and comparisons to tropical cyclones explicitly simulated in climate models are discussed.
Ocean Eddies Lower the Global‐Mean, Maximum Intensity of Tropical Cyclones in a One‐Year Global, Coupled Simulation
We quantify the impact of ocean eddies on the global‐mean tropical‐cyclone intensity in a 1‐year simulation run with a coupled atmosphere‐ocean model with quite‐realistic seasonal climatology that resolves both Tropical cyclones (TCs) and ocean eddies. We find a significantly lower global‐mean intensity and intensification rate for the subset of TCs that spend more time over cold‐core eddies than warm‐core eddies. While not statistically significant, we also find that TCs that encounter more warm than cold‐core eddies display a higher global‐mean intensity and intensification rate. The differing impact of warm‐core and cold‐core ocean eddies are consistent with coherent differences in sea‐surface cooling prior to peak intensity. Our results demonstrate that ocean eddies can have a statistically significant impact on the global‐mean intensity, suggesting that resolving ocean eddies does matter for global TC statistics.
On the Realism of Tropical Cyclone Intensification in Global Storm‐Resolving Climate Models
The physical processes governing a tropical cyclone's lifecycle are largely understood, but key processes occur at scales below those resolved by global climate models. Increased resolution may help simulate realistic tropical cyclone intensification. We examined fully coupled, global storm‐resolving models run at resolutions in the range 28–2.8 km in the atmosphere and 28–5 km in the ocean. Simulated tropical cyclone activity, peak intensity, intensification rate, and horizontal wind structure are all more realistic at a resolution of ∼5 km compared with coarser resolutions. Rapid intensification, which is absent at typical climate model resolutions, is also captured, and exhibits sensitivity to how, and if, deep convection is parameterized. Additionally, the observed decrease in inner‐core horizontal size with increasing intensification rate is captured at storm‐resolving resolution. These findings highlight the importance of global storm‐resolving models for quantifying risk and understanding the role of intense tropical cyclones in the climate system. Plain Language Summary Simulating strong tropical storms (i.e., major hurricanes, super typhoons) with climate models is challenging because important processes that act to intensify a storm occur over spatial scales that are too small for global models to capture. Typical models lack sufficient resolution in the atmosphere and ocean, often constrained by computational resources. Recently, in a few models, resolution has increased to a point where each grid cell represents an area of just a few square kilometres, a significant leap of one or two orders of magnitude. We analyzed tropical storms simulated by these state‐of‐the‐art, so‐called storm‐resolving models and found that peak tropical storm intensity and the rate at which storms intensify are both more realistic. These models also simulate the rapid intensification of tropical storms and capture the small eye diameters often seen in the most intense storms. Our work provides evidence that storm‐resolving resolution may help us better understand the role of tropical storms in the climate system and predict their behavior in a warming climate. Key Points Simulated tropical cyclone characteristics analyzed in two fully coupled global climate models at atmospheric resolutions of 28 to 2.8 km Tropical cyclone intensification rate is close to observations at resolutions of 5 km or finer, and rapid intensification is captured Storm‐resolving models also capture the observed relationship between high intensification rate and small inner‐core size
The Development of the NCEP Global Ensemble Forecast System Version 12
The Global Ensemble Forecast System (GEFS) is upgraded to version 12, in which the legacy Global Spectral Model (GSM) is replaced by a model with a new dynamical core—the Finite Volume Cubed-Sphere Dynamical Core (FV3). Extensive tests were performed to determine the optimal model and ensemble configuration. The new GEFS has cubed-sphere grids with a horizontal resolution of about 25 km and an increased ensemble size from 20 to 30. It extends the forecast length from 16 to 35 days to support subseasonal forecasts. The stochastic total tendency perturbation (STTP) scheme is replaced by two model uncertainty schemes: the stochastically perturbed physics tendencies (SPPT) scheme and stochastic kinetic energy backscatter (SKEB) scheme. Forecast verification is performed on a period of more than two years of retrospective runs. The results show that the upgraded GEFS outperforms the operational-at-the-time version by all measures included in the GEFS verification package. The new system has a better ensemble error–spread relationship, significantly improved skills in large-scale environment forecasts, precipitation probability forecasts over CONUS, tropical cyclone track and intensity forecasts, and significantly reduced 2-m temperature biases over North America. GEFSv12 was implemented on 23 September 2020.
Reducing a Tropical Cyclone Weak-Intensity Bias in a Global Numerical Weather Prediction System
The operational Canadian Global Deterministic Prediction System suffers from a weak-intensity bias for simulated tropical cyclones. The presence of this bias is confirmed in progressively simplified experiments using a hierarchical system development technique. Within a semi-idealized, simplified-physics framework, an unexpected insensitivity to the representation of relevant physical processes leads to investigation of the model’s semi-Lagrangian dynamical core. The root cause of the weak-intensity bias is identified as excessive numerical dissipation caused by substantial off-centering in the two time-level time integration scheme used to solve the governing equations. Any (semi)implicit semi-Lagrangian model that employs such off-centering to enhance numerical stability will be afflicted by a misalignment of the pressure gradient force in strong vortices. Although the associated drag is maximized in the tropical cyclone eyewall, the impact on storm intensity can be mitigated through an intercomparison-constrained adjustment of the model’s temporal discretization. The revised configuration is more sensitive to changes in physical parameterizations and simulated tropical cyclone intensities are improved at each step of increasing experimental complexity. Although some rebalancing of the operational system may be required to adapt to the increased effective resolution, significant reduction of the weak-intensity bias will improve the quality of Canadian guidance for global tropical cyclone forecasting.