Presentation is loading. Please wait.

Presentation is loading. Please wait.

SPATIO-TEMPORAL STATIONARITY OF THE MEAN RAINFALL Armand NZEUKOU University of Dschang Cameroon & Henri SAUVAGEOT University of Toulouse III France.

Similar presentations


Presentation on theme: "SPATIO-TEMPORAL STATIONARITY OF THE MEAN RAINFALL Armand NZEUKOU University of Dschang Cameroon & Henri SAUVAGEOT University of Toulouse III France."— Presentation transcript:

1 SPATIO-TEMPORAL STATIONARITY OF THE MEAN RAINFALL Armand NZEUKOU University of Dschang Cameroon & Henri SAUVAGEOT University of Toulouse III France

2 Localization –Tropical latitude with a seaward circulation –The Climate of the Dakar area is of sahelian type –The rainy season is reduced to about 3 months, from early July to late September –Most rainfalls become weaker and then disappear when crossing the coast and moving over the nearby ocean –A few systems grow stronger, advance over the sea, and seem eventually able to play a role in the genesis of the hurricanes of the west tropical Atlantic (Gray and Lansea, 1992)

3 Gauge-based mean annual cumulative rainfall for Senegal -The mean annual cumulative rainfall displays a strong meridional gradient, from 300, at the latitude of Saint Louis, to 1500 mm at Cap Skirring, which is 400 km away -As in most similar rain field representations, isohyets end at the coast. Thus the rain field characteristics over the sea are poorly documented -In this work, we are to describe and to discuss the characteristics of the rainfall distribution in coastal area, which offer an opportunity to observe the land – sea contrast It is possible to observe sea-land differences in the distribution of the rain field characteristics ? Computed over 39 years (1951-1989) by L’Hote and Mahé (1996). The dots are the synoptic observational station managed by national meteorological staff

4 Studied area and radar dataset Land and sea areas are colored North and south areas are half-annular areas located north and south of the latitude of the radar between 60 and 180 km Dataset –The data acquisition was performed by the staff of the Laboratoire de Physique de l’Atmosphère Siméon Fongang of the universitiy of Dakar, using a « SANAGA » acquiring system develop by Sauvageot. –Period of observation: 7 years (1993 à 1999) –sampling interval: between 10 and 20 min –number of scans: 7407 Location and shape of the areas used to computed the averaged parameters

5 Parameters to characterize precipitation Cumulative rainfall Rainfall duration Average rain rate Standad deviation of rain rate Variation coefficient

6 Distribution of the annual mean cumulative rainfall ( H ) SeaLandNorthSouth 298632344583 Very strong sea-land and north-south gradient. The differences are 112% and 69% respectively Area average of the cumulative rainfall (H) The surface echoes area is very asymmetrical and is mainly over the cape of Dakar. Screening effects are observed for azimuths 225° and 240° The scale is in millimeter

7 Distribution of the annual mean rain duration ( T ) SeaLandNorthSouth 53,410556,797,5 Area average of the rain duration (T) Very strong sea-land and north-south gradient. The differences are 97% and 72% respectively The T variation is almost the same as the H That suggests that the rain rate can be considered constant in the area average The scale is in days

8 Probability density function of the rain rate observed P(R) For all the R values higher than the mode of P(R), the frequency is lower over sea than over land. That suggest a convection slightly less vigorous over sea than over land The north and south P(R) curves coincide almost exactly despite the strong gradient of the cumulative rainfall The shape of P(R) is compatible with a lognormal distribution which is defined by two parameters, namely, the average (  R ) and the variance (  R ) of the rain rate

9 Distribution of the time-average rain rate  R SeaLandNorthSouth 4,85,355,185,03 The scale is in millimeter per hour Area average of the rain rate (  R ) The  R distribution is mostly homogeneous except for the northwestern quater plan beyond 100 km. The differences between sea-land and north-south are 11% and 3%, respectively The  R is almost constant for the whole observed area, with sligthly lower values over the sea

10 Distribution of the standard deviation  R of rain rate SeaLandNorthSouth 11,611,911,411,3 The scale is in millimeter per hour Area average of the standard deviation (  R ) The  R distribution is very homogeneous except for the northwestern quater plan beyond 100 km. The  R is very constant for the whole observed area

11 Distribution of the variation coefficient CV=  R /  R SeaLandNorthSouth 2,422,222,202,25 Area average of the variation coefficient (CV) The CV distribution is very homogeneous Only the knowledge of the mean rain rate enables the definition of  R and P(R). It shows that the observed rain rate fields are approximately spatio- temporal stationary (or ergodic) The mean value is 2.27 and very close to the value proposed by Sauvageot (2.24) over large space and time samples. i.e.,  R and  R do not differ when computed over different data samples (e.g., Bendat and Piersol)

12 CONCLUSION The rain volume or cumulative rainfall is higher over land than over sea by 112% The rain duration is longer over land than over sea by 97% The probability density distribution of the rain rate is well represented by a lognormal function, which is determined by two parameters, the mean  R and the standard deviation  R The stability of  R and  R through rain fields implies the same stability for the probability density function of R or P(R). The rain field studied is approximately spatio-temporal stationary or ergodic and justifies the validity of P(R) as a significant rain field characteristic


Download ppt "SPATIO-TEMPORAL STATIONARITY OF THE MEAN RAINFALL Armand NZEUKOU University of Dschang Cameroon & Henri SAUVAGEOT University of Toulouse III France."

Similar presentations


Ads by Google