Abstract
Mesoscale convective systems are high impact convectively driven weather systems that contribute large amounts to the precipitation daily and monthly totals at various locations globally. As such, an understanding of the lifecycle, characteristics, frequency and seasonality of these convective features is important for several sectors and studies in climate studies, agricultural and hydrological studies, and disaster management. This study explores the applicability of graph theory to creating a fully automated algorithm for identifying mesoscale convective systems and determining their precipitation characteristics from satellite datasets. Our results show that applying graph theory to this problem allows for the identification of features from infrared satellite data and the seamlessly identification in a precipitation rate satellite-based dataset, while innately handling the inherent complexity and non-linearity of mesoscale convective systems.
Similar content being viewed by others
References
Arnaud Y, Desbois M, Maizi J (1992) Automatic Tracking and Characterization of African Convective Systems on Meteosat Pictures. J Appl Meteorol 31(5):443–453
Blamey RC, Reason CJC (2012) Mesoscale Convective Complexes over Southern Africa. J Clim 25(2):753–766
Bouniol D, Delanoë J, Duroure C, Protat A, Giraud V, Penide G (2010) Microphysical characterisation of West African MCS anvils. Q J R Meteorol Soc 136(S1):323–344
Carvalho LM, Jones CA (2001) Satellite Method to Identify Structural Properties of Mesoscale Convective Systems Based on the Maximum Spatial Correlation Tracking Technique (MASCOTTE). J Appl Meteorol 40(10):1683–1701
Chaudhuri S, Middey A (2009) Applicability of bipartite graph model for thunderstorms forecast over Kolkata. Advances in Meteorol., pp 1–12
Chaudhuri S, Middey A (2011) Nowcasting thunderstorms with graph spectral distance and entropy estimation. Meteorol Appl 18(2):238–249
Desbois M, Kayiranga T, Gnamien B, Guessous S, Picon L (1988) Characteristics of Some Elements of the Sahelian Climate and Their Interannual Variations for July 1983, 1984 and 1985 from the Analysis of METEOSAT ISCCP Data. J Clim 1(9):867–904
Dijkstra EW (1959) A note on two problems in connexion with graphs. Numer Math 1(1):269–271
Dixon M, Wiener G (1993) TITAN: Thunderstorm Identification, Tracking Analysis and Nowcasting - A Radar-based Methodology. J Atmos Ocean Technol 10(6):785–797
Duvel JP (1989) Convection over Tropical Africa and the Atlantic Ocean during Northern Summer Part I. Interannual and Diurnal Variations Mon Wea Rev 117(12):2782–2799
Fiolleau T, Roca R (2013) An algorithm for the detection and tracking of tropical mesoscale convective systems using infrared images from geostationary satellite. IEEE Trans Geosci Remote Sens 51(7):1–14
Galvin JF (2010) Two easterly waves in West Africa in summer 2009. Weather 65(8):219–227
García-Herrera R, Barriopedro D, Hernández E, Paredes D, Correoso JF, Prieto F (2005) The 2001 mesoscale convective systems over Iberia and the Balearic Islands. Meteorog Atmos Phys 90(3–4):225–243
Goyens C, Lauwaet D, Schröder M, Demuzere M, Van Lipzig NPM (2011) Tracking mesoscale convective systems in the Sahel: relation between cloud parameters and precipitation. Int J Climatol 32(12):1921–1934
Hagberg AA, Schult DA, Swart PJ (2008). Exploring network structure, dynamics, and function using NetworkX, (Proceedings of the 7th Python in Science Conference (SciPy2008), Gäel Varoquaux, Travis Vaught, and Jarrod Millman (Eds), Pasadena, CA USA, 11–15, Aug 2008
Houze RA, Smull BF, Dodge P (1990) Mesoscale organization of springtime rainstorms in Oklahoma. Mon Weather Rev 118(3):613–654
Johnson JT, MacKeen PL, Witt A, Mitchell ED, Stumpp GJ, Eilts MD, Thomas KW (1998) The storm cell identification and tracking algorithm: An enhanced WSR-88D algorithm. Weather Forecast 13(2):263–276
Korf RE (1985) Depth-first iterative-deepening: An optimal admissible tree search. Artif Intell 27(1):97–109
Laing AG, Evans JL (2011) Introduction to tropical meteorology (2nd ed.). Retrieved from http://www.goes-r.gov/users/comet/tropical/textbook_2nd_edition/index.htm.
Laing A, Fritsch JM (1993) Mesoscale Convective Complexes in Africa. Mon Weather Rev 121(8):2254–2263
Laing A, Fritsch JM (1997) The global population of mesoscale convective complexes. Q J R Meteorol Soc 123(538):389–405
Laurent H, D'Amato N, Lebel T (1998) How important is the contribution of the mesoscale convective complexes to the Sahelian rainfall. Phys Chem Earth 23(5):629–633
Machado LAT, Laurent H (2004) The convective system area expansion over Amazonia and its relationships with convective system life duration and high-level wind divergence. Mon Weather Rev 132(3):714–725
Machado LAT, Duvel J-P, Desbois M (1993) Diurnal variations and modulation by easterly waves of the size distribution of convective cloud clusters over West Africa and Atlantic Ocean. Mon Weather Rev 121(1):37–49
Machado LAT, Rossow WB, Guedes RL, Walker AW (1998) Life cycle variations of mesoscale convective systems over the Americas. Mon Weather Rev 126(6):1630–1654
Maddox RA (1980) Mesoscale convective complexes. Bull Am Meteorol Soc 61(11):1374–1387
Mapes BE, Houze RA (1993) Cloud clusters and superclusters over the oceanic warm pool. Mon Weather Rev 121(5):1398–1415
Mathon V, Laurent H (2001) Life cycle of Sahelian mesoscale convective cloud systems. Q J R Meteorol Soc 127(572):377–406
Mukherjee DP, Acton ST (2002) Cloud Tracking by Scale Space Classification. IEEE Trans Geosci Remote Sens 40(2):405–415
Oliphant TE (2007) Python for Scientific Computing. Computing in Science & Engineering 9(3):10–20
Ray PS (1989) ed. Mesoscale Meteorology and Forecasting. American Meteorological Society, Boston.
Schröder M, König M, Schmetz J (2009) Deep convection observed by the Spinning Enhanced Visible and Infrared Imager on board Meteosat 8: Spatial distribution and temporal evolution over Africa in summer and winter 2006. J. of Geophys. Res.: Atmos. Vol. 114, No. D5
Velasco I, Fritsch JM (1987) Mesoscale convective complexes in the Americas. J Geophys Res Atmos 92(D8):9591–9613
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
Williams M, Houze RA Jr (1987) Satellite-observed characteristics of winter monsoon cloud clusters. Mon Weather Rev 115(22):505–519
Woodley WL, Griffith CG, Griffin JS, Stromatt SC (1980) The interference of GATE convective rainfall from SMS-1 imagery. J Appl Meteorol 19(4):338–408
Acknowledgments
We acknowledge the NASA GES DISC as the data source. The authors wish to thank the NASA Jet Propulsion Laboratory Regional Climate Model Evaluation System (RCMES) and the Apache Open Climate Workbench (Apache OCW) teams for their support. The authors also wish to thank the reviews for their comments that improved the quality of the article.
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by: H. A. Babaie
Rights and permissions
About this article
Cite this article
Whitehall, K., Mattmann, C.A., Jenkins, G. et al. Exploring a graph theory based algorithm for automated identification and characterization of large mesoscale convective systems in satellite datasets. Earth Sci Inform 8, 663–675 (2015). https://doi.org/10.1007/s12145-014-0181-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12145-014-0181-3