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J. C. Hess
and
J. B. Eisner

There is considerable interest in forecasting interannual hurricane activity for the Atlantic basin. Various predictors representing different components of the tropical Atlantic climate have been suggested. The choice of predictors is based on previous research into contemporaneous and lag relationships with seasonal hurricane and tropical storm frequency. Past research is divided into five distinct periods: the search for physical relationships, the use of composite charts, the use of satellite imagery and climatology of easterly waves, the emergence of recent ideas, and the development of prediction models. As an historical summary this paper describes the important research contributions in each period leading to our current understanding of yearly hurricane variability. The paper concludes by describing current methods for forecasting this variability and recommends an area for future investigations.

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J. C. Hess
,
J. B. Elsner
, and
N. E. LaSeur

Abstract

This paper demonstrates that improved forecasts of the annual number of hurricanes in the Atlantic tropical basin are possible by separating tropical-only hurricanes from hurricanes influenced by extratropical factors. It is revealed that variables previously shown to have a predictive relationship with the annual number of Atlantic hurricanes have a significantly stronger predictive association with the number of hurricanes formed solely from tropical mechanisms. This stronger relationship exists for extended-range (6-month lead) as well as for short-range (0-month lead) forecast models. Any future study of seasonal hurricane activity over this region should consider tropical-only hurricanes as separate from hurricanes influenced by baroclinic disturbances. The annual number of hurricanes that form or intensify as a result of interactions with baroclinic disturbances appears unrelated to significant tropical or midlatitude atmospheric anomalies and thus should be considered the random component of seasonal hurricane activity, at least until further insights are gained. Indeed, when prediction algorithms are developed to forecast the annual number of Atlantic hurricanes, best hindcast skill results from models that assume a simple average for baroclinically influenced storms. These regression-based forecast models are only marginally better than climatology.

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G. Louis Smith
,
Kory J. Priestley
,
Phillip C. Hess
,
Chris Currey
, and
Peter Spence

Abstract

The Clouds and the Earth’s Radiant Energy System (CERES) instrument is a scanning radiometer for measuring Earth-emitted and -reflected solar radiation to understand Earth’s energy balance. One CERES instrument was placed into orbit aboard the Tropical Rainfall Measuring Mission (TRMM) in 1997; two were aboard the Terra spacecraft, launched in 1999; and two were aboard the Aqua spacecraft, launched in 2002. These measurements are used together with data from higher-resolution instruments to generate a number of data products. The nominal footprint size of the pixel at Earth’s surface is 16 km in the cross-scan direction and 23 km in the scan direction for the TRMM platform and 36 km in the cross-scan direction and 46 km in the scan direction for the Terra and Aqua platforms. It is required that the location on Earth of each pixel be known to 1–2 km to use the CERES data with the higher-resolution instruments on a pixel basis. A technique has been developed to validate the computed geolocation of the measurements by use of coastlines. Scenes are chosen in which the reflected solar radiation changes abruptly from the land surface to the darker ocean surface and the Earth-emitted radiation changes from the warm land to the cool ocean, or vice versa, so that scenes can be detected both day and night. The computed coastline location is then compared with the World Bank II map. The method has been applied to data from the three spacecraft and shows that the pixel geolocations are accurate to within 10% of the pixel size and that the geolocation is adequate for current scientific investigations.

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K. J. Tory
,
M. E. Cope
,
G. D. Hess
,
S. Lee
,
K. Puri
,
P. C. Manins
, and
N. Wong

Abstract

A 4-day photochemical smog event in the Melbourne, Victoria, Australia, region (6–9 March 2001) is examined to assess the performance of the Australian Air Quality Forecasting System (AAQFS). Although peak ozone concentrations measured during this period did not exceed the 1-h national air quality standard of 100 ppb, elevated maximum ozone concentrations in the range of 50–80 ppb were recorded at a number of monitoring stations on all four days. These maximum values were in general very well forecast by the AAQFS. On all but the third day the system predicted the advection of ozone precursors over Port Phillip (the adjacent bay) during the morning, where, later in the day, relatively high ozone concentrations developed. The ozone was advected back inland by bay and sea breezes. On the third day, a southerly component to the background wind direction prevented the precursor drainage over the bay, and the characteristic ozone cycle was disrupted. The success of the system's ability to predict peak ozone at individual monitoring stations was largely dependent on the direction and penetration of the sea and bay breezes, which in turn were dependent on the delicate balance between these winds and the opposing synoptic flow.

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G. D. Hess
,
K. J. Tory
,
M. E. Cope
,
S. Lee
,
K. Puri
,
P. C. Manins
, and
M. Young

Abstract

The performance of the Australian Air Quality Forecasting System (AAQFS) is examined by means of a case study of a 7-day photochemical smog event in the Sydney region. This was the worst smog event for the 2000/ 01 oxidant season, and, because of its prolonged nature, it provided the opportunity to demonstrate the ability of AAQFS to forecast situations involving recirculation of precursors and remnant ozone, fumigation, and complex meteorological dynamics. The forecasting system was able to successfully predict high values of ozone, although at times the peak concentrations for the inland stations were underestimated. The dynamics for the Sydney region require a sensitive balance between the synoptic and mesoscale flows. Often high concentrations of ozone were advected inland by the sea breeze. On two occasions the system forecast a synoptic flow that was too strong, which blocked the inland advancement of the sea breeze. The peak ozone forecasts were underpredicted at the inland stations on those occasions. An examination of possible factors causing forecast errors has indicated that the AAQFS is more sensitive to errors in the meteorological conditions, rather than in the emissions or chemical mechanism in the Sydney region.

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M. E. Cope
,
G. D. Hess
,
S. Lee
,
K. Tory
,
M. Azzi
,
J. Carras
,
W. Lilley
,
P. C. Manins
,
P. Nelson
,
L. Ng
,
K. Puri
,
N. Wong
,
S. Walsh
, and
M. Young

Abstract

The Australian Air Quality Forecasting System (AAQFS) is the culmination of a 3-yr project to develop a numerical primitive equation system for generating high-resolution (1–5 km) short-term (24–36 h) forecasts for the Australian coastal cities of Melbourne and Sydney. Forecasts are generated 2 times per day for a range of primary and secondary air pollutants, including ozone, nitrogen dioxide, carbon monoxide, sulfur dioxide, and particles that are less than 10 μm in diameter (PM10). A preliminary assessment of system performance has been undertaken using forecasts generated over a 3-month demonstration period. For the priority pollutant ozone it was found that AAQFS achieved a coefficient of determination of 0.65 and 0.57 for forecasts of peak daily 1-h concentration in Melbourne and Sydney, respectively. The probability of detection and false-alarm rate were 0.71 and 0.55, respectively, for a 60-ppb forecast threshold in Melbourne. A similar level of skill was achieved for Sydney. System performance is also promising for the primary gaseous pollutants. Further development is required before the system can be used to forecast PM10 confidently, with a systematic overprediction of 24-h PM10 concentration occurring during the winter months.

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