Benjamin Schenkel and Robert Hart 3 rd International Summit on Hurricanes and Climate Change Department of Earth, Ocean, and Atmospheric.

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Presentation transcript:

Benjamin Schenkel and Robert Hart 3 rd International Summit on Hurricanes and Climate Change Department of Earth, Ocean, and Atmospheric Science The Florida State University Examination of TC Fidelity within Reanalyses and Quantifying the Climate Footprint of TCs Research Sponsored by NASA Earth and Space Science Fellowship and NSF Grant #ATM–

Motivation TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 2/16 Introduction TC Reanalysis Fidelity TC Climate Footprint Why does the atmosphere have a preference for a certain spacing of TCs in space and time?

Background and Previous Research Results – Evaluation of TCs within Reanalyses – Quantifying the TC Climate Footprint Concluding Thoughts Outline TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 3/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

Quantifying Restoration Time Scales of SSTs Anomalous warming of SSTs Cooling induced by TC Restoration to climatology Which large scale mechanisms are responsible for the pre-conditioning of the environment? Which processes are accountable for the removal of anomalies associated with the TC? TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 4/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

Objective: Quantify the spatio-temporal response of the local environment to TC passage Part I: Evaluation of TC representation within reanalysis datasets – Differences between reanalysis and best-track TC data – Comparison of structural composites Part II: Quantifying the TC climate footprint – Composites of SST and thickness anomalies – Composites of energy anomalies Statement of Research Objective: Quantify the spatio-temporal response of the local environment to TC passage Part I: Evaluation of TC representation within reanalysis datasets – Differences between reanalysis and best-track TC data – Comparison of structural composites Part II: Quantifying the TC climate footprint – Composites of SST and thickness anomalies – Composites of energy anomalies TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 5/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

Objective: Evaluate reanalysis TC fidelity to determine their utility for studying TCs Reanalysis: A hindcast that assimilates historical observations providing the most likely atmospheric state at a given time (Thorne and Vose, 2010) Reanalysis datasets examined: – NCEP CFSR – ECMWF ERA-40 – ECMWF ERA-I – JMA JRA-25 – NASA MERRA TCs from from the EPAC, NATL, and WPAC are included Evaluation focuses on variability of position differences, intensity differences, and storm- relative structural composites Methodology: Evaluation of TCs within Atmospheric Reanalyses TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 6/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert Hart The Florida State University 7/16 Spatial Variability of Position Differences CFSR and JRA -25 have smallest position differences due to use of supplemental best- track data (e.g. vortex relocation, tropical cyclone wind profile retrievals) Position difference decreases towards observationally dense areas in NATL/WPAC in ERA-40, ERA-I, and MERRA EPAC has largest position differences in all reanalyses except JRA-25 Mean value of position difference (km) at each gridpoint (km) TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 7/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

Mean Intensity Differences Between Reanalyses Underestimation of intensity is beyond that expected due to coarse resolution (Walsh et al. 2007) CFSR and JRA-25 have strongest intensities due to use of supplemental best-track data CFSR MSLPMIN and VMAX10M suggest differing wind-pressure relationship TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 8/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel The Florida State University 9/16 Cross-Section of NATL Cat 3-5 TC Temp Anomalies Credit: Hawkins and Rubsam (1968) 100 Pressure (hPa) Radius from TC Center (km) 0 TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 9/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

Objective: Quantify the spatio-temporal response of the local environment to TC passage Part I: Evaluation of TC representation within reanalysis datasets – Significant discrepancies exist between best-track and reanalysis TC position – Underestimation of reanalysis TC intensity is beyond what can be attributed to coarse resolution – Reanalyses that are supplemented with best-track data, CFSR and JRA-25, have smaller position differences with more robust intensity and structure – Replication of gross features of TCs provides limited confidence that reanalyses are suitable for climate scale studies of TCs Part II: Quantifying the TC climate footprint – Composites of SST and thickness anomalies – Composites of energy anomalies Statement of Research Objective: Quantify the spatio-temporal response of the local environment to TC passage Part I: Evaluation of TC representation within reanalysis datasets – Significant discrepancies exist between best-track and reanalysis TC position – Underestimation of reanalysis TC intensity is beyond what can be attributed to coarse resolution – Reanalyses that are supplemented with best-track data, CFSR and JRA-25, have smaller position differences with more robust intensity and structure – Replication of gross features of TCs provides limited confidence that reanalyses are suitable for climate scale studies of TCs Part II: Quantifying the TC climate footprint – Composites of SST and thickness anomalies – Composites of energy anomalies TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 10/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

