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Peter Vogel, Peter Knippertz, Andreas H. Fink, Andreas Schlueter, and Tilmann Gneiting

more than 10 years ( Haiden et al. 2018 ). A region generally characterized by low forecast skill and high uncertainty is the tropical belt. Haiden et al. (2012) note that 1-day precipitation forecasts at low latitudes have skill similar to 6-day forecasts in the extratropics. Little progress has been made also for free-tropospheric winds in the tropics ( Haiden et al. 2018 ). For variables with large forecast uncertainty, ensemble prediction is of particular importance, even for short ranges

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Ghislain Faure, Philippe Chambon, and Pierre Brousseau

of in situ observations: it makes both the initialization and the validation processes less reliable. While convection-permitting models that run operationally in the tropics become more and more common, their validation is not frequent in scientific literature, except for models dedicated for tropical cyclone forecasting, like HWRF ( Bernardet et al. 2015 ). One of the most comprehensive studies to date is Woodhams et al. (2018) , who characterized the added value of a convection

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K. P. Sooraj, H. Annamalai, Arun Kumar, and Hui Wang

ability to predict tropical climate variations with some success ( Kang and Shukla 2006 ; Kirtman and Pirani 2009 ). Here, we examine the seasonal forecast performance of the National Centers for Environmental Prediction’s (NCEP) Coupled Forecast System (CFS) over the tropics and also over the U.S. Affiliated Pacific Islands (USAPI). The hypothesis that boundary conditions such as sea surface temperature (SST), snow cover, and soil wetness have significant influence on seasonal mean tropical

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Paul W. Miller, Thomas L. Mote, and Craig A. Ramseyer

thermodynamic environments are characterized by greater low-level moisture content, trade-wind inversions, weaker vertical wind shear, and a higher melting level and tropopause. Taken together, these differences serve to alter both the dynamical and microphysical processes active in tropical thunderstorm updrafts compared to their midlatitude counterparts, and diminish the transferability of existing, predominantly midlatitude-centric, convective forecasting techniques to the tropics. For instance, abundant

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K. Fraedrich and L. M. Leslie

SEPTEMBER 1988 NOTES AND CORRESPONDENCE 243NOTES AND CORRESPONDENCEA Minimal Model for the Short-Term Prediction of Rainfall in the Tropics K. FRAEDRICH* AND L. M. LESLIE Bureau of Meteorology Research Centre, Melbourne, Victoria, Australia 8 December 1987 and 10 March 1988 ABSTRACT A "minimal" model is proposed hem for the short-term prediction (up to

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Luis M. Farfán, Rosario Romero-Centeno, and G. B. Raga

B42 version 6, which derives precipitation estimates from various satellite systems and, when possible, from rain gauge data over land ( Huffman et al. 2007 ). The gridded output has spatial resolution of 0.25° × 0.25°. This product provides good coverage over the tropics and has proven to be useful in determining TC contributions over the global basins (e.g., Jiang and Zipser 2010 ). Radar imagery from stations in BCS and Sinaloa is used to document the reflectivity and rain rate, respectively

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Dileep M. Puranik and R. N. Karekar

Abstract

In the present work the locations of precursors to summer thunderstorms over peninsular India are sought in images from the Advanced Microwave Sounding Unit-B (AMSU-B). At these locations, moisture maxima and brightness temperature (BT) minima may be expected. Prior literature suggests that the 150-GHz channel is useful in detecting the BT minima due to moisture in the lowest 1 km, the 183.3 ± 7- GHz channel is useful for detecting middle-level moist layers and clouds, and the other 183.3-GHz channels are useful for upper-air features such as high-level dry air incursion or upper-air troughs. Cloudy or moist pixels and low-emissivity ground pixels have similar BTs. The extraction of the locations of BT minima is therefore difficult. The scale 1 or 2 à trous wavelet transform (WT) allows unambiguous location of the BT minima due to clouds or moist regions from AMSU-B images.

