1. Spatiotemporal Evolution of Moisture Anomalies Fig. 3: Time-height cross sections of 500 km by 500 km box-averaged normalized (σ; contoured every 0.1σ from -0.3σ to 0.3σ excluding 0.0σ) and raw latent energy anomalies (J kg −1 ; shaded) for typhoon strength TCs. The inset figure provides a zoomed in view of the latent energy anomalies in the lower troposphere for four weeks following TC passage. The values following the word MAX (MIN) represent the maximum (minimum) raw and maximum (minimum) normalized latent energy anomalies. Spatiotemporal Evolution of Moisture Anomalies Fig. 3: Time-height cross sections of 500 km by 500 km box-averaged normalized (σ; contoured every 0.1σ from -0.3σ to 0.3σ excluding 0.0σ) and raw latent energy anomalies (J kg −1 ; shaded) for typhoon strength TCs. The inset figure provides a zoomed in view of the latent energy anomalies in the lower troposphere for four weeks following TC passage. The values following the word MAX (MIN) represent the maximum (minimum) raw and maximum (minimum) normalized latent energy anomalies. Example of the Construction of a Storm-Relative Grid Fig. 1: An example of a storm-relative grid (gray shading) constructed for Western North Pacific TC Yuri (1991) from Best-Track data. The track of TC Yuri is represented by the black line with the 0000 UTC positions of TC Yuri denoted by the filled circles. The storm-relative grid is centered in space and time on the 0000 UTC 27 November 1991 TC position which is denoted by the black star for 50 days prior through 50 days after TC passage. The process is then repeated for all 6-h Best- Track data points with all storm-relative grids for typhoon strength TCs eventually averaged together to obtain the composite grids. Example of the Construction of a Storm-Relative Grid Fig. 1: An example of a storm-relative grid (gray shading) constructed for Western North Pacific TC Yuri (1991) from Best-Track data. The track of TC Yuri is represented by the black line with the 0000 UTC positions of TC Yuri denoted by the filled circles. The storm-relative grid is centered in space and time on the 0000 UTC 27 November 1991 TC position which is denoted by the black star for 50 days prior through 50 days after TC passage. The process is then repeated for all 6-h Best- Track data points with all storm-relative grids for typhoon strength TCs eventually averaged together to obtain the composite grids. Spatiotemporal Evolution of Temperature Anomalies Fig. 4: As in Fig. 3, but for normalized (σ; contoured every 0.1σ from -0.3σ to 0.3σ excluding 0.0σ) and raw internal energy anomalies (J kg −1 ; shaded). Spatiotemporal Evolution of Temperature Anomalies Fig. 4: As in Fig. 3, but for normalized (σ; contoured every 0.1σ from -0.3σ to 0.3σ excluding 0.0σ) and raw internal energy anomalies (J kg −1 ; shaded). An Analysis of the Local Environmental Memory of Tropical Cyclone Passage Benjamin A. Schenkel (benschenkel@gmail.com) and Robert E. Hart (rhart@fsu.edu) Department of Earth, Ocean, and Atmospheric Science, The Florida State University Introduction Every year approximately 60 tropical cyclones (TCs) occur in the Northern Hemisphere (e.g., Frank 2007) sweeping out over 40% of the sea surface from the equator to 35°N (assuming a 500 km storm swath and ignoring track overlap; Hart 2011). Previous research has shown that TCs can cool sea surface temperatures (SSTs) for over a month following TC passage (e.g., Schenkel and Hart 2010) playing a potentially significant aggregate role in oceanic meridional heat transport (e.g., Emanuel 2001). While prior work has quantified the SST response to TC passage, the atmospheric environmental impacts of TCs have yet to be fully fleshed out. The question remains as to what role, if any, do TCs play in both the local and large scale redistribution of energy within the atmosphere. Building upon the foundation provided by prior work (e.g., Hart et al. 2007), the following study seeks to quantify the spatiotemporal scales of the impacts of TCs on the local SSTs and local atmospheric environment and analyze the processes responsible for the generation and restoration of the atmospheric anomalies. Introduction Every year approximately 60 tropical cyclones (TCs) occur in the Northern Hemisphere (e.g., Frank 2007) sweeping out over 40% of the sea surface from the equator to 35°N (assuming a 500 km storm swath and ignoring track overlap; Hart 2011). Previous research has shown that TCs can cool sea surface temperatures (SSTs) for over a month following TC passage (e.g., Schenkel and Hart 2010) playing a potentially significant aggregate role in oceanic meridional heat transport (e.g., Emanuel 2001). While prior work has quantified the SST response to TC passage, the atmospheric environmental impacts of TCs have yet to be fully fleshed out. The question remains as to what role, if any, do TCs play in both the local and large scale redistribution of energy within the atmosphere. Building