1. Possible impacts of improved GOES-R temporal resolution on tropical cyclone intensity estimates INTRODUCTION The Advanced Baseline imager (ABI) on GOES-R will include new spectral channels, improved horizontal resolution, and increased temporal resolution (5-15 min interval imagery, with higher resolution in critical areas) compared to current operational GOES imagers. These upgrades could lead to improvements in tropical cyclone (TC) intensity estimates provided by the manual (Dvorak 1984) and automated (Olander and Velden 2007) versions of the Dvorak technique. The automated version makes heavy use of temporal averaging, so it may be especially sensitive to the increases in imagery that will be provided by the ABI. Zehr et al. (2006) examined the possible impacts of the improved spatial resolution on the manual technique and an earlier version of the automated technique. They found that in a few cases the increased spatial resolution could impact the Dvorak intensity estimates. However, the overall impact would be minor. This study follows up on the Zehr et al. study by examining the impact of the increased temporal resolution on the Advanced Dvorak Technique (ADT) developed by Olander and Velden (2007). SUMMARY AND FUTURE PLANS THE DVORAK TECHNIQUE ADVANCED DVORAK TECHNIQUE REFERENCES John L. Beven II 2, Christopher Velden 1, and T. L. Olander 1 1 Univ. of Wisconsin/CIMSS, Madison, Wisconsin 2 Tropical Prediction Center/National Hurricane Center, Miami, Florida The Dvorak (1984) Technique (DT) estimates the intensity of TCs and pre-TC disturbances through subjective ‘measurements’ of convective cloud patterns processed through a set of rules. The cloud patterns (Fig. 1) include curved band (used with both visible (VIS) and standard infrared window (IR) imagery), shear (VIS and IR), the CDO pattern (VIS), the embedded center pattern (IR), and the eye pattern (VIS and IR). Primary parameters used to measure the cloud patterns include amount of convective curvature, the shear distance from the convection to the center, the size of the central convective feature, and the cloud temperatures of the eyewall and eye. Figure 2. Flowchart of ADT outlining all steps involved in the derivation of a TC intensity estimate. The Advanced Dvorak Technique (ADT), developed at the University of Wisconsin-Madison/Cooperative Institute for Meteorological Satellite Studies (UW-CIMSS), is an objective, computer-based algorithm designed to estimate TC intensity using geostationary IR imagery. The ADT is based upon the original DT, but employs various new analysis techniques and rules to advance beyond the scope defined in the original DT. It provides TC forecasters with a fast and reliable tool to assess TC intensity objectively, and to augment DT usage. An ADT outline is shown in Figure 2. The ADT relies on accurate TC center position determination (manually or automated; using an official TC forecast in conjunction with state-of-the-art image analysis routines) to assess the current TC intensity. Once determined, the ADT derives the “scene type” from the convective cloud patterns similar to those in the DT (curved band, shear, CDO/Embedded Center, and Eye). The satellite data used in this study are from Atlantic Hurricane Emily of 2005 (Beven et al 2008), during the NASA Tropical Cloud Systems and Processes (TCSP) experiment. It is comprised of digital IR imagery collected by GOES-11 from 14-21 July at 5- to 15-min. time intervals. The 5-min data is used as a proxy for the upcoming capability of the GOES-R ABI. During the study period, Emily underwent fluctuations in intensity, including a peak intensity 140 kt near 0000 UTC 17 July (Fig. 3). This makes it a good case to test the ADT on high temporal resolution data. However, there are three limitations in the data set: 1) The data are not at a uniform 5-min temporal resolution, 2) There are large gaps in the data on 15-16 July and again on 17 July, and 3) Emily made landfall on the Yucatan Peninsula of Mexico on 18 July, which caused a third large gap in the ADT measurements (ADT does not provide estimates over land). ADT intensity estimates using 30-min and 5-min data were compared to 59 coincident intensities derived from in situ reconnaissance data, with the results shown in Table 1. The use of the 5-min data produced lower root-mean- square (RMS) and average errors compared to the aircraft, with the RMS error improved by 0.5 kt and the average error by almost 1 kt. Figure 3. GOES-11 IR imagery of Hurricane Emily at 0005 UTC 17 July (left) and 0005 UTC 18 July 2005 (right). The images use the Dvorak BD enhancement. Table 1. Root-mean-square and average errors (kt) for 30-min and 5- min ADT intensity estimates for Hurricane Emily. Five-min data collected from GOES-11 during the TCSP experiment was used as a proxy for the GOES-R ABI in an experiment to determine the effects of high temporal resolution imagery on TC intensity estimates from the ADT algorithm. The one-case results suggest that the 5-min data have the potential for a small but positive impact on the accuracy of the estimates. It is necessary to examine additional cases to see if similar results can be obtained, especially for TCs where the entire life cycle can be sampled with the ADT. Good candidate cases would include Katrina and Rita of 2005 (Beven et al. 2008), both of which spent their life cycles in the CONUS rapid scan area of GOES-12. Beven, J. L., L. A. Avila, E. S. Blake, D. P. Brown, J. L. Franklin, R. D. Knabb, R. J. Pasch, J. R. Rhome, and Stacy R. Stewart, 2008: Atlantic Hurricane Season of 2005. Mon. Wea. Rev., 136, (accepted). Dvorak, V. E., 1984: Tropical cyclone intensity analysis using satellite data. NOAA Tech. Rep. NESDIS 11, National Oceanographic and Atmospheric Administration, Washington, DC, 47 pp. Olander, T. L., and C. S. Velden, 2007: The Advanced Dvorak Technique: Continued development of an objective scheme to estimate tropical cyclone intensity using geostationary infrared satellite imagery. Wea. and For., 22, 287-298. Zehr, R., J. L. Beven, and M. DeMaria, 2006: Analysis of high resolution infrared images of hurricanes from polar satellites as a proxy for GOES-R. Poster presented at the Fourth GOES Users Conference, Broomfield, CO. Figure 1. Schematic of cloud pattern types and intensities of the Dvorak technique. From Dvorak (1984) Since the correlation between the cloud patterns and TC intensity is not perfect, the technique includes a set of rules or constraints on how fast the estimated intensity can change. These rules include limits on how quickly the intensity can be increased during intensification, as well as limits on how quickly the intensity can be reduced during weakening. Operationally, the Dvorak Technique is typically employed every 6 h during the TC lifecycle. The output is in the form of a T-Number (T#) and Current Intensity (CI) number that are related to winds and pressure through empirically- derived tables. The technique has a track record for being generally accurate compared to ground truth data, and it is used at TC warning centers worldwide. However, it is somewhat subjective and manpower intensive. Thus, an objective and automated version of the technique has evolved since first being mentioned in Dvorak (1984). DATA SET AND RESULTS RMS Error (kt) Average Error (kt)# of Cases 30-min CI#14.1211.8559 5-min CI#13.6210.9959 It should be noted that the RMS and average errors are both fairly large – close to 1 category on the Saffir-Simpson Hurricane Scale. This is partially due to the gaps in the GOES-11 data set, which are known to cause problems for the time-averaging schemes of the ADT. This should be less of an issue with GOES-R, where the data gaps should be much smaller or non-existent. Once the scene type is selected, the initial intensity (Raw T#) is derived from various measured IR parameters specific to each scene type. After various DT intensity change constraints (adjusted Raw T#) and a time- averaging scheme (Final T#) have been applied, the final Current Intensity (CI#) is derived using several additional DT rules. Pressure and wind estimates are then derived from the CI# as is done with the DT. The accuracy of the automated ADT intensity estimates has been proven to be “on par” with the subjective DT estimates.