On 3–4 April 2001 there was a middle-level moisture incursion over the peninsula and on 17–18 April 2001 there was an upper-level dry air incursion. The wavelet components of AMSU-B data were extracted during these two events. From the Meteosat-5 infrared images it was verified that convection occurred within 2 h of the AMSU-B pass in the low-BT regions separated by the à trous WT. On the other hand, peninsular discontinuities on 3–4 April 2001 and 7 April 2002 and other days in 2002 showed that useful precursors could not be extracted from the 150-GHz signal. The BTs for the 150-GHz channel in dry air are affected significantly by ground altitude and by changes in surface emissivity. Failure and success in precursor detection are both attributed to the variability in the BTs.

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John P. Cangialosi, Todd B. Kimberlain, John L. Beven II, and Mark Demaria

Abstract

The Dvorak technique is used operationally worldwide for tropical cyclone intensity analysis. This study tests Dvorak intensity change constraints, using a database of simultaneous aircraft and satellite fixes for tropical cyclones (TCs) in the 1998–2012 period. Results indicate that, in the vast majority of cases, Dvorak intensity constraints are valid with only a small percentage of strengthening TCs violating the constraints. Of the small sample that broke the constraints, most had initial intensities ranging from moderately strong tropical storms to minimal hurricanes.

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Elizabeth E. Ebert, Michael Turk, Sheldon J. Kusselson, Jianbin Yang, Matthew Seybold, Peter R. Keehn, and Robert J. Kuligowski

Abstract

Ensemble tropical rainfall potential (eTRaP) has been developed to improve short-range forecasts of heavy rainfall in tropical cyclones. Evolving from the tropical rainfall potential (TRaP), a 24-h rain forecast based on estimated rain rates from microwave sensors aboard polar-orbiting satellites, eTRaP combines all single-pass TRaPs generated within ±3 h of 0000, 0600, 1200, and 1800 UTC to form a simple ensemble. This approach addresses uncertainties in satellite-derived rain rates and spatial rain structures by using estimates from different sensors observing the cyclone at different times. Quantitative precipitation forecasts (QPFs) are produced from the ensemble mean field using a probability matching approach to recalibrate the rain-rate distribution against the ensemble members (e.g., input TRaP forecasts) themselves. ETRaPs also provide probabilistic forecasts of heavy rain, which are potentially of enormous benefit to decision makers. Verification of eTRaP forecasts for 16 Atlantic hurricanes making landfall in the United States between 2004 and 2008 shows that the eTRaP rain amounts are more accurate than single-sensor TRaPs. The probabilistic forecasts have useful skill, but the probabilities should be interpreted within a spatial context. A novel concept of a “radius of uncertainty” compensates for the influence of location error in the probability forecasts. The eTRaPs are produced in near–real time for all named tropical storms and cyclones around the globe. They can be viewed online (http://www.ssd.noaa.gov/PS/TROP/etrap.html) and are available in digital form to users.

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Elizabeth A. Ritchie, Genevieve Valliere-Kelley, Miguel F. Piñeros, and J. Scott Tyo

Abstract

This paper describes results from an improvement to the objective deviation angle variance technique to estimate the intensity of tropical cyclones from satellite infrared imagery in the North Atlantic basin. The technique quantifies the level of organization of the infrared cloud signature of a tropical cyclone as an indirect measurement of its maximum wind speed. The major change described here is to use the National Hurricane Center’s best-track database to constrain the technique. Results are shown for the 2004–10 North Atlantic hurricane seasons and include an overall root-mean-square intensity error of 12.9 kt (6.6 m s−1, where 1 kt = 0.514 m s−1) and annual root-mean-square intensity errors ranging from 10.3 to 14.1 kt. A direct comparison between the previous version and the one reported here shows root-mean-square intensity error improvements in all years with a best improvement in 2009 from 17.9 to 10.6 kt and an overall improvement from 14.8 to 12.9 kt. In addition, samples from the 7-yr period are binned based on level of intensity and on the strength of environmental vertical wind shear as extracted from Statistical Hurricane Intensity Prediction Scheme (SHIPS) data. Preliminary results suggest that the deviation angle variance technique performs best at the weakest intensity categories of tropical storm through hurricane category 3, representing 90% of the samples, and then degrades in performance for hurricane categories 4 and 5. For environmental vertical wind shear, there is far less spread in the results with the technique performing better with increasing vertical wind shear.

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