L'étude des séries temporelles

1. Impacts of local climatology on heavy rain
cells: case study in the southeast of France
First results
Florent Renard
Université Jean Moulin Lyon 3
UMR 5600 CNRS Environment City Society

2. Introduction
South-East of France : subject to extremely heavy rainfall causing flash floods
October 4th, 2015 :
• several towns devastated in the rivieira
• death of 21 people
• tens of thousands of euros of damage
Greater Lyon :
• 59 towns
• 515 km2
• 1.3 millions inhabitants
• a dense urban area prone to (flash) floods

3. • outdoor laboratory
• acquire reliable data on urban wet weather effluents and their impact on receiving water
• provide knowledge, methodologies and results to assess the sustainability of urban water system
• to propose some support for operational decision making
Field Observatory for urban water management (www.othu.org)
• a research teams federation
• 9 universities and engineering schools (hydrology, climatology, economy, geography, history, socilogy, etc.).
• 13 research laboratories, 80 researchers

4. • Study the effects of :
- land cover (especially in urban environments)
- topography (altitude, slope and exposure)
on the density, intensity and area of rainfall cells
• Scope : scientific and operational scope as the results may increase the knowledge on intense rain cells behaviours
and provide lines for rainwater management
• Urban environment : might affect precipitation variability
- Urban heat island : thermic perturbation
- Pollution : cloud condensation nuclei
- Roughness : convergence
- Humidity: impacts
?

5. 1. Characteristics of the rainfall samples
• Data : Météo-France C-band weather radar
• Reflectivity converted to rain intensity (Marshall-Palmer 1948)
• Frequency : Δ 5 minutes ; resolution : 1 km²
• Previous studies : good quality since 2001
• Areal uniform correction by the Lyon raingauges
• Radar covering zone : 280 km range
• Focus on intense rainfalls : int > 8 mm/h (Météo-France definition)
• Two scales for studying the characteristics of intense rainfall cells :
– complete study zone : 280 km radius
density
– QPE study zone : 100 km radius
rain cell intensity and area
1.1 Weather radar data

6. 1.2 Acquisition of samples of intense rainfall cells
• First step : identification of intense cells
• Second step : identification of weighted mean center, maximum intensity and area of intense rain cells
• Model Builder (ArcGis)

7. Data samples :
Five most intense rainfall events in Greater Lyon from 2001 to 2005
(9 and 22 September 2002, 23 July 2004, 4 August 2004 and 29 July 2005)
• 109,979 intense cells
• 49,663 cells in the QPE zone

8. 2.1 Contrasted topographical characteristics
2. Characteristics of the study field
• Exclusion of areas higher than 1500 m for radar coverage and higher than 1100 m for the hydrological zone :
ground echoes, non-representative proportion
Elevation :
• 2 DEMs used (IGN) : 1000 m and 250 m resolution (to study the sensitivity effect)

9. Slope :
Gradient
(°)
Hydrological study zone Total radar cover
0 to 10 84.3 (84.3) 76.5 (76.5)
10 to 20 13.6 (97.9) 14.2 (90.7)
20 to 30 1.8 (99.7) 6.0 (96.7)
30 to 40 0.2 (99.9) 2.5 (99.2)
40 to 50 < 0.1 0.7 (99.9)
50 to 60 < 0.1 0.1 (100)
gradient : mainly 0 to 20° (97.7% hydrological study zone - 90.7% entire area)
Aspect (slope exposure) :
no slope more exposed in one direction than another
Slope
direction
Hydrological study zone Total radar cover
N 12.0 12.3
NE 12.1 11.4
E 13.7 12.5
SE 11.6 11.8
S 10.8 11.7
SW 11.1 11.7
W 14.0 13.8
NW 12.7 13.3
flat 1.9 1.4

10. 2.2 Varied land cover
• Land cover data : European database Corine Land Cover
• Study limited to level 1 (five main categories)
• Exclusion of wetlands and water bodies : non representative parts
Land cover Hydrological study zone (%) Total radar cover (%)
Artificial areas 6.5 3.8
Arable land/permanent crops 64.0 51.4
Forest and semi-natural vegetation 27.4 42.8
Wetlands 0.0 0.1
Water bodies 1.0 0.9

