Stochastic tracking of mesoscale convective systems: evaluation in the West African Sahel

  • Alexandros Makris
  • Clémentine Prieur
  • Théo Vischel
  • Guillaume Quantin
  • Thierry Lebel
  • Rémy Roca
Original Paper


In this work we apply a recently proposed Bayesian multiple target tracking model to mesoscale convective systems tracking. This stochastic model follows the multiple hypothesis tracking paradigm and can handle a varying number of targets while detecting the target birth, death, split, and merge events. The model is tested experimentally with real MCS targets detected from meteosat IR data over the Sahelian region. The performance of the stochastic tracking is evaluated by comparing it qualitatively and quantitatively with well established deterministic methods.


False Alarm Mesoscale Convective System Probability Hypothesis Density Multiple Hypothesis Tracking Merging Event 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Addesso P, Conte R, Longo M, Restaino R, Vivone G (2012) Map-mrf cloud detection based on phd filtering. Sel Top Appl Earth Obs Remote Sens IEEE J 5(3):919–929. doi: 10.1109/JSTARS.2012.2191144 CrossRefGoogle Scholar
  2. Avenel C, Mmin E, Prez P (2014) Stochastic level set dynamics to track closed curves through image data. J Math Imaging Vis 49(2):296–316. doi: 10.1007/s10851-013-0464-1 CrossRefGoogle Scholar
  3. Balme M, Vischel T, Lebel T, Peugeot C, Galle S (2006) Assessing the water balance in the sahel: impact of small scale rainfall variability on runoff: part 1: rainfall variability analysis. J Hydrol 331(1–2):336–348CrossRefGoogle Scholar
  4. Bar-Shalom Y, Willett PK, Tian X (2011) Tracking and data fusion: a handbook of algorithms, YBS Publishing, StorrsGoogle Scholar
  5. Blackman S (2004) Multiple hypothesis tracking for multiple target tracking. Aerosp Electron Syst Mag IEEE 19(1):5–18. doi: 10.1109/MAES.2004.1263228 CrossRefGoogle Scholar
  6. Desbois M, Kayiranga T, Gnamien B, Guessous S, Picon L (1988) Characterization of some elements of the sahelian climate and theirinterannual variations for july 1983, 1984 and 1985 from theanalysis of METEOSAT ISCCP data. J Clim 1(9),867–904 (1988). doi: 10.1175/1520-0442 CrossRefGoogle Scholar
  7. Dixon M, Wiener G (1993) TITAN: thunderstorm identification, tracking, analysis and nowcasting—a radar-based methodology. J Atmos Ocean Technol 10:785–797CrossRefGoogle Scholar
  8. Fiolleau T, Roca R (2013) An algorithm for the detection and tracking of tropical mesoscale convective systems using infrared images from geostationary satellite. Geosci Remote Sens IEEE Trans 51(7):4302–4315. doi: 10.1109/TGRS.2012.2227762 CrossRefGoogle Scholar
  9. Goutte C, Gaussier E (2005) A probabilistic interpretation of precision, recall and f-score, with implication for evaluation. In: Advances in information retrieval. Springer, Berlin, pp 345–359Google Scholar
  10. Guillot G, Lebel T (1999) Approximation of sahelian rainfall fields with meta-gaussian random functions. Stoch Environ Res Risk Assess 13(1–2):113–130CrossRefGoogle Scholar
  11. Houze RA (2004) Mesoscale convective systems. Rev Geophys 42(4):1944–9208. doi: 10.1029/2004RG000150 CrossRefGoogle Scholar
  12. Johnson J, MacKeen P, Witt A, Mitchell E, Stumpf G, Eilts M, Thomas K (1998) The storm cell identification and tracking algorithm: an enhanced WSR-88D algorithm. Weather Forecast 13:263–276CrossRefGoogle Scholar
  13. Kastella K (1995) Event-averaged maximum likelihood estimation and mean-field theory in multitarget tracking. Autom Control IEEE Trans 40(6):1070–1074. doi: 10.1109/9.388686 CrossRefGoogle Scholar
  14. Kreucher C, Kastella K, Hero A (2005) Multitarget tracking using the joint multitarget probability density. Aerosp Electron Syst IEEE Trans 41(4):1396–1414. doi: 10.1109/TAES.2005.1561892 CrossRefGoogle Scholar