upon the foundation provided by prior work (e.g., Hart et al. 2007), the following study seeks to quantify the spatiotemporal scales of the impacts of TCs on the local SSTs and local atmospheric environment and analyze the processes responsible for the generation and restoration of the atmospheric anomalies. Data and Methods In this study, the impact of TCs on their atmospheric and oceanic environment is examined using 500 km by 500 km box-averaged storm- relative composites. Typhoon strength TCs (10-m wind speed  64 kt) equatorward of 36ºN from 1982 to 2009 in the Western North Pacific (N = 477 distinctly named TCs) are chosen for study. The intensity and position of the TCs is obtained from the JTWC Best-Track dataset (Chu et al. 2002). Storm-relative composites of SSTs are constructed from the daily 0.25° x 0.25° NASA Optimal Interpolation (OI) SST dataset (Reynolds et al. 2007) and atmospheric composites are calculated using the 6-h 0.5° x 0.5° NCEP Climate Forecast System Reanalysis (CFSR; Saha et al. 2010). The CFSR is chosen to represent the atmospheric environment given that it has the most robust depiction of TC intensity and TC position relative to other atmospheric reanalyses (Schenkel and Hart 2012). Composites are computed from 50 days prior to 50 days after TC passage at 1 day intervals for all variables from the surface to 50 hPa. The figures to follow primarily consist of anomalies and normalized anomalies (anomalies divided by the climatological standard deviation) computed relative to a 6-h climatology from 1982 to 2009. In light of the preference of typhoon strength TCs to occur during El Niño, TC-induced anomalies are considered to be significant when the anomalies are 0.2σ greater than the pre-storm state (average of anomalies from day 38 to day 8 prior to TC passage). A threshold of 0.2σ is chosen because it is both significant at the 95% confidence level according to a Student’s t-test while being equivalent in magnitude to anomalies associated with larger scale phenomena (e.g., Madden Julian Oscillation) known to have significant impacts upon the atmosphere and ocean. To attribute anomalies to physical processes, vertically integrated total energy budgets are computed similar to Trenberth (1997): where p s is the surface pressure, p t is the uppermost limit of the integral (50 hPa), c v is the specific heat capacity of air at constant volume, T is the temperature, u is the zonal wind, v is the meridional wind, L v is the latent heat of vaporization, q is the mixing ratio, g is the gravitational constant, z is the geopotential height, R t is the net downward top of the atmosphere radiative flux, and F sfc is the net upward surface flux. We define total energy (TE) as the sum of internal energy, kinetic energy, latent energy, and potential energy. F sfc can be further broken down into three components: upward surface latent heat flux (LE), upward surface sensible heat flux (H s ), and the upward net surface radiative flux (-R s ). Finally, although these budgets will not be closed, they should provide a relative estimate of the salient processes responsible for anomaly generation. Data and Methods In this study, the impact of TCs on their atmospheric and oceanic environment is examined using 500 km by 500 km box-averaged storm- relative composites. Typhoon strength TCs (10-m wind speed  64 kt) equatorward of 36ºN from 1982 to 2009 in the Western North Pacific (N = 477 distinctly named TCs) are chosen for study. The intensity and position of the TCs is obtained from the JTWC Best-Track dataset (Chu et al. 2002). Storm-relative composites of SSTs are constructed from the daily 0.25° x 0.25° NASA Optimal Interpolation (OI) SST dataset (Reynolds et al. 2007) and atmospheric composites are calculated using the 6-h 0.5° x 0.5° NCEP Climate Forecast System Reanalysis (CFSR; Saha et al. 2010). The CFSR is chosen to represent the atmospheric environment given that it has the most robust depiction of TC intensity and TC position relative to other atmospheric reanalyses (Schenkel and Hart 2012). Composites are computed from 50 days prior to 50 days after TC passage at 1 day intervals for all variables from the surface to 50 hPa. The figures to follow primarily consist of anomalies and normalized anomalies (anomalies divided by the climatological standard deviation) computed relative to a 6-h climatology from 1982 to 2009. In light of the preference of typhoon strength TCs to occur during El Niño, TC-induced anomalies are considered to be significant when the anomalies are 0.2σ greater than the pre-storm state (average of anomalies from day 38 to day 8 prior to TC passage). A threshold of 0.2σ is chosen because it is both significant at the 95% confidence level according to a Student’s t-test while being equivalent in magnitude to anomalies associated with larger scale phenomena (e.g., Madden Julian Oscillation) known to have significant impacts upon the atmosphere and ocean. To