Tropical cyclone rainfall forecasting

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Hurricane QPF Rita5dayqpf.png
Hurricane QPF

Tropical cyclone rainfall forecasting involves using scientific models and other tools to predict the precipitation expected in tropical cyclones such as hurricanes and typhoons. Knowledge of tropical cyclone rainfall climatology is helpful in the determination of a tropical cyclone rainfall forecast. More rainfall falls in advance of the center of the cyclone than in its wake. The heaviest rainfall falls within its central dense overcast and eyewall. Slow moving tropical cyclones, like Hurricane Danny and Hurricane Wilma, can lead to the highest rainfall amounts due to prolonged heavy rains over a specific location. However, vertical wind shear leads to decreased rainfall amounts, as rainfall is favored downshear and slightly left of the center and the upshear side is left devoid of rainfall. The presence of hills or mountains near the coast, as is the case across much of Mexico, Haiti, the Dominican Republic, much of Central America, Madagascar, Réunion, China, and Japan act to magnify amounts on their windward side due to forced ascent causing heavy rainfall in the mountains. A strong system moving through the mid latitudes, such as a cold front, can lead to high amounts from tropical systems, occurring well in advance of its center. Movement of a tropical cyclone over cool water will also limit its rainfall potential. A combination of factors can lead to exceptionally high rainfall amounts, as was seen during Hurricane Mitch in Central America. [1]

Contents

Use of forecast models can help determine the magnitude and pattern of the rainfall expected. Climatology and persistence models, such as r-CLIPER, can create a baseline for tropical cyclone rainfall forecast skill. Simplified forecast models, such as the Kraft technique and the eight and sixteen-inch rules, can create quick and simple rainfall forecasts, but come with a variety of assumptions which may not be true, such as assuming average forward motion, average storm size, and a knowledge of the rainfall observing network the tropical cyclone is moving towards. The forecast method of TRaP assumes that the rainfall structure the tropical cyclone currently has changes little over the next 24 hours. The global forecast model which shows the most skill in forecasting tropical cyclone-related rainfall in the United States is the ECMWF IFS (Integrated Forecasting System). [2] [3]

Rainfall distribution around a tropical cyclone

The relative sizes of Typhoon Tip, Cyclone Tracy, and the United States. Typhoonsizes.jpg
The relative sizes of Typhoon Tip, Cyclone Tracy, and the United States.

A larger proportion of rainfall falls in advance of the center (or eye) than after the center's passage, with the highest percentage falling in the right-front quadrant. A tropical cyclone's highest rainfall rates can lie in the right rear quadrant within a training (non-moving) inflow band. [4] Rainfall is found to be strongest in their inner core, within a degree of latitude of the center, with lesser amounts farther away from the center. Most of the rainfall in hurricanes is concentrated within its radius of gale-force winds. [5] Larger tropical cyclones have larger rain shields, which can lead to higher rainfall amounts farther from the cyclone's center. [5] Storms which have moved slowly, or loop, lead to the highest rainfall amounts. Riehl calculated that 33.97 inches (863 mm) of rainfall per day can be expected within one-half degree, or 35 miles (56 km), of the center of a mature tropical cyclone. [6] Many tropical cyclones progress at a forward motion of 10 knots, which would limit the duration of this excessive rainfall to around one-quarter of a day, which would yield about 8.50 inches (216 mm) of rainfall. This would be true over water, within 100 miles (160 km) of the coastline, [7] and outside topographic features. As a cyclone moves farther inland and is cut off from its supply of warmth and moisture (the ocean), rainfall amounts from tropical cyclones and their remains decrease quickly. [8]

Vertical wind shear

Circulation around the east side of Floyd forcing rainfall near and behind a front to its northeast Floyd1999RadarPANYNJDMP.gif
Circulation around the east side of Floyd forcing rainfall near and behind a front to its northeast

Vertical wind shear forces the rainfall pattern around a tropical cyclone to become highly asymmetric, with most of the precipitation falling to the left and downwind of the shear vector, or downshear left. In other words, southwesterly shear forces the bulk of the rainfall north-northeast of the center. [9] If the wind shear is strong enough, the bulk of the rainfall will move away from the center leading to what is known as an exposed circulation center. When this occurs, the potential magnitude of rainfall with the tropical cyclone will be significantly reduced.