  15. Kwon HH, Lall U, Obeysekera J (2009) Simulation of daily rainfall scenarios with interannual and multidecadal climate cycles for south florida. Stoch Environ Res Risk Assess 23(7):879–896. doi: 10.1007/s00477-008-0270-2 CrossRefGoogle Scholar
  16. Lakshmanan V, Miller M, Smith T (2013) Quality control of accumulated fields by applying spatial and temporal constraints. J Atmos Ocean Technol 30:745–757CrossRefGoogle Scholar
  17. Lebel T, Ali A (2009) Recent trends in the central and western sahel rainfall regime (1990–2007). J Hydrol 375(1–2):52–64CrossRefGoogle Scholar
  18. Lebel T, Delclaux F, Le Barb L, Polcher J (2000) From gcm scales to hydrological scales: rainfall variability in west africa. Stoch Environ Res Risk Assess 14(4–5):275–295. doi: 10.1007/s004770000050 CrossRefGoogle Scholar
  19. Lebel T, Diedhiou A, Laurent H (2003) Seasonal cycle and interannual variability of the sahelian rainfall at hydrological scales. J Geophys Res 108:83–89. doi: 10.1029/2001JD001,580 Google Scholar
  20. Long T, Zheng L, Chen X, Li Y, Zeng T (2011) Improved probabilistic multi-hypothesis tracker for multiple target tracking with switching attribute states. Signal Process IEEE Trans 59(12):5721–5733. doi: 10.1109/TSP.2011.2167616 CrossRefGoogle Scholar
  21. Ma J, Antoniadis A, Le Dimet FX (2006) Curvelet-based snake for multiscale detection and tracking of geophysical fluids. Geosci Remote Sens IEEE Trans 44(12):3626–3638. doi: 10.1109/TGRS.2006.885017 CrossRefGoogle Scholar
  22. Mahler R (2003) Multitarget bayes filtering via first-order multitarget moments. Aerosp Electron Syst IEEE Trans 39(4):1152–1178. doi: 10.1109/TAES.2003.1261119 CrossRefGoogle Scholar
  23. Makris A, Prieur C (2014) Bayesian multiple-hypothesis tracking of merging and splitting targets. Geosci Remote Sens IEEE Trans 52(12):7684–7694. doi: 10.1109/TGRS.2014.2316600 CrossRefGoogle Scholar
  24. Mathon V, Laurent H (2001) Life cycle of sahelian mesoscale convective cloud systems. Q J R Meteorol Soc 127(572):377–406. doi: 10.1002/qj.49712757208 CrossRefGoogle Scholar
  25. Mathon V, Laurent H, Lebel T (2002) Mesoscale convective system rainfall in the sahel. J Appl Meteorol 41:1081–1092CrossRefGoogle Scholar
  26. Miller ML, Lakshmanan V, Smith TM (2012) An automated method for depicting mesocyclone paths and intensities. Weather Forecas 28(3):570–585. doi: 10.1175/WAF-D-12-00065.1 CrossRefGoogle Scholar
  27. Morelande M, Kreucher C, Kastella K (2007) A bayesian approach to multiple target detection and tracking. Signal Process IEEE Trans 55(5):1589–1604. doi: 10.1109/TSP.2006.889470 CrossRefGoogle Scholar
  28. Mukherjee D, Acton S (2002) Cloud tracking by scale space classification. Geosci Remote Sens IEEE Trans 40(2):405–415. doi: 10.1109/36.992803 CrossRefGoogle Scholar
  29. Onof C, Chandler RE, Kakou A, Northrop P, Wheater HS, Isham V (2000) Rainfall modelling using poisson-cluster processes: a review of developments. Stoch Environ Res Risk Assess 14(6):384–411. doi: 10.1007/s004770000043 CrossRefGoogle Scholar
  30. Panta K, Vo BN, Singh S (2007) Novel data association schemes for the probability hypothesis density filter. Aerosp Electron Syst IEEE Trans 43(2):556–570. doi: 10.1109/TAES.2007.4285353 CrossRefGoogle Scholar
  31. Panta K, Clark D, Vo BN (2009) Data association and track management for the gaussian mixture probability hypothesis density filter. Aerosp Electron Syst IEEE Trans 45(3):1003–1016. doi: 10.1109/TAES.2009.5259179 CrossRefGoogle Scholar
  32. Panthou G, Vischel T, Lebel T (2014) Recent trends in the regime of extreme rainfall in the central sahel. International Journal of Climatology 34:3998–4006. doi: 10.1002/joc.3984 CrossRefGoogle Scholar
  33. Papin C, Bouthemy P, Mémin E, Rochard G (2000) Tracking and characterization of highly deformable cloud structures. In: Vernon D (ed) Computer vision ECCV 2000, lecture notes in computer science, vol 1843. Springer, Berlin, pp 428–442. doi: 10.1007/3-540-45053-X_28 CrossRefGoogle Scholar
