1. Flash-flood-producing storm events in Saudi Arabian
Liping Deng1, Matthew F. McCabe2, Georgiy Stenchikov1,
Jason P. Evans3 and Paul A. Kucera4
1 Physical Sciences and Engineering Division, King Abdullah University of Science & Technology, Thuwal, Saudi Arabia;
2. Water Desalination and Reuse Center, Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science & Technology, Thuwal, Saudi Arabia;
3. Climate Change Research Centre, University of New South Wales, Sydney, Australia;
4. NCAR Research Applications Laboratory, Boulder, CO, USA

2. Outline Why? How? Results Conclusion Flash floods at Jeddah
Jeddah topography
Synoptic features for Jeddah flash floods
How?
Weather Research and Forecasting (WRF) model setup
Results
Evaluation of extreme values and evolution of storm events
Impact of model resolution on storm reproduction
Impact of cumulus scheme at 5km-resolution intermediate domain
Conclusion
Here is my outline, inlucedes why we study it, and how to study it, and then the results and concluson

3. Why? Monitoring and forecasting flash-flood-producing storm events
This is a picture from website about Jeddah flash floods. In fact due to this is reason, why we want to study it, we want to monitor and forecast it. Next we will give some basic reasons for Jeddah flash floods, this could answer why there is a flash fllood.

4. Jeddah topography (Saud 2010)
This is the figure from previous results about the Jeddah topography, which helps explain the Jeddah flash floods.
Whenever, there is water in this area, it will go tot the Jeddah city, so a strong rain storm passing will make a flash flood in Jeddah easily.
(Saud 2010)

5. Synoptic features Case 1: 2009 Nov. 24 00 – 26 00
Case 2: 2010 Dec – 31 00
Case 3: 2011 Jan – 16 00
Synoptic features at initial time point
Another important reason for flash flood in the Jeddah is the strong storm, here we look through three cases for synoptic features at initial time point.

6. Synoptic features Case1 Case2 Case3 700 hPa U/V and geopotential heigt
Low –level
jet L H
700 hPa trough
These are figures for wind and geopotential height.
U / V wind component (m/s; vector)
Geopotential height (m; color contour)
850 hPa U/V and geopotential heigt

7. Synoptic features Case1 Case2 Case3
10-meter U/V, total column water vapour
850 hPa U/V and specific humidity
Low –level
jet L H
700 hPa trough
Moist base
All these figures are trying to give moisture information.
850 hPa Specific humidity (g/kg)
Total column water vapour (mm)

8. Synoptic features Case1 Case2 Case3 L H 850 hPa U/V and Temperature
Low –level
jet L H
700 hPa trough
Temperature
Low troposphere
convergence zone
Moist base
850 hPa U/V and Temperature
Mesoscale convective systems (MCSs)
Thunderstorms
Squall lines
Temperature (K; color contour)
Total column water vapour (mm; blue dah line)
10-meter U/V, 2-meter Temperature

9. Initial synoptic features
Schematic plot of initial synoptic features for all three cases:
The red dot indicates Jeddah.
“H” refers to anticyclone and “L” refers to the cyclone.
The figure also represents the moisture base (green triangle), low-tropospheric convergence zone (purple oval), low-level jet (blue oval), trough (brown line) and temperature (red dashed line). H
Trough
Low troposphere
convergence zone
Jeddah
Temperature
Moist base
Low level jet L
Two anticyclones separated by a cyclone (L)
A trough
Low-level jet zone ahead of the trough
Strong moist tongue covering the Jeddah area
A strong convergence zone around Jeddah.