attribute anomalies to physical processes, vertically integrated total energy budgets are computed similar to Trenberth (1997): where p s is the surface pressure, p t is the uppermost limit of the integral (50 hPa), c v is the specific heat capacity of air at constant volume, T is the temperature, u is the zonal wind, v is the meridional wind, L v is the latent heat of vaporization, q is the mixing ratio, g is the gravitational constant, z is the geopotential height, R t is the net downward top of the atmosphere radiative flux, and F sfc is the net upward surface flux. We define total energy (TE) as the sum of internal energy, kinetic energy, latent energy, and potential energy. F sfc can be further broken down into three components: upward surface latent heat flux (LE), upward surface sensible heat flux (H s ), and the upward net surface radiative flux (-R s ). Finally, although these budgets will not be closed, they should provide a relative estimate of the salient processes responsible for anomaly generation. Quantifying the SST Memory of TC Passage Fig. 2: Time series of 500 km by 500 km box-averaged composites of NASA OI SST anomalies (K) for typhoon strength TCs (10-m wind speed  64 kt). The blue line denotes the mean SST anomalies while the blue shading denotes the 95% confidence interval of the mean. The gray shading represents the period over which the SST anomalies are significant relative to the pre-storm state. Quantifying the SST Memory of TC Passage Fig. 2: Time series of 500 km by 500 km box-averaged composites of NASA OI SST anomalies (K) for typhoon strength TCs (10-m wind speed  64 kt). The blue line denotes the mean SST anomalies while the blue shading denotes the 95% confidence interval of the mean. The gray shading represents the period over which the SST anomalies are significant relative to the pre-storm state. Spatiotemporal Evolution of Total Energy Anomalies Fig. 5: As in Fig. 3, but for normalized (σ; contoured every 0.1σ from -0.3σ to 0.3σ excluding 0.0σ) and raw total energy anomalies (J kg −1 ; shaded). Spatiotemporal Evolution of Total Energy Anomalies Fig. 5: As in Fig. 3, but for normalized (σ; contoured every 0.1σ from -0.3σ to 0.3σ excluding 0.0σ) and raw total energy anomalies (J kg −1 ; shaded). Discussion The composites exhibit a significant response to typhoon strength TCs both within the atmosphere and ocean (Fig. 8). SST composites show anomalies with maximum magnitudes of 0.73°C with significant anomalies lasting for four to five weeks following TC occurrence (Fig. 2). The impacts of the anomalously cool SSTs extend to the atmospheric environment helping to yield a significant stabilization of the environment by both drying (Fig. 3) and cooling (Fig. 4) the lower troposphere partially due to a reduction in sea surface fluxes. Of the four types of energy composing total energy, latent energy is found to be most anomalous in a raw sense (Fig. 3) while internal energy anomalies are found to be strongest in a normalized sense (Fig. 4). The most significant atmospheric environmental response is found for surface internal energy anomalies (Fig. 4) with substantial values lasting between three to four weeks after TC passage. Due to the dominance of latent energy and internal energy, total energy anomalies (Fig. 5) are found to be most significant in the lower troposphere lasting two to three weeks after TC occurrence. Total energy budgets reveal that the anomalous stabilization of the environment is due to a vertically integrated flux divergence of total energy from the column and a reduction in surface fluxes (Fig. 6). The initial vertically integrated flux divergence of total energy primarily results from a strong lower tropospheric divergence of heat and moisture. Eventually, a reduction in the export of low level heat and moisture from the column yields a flux convergence of total energy due to the dominance of potential energy and sensible heat imports in the upper troposphere perhaps suggesting that the flux divergence term is partly responsible for the restoration of atmospheric anomalies back to climatology. With regards to the surface fluxes, significant anomalies due to the TC- induced SST cold wake are found to last only one to two weeks following TC occurrence (Fig. 7). Latent heat fluxes are found to have the strongest raw contribution to the surface flux anomalies although surface sensible heat fluxes are found to be just as large in a normalized sense. In their totality, these results are among the first to suggest that TCs serve as energy sinks within the tropics yielding significant anomalies within both the atmosphere and ocean for several weeks following TC passage. Discussion The composites exhibit a significant response to typhoon strength TCs both within the atmosphere and ocean (Fig. 8). SST composites show anomalies with maximum magnitudes of 0.73°C with significant anomalies lasting for four to five weeks following TC occurrence (Fig. 