1. Highlights of Refractivity Observations by Radar (and Some More) during IHOP_2002 Frédéric Fabry and ShinJu Park McGill University Montréal, Canada

2. A Few Definitions IHOP_2002 IHOP_2002: International H 2 O Project. Its goal: Determine how much does knowing 4-D H 2 O distribution help in QPF. Refractivity (N) Refractivity (N): A quantity related to the index of refraction (n) of air: N = 10 6 (n−1) = 77.6 P/T + 373000 e/T 2 N = 10 6 (n−1) = 77.6 P/T + 373000 e/T 2. Surface N can be measured by radar used to infer e and T d Surface N can be measured by radar up to a range of about 50 km using ground targets. Since over that range, P and T are (fairly) uniform, N can be used to infer e and T d.

3. IHOP: Instrumentation Deployment

4. IHOP: S-Pol

5. Early fears that ground targets would be in short supply in the Panhandle were unfounded, thanks to unburied power/phone lines, farms, elevators… Liberal Hooker Beaver Perryton Booker Beaver R. valley KS OK TX IHOP: Ground Targets at S-Pol Homestead

6. Real-Time/Default Display Storm Outflow 60 Rapid moistening Wet Dry Diurnal cycle (mostly)

7. Example: Surface Moistening, 25 May No wind (!) Maximizes local effects Sunny, cool, calm morning; will warm quickly Anomalous propagation echoes Previous rain

8. Example: Surface Moistening, 25 May Previous rain

9. Example: Surface Moistening, 25 May Previous rain

10. Example: Surface Moistening, 25 May Previous rain

11. Example: Surface Moistening, 25 May Previous rain

12. Example: Surface Moistening, 25 May Previous rain

13. Example: Surface Moistening, 25 May Previous rain

14. Example: Surface Moistening, 25 May Previous rain

15. Example: Surface Moistening, 25 May Previous rain

16. Example: Surface Moistening, 25 May Previous rain

17. Example: Surface Moistening, 25 May Previous rain

18. Example: Surface Moistening, 25 May Previous rain

19. Example: Surface Moistening, 25 May Previous rain (g m -2 s -1 ) 120 W 360 W Flux computed thanks to a lot of crude assumptions (too high contrast expected)

20. Example: Surface Moistening, 25 May

28. Previous rain Note how “fragile” the moisture patch was under light winds

29. Contrasting Example: 29 May 72 hrs later, on a sunny day prior to 29 May No wind again. Maximizes local effects Some weak differentialmoistening

30. Contrasting Example: 29 May

34. East winds building up

35. Contrasting Example: 29 May East winds building up

36. Contrasting Example: 29 May East winds building up

37. Contrasting Example: 29 May East winds building up Moistureboundary

38. Contrasting Example: 29 May Moistureboundary

39. Moistureboundary

40. Moistureboundary

41. Winds shift to SE behind 2 nd boundary Moistureboundaries

42. Contrasting Example: 29 May Winds shift to SE behind 2 nd boundary Moistureboundaries

43. Contrasting Example: 29 May Winds shift to SE behind 2 nd boundary Moistureboundaries

44. Contrasting Example: 29 May Winds shift to SE behind 2 nd boundary Moistureboundaries

45. Contrasting Example: 29 May

53. Windsshifting to South Boundary still lurking

54. Contrasting Example: 29 May Windsshifting to South Boundary still lurking

55. Contrasting Example: 29 May Windsshifting to South Boundary still lurking

56. Contrasting Example: 29 May Windsshifting to South Boundary still lurking

57. Contrasting Example: 29 May

65. And now to the SW, and then to the West

66. Contrasting Example: 29 May And now to the SW, and then to the West

67. Contrasting Example: 29 May And now to the SW, and then to the West

68. Contrasting Example: 29 May And now to the SW, and then to the West

69. Contrasting Example: 29 MayBoundary makes a comeback

70. Contrasting Example: 29 MayBoundary makes a comeback

71. Contrasting Example: 29 MayBoundary makes a comeback

72. Contrasting Example: 29 MayBoundary makes a comeback

73. Contrasting Example: 29 May

85. Advection of drier air on the dry side

86. Contrasting Example: 29 May Advection of drier air on the dry side

87. Contrasting Example: 29 May King Air overflights start Winds are not very strong but not light. Advectedboundariesintersects flight path

