Genesis Parameters, Genesis Thresholds, and Mid-Level Humidity

Transcription

1 Genesis Parameters, Genesis Thresholds, and Mid-Level Humidity Michael G. McGauley and David S. Nolan Rosenstiel School of Marine and Atmospheric Science University of Miami Miami, Florida, USA This work is supported by the National Science Foundation.

2 I. Background 2 A genesis parameter is an attempt to correlate large-scale, environmental variables with annual or seasonal frequency of TC formation, e.g., Gray (975): GP = f + 5 V p E Ocean e + 5 p max RH

3 Since then, a number of other genesis parameters have been developed, e.g., 3 Emanuel and Nolan (4): GP EN RH V pot 7 3 = +. V 2 shear Figure from Camargo, Emanuel, Sobel (7). They used this GP to diagnose the mechanisms of ENSO influence on TC activity.

4 Emanuel () revised the genesis index to: GP E = maxv pot V shear 4 4 Tippett, Camargo, Sobel () derived a GP based on a Poisson regression: GP T = expb + b + b RH RH + b R-SST R-SST + b shear V shear + log cos

5 II. A New Approach 5 Of course, the GP approach reflects a number of assumptions: * The influence of each parameter is independent of the values of the others * The number and strength of pre-cursor disturbances does not matter (some evidence for this) * Mean values can be used a consistent proxy for more favorable conditions (PDF does not vary with location or season)

6 II. A New Approach 6 Of course, the GP approach reflects a number of assumptions: * The influence of each parameter is independent of the values of the others * The number and strength of pre-cursor disturbances does not matter (some evidence for this) * Mean values can be used a consistent proxy for more favorable conditions (PDF does not vary with location or season) But in fact - the shapes of these PDFs can vary substantially:

7 7 With the last issue in mind, we have developed an alternate approach: the genesis frequency index: GFI = f Vpot f shear f RH f where each f is the frequency that each parameter is above or below some threshold value that will permit TC genesis - given that all the other parameters are highly favorable. The GFI formula is very flexible: one can remove or add parameters without reformulation For now we are also neglecting the issue of generating disturbances

8 8 To build the GFI, we need to: ) Identify a highly favorable but realistic atmospheric environment, where each parameter is in its most advantageous but realistic (MABR) state. 2) For each parameter, we adjust it toward a more unfavorable value while holding the other parameters in the MABR state, until TC genesis can not occur. To identify when genesis is not possible, we use idealized numerical simulations. 3) Compute from reanalyses the frequency that each of the parameters is above or below the threshold value.

9 III. Constructing the MABR Environment 9 The thermodynamic component of the MABR environment is a combination of SST, temperature profile, and humidity profile frequency (x) 25 5 height (hpa) sst ( C) September Atlantic MDR SST Histogram 8 6 temperature ( C) Mean September sounding and +/- one standard deviation MABR SST = 3 C We use the mean sounding

10 For humidity, we construct a moistened profile as follows: 3 (a).7 (b) EOFs of variations in q vapor height (hpa) fraction of total variance Mean RH and mean plus st and 2nd EOFs height (hpa) (c) (d) relative humidity (%) 5 5 q vapor (g kg )

11 For wind shear, a similar approach: (a) height (hpa) 6 8 st EOF 2nd EOF 3rd EOF 4th EOF (b) fraction of total variance (c) height (hpa) 6 8 Mean mean st EOF zonal winds (m s )

12 IV. Finding the Threshold Values 2 To find the threshold value where TC genesis cannot occur, we use idealized numerical simulations with the WRF model: * Doubly-periodic f-plane at 5 N, domain size 43km x 43km * Nested, vortex-following grids with 8/6/2km resolution. * No cumulus parameterization, 6-class microphysics * MABR SST, sounding, and wind shear profiles * Initial condition: A weak vortex with peak tangential flow of 2 m/s at mid-levels, 6 m/s at surface. (Same surface pressure anomaly as pre-depression waves in Atlantic.)