Interaction with frontal boundaries and upper level troughs

As a tropical cyclone interacts with an upper-level trough and the related surface front, a distinct northern area of precipitation is seen along the front ahead of the axis of the upper level trough. Surface fronts with precipitable water amounts of 1.46 inches (37 mm) or more and upper level divergence overhead east of an upper level trough can lead to significant rainfall. [10] This type of interaction can lead to the appearance of the heaviest rainfall falling along and to the left of the tropical cyclone track, with the precipitation streaking hundreds of miles or kilometers downwind from the tropical cyclone. [11]

Mountains

Moist air forced up the slopes of coastal hills and mountain chains can lead to much heavier rainfall than in the coastal plain. [12] This heavy rainfall can lead to landslides, which still cause significant loss of life such as seen during Hurricane Mitch in Central America, where several thousand perished. [13]

Tools used in preparation of forecast

r-CLIPER for Isabel (2003) Isabel2003rcliper.jpg
r-CLIPER for Isabel (2003)

Climatology and persistence

The Hurricane Research Division of the Atlantic Oceanographic and Meteorological Laboratory created the r-CLIPER (rainfall climatology and persistence) model to act as a baseline for all verification regarding tropical cyclone rainfall. The theory is, if the global forecast models cannot beat predictions based on climatology, then there is no skill in their use. There is a definite advantage to using the forecast track with r-CLIPER because it could be run out 120 hours/5 days with the forecast track of any tropical cyclone globally within a short amount of time. [14] The short range variation which uses persistence is the Tropical Rainfall Potential technique (TRaP) technique, which uses satellite-derived rainfall amounts from microwave imaging satellites and extrapolates the current rainfall configuration forward for 24 hours along the current forecast track. [15] This technique's main flaw is that it assumes a steady state tropical cyclone which undergoes little structural change with time, which is why it is only run forward for 24 hours into the future. [16]

GFS for Isabel (2003) GFSisabel2003.jpg
GFS for Isabel (2003)

Numerical weather prediction

Computer models can be used to diagnose the magnitude of tropical cyclone rainfall. Since forecast models output their information on a grid, they only give a general idea as to the areal coverage of moderate to heavy rainfall. No current forecast models run at a small enough grid scale (1 km or smaller) to be able to detect the absolute maxima measured within tropical cyclones. Of the United States forecasting models, the best performing model for tropical cyclone rainfall forecasting is known as the GFS, or Global Forecasting System. [17] The GFDL model has been shown to have a high bias concerning the magnitude of heavier core rains within tropical cyclones. [18] Beginning in 2007, the NCEP Hurricane-WRF became available to help predict rainfall from tropical cyclones. [19] Recent verification shows that both the European ECMWF forecast model and North American Mesoscale Model (NAM) show a low bias with heavier rainfall amounts within tropical cyclones. [20]

Kraft rule

During the late 1950s, this rule of thumb came into being, developed by R. H. Kraft. [21] It was noted from rainfall amounts (in imperial units) reported by the first order rainfall network in the United States that the storm total rainfall fit a simple equation: 100 divided by the speed of motion in knots. [22] This rule works, even in other countries, as long as a tropical cyclone is moving and only the first order or synoptic station network (with observations spaced about 60 miles (97 km) apart) are used to derive storm totals. Canada uses a modified version of the Kraft rule which divides the results by a factor of two, which takes into account the lower sea surface temperatures seen around Atlantic Canada and the prevalence of systems undergoing vertical wind shear at their northerly latitudes. [20] The main problem with this rule is that the rainfall observing network is denser than either the synoptic reporting network or the first order station networks, which means the absolute maximum is likely to be underestimated. Another problem is that it does not take the size of the tropical cyclone or topography into account.

