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Ulrike Romatschke, Robert Houze, Socorro Medina
Regional, Seasonal and Diurnal Variations of Convection in the Asian Monsoon Region Authors Ulrike Romatschke, Robert Houze, Socorro Medina Clouds and Precipitation Seminar, University of Washington, 15 November 2007
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Region of Study
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Outline Dataset Comparison with Houze et al. Premonsoon – Monsoon
Introduction Dataset Regonal Variations Comparison with Houze et al. Seasonal Variations Premonsoon – Monsoon Diurnal Variations Dependence on topography Conclusion and future Work
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Dataset TRMM Precipitation Radar (PR), Version 6 Products
2A23: Radar Rain Characteristics 2A25: Radar Rainfall Rate and Profile Monsoon Season: June - September Premonsoon Season: May
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Data Processing Gridspacing Interpolation on Cartesian Grid
horizontal: ~5 km vertical: 250 m Search for individual systems contiguous pixels define system characteristic parameters (e.g. time, location, size,…)
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Definitions Deep Intense Convective Cores
20 16 12 8 4 Definitions Height [km] Deep Intense Convective Cores 40 dBZ echo > 10 km in hight Wide Intense Convective Cores 40 dBZ echo area > 1,000 km² Broad Stratiform Echos area > 50,000 km² Distance [km] 24 22 20 Latitude Longitude 15 20 Latitude [dBZ] Longitude
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Objectives Compare with Houze et al. (2007) Extend dataset
geographical region Premonsoon Season Diurnal Cycle Find especially active regions
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Outline Dataset Comparison with Houze et al. Premonsoon – Monsoon
Introduction Dataset Regonal Variations Comparison with Houze et al. Seasonal Variations Premonsoon – Monsoon Diurnal Variations Dependence on topography Conclusion and future Work
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Comparison Deep Intense Convective Cores /
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Large Scale Flow Patterns during Monsoon
1000 mb 700 mb 40 30 20 10 / Terrain [km]
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Comparison Wide Intense Convective Cores /
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Comparison Broad Stratiform Systems /
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Outline Dataset Comparison with Houze et al. Premonsoon – Monsoon
Introduction Dataset Regonal Variations Comparison with Houze et al. Seasonal Variations Premonsoon – Monsoon Diurnal Variations Dependence on topography Conclusion and future Work
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Deep Intense Convective Cores
Premonsoon Monsoon
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The Indian Dry-Line Weston (1971) 1000 mb 700 mb
Surface p [mb] and v mb v Weston (1971)
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The Indian Dry-Line 200 mb mb mb Monsoon Premonsoon
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Wide Intense Convective Cores
Premonsoon Monsoon
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Wide vs. Deep Intense Convective Cores
Premonsoon Premonsoon
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Wide vs. Deep Intense Convective Cores
Monsoon Monsoon
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Wide vs. Deep Intense Convective Cores
Ganges Delta Monsoon
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Broad Stratiform Systems
Premonsoon Monsoon
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Broad Stratiform Systems
Rain Climatology Monsoon Xie et al. (2006)
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Outline Dataset Comparison with Houze et al. Premonsoon – Monsoon
Introduction Dataset Regonal Variations Comparison with Houze et al. Seasonal Variations Premonsoon – Monsoon Diurnal Variations Dependence on topography Conclusion and future Work
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Diurnal Cycle, Monsoon
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Diurnal Cycle
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Diurnal Cycle
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Diurnal Cycle, Monsoon
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Diurnal Cycle Deep Intense Convective Cores Monsoon
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Diurnal Cycle Deep Intense Convective Cores Monsoon
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Diurnal Cycle Deep Intense Convective Cores Monsoon
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Diurnal Cycle Deep Intense Convective Cores Monsoon
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Diurnal Cycle Deep Intense Convective Cores Premonsoon
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Diurnal Cycle Deep Intense Convective Cores Premonsoon
Surface p [mb] and v Weston (1971) Xie et al. (2006)
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Diurnal Cycle, Deep Intense Convective Cores, Premonsoon
Zuidema (2002) Mean percent high cloudiness Cloud Top < 210 K May – September 1999
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Diurnal Cycle, Monsoon
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Diurnal Cycle, Monsoon Wide Intense Convective Cores 1999-2001 vs
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Diurnal Cycle Wide Intense Convective Cores Monsoon
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Diurnal Cycle Wide Intense Convective Cores Monsoon
Xie et al. (2006)
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Diurnal Cycle Wide Intense Convective Cores Premonsoon - Monsoon
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Diurnal Cycle Wide Intense Convective Cores Premonsoon
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Diurnal Cycle, Monsoon
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Diurnal Cycle, Monsoon
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Diurnal Cycle Broad Stratiform Systems Monsoon
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Diurnal Cycle Broad Stratiform Systems Monsoon
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Diurnal Cycle Broad Stratiform Systems Monsoon
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Diurnal Cycle Broad Stratiform Systems Monsoon
Williams and Houze (1987)
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Outline Dataset Comparison with Houze et al. Premonsoon – Monsoon
Introduction Dataset Regonal Variations Comparison with Houze et al. Seasonal Variations Premonsoon – Monsoon Diurnal Variations Dependence on topography Conclusion and future Work
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Conclusions Larger independent dataset seems to confirm Houze et al. (2007) Premonsoon – Monsoon • Shift in places of occurrence of Deep and Wide Intense Convective Cores. • More Wide Intense Convective Cores and Broad Stratiform Systems over the ocean during Monsoon. Diurnal Cycles • Strong afternoon peak in Deep Intense Convective Cores. • Afternoon and night peaks in Wide Intense Convective Cores. • Evening minimum in Broad Stratiform Systems. Rain climatology compares • with Broad Stratiform Systems over the ocean. • with Wide Intense Convective Cores at the Himalayan Foothills. • not with Deep Intense Convective Cores.
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Conclusions Larger independent dataset seems to confirm Houze et al. (2007) Premonsoon – Monsoon • Shift in places of occurrence of Deep and Wide Intense Convective Cores. • More Wide Intense Convective Cores and Broad Stratiform Systems over the ocean during Monsoon. Diurnal Cycles • Strong afternoon peak in Deep Intense Convective Cores. • Afternoon and night peaks in Wide Intense Convective Cores. • Evening minimum in Broad Stratiform Systems. Rain climatology compares • with Broad Stratiform Systems over the ocean. • with Wide Intense Convective Cores at the Himalayan Foothills. • not with Deep Intense Convective Cores. This is just the beginning!
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Future Work Get 2002/2003 Version 6 data.
Statistics for other variables. Look at specific regions • physical background • different variable fields (e.g. wind) • satellite data
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Variables Orbitnumber Number of convective pixels Date
Time Number of pixels 3D Number of pixels 2D Latitude Longitude Height Longest horizontal dimension Height of terrain Area Number of convective pixels Number of stratiform pixels Convective, stratiform, total • rain rate • volumetric rain rate • rain fraction • area fraction
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Future Work Get 2002/2003 Version 6 data.
Statistics for other variables. Look at specific regions • physical background • different variable fields (e.g. wind) • satellite data
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Future Work
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