13 3 Finding the threshold: V pot 4 3 C Vpot 82.8 m/s (ideal) 28 C Vpot 64. m/s 27 C Vpot 53.3 m/s 26 C Vpot 4.3 m/s 2 minimum pressure (hpa) We vary V pot only by varying SST. time (d) If the pressure does not fall and stay below hpa, genesis has failed. From these results, the threshold for V pot is set to 47 m/s.

14 Finding the threshold: Wind Shear 4 (a) height (hpa) 6 Shear =.4 m/s (ideal) Shear = 8. m/s Shear =. m/s Shear = 2. m/s Shear varied by varying amplitude of st EOF zonal winds (m s ) minimum pressure (hpa) (b) Shear =.4 m/s (ideal) Shear = 8. m/s Shear =. m/s Shear = 2. m/s Threshold value m/s time (d)

15 Finding the threshold: Environmental Vorticity minimum pressure (hpa) Lat = 5 (ideal) Lat = Lat = 9 Lat = time (d) Rather than trying to model horizontal wind shear, we use planetary vorticity as a proxy for environmental absolute vorticity. The environmental absolute vorticity threshold is set to 2.x -5 s - (~ 8N).

16 Finding the threshold: Humidity 6 All simulations develop, even for RH 6 --> (!) Our method does not work for humidity. With very low (MABR) shear, convection in the disturbance can easily saturate the core. Shear is necessary for dryness to prohibit genesis.

17 We fall back on a purely empirical approach to find the threshold. 7 Our humidity variable is the normalized saturation deficit: NSD (a) = q 6 q q SST q normalized frequency Histogram of NSD around TC genesis events Threshold is mean plus two standard deviations normalized frequency (b) NSD from randomly sampled locations in TC genesis regions and seasons saturation deficit

18 V. Results: Putting it all together (a) July (b) Shear <.4.4 Vpot > (c) (d).8 Lat > 8N > 2.x (e) (f) NSD > (a) x (b) x (d) x (e) = GFI longitude ( W) 8 6 longitude ( W)

19 GFI: Atlantic 9 (a) (b).8.8 July August (c) (d).8.8 September October (e) (f) November December longitude ( W) 8 6 longitude ( W)

20 GFI: East Pacific (a) (b).8.8 July August (c) (d).8.8 September October (e) (f) November December longitude ( W) longitude ( W)

21 GFI: West Pacific 2 (a) (b).8.8 July August (c) (d).8.8 September October (e) (f) November December longitude ( E) longitude ( E)

22 An objective assessment of spatial correlations: * Each basin is divided into n boxes. n * In each basin, score = index i TCcount i 2 2 n, i = where (index i ) and (TCcount i ) are normalized by maximum values in all basins for all seasons. 22 ATL EPAC WPAC NIND SIND SPAC month month

23 8 VI. Applications GFI = f Vpot f shear f RH f 23 As in the development of the GPs, we have neglected the frequency of initiating disturbances. If we had a good count, we could simply attach it to the end of the GFI to get a prediction of actual TC numbers. Assuming the GFI is perfect, we can back out the number of disturbances: longitude ( W) 6 6

24 As in Camargo et al. (7) and Vecchi and Soden (7), the GFI could be used to diagnose changes due to ENSO and/or climate change. 24

25 All details and further discussion can be found in our publication: 25

26 VII. Ongoing Work 26 Both statistical analyses and idealized simulations show that: ) A sufficient environmental vorticity is needed for genesis, but 2) Increasing beyond that value does not further favor genesis. Tippett et al. () What physical processes are limiting development - on either side of the threshold?

27 GFI: Northern Indian 27 (a) (b).8.8 July August (c) (d).8.8 September October (e) (f) November December longitude ( E) 6 8 longitude ( E)

28 GFI: Southern Indian 28 (a) (b).8.8 January latitude ( S) February (c) (d).8.8 March latitude ( S) April (e) (f).8.8 May.6.6 June latitude ( S) longitude ( E) 6 8 longitude ( E)

29 GFI: Southern Pacific 29 (a) (b).8.8 January latitude ( S) February (c) (d).8.8 March latitude ( S) April (e) (f).8.8 May.6.6 June latitude ( S) longitude ( E) longitude ( E)