10. WRF model setup D1-25km D2-5km D3-1km
Each test case is a nested on-way run with spectral nudging in the upper troposphere (<500 hPa) for parent domain (D1) only
The model has been integrated with two nested domains.
D1 has 208× 176 grid points in the horizontal with 25-km grid spacing.
D2 has 336× 416 grid points with 5-km grid spacing.
D3 has 256 × 176 grid points with 1-km grid spacing.
D1-25km
D2-5km
D3-1km
Topography height (m)
The configuration of WRF consisted of a 1-km-resolution domain nested in coarser domains (d01-25km, d02-5km and d03-1km) driven by ECMWF Interim Reanalysis (ERA Interim) data, with spectral nudging in the upper troposphere (above 500hPa) employed over the latter domain. The use of spectral nudging is to reduce the impact of the domain design but retains large-scale features, and the inner domain (d03) covers Jeddah area with 256 × 176 grid points in the horizontal and 50 vertical levels.

11. WRF model setup WRF3.5 2009 Nov. 24 00 – 26 00 (48 hours) for case 1
2010 Dec – for case 2
2011 Jan – for case 3
ERA-Interim (Meteorology IC and BC)
Time step = 30s, output hourly
Vertical levels = 50
Physics
option
mp_physics
2/5 (Lin/Eta)
ra_lw_physics
4 (RRTMG)
ra_sw_physics
sf_sfclay_physics
2 (Janjic Eta)
sf_surface_physics
2 (Noah)
bl_pbl_physics
2 (MYJ)
cu_physics
1/5 (KF/Grell)
Micro long wave short wave surface layer option land surface option boundary scheme cumulus scheme

12. Results Atmospheric state
Simulated Case 1
Jeddah (King Abdul Aziz Airport) (lat=21.7N; lon=39.18E)
University of Wyoming sounding data
2009 Nov :00
WRF could reproduce local temperature and moisture conditions
Air parcel to 1000 hPa more physic meaning for comparing

13. Results At the rain gauge stationb) c)
Case 1
Case 2
Case 3
Jeddah rain gauge station (21.5°N; 39.2°E).
Accumulated 48-hour rainfall (mm) for Case 1 (a), Case 2 (b) and Case 3 (c).
The red line is the hourly WRF simulations, the blue line is the TRMM data, the black dashed line is the daily rain gauge data and the green line is the Taif radar rainfall data.
23+30=53
In general, the WRF simulations in Jeddah are comparable to the observations, especially for the rain-gauge station observations.

14. Results Over the Jeddah catchmentb) d) f)
Case 1
Case 2
Case 3
Averaged over the Jeddah catchment.
Accumulated 48-hour rainfall (mm; a, c and e) and precipitation rate (mm hr-1; b, d and f) for Case 1 (a-b), Case 2 (c-d) and Case 3 (e-f).
The red line is for WRF simulations (D3-1km), the blue line is for TRMM rainfall data and the green line is for the Taif radar rainfall data.
The rainfall peaks associated with the individual rain events generally are captured reasonably well for the Jeddah catchment with some temporal shifts in either peak or storm initiation time for Case 1 and Case 3.

15. Results Evolution of rainstorm
Hourly time evolution of rainstorms (mm) for Case 1 from Taif radar data (left column) and WRF (right column) D3-1km. The white circle is for downtown Jeddah.
Precipitation radar dataset collected by an C-Band Doppler located near city of Taif which is east of Jeddah (Kucera et al. 2010).
Observed rainstorm extends in a direction from the southwest to the northeast, perpendicular to the direction of movement of the storm center (from the northwest to the southeast).
WRF model with nesting has the capability to forecast extreme weather event (Heavy rainfall / mesoscale convective systems) with some temporal and spatial displacement.
Radar
WRF
D3-1km

16. Results Domain 2 – 5 km vs. Domain 3 – 1 km
Downscaling will not necessarily improve model simulations of heavy rainfall in all cases (e.g., Almazroui 2011).
Jeddah region has complex orographic and geographic features, such as a mountain range close to the city and a land-ocean boundary, that warrant model simulation improvements along with an increasing resolution (e.g., from 5 km to 1 km).
Explore the rainfall comparisons of results from Domain 2 with 5 km resolution (D2-5km) and Domain 3 with 1 km resolution (D3-1km).

