Fidelity of Tropical Cyclone Intensity and Structure within

Reanalyses

Benjamin Schenkel and Robert HartDepartment of Earth, Ocean, and Atmospheric ScienceThe Florida State University

Research Sponsored by NASA Earth and Space Science Fellowship and NSF Grant #ATM-0842618

What is a Reanalysis?

• Retrospective examination of the atmosphere over a long period using a constant atmospheric model and data assimilation system

• Provides homogeneous source of spatially and temporally dense data available on a global scale

• Changes in the observations input into the reanalysis are the only sources of “artificial” trends

• Reanalyses are ideal for climate scale studies, but caveats should be known!

Why is TC Representation within Reanalyses Poor?• Reanalyses have coarse horizontal resolutions (~50-125 km)

• Features with scales of 3-5 times the grid spacing can be resolved

• Tropical cyclones (TCs) have horizontal scales of ~1000 km from eye to environment, but the strongest winds are localized to mean radii of ~60 km

• Coarse resolution results in existence of TC within these datasets with significantly weakened intensity

• What are the global climate implications of incorrectly quantifying TC intensity?

Data and Methods• Data from five reanalyses were used:

NCEP’s CFSR (Saha et al. 2010)

ECMWF’s ERA-40 (Uppala et al. 2005)

ECMWF’s ERA-I (Simmons et al. 2007)

JMA’s JRA-25 (Onogi et al. 2007)

NASA’s MERRA (Bosilovich et al. 2006)

• Period from 1979-2001 was chosen for overlap between reanalyses* and satellite era

• All TCs within the EPAC, NATL, and WPAC from the best-track (Jarvinen et al. 1984; Neumann et al. 1993; Chu et al. 2002) were included

• Analysis utilizes maximum 10 m winds (VMAX10M) for TC intensity and composited anomalies to examine TC structure* ERA-I only available from 1989-2001

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; intensity is much weaker. Causes of poor representation are not clear.

Mean value of position difference at each gridpoint (km)

Mean Intensity Differences Between Reanalyses

• Coarse resolution of reanalyses precludes replication of intensity

• CFSR/JRA-25 have strongest intensities due to use of supplemental best-track data

• Increasing reanalysis intensity with increasing best-track intensity category

Cross-Section of NATL Cat 3-5 Temp Anomalies

Taken from Hawkins and Rubsam (1968)

100 200

Pres

sure

(hPa

)

1000

500

200

600

400

700

800

900

300

200 100Radius from TC Center (km)

Concluding Thoughts

• Resolution precludes replication of best-track intensity, but large scale structure is consistent with a warm core cyclone. What are implications of not capturing the magnitude of TC intensity?

• CFSR and JRA-25 have most robust representation due to use of supplemental data. Are such approaches necessary for future generations of reanalyses?

• Relative to NATL and WPAC, substantial issues with TC representation in the EPAC exists. Is this merely an observation density issue?

ReferencesBosilovich, M. et al., 2006: NASA’s Modern Era Retrospective-Analysis for Research and Applications (MERRA). Geo. Res. Abstracts, 8.Chu, J., C. Sampson, A. Levine, and E. Fukada, 2002: The Joint Typhoon Warning Center Tropical Cyclone Best-Tracks, 1945-2000. Naval Research Laboratory, Reference Number NRL/MR/7540-02-16.Hawkins, H. and D. Rubsam, 1968: Hurricane Hilda, 1964. Mon. Wea. Rev., 96, 617-636.Jarvinen, B., C. Neumann, and M. Davis, 1984: Tropical Cyclone Data Tape for the North Atlantic Basin, 1886-1983: Contents, Limitations and Uses. NOAA Tech. Memorandum NWS NHC 22.Neumann, C., B. Jarvinen, C. McAdie, and J. Elms, 1993: Tropical Cyclones of the North Atlantic Ocean, 1871-1992. National Climatic Data Center in cooperation with the National Hurricane Center, coral Gables, FL, 193 pp.Onogi, K. et al., 2007: The JRA-25 Reanalysis. J. Meteor. Soc. Japan, 85, 369-432.Saha, S. et al., 2010: The NCEP climate forecast system reanalysis. Bull. Amer. Meteor. Soc., 91, 1015-1057.Simmons, A., S. Uppala, D. Dee, and S. Kobayashi: ERA-Interim: New ECMWF Reanalysis Products from 1989 Onwards. ECMWF Newsletter, 110, 25-35.Uppala, S. et al., 2005: The ERA-40 Reanalysis. Quart. J. Roy. Meteor. Soc., 131, 2961-3012.Uppala, S. et al., 2004: The ECMWF 45-year reanalysis of the global atmosphere and surface conditions 1957-2002. ECMWF Newsletter, 101, 2-21.

Relevant Questions• What type of variability do reanalysis TC intensity and

structure display within datasets? Among datasets?

• How can differences among reanalyses in TC intensity and structure be physically accounted for?

• How does the intensity and structure of reanalysis TCs compare to observations?

• What are the deficiencies in the representation of reanalysis TCs?

• What are the global climate implications of inadequate reanalysis TC representation?

Motivation

• Significant discrepancies can exist in reanalysis tropical cyclone (TC) position and intensity compared to the best-track

Comparison of Reanalysis Detection Efficiencies

Taken from Uppala et al. (2004)

Taken from Onogi et al. (2007)

• TC detection frequencies are sensitive to tracking criteria

• Detection frequency, by itself, is not good metric for evaluating reanalysis TCs

• Need to reconcile differences in detection frequencies by examining TC intensity and structure

JRA-25: Black linesERA-40: Grey lines

ERA-40 Detection Frequencies

ERA-40 and JRA-25 Detection Frequencies100

60

40

20

0

80

%

1991 1994 1997 2000 20031988198519821979

Spatial Variability of TC Structure• Lower level thermal wind: positive

(red) for warm core cyclones, negative (blue) for cold core cyclones

• CFSR displays spatial structure resembling expected mean best-track values

• Other reanalyses show magnitude of warm core increasing towards observationally dense areas in NATL/WPAC

• EPAC has marginal mean warm core/cold core in ERA-40, ERA-I, and MERRA

• Bias towards premature extratropical transition in the NATL and WPAC

Mean value of lower level thermal wind for a given gridpoint

Data and Methods• Data from five reanalyses was used:

NCEP’s CFSR (Saha et al. 2010)

ECMWF’s ERA-40 (Uppala et al. 2005)

ECMWF’s ERA-I (Simmons et al. 2007)

JMA’s JRA-25 (Onogi et al. 2007)

NASA’s MERRA (Bosilovich et al. 2006)

• Period from 1979-2001 was chosen for overlap between reanalyses* and satellite era

• All TCs within the EPAC, NATL, and WPAC from the best-track (Jarvinen et al. 1984; Neumann et al. 1993; Chu et al. 2002) were included

• Analysis utilizes minimum mean sea-level pressure (MSLPmin), maximum 10 m

winds (VMAX10m), cyclone phase space parameters (Hart et al. 2003), and

composited anomalies to examine TC intensity and structure* ERA-I only available from 1989-2001