11. 3. Analysis of the spatial models and comparison of the intense rainfall cells with topography
and land cover
3.1 Preliminary test of the distribution of high intensity rainfall cells
Aim : study the spatial distribution with density calculation
to confirm the inhomogeneous distribution of rainfall cells
Density of intense rainfall cells in standard samples (left) and random samples (right)

12. 3.2 Analysis of spatial models and the matching of clusters of intense rainfall cells
• Identification of geographic models : fundamental for understanding the behaviour of spatial phenomena
• Study the spatial distribution trends of rainfall cells
clustering, dispersal or random
• Identification of statistically significant spatial clusters of cells of strong (hot spots) or weak (cold spots) intensity
- Spatial auto-correlation
- Degree of clustering of the high and low intensity values

13. 3.3 Bivariate and non-parametric statistics for the study of relations with local effects
• Cell density :
- number of occurrence per unit area
- expressed by classes (for altitude and slope) or categories (for exposure and land use)
- cells / km²
• Samples : not distributed following a normal distribution
• Normality required for the use of multiple comparison tests (ANOVA)
Non parametric Kruskal-Wallis test

14. 4. Results and discussion
4.1 Spatial models with non-random distribution?
Sample
Calculated
Moran's index
Forecast Moran's
index
Variance Z score p value Distribution
radar 0.143 -0.00002 0.000012 42.061 0 Clustered
control -0.0002 -0.00002 0.000001 -0.243 0.841 Random
• Moran’s I : spatial distribution of intense cells is clustered
confirms the heterogeneous density maps previously obtained
Sample
Calculated
General G
Forecast General
G
Variance Z score p value Distribution
radar 0.0211 0.0187 0 25.093 0 High-clusters
control 0.000002 0.000002 0 -246014 0.805 random
• General G statistic : clusters of high intensity raincells

15. 4.2 Might topographical variables have no effects on the characteristics of highly intense cells?
4.2.1 The effect of elevation
• Density of cells does not depend on elevation: remains close to the average (both DEM)
• No effect on intensity and area Average Standard deviation
Density 0.571 cells / km² NA
Intensity 27.349 mm/h 28.633
Area 6.438 km² 45.1474.2.2 The effect of slope
• Increase in cell density as a function of the slope (both DEM)
• No effect on intensity and area
4.2.3 Influence of slope exposure
aspect density (250m DEM) density (1000m DEM)
N 0,54 0,55
NE 0,54 0,52
E 0,60 0,61
SE 0,57 0,59
S 0,52 0,53
SW 0,56 0,55
W 0,63 0,67
NW 0,61 0,60
• No effect (both DEM)

16. 4.3 More cells above artificialised areas
Landcover Cells / km²
Farm land 0,6
Forested land and semi-natural vegetation 0,5
Artificial areas 1,1
• Potential bias in choice of rainfall events : selected for maximum intensity above the greater Lyon (artificialised area)
- Repetition of the study without the greater Lyon area
- Similar results : density of 0.92 cells/km²
• Kruskal-Wallis test followed by the Steel-Dwass-Critchlow-Fligner procedure :
intensity is highest above the urban areas : 28.4 mm/h (agricultural land : 27.8 mm/h ; forests and semi-
natural areas : 25.9 mm/h)
• In accordance with other studies in different countries (Mahmood et al. 2014; Daniels et al. 2015; Shastri et al.
2015; Yu and Liu 2015, etc.)

17. 5. Limits and outlooks
• Use of a unique Z-R relationship for the radar QPE, regardless of the precipitation type. Might create biases
(Delrieu et al., 2009 ; Kirstetter et al., 2015)
can affect the choice of the 8 mm/h threshold apply to identify rain cells
• 8 mm/h threshold : too low ?
Focus on a higher intensity threshold
• Selection of episodes :
Study of continuous months / years
• Computation time
• Use of a better DEM
25 meters resolution ?
• Use of a X-band radar with a better land cover database (urban atlas)
Local influence of southeast France topography and land cover on the distribution and characteristics of intense rainfall
cells, 2016. Theoretical and applied climatology, in press.