Object-based analysis of satellite-derived precipitation systems over the low- and mid-latitude Pacific Ocean

Monthly Weather Review

Volumn 137, Issue 10, 2009, Pages 3196-3218

  Skok, Gregor ^a   Tribbia, Joe ^b   Rakovec, Jože ^a   Brown, Barbara ^b  

^a UNIVERSITY OF LJUBLJANA   (Slovenia)

^b NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK; DATA SETS; DIAGNOSTIC ANALYSIS; EQUATORIAL PACIFIC OCEAN; LARGE OBJECTS; LONG LIFE; MIDLATITUDES; OBJECT BASED; PACIFIC OCEAN; PRECIPITATION ESTIMATION FROM REMOTELY SENSED INFORMATION; PRECIPITATION SYSTEMS; SATELLITE PRODUCTS; SPATIAL CONVOLUTION; SPATIAL DISTRIBUTION; TEMPORAL BEHAVIOR; TROPICAL RAINFALL MEASURING MISSIONS;

BACKPROPAGATION; CONVOLUTION; NEURAL NETWORKS; OCEANOGRAPHY; RAIN; RAIN GAGES; REMOTE SENSING; SATELLITES; TROPICS;

SENSITIVITY ANALYSIS;

ARTIFICIAL NEURAL NETWORK; PRECIPITATION ASSESSMENT; RAINFALL; REMOTE SENSING; SATELLITE DATA; SENSITIVITY ANALYSIS; SPATIAL DISTRIBUTION;

PACIFIC OCEAN;

EID: 70449102434     PISSN: 00270644     EISSN: None     Source Type: Journal    
DOI: 10.1175/2009MWR2900.1     Document Type: Article

References (13)

1. Dai, A., X. Lin, and K. L. Hsu, 2007: The frequency, intensity, and diurnal cycle of precipitation in surface and satellite observations over low- and mid-latitudes. Climate Dyn., 29, 727-744.
2. Davis, C., B. Brown, and R. Bullock, 2006a: Object-based verification of precipitation forecasts. Part I: Methodology and application to mesoscale rain areas. Mon. Wea. Rev., 134, 1772-1784.
3. Davis, C., B. Brown, and R. Bullock, 2006b: Object-based verification of precipitation forecasts. Part II: Application to convective rain systems. Mon. Wea. Rev., 134, 1785-1795.
4. Davis, C., B. Brown, R. Bullock and J. Halley Gotway, 2009: The Method for Object-based Diagnostic Evaluation (MODE) applied to WRF forecasts from the 2005 SPC Spring Program. Wea. Forecasting, 24, 1327-1342.
5. Hsu, K., X. Gao, S. Sorooshian, and H. V. Gupta, 1997: Precipitation estimation from remotely sensed information using artificial neural networks. J. Appl. Meteor., 36, 1176-1190.
6. Huffman, G. J., and Coauthors, 2007: The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J. Hydrometeor., 8, 38-55.
7. Joyce, R. J., J. E. Janowiak, P. A. Arkin, and P. Xie, 2004: CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J. Hydrometeor., 5, 487-503.
8. Machado, L. A. T., W. B. Rossow, R. L. Guedes, and A. W. Walker, 1998: Life cycle variations of mesoscale convective systems over the Americas. Mon. Wea. Rev., 126, 1630-1654.
9. Madden, R. A., and P. R. Julian, 1971: Detection of a 40-50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702-708.
10. Mapes, B. E., and R. A. Houze, 1993: Cloud clusters and super-clusters over the oceanic warm pool. Mon. Wea. Rev., 121, 1398-1416.
11. Press, W., S. Teukolsky, W. Vetterling, and B. Flannery, 1992: Numerical Recipes in C. Cambridge University Press, 994 pp.
12. Welch, R., K. Kuo, B. Wielicki, S. Sengupta, and L. Parker, 1988: Marine stratocumulus cloud fields off the coast of southern California observed using LANDSAT imagery. Part I: Structural characteristics. J. Appl. Meteor., 27, 341-362.
13. Wilcox, E. M., 2003: Spatial and temporal scales of precipitating tropical cloud systems in satellite imagery and the NCAR CCM3. J. Climate, 16, 3545-3559.