Abstract

Abstract. The validation of convective processes in global climate models (GCMs) could benefit from the use of large datasets that provide long-term climatologies of the spatial statistics of convection. To that regard, echo top heights (ETHs), convective areas, and frequencies of mesoscale convective systems (MCSs) from 17 years of data from a C-band polarization (CPOL) radar are analyzed in varying phases of the Madden–Julian Oscillation (MJO) and northern Australian monsoon in order to provide ample validation statistics for GCM validation. The ETHs calculated using velocity texture and reflectivity provide similar results, showing that the ETHs are insensitive to various techniques that can be used. Retrieved ETHs are correlated with those from cloud top heights retrieved by Multifunctional Transport Satellites (MTSATs), showing that the ETHs capture the relative variability in cloud top heights over seasonal scales. Bimodal distributions of ETH, likely attributable to the cumulus congestus clouds and mature stages of convection, are more commonly observed when the active phase of the MJO is over Australia due to greater mid-level moisture during the active phase of the MJO. The presence of a convectively stable layer at around 5 km altitude over Darwin inhibiting convection past this level can explain the position of the modes at around 2–4 km and 7–9 km. Larger cells were observed during break conditions compared to monsoon conditions, but only during the inactive phase of the MJO. The spatial distributions show that Hector, a deep convective system that occurs almost daily during the wet season over the Tiwi Islands, and sea-breeze convergence lines are likely more common in break conditions. Oceanic MCSs are more common during the night over Darwin. Convective areas were generally smaller and MCSs more frequent during active monsoon conditions. In general, the MJO is a greater control on the ETHs in the deep convective mode observed over Darwin, with higher distributions of ETH when the MJO is active over Darwin.

Highlights

  • Convection in the tropics has an important impact on the global radiative budget

  • The enhanced mid-level specific humidities during active monsoon and Madden–Julian Oscillation (MJO) phases in Figs. 4d and 5d provide an environment that supports the transition of congestus to deep convection and is likely contributing to the enhanced bimodality of echo top heights (ETHs) observed when the active phase of the MJO is over Australia (Hagos et al, 2013)

  • This study examined the macrophysical properties of convection in Darwin in differing phases of the MJO and northern Australian monsoon, including the echo top heights, convective areas, and number of mesoscale convective systems detected by C-band polarization (CPOL) during 17 wet seasons

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Summary

Introduction

Convection in the tropics has an important impact on the global radiative budget. For example, anvil cirrus that is detrained from convection can have a solar forcing of the order of 100 W m−2 (Jensen et al, 1994). Kumar et al (2013b) analyzed two wet seasons of CPOL data and found evidence of bimodal ETH distributions They found that convection formed during active monsoon conditions has lower cloud top heights than convection formed during break conditions similar to May and Ballinger (2007). The analysis is expanded to the full CPOL record of 17 wet seasons to analyze the relationship between convective properties and the large-scale environment on a more statistically representative dataset than has been done in Johnson et al (1999), May and Ballinger (2007), and Kumar et al (2013a, b) This is possible using recent advances in supercomputing and recent developments of highly customizable distributed data analysis packages written in Python such as Dask (Dask Development Team, 2016).

Data products
Radar data processing
Calculation of ETHs
Quantification of large-scale forcing
Quantification of convective areas and MCSs
Normalized frequency distributions of ETH and convective area
Diurnal cycle and spatial distribution of ETHs
Findings
Conclusions
Full Text
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