Dynamical Studies in Hurricane Intensity Change

2000 ◽  
Author(s):  
Michael T. Montgomery
Keyword(s):  
Intensity Change ◽  
Hurricane Intensity

scholarly journals Reducing Operational Hurricane Intensity Forecast Errors during Eyewall Replacement Cycles

2016 ◽  
Vol 31 (2) ◽  
pp. 601-608 ◽  
Author(s):  
James P. Kossin ◽  
Mark DeMaria
Keyword(s):  
Forecast Error ◽  
Intensity Change ◽  
Forecast Errors ◽  
Hurricane Intensity ◽  
Intensity Forecast ◽  
Prediction Scheme ◽  
Hurricane Prediction ◽  
Eyewall Replacement Cycles ◽  
National Hurricane Center ◽  
Intensity Evolution

Abstract Eyewall replacement cycles (ERCs) are fairly common events in tropical cyclones (TCs) of hurricane intensity or greater and typically cause large and sometimes rapid changes in the intensity evolution of the TC. Although the details of the intensity evolution associated with ERCs appear to have some dependence on the ambient environmental conditions that the TCs move through, these dependencies can also be quite different than those of TCs that are not undergoing an ERC. For example, the Statistical Hurricane Prediction Scheme (SHIPS), which is used in National Hurricane Center operations and provides intensity forecast skill that is, on average, equal to or greater than deterministic numerical model skill, typically identifies an environment that is not indicative of weakening during the onset and subsequent evolution of an ERC. Contrarily, a period of substantial weakening does typically begin near the onset of an ERC, and this disparity can cause large SHIPS intensity forecast errors. Here, a simple model based on a climatology of ERC intensity change is introduced and tested against SHIPS. It is found that the application of the model can reduce intensity forecast error substantially when applied at, or shortly after, the onset of ERC weakening.

scholarly journals Application of Oceanic Heat Content Estimation to Operational Forecasting of Recent Atlantic Category 5 Hurricanes

2008 ◽  
Vol 23 (1) ◽  
pp. 3-16 ◽  
Author(s):  
Michelle Mainelli ◽  
Mark DeMaria ◽  
Lynn K. Shay ◽  
Gustavo Goni
Keyword(s):  
Tropical Cyclone ◽  
Positive Impact ◽  
Thermal Structure ◽  
Heat Content ◽  
Intensity Change ◽  
Upper Ocean ◽  
Average Intensity ◽  
Hurricane Intensity ◽  
Structure Information ◽  
Maximum Improvement

Abstract Research investigating the importance of the subsurface ocean structure on tropical cyclone intensity change has been ongoing for several decades. While the emergence of altimetry-derived sea height observations from satellites dates back to the 1980s, it was difficult and uncertain as to how to utilize these measurements in operations as a result of the limited coverage. As the in situ measurement coverage expanded, it became possible to estimate the upper oceanic heat content (OHC) over most ocean regions. Beginning in 2002, daily OHC analyses have been generated at the National Hurricane Center (NHC). These analyses are used qualitatively for the official NHC intensity forecast, and quantitatively to adjust the Statistical Hurricane Intensity Prediction Scheme (SHIPS) forecasts. The primary purpose of this paper is to describe how upper-ocean structure information was transitioned from research to operations, and how it is being used to generate NHC’s hurricane intensity forecasts. Examples of the utility of this information for recent category 5 hurricanes (Isabel, Ivan, Emily, Katrina, Rita, and Wilma from the 2003–05 hurricane seasons) are also presented. Results show that for a large sample of Atlantic storms, the OHC variations have a small but positive impact on the intensity forecasts. However, for intense storms, the effect of the OHC is much more significant, suggestive of its importance on rapid intensification. The OHC input improved the average intensity errors of the SHIPS forecasts by up to 5% for all cases from the category 5 storms, and up to 20% for individual storms, with the maximum improvement for the 72–96-h forecasts. The qualitative use of the OHC information on the NHC intensity forecasts is also described. These results show that knowledge of the upper-ocean thermal structure is fundamental to accurately forecasting intensity changes of tropical cyclones, and that this knowledge is making its way into operations. The statistical results obtained here indicate that the OHC only becomes important when it has values much larger than that required to support a tropical cyclone. This result suggests that the OHC is providing a measure of the upper ocean’s influence on the storm and improving the forecast.

Oceanic Heat Content Variability in the Eastern Pacific Ocean for Hurricane Intensity Forecasting

2010 ◽  
Vol 138 (6) ◽  
pp. 2110-2131 ◽  
Author(s):  
Lynn K. Shay ◽  
Jodi K. Brewster
Keyword(s):  
Pacific Ocean ◽  
Heat Content ◽  
Ocean Basin ◽  
Eastern Pacific ◽  
Intensity Change ◽  
Upper Ocean ◽  
Eastern Pacific Ocean ◽  
Hurricane Intensity ◽  
Tropical Ocean