Objective: Computation and analysis of four-dimensional storm relative composites Evaluation of full TC footprint will occur using four-dimensional storm-relative composites of raw variables, anomalies, and normalized anomalies Composites constructed using the CFSR for category 3-5 TCs in the WPAC from Anomalies in atmosphere and ocean computed for 60 days prior to 60 days after TC passage at 1 day intervals Methodology: Quantification of TC Memory TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 11/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

Quantifying Interactions Between TCs and Their Environment What are implications of anomalies not being restored to climatology after two months? Cooling of SSTs due to entrainment mixing and upwelling No indication of substantial environmental pre- conditioning Restoration to climatology does not occur Absence of environmental pre-conditioning Warming and moistening associated with TC Cooling and drying TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 12/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

Quantifying Interactions Between TCs and Their Environment C p T: Temperature Cooling of lower levels Cooling of middle levels Delay in initiation of anomalies with height TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 13/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

Quantifying Interactions Between TCs and Their Environment L v q: Moisture Pulsation of dry anomalies Drying of lower levels Strongest drying immediately after TC passage Pre-storm drying Delay in initiation of anomalies with height TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 14/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

Quantifying Interactions Between TCs and Their Environment Moist static energy losses primarily due to drying! MSE = C p T + L v q + gz TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 15/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

Broader Implications Would this figure look any different for GCMs and, if so, why? TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert HartThe Florida State University 16/16 Introduction TC Reanalysis Fidelity TC Climate Footprint

Given issues in correctly hindcasting TCs within reanalyses, GCM simulations of the future climate may have even poorer representation of TCs without any observations to correct them as happens in reanalyses Large spatio-temporal scales of SST anomalies imply that underrepresentation of TC intensity or unrealistic simulation of ocean dynamics may seriously impact the fidelity of GCM forecasts Large spatial scales of TC impacts upon the atmosphere as well as possible feedbacks onto larger scales also seem to indicate issues with muted representation of TC intensity within GCMs These results may influence the confidence in GCM simulations of future climates given in the fourth assessment by the IPCC TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert Hart The Florida State University 17/16 Possible Implications of Results Introduction Previous Research Results Summary

Relationship Between TC Age and Intensity Introduction Previous Research Results Summary Reanalyses exhibit steadier intensification rates over a longer period than best-track TCs Peak normalized intensity occurs in best-track days later than reanalyses Reanalysis TCs generally decay more slowly, if at all, over a shorter time interval

TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert Hart The Florida State University 19/16 Extending the Analysis into Four Dimensions Credit: Schenkel and Hart (2010d) Cooling and drying Warming and moistening TC passing Cooling and drying beyond scales of TC Cooling and dryingWarming and moistening Introduction Previous Research Results Summary

TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert Hart The Florida State University 20/16 Existence of Forcings on Multiple Scales? SST cold wake Boundary layer cooling and drying Northward propagation of cool and dry anomalies Introduction Previous Research Results Summary

TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert Hart The Florida State University 21/16 Examining the Vertical Structure of the Anomalies Pulsation of dry anomalies Drying of lower levels Cooling of lower levels Cooling of middle levels Easterly outflow Introduction Previous Research Results Summary

TC Reanalysis Fidelity and Climate Footprint of TCs Benjamin Schenkel and Robert Hart The Florida State University 22/16 Rossby Wave Response to TC Passage Introduction Previous Research Results Summary