See also

Related Research Articles

<span class="mw-page-title-main">2000 Atlantic hurricane season</span> Hurricane season in the Atlantic Ocean

The 2000 Atlantic hurricane season was a fairly active hurricane season, but featured the latest first named storm in a hurricane season since 1992. The hurricane season officially began on June 1, and ended on November 30. It was slightly above average due to a La Niña weather pattern although most of the storms were weak. It was also the only Season to Include 2 storms in Ireland. The first cyclone, Tropical Depression One, developed in the southern Gulf of Mexico on June 7 and dissipated after an uneventful duration. However, it would be almost two months before the first named storm, Alberto, formed near Cape Verde; Alberto also dissipated with no effects on land. Several other tropical cyclones—Tropical Depression Two, Tropical Depression Four, Chris, Ernesto, Nadine, and an unnamed subtropical storm—did not impact land. Five additional storms—Tropical Depression Nine, Florence, Isaac, Joyce, and Leslie—minimally affected land areas.

<span class="mw-page-title-main">1992 Atlantic hurricane season</span> Hurricane season in the Atlantic Ocean

The 1992 Atlantic hurricane season was a significantly below average season in which only ten tropical or subtropical cyclones formed. Six became named tropical storms, of which four became hurricanes. Among the four was Hurricane Andrew, a major hurricane, and the costliest Atlantic hurricane on record at the time, surpassing Hugo of 1989. The season officially started on June 1 and officially ended on November 30. However, tropical cyclogenesis is possible at any time of the year, as demonstrated by formation in April of an unnamed subtropical storm in the central Atlantic. A June tropical depression caused flooding in Cuba and in Florida, where two people were killed. In August, Andrew struck the Bahamas, Florida, and Louisiana. In all, it caused $27.3 billion in damage, mostly in Florida, as well as 65 fatalities. The greatest impact was in South Florida, where the storm made landfall with 1-minute sustained winds of 175 mph (280 km/h).

<span class="mw-page-title-main">Hurricane Klaus (1990)</span> Category 1 Atlantic hurricane in 1990

Hurricane Klaus was a minimal Atlantic hurricane that dropped heavy rainfall across the Lesser Antilles in October 1990. The eleventh tropical cyclone and sixth hurricane of the 1990 Atlantic hurricane season, Klaus developed from a tropical wave on October 3 a short distance east of Dominica. It drifted northwestward, and quickly intensified to attain hurricane status on October 5. Though its closest approach to the Lesser Antilles was within 12 miles (19 km), the strongest winds remained to its northeast due to strong wind shear, which caused Klaus to steadily weaken. After deteriorating into a tropical depression, Klaus briefly restrengthened over the Bahamas before dissipating on October 9 under the influence of developing tropical storm, Marco.

<span class="mw-page-title-main">Weather Prediction Center</span> United States weather agency

The Weather Prediction Center (WPC), located in College Park, Maryland, is one of nine service centers under the umbrella of the National Centers for Environmental Prediction (NCEP), a part of the National Weather Service (NWS), which in turn is part of the National Oceanic and Atmospheric Administration (NOAA) of the U.S. Government. Until March 5, 2013 the Weather Prediction Center was known as the Hydrometeorological Prediction Center (HPC). The Weather Prediction Center serves as a center for quantitative precipitation forecasting, medium range forecasting, and the interpretation of numerical weather prediction computer models.

<span class="mw-page-title-main">Rainband</span> Cloud and precipitation structure

A rainband is a cloud and precipitation structure associated with an area of rainfall which is significantly elongated. Rainbands can be stratiform or convective, and are generated by differences in temperature. When noted on weather radar imagery, this precipitation elongation is referred to as banded structure. Rainbands within tropical cyclones are curved in orientation. Rainbands of tropical cyclones contain showers and thunderstorms that, together with the eyewall and the eye, constitute a hurricane or tropical storm. The extent of rainbands around a tropical cyclone can help determine the cyclone's intensity.

