Re-submitted to JClimate Records of Atlantic basin tropical cyclones (TCs) since the late-19 th Century indicate a very large upward trend in storm frequency. This increase in documented TCs has been previously interpreted as resulting from anthropogenic climate change. However, improvements in observing and recording practices provide an alternative interpretation for these changes: recent studies suggest that the number of potentially missed TCs is sufficient to explain a large part of the recorded increase in TC counts. This study explores the influence of another factor--TC duration--on observed changes in TC frequency, using a widely-used Atlantic TC database: HURDAT. We find that the occurrence of short-lived storms (duration two days or less) in the database has increased dramatically, from less than one per year in the late-19 th /early-20 th Century to about five per year since about 2000, while moderate to long-lived storms have increased little, if at all. Thus, the previously documented increase in total TC frequency since the late 19 th Century in the database is primarily due to an increase in very short-lived TCs.

New objective methods are introduced that use readily available data to estimate various aspects of the two-dimensional surface wind field structure in hurricanes. The methods correlate a variety of wind field metrics to combinations of storm intensity, storm position, storm age, and information derived from geo-stationary satellite infrared (IR) imagery. The first method estimates the radius of maximum wind (RMW) in special cases when a clear symmetric eye is identified in the IR imagery. The second method estimates RMW, and the additional critical wind radii of 34-, 50-, and 64-kt winds for the general case with no IR scene–type constraint. The third method estimates the entire two-dimensional surface wind field inside a storm-centered disk with a radius of 182 km. For each method, it is shown that the inclusion of infrared satellite data measurably reduces error. All of the methods can be transitioned to an operational setting or can be used as a postanalysis tool. 1.

Horizontal winds at 850 hPa from tropical cyclones retrieved using the nonlinear balance equation, where the mass field was determined from Advanced Microwave Sounding Unit (AMSU) temperature soundings, are compared with the surface wind fields derived from NASA’s Quick Scatterometer (QuikSCAT) and Hurricane Research Division H*Wind analyses. It was found that the AMSU-derived wind speeds at 850 hPa have linear relations with the surface wind speeds from QuikSCAT or H*Wind. There are also characteristic biases of wind direction between AMSU and QuikSCAT or H*Wind. Using this information to adjust the speed and correct for the directional bias, a new algorithm was developed for estimation of the tropical cyclone surface wind field from the AMSU-derived 850-hPa winds. The algorithm was evaluated in two independent cases from Hurricanes Floyd (1999) and Michelle (2001), which were observed simulta-neously by AMSU, QuikSCAT, and H*Wind. In this evaluation the AMSU adjustment algorithm for wind speed worked well. Results also showed that the bias correction algorithm for wind direction has room for improvement.

Advanced Microwave Sounding Unit (AMSU) data are used to provide objective estimates of 1-min maximum sustained surface winds, minimum sea level pressure, and the radii of 34-, 50-, and 64-kt (1 kt [ 0.5144 m s21) winds in the northeast, southeast, southwest, and northwest quadrants of tropical cyclones. The algorithms are derived from AMSU temperature, pressure, and wind retrievals from all tropical cyclones in the Atlantic and east Pacific basins during 1999–2001. National Hurricane Center best-track intensity and operational radii estimates are used as dependent variables in a multiple-regression approach. The intensity algorithms are eval-uated for the developmental sample using a jackknife procedure and independent cases from the 2002 hurricane season. Jackknife results for the maximum winds and minimum sea level pressure estimates are mean absolute errors (MAE) of 11.0 kt and 6.7 hPa, respectively, and rmse of 14.1 kt and 9.3 hPa, respectively. For cases with corresponding reconnaissance data, the MAE are 10.7 kt and 6.1 hPa, and the rmse are 14.9 kt and 9.2 hPa. The independent cases for 2002 have errors that are only slightly larger than those from the developmental sample. Results from the jackknife evaluation of the 34-, 50-, and 64-kt radii show mean errors of 30, 24, and 14 n mi, respectively. The results for the independent sample from 2002 are generally comparable to the developmental sample, except for the 64-kt wind radii, which have larger errors. The radii errors for the 2002 sample with aircraft reconnaissance data available are all comparable to the errors from the jackknife sample, including the 64-kt radii.

Geostationary infrared (IR) satellite data are used to provide estimates of the symmetric and total low-level wind fields in tropical cyclones, constructed from estimations of an azimuthally averaged radius of maximum wind (RMAX), a symmetric tangential wind speed at a radius of 182 km (V182), a storm motion vector, and the maximum intensity (VMAX). The algorithm is derived using geostationary IR data from 405 cases from 87 tropical systems in the Atlantic and east Pacific Ocean basins during the 1995–2003 hurricane seasons that had corresponding aircraft data available. The algorithm is tested on 50 cases from seven tropical storms and hurricanes during the 2004 season. Aircraft-reconnaissance-measured RMAX and V182 are used as dependent variables in a multiple linear regression technique, and VMAX and the storm motion vector are estimated using conventional methods. Estimates of RMAX and V182 exhibit mean absolute errors (MAEs) of 27.3 km and 6.5 kt, respectively, for the dependent samples. A modified combined Rankine vortex model is used to estimate the one-dimensional symmetric tangential wind field from VMAX, RMAX, and V182. Next, the storm motion vector is added to the symmetric wind to produce estimates of the total wind field. The MAE of the IR total wind retrievals is 10.4 kt, and the variance explained is 53%, when compared with the two-dimensional wind fields from the aircraft data for the independent cases. 1.

Axisymmetric temperatures and gradient-balanced winds associated with tropical cyclones derived from the Advanced Microwave Sounding Unit are stratified by the 24-h averaged vector difference of the horizontal wind between 200 and 850 hPa (or vertical wind shear). Using 186 total cases that are limited to tropical cyclones with intensities greater than 33 m s21 (or mature) and are located over sea surface temperatures greater than 26.48C, vertical wind shear–based composites are created. Results show that as the vertical wind shear increased, the upper-level warm-core structure associated with the tropical cyclone descended, resulting in a shallower balanced vortex. These observationally based results are presented in the context of recent mesoscale modeling results of the effect of shear on tropical cyclone structure. 1.

Abstract—This letter presents preliminary results concerning the use of new observations from the A-Train Constellation for testing a new technique of remotely sensing hurricane intensity from space based on modeling a hurricane as a balanced, con-vectively neutral vortex. The key observational requirements are simultaneous, accurate measurements of cloud-top height, cloud-top temperature, and cloud profiling information across the center of the storm, although there are ways to bypass the need for cloud-top temperature. In this letter, the Moderate Resolution Imaging Spectroradiometer onboard Aqua provides an estimation of the cloud-top temperature, and the near-simultaneous CloudSat observations provide the essential cloud-top height and cloud pro-filing information. Initial results indicate that the new technique is a promising method for estimating storm intensity when compared post facto to the best track database. Potential uncertainties and room for further refinement of the technique are discussed. Index Terms—Radar applications, radar meteorological fac-tors, satellite applications. I.

atmosphere

A neural network approach for temperature retrieval from AMSU-A measurements onboard NOAA-15 and NOAA-16 satellites and a case study during Gonu cyclone

A neural network approach for temperature retrieval from AMSU-A measurements onboard NOAA-15 and NOAA-16 satellites and a case study during Gonu cyclone Atmósfera, vol. 23, núm. 3, enero, 2010, pp. 225-239