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

Slides:



Advertisements
Similar presentations
Introduction to modelling extremes
Advertisements

AGENZIA REGIONALE PER LA PROTEZIONE DELLAMBIENTE DELLA SARDEGNA ARPAS Andrea Motroni Climate, climate change and desertification.
Multiple Linear Regression uses 2 or more predictors General form: Let us take simplest multiple regression case--two predictors: Here, the b’s are not.
1 The relation between rainfall and area-time Integrals At the transition from and arid to an equatorial Climate: application to rainfall estimation by.
Contrasting Tropical Rainfall Regimes Using TRMM and Ground-Based Polarimetric Radar Steven A. Rutledge, Robert Cifelli, Timothy J. Lang Colorado State.
Maximum Covariance Analysis Canonical Correlation Analysis.
Estimation of Rainfall Areal Reduction Factors Using NEXRAD Data Francisco Olivera, Janghwoan Choi and Dongkyun Kim Texas A&M University – Department of.
Variability in Ozone Profiles at TexAQS within the Context of an US Ozone Climatology Mohammed Ayoub 1, Mike Newchurch 1 2, Brian Vasel 3 Bryan Johnson.
Atmospheric Motion ENVI 1400: Lecture 3.
ROLE OF HEADLANDS IN LARVAL DISPERSAL Tim Chaffey, Satoshi Mitarai Preliminary results and research plan.
Contrasting Tropical Rainfall Regimes Using TRMM and Ground-Based Polarimetric Radar by S. A. Rutledge, R. Cifelli, T. Lang and S. W. Nesbitt EGU 2009.
Coastal front formation at the Llobregat delta. Preliminary study David Pino 1,2 & Jordi Mazón 1 1 Applied Physics Department (UPC) 2 Institut d’Estudis.
GOES-R 3 : Coastal CO 2 fluxes Pete Strutton, Burke Hales & Ricardo Letelier College of Oceanic and Atmospheric Sciences Oregon State University 1. The.
WEST AFRICAN STORM TRACKS AND THEIR RELATIONSHIP WITH ATLANTIC TROPICAL CYCLONES Susanna Hopsch Department of Earth and Atmospheric Sciences University.
1 Improved Sea Surface Temperature (SST) Analyses for Climate NOAA’s National Climatic Data Center Asheville, NC Thomas M. Smith Richard W. Reynolds Kenneth.
Spaceborne Weather Radar
Ocean Current Sungwoo & Irving Grade 8G. What is Climate? Climate is the average weather usually taken over a 30-year time period for a particular region.
Seasonal outlook of the East Asian Summer in 2015 Motoaki Takekawa Tokyo Climate Center Japan Meteorological Agency May th FOCRAII 1.
Comparison of spatial interpolation techniques for agroclimatic zoning of Sardinia (Italy) Cossu A., Fiori M., Canu S. Agrometeorological Service of Sardinia.
WWRP International Symposium on Nowcasting and Very Short Range forecasting Toulouse, France, 5 – 9 September, 2005 SOME RESULT OF TEST NOWCASTING THE.
Sub-Saharan rainfall variability as simulated by the ARPEGE AGCM, associated teleconnection mechanisms and future changes. Global Change and Climate modelling.
Are Exceptionally Cold Vermont Winters Returning? Dr. Jay Shafer July 1, 2015 Lyndon State College 1.
The Caribbean Low Level Jet variability during August and September and its relation with the regional hydroclimate Ernesto Muñoz.
LMD/IPSL 1 Ahmedabad Megha-Tropique Meeting October 2005 Combination of MSG and TRMM for precipitation estimation over Africa (AMMA project experience)
“Nature Run” Diagnostics Thomas Jung ECMWF. Another “Nature Run” A large set of seasonal T L 511L91 integrations has been carried out for many summers.
The Role of Tropical Forests in the Regional and Global Hydroclimate Roni Avissar W.H. Gardner Professor and Chair Department of Civil & Environmental.
Constructing Climate Graphs
Characteristics of Extreme Events in Korea: Observations and Projections Won-Tae Kwon Hee-Jeong Baek, Hyo-Shin Lee and Yu-Kyung Hyun National Institute.
INTER-TROPICAL CONVERGENCE ZONE (ITCZ).
Assessing Predictability of Seasonal Precipitation for May-June-July in Kazakhstan Tony Barnston, IRI, New York, US.
The La Niña Influence on Central Alabama Rainfall Patterns.
Chapter 3 The Changing Weather. Chapter 3 Terms Condensation Condensation Orographic Condensation Orographic Condensation Convectional Condensation Convectional.
1 The Wind. 2 3 The origin of wind The earth is unevenly heated by the sun resulting in the poles receiving less energy from the sun than the equator.
In this study, HWRF model simulations for two events were evaluated by analyzing the mean sea level pressure, precipitation, wind fields and hydrometeors.
Climates.
Lecture 5 The Climate System and the Biosphere. One significant way the ocean can influence climate is through formation of sea ice. Sea ice is much more.
The climate and climate variability of the wind power resource in the Great Lakes region of the United States Sharon Zhong 1 *, Xiuping Li 1, Xindi Bian.