  34. Pece AEC (2002) The problem of sparse image coding. J Math Imaging Vis 17(2):89–108. doi: 10.1023/A:1020677318841. Special issue on statistics of shapes and texturesCrossRefGoogle Scholar
  35. Pulford G (2005) Taxonomy of multiple target tracking methods. Radar Sonar Navig IEE Proc 152(5):291–304. doi: 10.1049/ip-rsn:20045064 CrossRefGoogle Scholar
  36. Reid DB (1979) An algorithm for tracking multiple targets. IEEE Trans Autom Control 24:843–854CrossRefGoogle Scholar
  37. Root B, Yu TY, Yeary M (2011) Consistent clustering of radar reflectivities using strong point analysis: a prelude to storm tracking. Geosci Remote Sens Lett IEEE 8(2):273–277. doi: 10.1109/LGRS.2010.2070787 CrossRefGoogle Scholar
  38. Salari V, Sethi IK (1990) Feature point correspondence in the presence of occlusion. IEEE Trans Pattern Anal Mach Intel 12(1):87–91CrossRefGoogle Scholar
  39. Sethi IK, Jain R (1987) Finding trajectories of feature points in a monocular image sequence. Pattern Anal Mach Intel IEEE Trans 1:56–73CrossRefGoogle Scholar
  40. Storlie C, Lee T, Hannig J, Nychka D (2009) Tracking of multiple merging and splitting targets: a statistical perspective. Statistica Sinica 19(1):1–52. doi:URL
  41. Thomas C, Corpetti T, Memin E (2010) Data assimilation for convective-cell tracking on meteorological image sequences. Geosci Remote Sens IEEE Trans 48(8):3162–3177. doi: 10.1109/TGRS.2010.2045504 CrossRefGoogle Scholar
  42. Ulmke M, Erdinc O, Willett P (2007) Gaussian mixture cardinalized phd filter for ground moving target tracking. In: Information fusion, 2007 10th international conference on, pp. 1–8. doi: 10.1109/ICIF.2007.4408105Google Scholar
  43. Vila DA, Machado LAT, Laurent H, Velasco I (2008) Forecast and tracking the evolution of cloud clusters (fortracc) using satellite infrared imagery: methodology and validation. Weather Forecast 23(2):233–245. doi: 10.1175/2007WAF2006121.1 CrossRefGoogle Scholar
  44. Vischel T, Lebel T, Massuel S, Cappelaere B (2009) Conditional simulation schemes of rain fields and their application to rainfallrunoff modeling studies in the sahel. J Hydrol 375(12), 273–286. doi: 10.1016/j.jhydrol.2009.02.028. Surface processes and water cycle in West Africa, studied from the AMMA-CATCH observing system
  45. Vischel T, Quantin G, Lebel T, Viarre J, Gosset M, Cazenave F, Panthou G (2011) Generation of high resolution rainfields in west Africa: evaluation of dynamical interpolation methods. J Hydrometeorol. doi: 10.1175/JHM-D-10-05015.1 Google Scholar
  46. Vo BN, Ma WK (2006) The gaussian mixture probability hypothesis density filter. Signal Process IEEE Trans 54(11):4091–4104. doi: 10.1109/TSP.2006.881190 CrossRefGoogle Scholar
  47. Vo BN, Singh S, Doucet A (2005) Sequential monte carlo methods for multitarget filtering with random finite sets. Aerosp Electron Syst IEEE Trans 41(4):1224–1245. doi: 10.1109/TAES.2005.1561884 CrossRefGoogle Scholar
  48. Vo BT, Vo BN, Cantoni A (2006) The cardinalized probability hypothesis density filter for linear gaussian multi-target models. In: Information sciences and systems, 2006 40th annual conference on, pp. 681–686. doi: 10.1109/CISS.2006.286554Google Scholar
  49. Wu SJ, Tung YK, Yang JC (2006) Stochastic generation of hourly rainstorm events. Stoch Environ Res Risk Assess 21(2):195–212. doi: 10.1007/s00477-006-0056-3 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Alexandros Makris
    • 1
  • Clémentine Prieur
    • 2
  • Théo Vischel
    • 3
  • Guillaume Quantin
    • 3
  • Thierry Lebel
    • 3
  • Rémy Roca
    • 4
  1. 1.ICS FORTHCreteGreece
  2. 2.INRIA GrenobleGrenobleFrance
  3. 3.LTHEUniversit Joseph FourierGrenobleFrance
  4. 4.OMP/LEGOS/CNRSToulouseFrance

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