Abstract Recent evidence supports the premise that the subsurface ocean structure plays an important role in modulating air–sea fluxes during hurricane passage, which in turn, affects intensity change. Given the generally sparse in situ data, it has been difficult to provide region-to-basin-wide estimates of isotherm depths and upper-ocean heat content (OHC). In this broader context, satellite-derived sea surface height anomalies (SSHAs) from multiple platforms carrying radar altimeters are blended, objectively analyzed, and combined with a hurricane-season climatology to estimate isotherm depths and OHC within the context of a reduced gravity model at 0.25° spatial intervals in the eastern Pacific Ocean where tropical cyclone intensity change occurs. Measurements from the Eastern Pacific Investigation of Climate in 2001, long-term tropical ocean atmosphere mooring network, and volunteer observing ship deploying expendable bathythermograph (XBT) profilers are used to carefully evaluate satellite-based measurements of upper-ocean variability. Regression statistics reveal small biases with slopes of 0.8–0.9 between the subsurface measurements compared with isotherm depths (20° and 26°C), and OHC fields derived from objectively analyzed SSHA field. Root-mean-square differences in OHC range between 10 and 15 kJ cm−2 or roughly 10%–15% of the mean signals. Similar values are found for isotherm depth differences between in situ and inferred satellite-derived values. Blended daily values are used in the Statistical Hurricane Intensity Prediction Scheme (SHIPS) forecasts as are OHC estimates for the Atlantic Ocean basin. An equivalent OHC variable is introduced that incorporates the strength of the thermocline at the base of the oceanic mixed layer using a climatological stratification parameter  /No, which seems better correlated to hurricane intensity change than just anomalies as observed in Hurricane Juliette in 2001.

scholarly journals SHIPS-MI Forecast Analysis of Hurricanes Claudette (2003), Isabel (2003), and Dora (1999)

2007 ◽  
Vol 22 (4) ◽  
pp. 689-707 ◽  
Author(s):  
Thomas A. Jones ◽  
Daniel J. Cecil
Keyword(s):  
Inner Core ◽  
Forecast Accuracy ◽  
Precipitation Forecast ◽  
Intensity Change ◽  
Forecast Errors ◽  
Positive Contribution ◽  
Hurricane Intensity ◽  
Intensity Prediction ◽  
Prediction Scheme ◽  
Dependent Sample

Abstract Three hurricanes, Claudette (2003), Isabel (2003), and Dora (1999), were selected to examine the Statistical Hurricane Intensity Prediction Scheme with Microwave Imagery (SHIPS-MI) forecast accuracy for three particular storm types. This research was conducted using model analyses and tropical cyclone best-track data, with forecasts generated from a dependent sample. The model analyses and best-track data are assumed to be a “perfect” representation of the actual event (e.g., perfect prog assumption). Analysis of intensity change forecasts indicated that SHIPS-MI performed best, compared to operational SHIPS output, for tropical cyclones that were intensifying from tropical storm to hurricane intensity. Passive microwave imagery, which is sensitive to the intensity and coverage of precipitation, improved intensity forecasts during these periods with a positive intensity change contribution resulting from above normal inner-core precipitation. Forecast improvement was greatest for 12–36-h forecasts, where the microwave contribution to SHIPS-MI was greatest. Once a storm reached an intensity close to its maximum potential intensity, as in the case of Isabel and Dora, both SHIPS and SHIPS-MI incorrectly forecast substantial weakening despite the positive contribution from microwave data. At least in Dora’s case, SHIPS-MI forecasts were slightly stronger than those of SHIPS. Other important contributions to SHIPS-MI forecasts were examined to determine their importance relative to the microwave inputs. Inputs related to sea surface temperature (SST) and persistence–climatology proved to be very important to intensity change forecasts, as expected. These predictors were the primary factor leading to the persistent weakening forecasts made by both models for Isabel and Dora. For Atlantic storms (Claudette and Isabel), the contribution from shear also proved important at characterizing the conduciveness of the environment toward intensification. However, the shear contribution was often small as a result of multiple offsetting shear-related predictors. Finally, it was observed that atmospheric parameters not included in SHIPS, such as eddy momentum flux, could substantially affect the intensity, leading to large forecast errors. This was especially true for the Claudette intensity change forecasts throughout its life cycle.

scholarly journals Past and Future Hurricane Intensity Change along the U.S. East Coast

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Mingfang Ting ◽  
James P. Kossin ◽  
Suzana J. Camargo ◽  
Cuihua Li
Keyword(s):  
East Coast ◽  
Intensity Change ◽  
Hurricane Intensity ◽  
The U.S

scholarly journals Understanding Error Distributions of Hurricane Intensity Forecasts during Rapid Intensity Changes

2020 ◽  
Vol 35 (6) ◽  
pp. 2219-2234
Author(s):  
Benjamin C. Trabing ◽  
Michael M. Bell
Keyword(s):  
Inner Core ◽  
Forecast Error ◽  
Vertical Wind Shear ◽  
Probability Of Detection ◽  
Intensity Change ◽  
Forecast Errors ◽  
Hurricane Intensity ◽  
East Pacific ◽  
Intensity Forecast ◽  
Error Distributions

AbstractThe characteristics of official National Hurricane Center (NHC) intensity forecast errors are examined for the North Atlantic and east Pacific basins from 1989 to 2018. It is shown how rapid intensification (RI) and rapid weakening (RW) influence yearly NHC forecast errors for forecasts between 12 and 48 h in length. In addition to being the tail of the intensity change distribution, RI and RW are at the tails of the forecast error distribution. Yearly mean absolute forecast errors are positively correlated with the yearly number of RI/RW occurrences and explain roughly 20% of the variance in the Atlantic and 30% in the east Pacific. The higher occurrence of RI events in the east Pacific contributes to larger intensity forecast errors overall but also a better probability of detection and success ratio. Statistically significant improvements to 24-h RI forecast biases have been made in the east Pacific and to 24-h RW biases in the Atlantic. Over-ocean 24-h RW events cause larger mean errors in the east Pacific that have not improved with time. Environmental predictors from the Statistical Hurricane Intensity Prediction Scheme (SHIPS) are used to diagnose what conditions lead to the largest RI and RW forecast errors on average. The forecast error distributions widen for both RI and RW when tropical systems experience low vertical wind shear, warm sea surface temperature, and moderate low-level relative humidity. Consistent with existing literature, the forecast error distributions suggest that improvements to our observational capabilities, understanding, and prediction of inner-core processes is paramount to both RI and RW prediction.

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