2). The impacts of the anomalously cool SSTs extend to the atmospheric environment helping to yield a significant stabilization of the environment by both drying (Fig. 3) and cooling (Fig. 4) the lower troposphere partially due to a reduction in sea surface fluxes. Of the four types of energy composing total energy, latent energy is found to be most anomalous in a raw sense (Fig. 3) while internal energy anomalies are found to be strongest in a normalized sense (Fig. 4). The most significant atmospheric environmental response is found for surface internal energy anomalies (Fig. 4) with substantial values lasting between three to four weeks after TC passage. Due to the dominance of latent energy and internal energy, total energy anomalies (Fig. 5) are found to be most significant in the lower troposphere lasting two to three weeks after TC occurrence. Total energy budgets reveal that the anomalous stabilization of the environment is due to a vertically integrated flux divergence of total energy from the column and a reduction in surface fluxes (Fig. 6). The initial vertically integrated flux divergence of total energy primarily results from a strong lower tropospheric divergence of heat and moisture. Eventually, a reduction in the export of low level heat and moisture from the column yields a flux convergence of total energy due to the dominance of potential energy and sensible heat imports in the upper troposphere perhaps suggesting that the flux divergence term is partly responsible for the restoration of atmospheric anomalies back to climatology. With regards to the surface fluxes, significant anomalies due to the TC- induced SST cold wake are found to last only one to two weeks following TC occurrence (Fig. 7). Latent heat fluxes are found to have the strongest raw contribution to the surface flux anomalies although surface sensible heat fluxes are found to be just as large in a normalized sense. In their totality, these results are among the first to suggest that TCs serve as energy sinks within the tropics yielding significant anomalies within both the atmosphere and ocean for several weeks following TC passage. Attributing Total Energy Anomalies to Physical Processes Fig. 6: Time series of 500 km by 500 km box-averaged anomalous vertically integrated raw total energy time tendency (W m −2 ) for typhoon strength TCs. The blue line represents the Eulerian time tendency of total energy, the red line represents the flux convergence of total energy, the green line represents the top of the atmosphere radiative flux anomalies, and the orange line represents the net upward surface flux. The shading denotes the 95% confidence interval of the mean. The y-axis is broken in two places to more clearly highlight the anomalies occurring after TC passage. Attributing Total Energy Anomalies to Physical Processes Fig. 6: Time series of 500 km by 500 km box-averaged anomalous vertically integrated raw total energy time tendency (W m −2 ) for typhoon strength TCs. The blue line represents the Eulerian time tendency of total energy, the red line represents the flux convergence of total energy, the green line represents the top of the atmosphere radiative flux anomalies, and the orange line represents the net upward surface flux. The shading denotes the 95% confidence interval of the mean. The y-axis is broken in two places to more clearly highlight the anomalies occurring after TC passage. A Closer Examination of the Anomalous Surface Fluxes Fig. 7: Time series of 500 km by 500 km box-averaged anomalous raw surface fluxes (W m −2 ) for typhoon strength TCs. The blue line represents the net upward surface flux, the red line represents the upward surface latent heat flux, the green line represents the upward surface sensible heat flux, and the orange line represents the upward surface radiative flux. The shading denotes the 95% confidence interval of the mean. A Closer Examination of the Anomalous Surface Fluxes Fig. 7: Time series of 500 km by 500 km box-averaged anomalous raw surface fluxes (W m −2 ) for typhoon strength TCs. The blue line represents the net upward surface flux, the red line represents the upward surface latent heat flux, the green line represents the upward surface sensible heat flux, and the orange line represents the upward surface radiative flux. The shading denotes the 95% confidence interval of the mean. Schematic Depicting Impacts of TCs on Their Local Environment Fig. 8: Schematic of cross-track vertical cross section looking downstream with respect to the TC depicting the processes responsible for generating total energy anomalies following typhoon strength TC passage. The values given in the figures represent the mean values of the respective raw (and normalized anomalies when available) variables or tendency terms from the day at which the composite TC departs the area to the day before the anomalies become insignificant. The arrows denote the direction in which the anomalous