11 Predictability of Monsoons in CFS V. Krishnamurthy Center for Ocean-Land-Atmosphere Studies Institute of Global Environment and Society Calverton, MD.
INTRODUCTORY STUDY : WATER INDICATORS AND STATISTICAL ANALYSIS OF THE HYDROLOGICAL DATA EAST OF GUADIANA RIVER by Nikolas Kotsovinos,P. Angelidis, V. Hrissanthou,
Relationships between Lightning and Radar Parameters in the Mid-Atlantic Region Scott D. Rudlosky Cooperative Institute of Climate and Satellites University.
PREDICTABILITY OF WESTERN NORTH PACIFIC TROPICAL CYCLONE EVENTS ON INTRASEASONAL TIMESCALES WITH THE ECMWF MONTHLY FORECAST MODEL Russell L. Elsberry and.
Atmospheric Motion SOEE1400: Lecture 7. Plan of lecture 1.Forces on the air 2.Pressure gradient force 3.Coriolis force 4.Geostrophic wind 5.Effects of.
Renata Gonçalves Tedeschi Alice Marlene Grimm Universidade Federal do Paraná, Curitiba, Paraná 1. OBJECTIVES 1)To asses the influence of ENSO on the frequency.
Morphology of organized convection in tropics and subtropics Chuntao Liu.
Joanna Futyan and Tony DelGenio GIST 25, Exeter, 24 th October 2006 The Evolution of Convective Systems over Africa and the Tropical Atlantic.
Northwest European High Summer Climate Variability, the West African Monsoon and the Summer North Atlantic Oscillation Jim Hurrell, NCAR, & Chris Folland,
Chapter 20 Statistical Considerations Lecture Slides The McGraw-Hill Companies © 2012.
1 Day 1 Quantitative Methods for Investment Management by Binam Ghimire.
MSG cloud mask initialisation in hydrostatic and non-hydrostatic NWP models Sibbo van der Veen KNMI De Bilt, The Netherlands EMS conference, September.
1 Spatio-temporal Distribution of Latent Heating in the Southeast Asian Monsoon Region School of Earth and Atmospheric Sciences Georgia Institute of Technology.
Estimating the Surface Mass Balance of the Antarctic coastal area for climate models validation 1 – Coastal area SMB & sea level rise 2 – SMB observation.
SeaWiFS Views Equatorial Pacific Waves Gene Feldman NASA Goddard Space Flight Center, Lab. For Hydrospheric Processes, This.
1. Session Goals 2 __________________________________________ FAMINE EARLY WARNING SYSTEMS NETWORK Become familiar with the available data sources for.
Diurnal Cycle of Precipitation Based on CMORPH Vernon E. Kousky, John E. Janowiak and Robert Joyce Climate Prediction Center, NOAA.
1. Session Goals 2 __________________________________________ FAMINE EARLY WARNING SYSTEMS NETWORK Understand use of the terms climatology and variability.
Indicators for Climate Change over Mauritius Mr. P Booneeady Pr. SDDV Rughooputh.
Air Masses and ITCZ. Topic 4: Air Masses and ITCZ Global wind circulation and ocean currents are important in determining climate patterns. These are.
1 Role of Antecedent Land Surface Conditions on North American Monsoon Rainfall Variability Chunmei Zhu Department of Civil and Environmental Engineering.
Tropical and subtropical convection in South Asia and South America
UK Climate is Temperature – Cool, Wet Winters and Warm, Wet Summers
Overview of Downscaling
OCEAN RESPONSE TO AIR-SEA FLUXES Oceanic and atmospheric mixed
Analysis of rainfall fields in Southern Italy
José J. Hernández Ayala Department of Geography University of Florida
Soo-Hyun Yoo and Pingping Xie
Ulrike Romatschke University of Washington, University of Vienna
Coastal CO2 fluxes from satellite ocean color, SST and winds
‘Aquarius’ Maps Ocean Salinity Fine-scale Structure
Validation of Satellite Precipitation Estimates using High-Resolution Surface Rainfall Observations in West Africa Paul A. Kucera and Andrew J. Newman.
Session D6: Process Based Evaluation of the West African Monsoon in CORDEX Projections Goal: Assess components of the West African Monsoon that are both.
Presentation transcript:

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

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)

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 ( ) by L’Hote and Mahé (1996). The dots are the synoptic observational station managed by national meteorological staff

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

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

Distribution of the annual mean cumulative rainfall ( H ) SeaLandNorthSouth 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

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

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

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

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

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)

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