17. Results Domain 2 – 5 km vs. Domain 3 – 1 km
Station
Catchment a) b) c) d) e) f)
D3-1km
D2-5km
Accumulated rainfall (mm; a-b) at Jeddah station, accumulated rainfall (mm; c-d) averaged over the Jeddah catchment and precipitation rate (mm hr-1; e-f) averaged over the Jeddah catchment from WRF D3-1km (left; a, c and e) and D2-5km (right; b, d and f) for Case 1.
The red line is for WRF simulations, the blue line is for TRMM rainfall data, the green line is for the Taif radar rainfall data and the black line is for the daily rain gauge data.
Simulation with higher horizontal grid resolution (e.g., D3-1km) generally has a better capacity in reproducing heavy rainfall, especially for the extreme value.

18. Results Domain 2 – 5 km vs. Domain 3 – 1 kmb) c) d)
Vertical profile of divergence (10-5 s-1; a), upward motion (m s-1; b), relative humidity (%; c) and equivalent potential temperature (K; d) averaged over the Jeddah catchment during rainstorms for the mean of all three cases from D3-1km (red line) and D2-5km (blue line).
Stronger deep convective activity and its associated features are the main reasons for the enhancement of heavy rainfall in the simulations around Jeddah area, when downscaling from D2-5km to D3-1km.
With the equivalent potential temperature decreasing with height, the atmosphere is unstable in the lower troposphere for both D3-1km and D2-5km, which favors the occurrence of convection

19. Results Impact of cumulus scheme at 5km-resolution intermediate domain
No comprehensive guidance on the use of a dedicated cumulus scheme at the intermediate resolutions between approximately 3-10 kilometers .
To explore the most appropriate reproduction of the flash-flood events, we examine the use of the cumulus scheme in Domain 2 at the 5km-resolution.
Through comparisons of Grell-D1 with Grell-D1.D2 and KF-D1 with KF-D1.D2, we can explore the impact of the use of cumulus scheme at 5km-resolution in Domain 2 for heavy rainfall simulations.
Cu_physics
D1-25km
D2-5km
D3-1km
Test-1 (Grell-D1)
Grell No
Test-2 (KF-D1) KF
Test-3 (Grell-D1.D2)
Test-4 (KF-D1.D2)

20. Results Impact of cumulus scheme at 5km-resolution intermediate domainb) c)
Station
Catchment
Time evolution of accumulated rainfall (mm) at Jeddah station (a), and accumulated rainfall (mm; b) and precipitation rate (mm hr-1; c) averaged over the Jeddah catchment for Case 1 from the Taif radar, rain gauge (daily), TRMM and WRF (D3-1km).
Simulated rainfall in the Jeddah region is enhanced if the intermediate 5-km Domain 2 does not use a cumulus scheme .

21. Results Impact of cumulus scheme at 5km-resolution intermediate domainb) c) d)
Vertical profiles of divergence (10-5 s-1; a), upward motion (m s-1; b), relative humidity (%; c) and equivalent potential temperature (K; d) averaged over the Jeddah catchment during the rainstorms for the mean of all three cases from WRF (D3-1km).
Test cases without a cumulus scheme at the intermediate domain (D2-5km) resolution lead to a stronger deep convection with a more wet and warm environment in the middle-upper troposphere of D3-1km, corresponding to a rainfall enhancement.

22. Conclusion
Mesoscale convective systems associated with strong moisture convergence ahead of a trough were the major initial features for the occurrence of these intense rain events.
Localized extreme values of heavy rainfall and the duration of rainstorms within the Jeddah catchment area can be captured reasonably well by a convection-permitting WRF model, albeit with some displacement of rainstorm events.
Through the comparison between Domains 2 and 3, it is found that higher-resolution topography in the WRF model over the Jeddah area generally contributes to an enhancement of local deep convective systems and the related heavy rainfall intensities.
Compared to the intermediate Domain 2 (5km-resolution) with a cumulus scheme, the one without a cumulus scheme shows positive impacts on Domain 3’s deep convective activity, which leads to a larger localized volume of rainfall.

23. Thank you very much!
Questions?