fluxes are transported. The sizes of the arrows are not meant to scale with the magnitude of the anomalous processes. The blue shading in the atmosphere denotes a reduction in total energy following TC passage associated with a cooling and drying of the atmosphere while the blue shading of the ocean signifies a cooling of SSTs and the mixed layer. Schematic Depicting Impacts of TCs on Their Local Environment Fig. 8: Schematic of cross-track vertical cross section looking downstream with respect to the TC depicting the processes responsible for generating total energy anomalies following typhoon strength TC passage. The values given in the figures represent the mean values of the respective raw (and normalized anomalies when available) variables or tendency terms from the day at which the composite TC departs the area to the day before the anomalies become insignificant. The arrows denote the direction in which the anomalous fluxes are transported. The sizes of the arrows are not meant to scale with the magnitude of the anomalous processes. The blue shading in the atmosphere denotes a reduction in total energy following TC passage associated with a cooling and drying of the atmosphere while the blue shading of the ocean signifies a cooling of SSTs and the mixed layer. Acknowledgments and References Funding for this research was provided by the NASA Earth and Space Science Fellowship Program and NSF Grant ATM-0842618 The authors would like to thank Lance Bosart (SUNY-Albany), Dan Voss (FSU), Michael Bosilovich (GSFC), Ming Cai (FSU), Bill Dewar (FSU) and Bob Ellingson (FSU) for fruitful discussions. We also acknowledge the FSU HPC for contributions to the results presented in this paper. --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Chu, J., C. Sampson, A. Levine, and E. Fukada, 2002: The JTWC Tropical Cyclone Best- Tracks, 1945–2000. Naval Research Laboratory, Reference Number NRL/MR/7540-02-16. Emanuel, K., 2001: Contribution of Tropical Cyclones to Meridional Heat Transport by the Oceans. J. Geophys. Res., 106, 14,771–14,781. Frank, W. and G. Young, 2007: The Interannual Variability of TCs. MWR135, 3587-3598. Hart, R., 2011: An Inverse Relationship Between Aggregate Northern Hemisphere Tropical Cyclone Activity and Subsequent Winter Climate. Geophys. Res. Lett., 38, L01 705. Hart, R., R. Maue, and M. Watson, 2007: Estimating Local Memory of Tropical Cyclones Through MPI Anomaly Evolution. Mon. Wea. Rev., 135, 3990-4005. Reynolds, R. and Coauthors, 2007: Daily High-Resolution-Blended Analyses for SST. J. Climate, 20, 5473-5496. Saha, S. and Coauthors, 2010: The NCEP CFSR. BAMS, 91, 1015-1057. Schenkel, B. and R. Hart, 2010: An Examination of the Spatial and Temporal Extent of the Climate Memory of Tropical Cyclones. 22nd Conf. on Climate Variability and Change, Atlanta, GA, Amer. Meteor. Soc. Schenkel, B. and R. Hart, 2012: An Examination of Tropical Cyclone Position, Intensity, and Intensity Life Cycle within Atmospheric Reanalysis Datasets. J. Climate, 25, 3453-3475. Trenberth, K., 1997: Using Atm. Budgets as a Constraint on Surface Fluxes. J. Climate, 10, 2796-2809. Acknowledgments and References Funding for this research was provided by the NASA Earth and Space Science Fellowship Program and NSF Grant ATM-0842618 The authors would like to thank Lance Bosart (SUNY-Albany), Dan Voss (FSU), Michael Bosilovich (GSFC), Ming Cai (FSU), Bill Dewar (FSU) and Bob Ellingson (FSU) for fruitful discussions. We also acknowledge the FSU HPC for contributions to the results presented in this paper. --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Chu, J., C. Sampson, A. Levine, and E. Fukada, 2002: The JTWC Tropical Cyclone Best- Tracks, 1945–2000. Naval Research Laboratory, Reference Number NRL/MR/7540-02-16. Emanuel, K., 2001: Contribution of Tropical Cyclones to Meridional Heat Transport by the Oceans. J. Geophys. Res., 106, 14,771–14,781. Frank, W. and G. Young, 2007: The Interannual Variability of TCs. MWR135, 3587-3598. Hart, R., 2011: An Inverse Relationship Between Aggregate Northern Hemisphere Tropical Cyclone Activity and Subsequent Winter Climate. Geophys. Res. Lett., 38, L01 705. Hart, R., R. Maue, and M. Watson, 2007: Estimating Local Memory of Tropical Cyclones Through MPI Anomaly Evolution. Mon. Wea. Rev., 135, 3990-4005. Reynolds, R. and Coauthors, 2007: Daily High-Resolution-Blended Analyses for SST. J. Climate, 20, 5473-5496. Saha, S. and Coauthors, 2010: The NCEP CFSR. BAMS, 91, 1015-1057. Schenkel, B. and R. Hart, 2010: An Examination of the Spatial and Temporal Extent of the Climate Memory of Tropical Cyclones. 22nd Conf. on Climate Variability and Change, Atlanta, GA, Amer. Meteor. Soc. Schenkel, B. and R. Hart, 2012: An Examination of Tropical Cyclone Position, Intensity, and Intensity Life Cycle within Atmospheric Reanalysis Datasets. J. Climate, 25, 3453-3475. Trenberth, K., 1997: Using Atm. Budgets as a Constraint on Surface Fluxes. J. Climate, 10, 2796-2809.