<span class="mw-page-title-main">Annular tropical cyclone</span> Tropical cyclone with a symmetrical shape

An annular tropical cyclone is a tropical cyclone that features a normal to large, symmetric eye surrounded by a thick and uniform ring of intense convection, often having a relative lack of discrete rainbands, and bearing a symmetric appearance in general. As a result, the appearance of an annular tropical cyclone can be referred to as akin to a tire or doughnut. Annular characteristics can be attained as tropical cyclones intensify; however, outside the processes that drive the transition from asymmetric systems to annular systems and the abnormal resistance to negative environmental factors found in storms with annular features, annular tropical cyclones behave similarly to asymmetric storms. Most research related to annular tropical cyclones is limited to satellite imagery and aircraft reconnaissance as the conditions thought to give rise to annular characteristics normally occur over open water, well removed from landmasses where surface observations are possible.

<span class="mw-page-title-main">Tropical cyclone rainfall climatology</span>

A tropical cyclone rainfall climatology is developed to determine rainfall characteristics of past tropical cyclones. A tropical cyclone rainfall climatology can be used to help forecast current or upcoming tropical cyclone impacts. The degree of a tropical cyclone rainfall impact depends upon speed of movement, storm size, and degree of vertical wind shear. One of the most significant threats from tropical cyclones is heavy rainfall. Large, slow moving, and non-sheared tropical cyclones produce the heaviest rains. The intensity of a tropical cyclone appears to have little bearing on its potential for rainfall over land, but satellite measurements over the last several years show that more intense tropical cyclones produce noticeably more rainfall over water. Flooding from tropical cyclones remains a significant cause of fatalities, particularly in low-lying areas.

<span class="mw-page-title-main">Tropical cyclone forecast model</span> Computer program that uses meteorological data to forecast tropical cyclones

A tropical cyclone forecast model is a computer program that uses meteorological data to forecast aspects of the future state of tropical cyclones. There are three types of models: statistical, dynamical, or combined statistical-dynamic. Dynamical models utilize powerful supercomputers with sophisticated mathematical modeling software and meteorological data to calculate future weather conditions. Statistical models forecast the evolution of a tropical cyclone in a simpler manner, by extrapolating from historical datasets, and thus can be run quickly on platforms such as personal computers. Statistical-dynamical models use aspects of both types of forecasting. Four primary types of forecasts exist for tropical cyclones: track, intensity, storm surge, and rainfall. Dynamical models were not developed until the 1970s and the 1980s, with earlier efforts focused on the storm surge problem.

<span class="mw-page-title-main">Rapid intensification</span> Sudden, violent increase in a tropical cyclones severity

Rapid intensification (RI) is any process wherein a tropical cyclone strengthens dramatically in a short period of time. Tropical cyclone forecasting agencies utilize differing thresholds for designating rapid intensification events, though the most widely-used definition stipulates an increase in the maximum sustained winds of a tropical cyclone of at least 30 knots in a 24-hour period. However, periods of rapid intensification often last longer than a day. About 20–30% of all tropical cyclones undergo rapid intensification, including a majority of tropical cyclones with peak wind speeds exceeding 51 m/s.

<span class="mw-page-title-main">Tropical Storm Alberto (2006)</span> Atlantic tropical cyclone

Tropical Storm Alberto was the first tropical storm of the 2006 Atlantic hurricane season. Forming on June 10 in the northwestern Caribbean, the storm moved generally to the north, reaching a maximum intensity of 70 mph (110 km/h) before weakening and moving ashore in the Big Bend area of Florida on June 13. Alberto then moved through eastern Georgia, North Carolina, and Virginia as a tropical depression before becoming extratropical on June 14.