88. Contrasting Example: 29 May King Air overflights in progress Winds are not very strong but not light. Advectedboundariesintersects flight path

89. Contrasting Example: 29 May Winds are not very strong but not light. King Air overflights in progressAdvectedboundariesintersects flight path

90. Contrasting Example: 29 May  A strength of N maps: Provide context to ABL work

91. Example: Boundary Evolution

102. Example: Convection Initiation Confused boundary (more in Z than in N) that will sharpen with time. Rolls-like bands Cold front approaching

103. Example: Convection Initiation

111. Dry line Cold front approaching

112. Example: Convection Initiation Dry line Cold front approaching Moisture

113. Example: Convection Initiation Dry line Cold front approaching Moisture New cells

114. Example: Convection Initiation Dry line Collision Moisture New cells

115. Example: Convection Initiation Dry line Collision Moisture New cells New cell

116. Example: Convection Initiation Rain-induced moist patch New cells New cell

117. Example: Convection Initiation Rain-induced moist patch New cells

118. Example: Convection Initiation

121. Anothercollision

122. Anothercollision

123. Anothercollision

124. Anothercell

125. Anothercell

126. Anothercell

127. ShinJu Park (Ph.D. student) is investigating this event. Advices welcome. More on this event coming…

128. Phenomena Observed during IHOP Boundary layer processes: Convective rolls; Uneven moistening of BL by surface fluxes. A variety of moisture discontinuities: Fronts; Drylines and other convergence lines; Gust fronts and outflow boundaries; More diffuse (10-20 km wide) gradients. (Primarily) nocturnal wave phenomena: Nocturnal bores; Other waves by themselves or embedded in fronts. Now we need to digest at least some of it…

129. Data Processing: IHOP “Climatology” Broad WNW-ESE refractivity and daily N gradient observed. Mimics (reflects?) climatological moisture gradient in the area.

130. Small-Scale Structure of N Thanks to the distributed measurements and the near-continuous coverage in time, one can perform some statistics that would be very hard to do with other sensors. Ex.: Systematic study of the spatial variability of N. How fast does N change with distance?

131. Small-Scale Structure of N Lesser variability in along-wind direction than across: More mixing in along-wind direction via surface friction? More advection-driven E-W gradients (across wind).

132. Small-Scale Structure of N Greatest variability in the afternoon until after sunset; Smallest just around sunrise (some wind dependence).  Implications on representativeness of in-situ data.

133. Small-Scale Structure of Humidity The amount of afternoon-time small-scale variability changes significantly from day to day. Causes? Possibilities: Surface-flux driven; BL top driven (dry air entrainment); Large-scale driven. More?

134. Small-Scale Structure of Humidity First (and only) hypothesis tested: BL top driven. If true, small-scale variability should be well correlated with the amount and dryness of inversion air entrained. Sounding now Sounding later Inversion air now included in BL will dry BL

135. MAD measured by surface data; Expected drying computed from Homestead soundings and measured surface warming. Small-Scale Structure of Humidity On days with a well-developed BL, correlation between BL drying by entrainment and small-scale variability is high.  Possible to predict? If yes, it could be useful to evaluate the expected errors in BL humidity from sondes.

136. Distance (km) Spatial Structure of T, q, w How important is the observed variability in N or humidity for CI?  Need to contrast with effect on CIN of heat, updrafts. Step 1: Measure the variability of all these parameters in the (upper) boundary layer (King Air data used).

137. Spatial Structure of CIN At large scales: Temperature is the biggest player. At small scales: Updrafts are the most important. Moisture variability generally plays a lesser role (!) Step 2: Convert the spatial variability of all these parameters into CIN variability.

138. A More Detailed Look at a CI Event (1) Cold front (2) Dry line (3) Moist air (4) Extensions of waves on the dry line in the moist air? (5) New cells forming on these extensions (6) Cold front-dry line collision in the making

139. A More Detailed Look at a CI Event (5) New cells forming on these extensions (6) Cold front-dry line collision in the making (7) Cell resulting from that collision