<span class="mw-page-title-main">Tropical Storm Marco (1990)</span> 1990 North Atlantic tropical storm

Tropical Storm Marco was the only tropical cyclone to make landfall on the United States during the 1990 Atlantic hurricane season. The 13th named storm of the season, Marco formed from a cold-core low pressure area along the northern coast of Cuba on October 9, and tracked northwestward through the eastern Gulf of Mexico. With most of its circulation over the western portion of Florida, Tropical Storm Marco produced 65 mph (105 km/h) winds over land. However, it weakened to a tropical depression before moving ashore near Cedar Key. The cyclone combined with a cold front and the remnants of Hurricane Klaus to produce heavy rainfall in Georgia and the Carolinas. After interacting with the nearby Hurricane Lili, Marco continued northward until being absorbed by a cold front on October 13.

<span class="mw-page-title-main">United States tropical cyclone rainfall climatology</span>

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<span class="mw-page-title-main">Tropical cyclone forecasting</span> Science of forecasting how a tropical cyclone moves and its effects

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<span class="mw-page-title-main">Tropical cyclone track forecasting</span> Predicting where a tropical cyclone is going to track over the next five days, every 6 to 12 hours

Tropical cyclone track forecasting involves predicting where a tropical cyclone is going to track over the next five days, every 6 to 12 hours. The history of tropical cyclone track forecasting has evolved from a single-station approach to a comprehensive approach which uses a variety of meteorological tools and methods to make predictions. The weather of a particular location can show signs of the approaching tropical cyclone, such as increasing swell, increasing cloudiness, falling barometric pressure, increasing tides, squalls and heavy rainfall.

<span class="mw-page-title-main">Quantitative precipitation forecast</span> Expected amount of melted precipitation

The quantitative precipitation forecast is the expected amount of melted precipitation accumulated over a specified time period over a specified area. A QPF will be created when precipitation amounts reaching a minimum threshold are expected during the forecast's valid period. Valid periods of precipitation forecasts are normally synoptic hours such as 00:00, 06:00, 12:00 and 18:00 GMT. Terrain is considered in QPFs by use of topography or based upon climatological precipitation patterns from observations with fine detail. Starting in the mid-to-late 1990s, QPFs were used within hydrologic forecast models to simulate impact to rivers throughout the United States. Forecast models show significant sensitivity to humidity levels within the planetary boundary layer, or in the lowest levels of the atmosphere, which decreases with height. QPF can be generated on a quantitative, forecasting amounts, or a qualitative, forecasting the probability of a specific amount, basis. Radar imagery forecasting techniques show higher skill than model forecasts within 6 to 7 hours of the time of the radar image. The forecasts can be verified through use of rain gauge measurements, weather radar estimates, or a combination of both. Various skill scores can be determined to measure the value of the rainfall forecast.

<span class="mw-page-title-main">Hurricane Flossie (2007)</span> Category 4 Pacific hurricane in 2007

Hurricane Flossie was a powerful Pacific tropical cyclone that brought squally weather and light damage to Hawaii in August 2007. The sixth named storm, second hurricane, first and only major hurricane of the inactive 2007 Pacific hurricane season, Flossie originated from a tropical wave that emerged off Africa on July 21. After traversing the tropical Atlantic, the wave crossed Central America and entered the eastern Pacific on August 1. There, a favorable environment allowed it to become a tropical depression and a tropical storm shortly thereafter on August 8.

The following outline is provided as an overview of and topical guide to tropical cyclones:

<span class="mw-page-title-main">Meteorological history of Hurricane Florence</span>

The meteorological history of Hurricane Florence spanned 22 days from its inception on August 28, 2018, to its dissipation on September 18. Originating from a tropical wave over West Africa, Florence quickly organized upon its emergence over the Atlantic Ocean. Favorable atmospheric conditions enabled it to develop into a tropical depression on August 31 just south of the Cape Verde islands. Intensifying to a tropical storm the following day, Florence embarked on a west-northwest to northwest trajectory over open ocean. Initially being inhibited by increased wind shear and dry air, the small cyclone took advantage of a small area of low shear and warm waters. After achieving hurricane strength early on September 4, Florence underwent an unexpected period of rapid deepening through September 5, culminating with it becoming a Category 4 hurricane on the Saffir-Simpson scale. Thereafter, conditions again became unfavorable and the hurricane quickly diminished to a tropical storm on September 7.

References

  1. Federal Emergency Management Agency. Are You Ready? Archived 2006-06-29 at the Wayback Machine Retrieved on 2006-04-05.
  2. "Tropical Cyclone Guidance".
  3. "US forecast models have been pretty terrible during Hurricane Irma". 8 September 2017.
  4. Ivan Ray Tannehill. Hurricanes. Princeton University Press: Princeton, 1942. Pages 70-76.
  5. 1 2 Corene J. Matyas. Relating Tropical Cyclone Rainfall Patterns to Storm Size. Retrieved on 2007-02-14.
  6. Herbert Riehl. Tropical Meteorology. McGraw-Hill Book Company, Inc.: New York, 1954. Pages 293-297.
  7. Russell Pfost. Tropical Cyclone Quantitative Precipitation Forecasting. Retrieved on 2007-02-25.
  8. Roth, David M (May 12, 2022). "Maximum Rainfall caused by North Atlantic and Northeast Pacific Tropical Cyclones and their remnants Per State (1950–2020)". Tropical Cyclone Rainfall. United States Weather Prediction Center. Retrieved January 6, 2023.PD-icon.svg This article incorporates text from this source, which is in the public domain .
  9. Shuyi S. Chen, John A. Knaff, and Frank D. Marks, Jr. Effects of Vertical Wind Shear and Storm Motion on Tropical Cyclone Rainfall Asymmetries Deduced from TRMM. Retrieved on 2007-03-28.
  10. Norman W. Junker. Original Maddox et al. MCS archetypes associated with flash flooding. Retrieved on 2007-06-24.
  11. Norman W. Junker. Hurricanes and extreme rainfall. Retrieved on 2006-02-13.
  12. Yuh-Lang Lin, S. Chiao, J. A. Thurman, D. B. Ensley, and J. J. Charney. Some Common Ingredients for heavy Orographic Rainfall and their Potential Application for Prediction. Retrieved on 2007-04-26.
  13. John L. Guiney and Miles B. Lawrence. Hurricane Mitch. Retrieved on 2007-04-26.
  14. Frank Marks. GPM and Tropical Cyclones. Archived 2006-10-06 at the Wayback Machine Retrieved on 2007-03-15.
  15. Elizabeth Ebert, Sheldon Kusselson, and Michael Turk. Validation of Tropical Rainfall Potential (TRaP) Forecasts for Australian Tropical Cyclones. Retrieved on 2007-03-28.
  16. Stanley Q. Kidder, Sheldon J. Kusselson, John A. Knaff, and Robert J. Kuligowski. Improvements to the Experimental Tropical Rainfall Potential (TRaP) Technique. Archived 2007-08-17 at the Wayback Machine Retrieved on 2007-03-15.
  17. Timothy P. Marchok, Robert F. Rogers, and Robert E. Tuleya. Improving the Validation and Prediction of Tropical Cyclone Rainfall. Archived 2006-10-10 at the Wayback Machine Retrieved on 2007-03-15.
  18. Robert E. Tuleya, Mark DeMaria, and Robert J. Kuligowski. Evaluation of GFDL and Simple Statistical Model Rainfall Forecasts for U. S. Landfalling Tropical Storms.
  19. WRF Program Coordinator. Monthly Report of the WRF Program Coordinator. Archived 2007-10-11 at the Wayback Machine Retrieved on 2007-04-10.
  20. 1 2 David M. Roth Tropical Cyclone Rainfall (July 2007 presentation). Retrieved on 2009-05-07.
  21. Frank Marks. WSR-88D Derived Rainfall Distributions in Hurricane Danny (1997). Retrieved on 2007-04-13.
  22. Norman W. Junker. Hurricanes and Extreme Rainfall. Retrieved on 2007-03-15.