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cycle and its variability is required in order to benefit forecast skill locally and convective parameterizations. This paper aims to add to the body of work on the variability of the diurnal cycle on intraseasonal time scales. Here, the focus is on the overlooked boreal summer season with a focus on the Philippines and South China Sea. The mean state of the MC diurnal cycle has been studied extensively, primarily focusing on the islands of Sumatra, Borneo, and New Guinea. Houze et al. (1981
cycle and its variability is required in order to benefit forecast skill locally and convective parameterizations. This paper aims to add to the body of work on the variability of the diurnal cycle on intraseasonal time scales. Here, the focus is on the overlooked boreal summer season with a focus on the Philippines and South China Sea. The mean state of the MC diurnal cycle has been studied extensively, primarily focusing on the islands of Sumatra, Borneo, and New Guinea. Houze et al. (1981
and December 2013 was chosen to compute OLR climatology. The OLR for December 2016 is obtained from NOAA Climate Data Record (CDR) of OLR version 1.2 ( Lee and NOAA CDR Program 2011 ), which is estimated from High-Resolution Infrared Radiation Sounder (HIRS) radiance observations with a 2-day lag. It is given daily with 1° × 1° horizontal resolution. The European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim, hereinafter ERA-Int; Dee et al. 2011 ) is utilized for zonal
and December 2013 was chosen to compute OLR climatology. The OLR for December 2016 is obtained from NOAA Climate Data Record (CDR) of OLR version 1.2 ( Lee and NOAA CDR Program 2011 ), which is estimated from High-Resolution Infrared Radiation Sounder (HIRS) radiance observations with a 2-day lag. It is given daily with 1° × 1° horizontal resolution. The European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim, hereinafter ERA-Int; Dee et al. 2011 ) is utilized for zonal
-resolving model (CRM) simulations of an MJO event over New Guinea by Vincent and Lane (2016) also showed increased DCP amplitude over New Guinea land prior to the arrival of MJO active conditions. However, TRMM 3B42 and Climate Prediction Center morphing technique (CMORPH) observations examined by Vincent and Lane (2016) over New Guinea contradicted their modeling results by showing a similar DCP amplitude just prior to and during the most active MJO conditions over the MC. Several papers based on
-resolving model (CRM) simulations of an MJO event over New Guinea by Vincent and Lane (2016) also showed increased DCP amplitude over New Guinea land prior to the arrival of MJO active conditions. However, TRMM 3B42 and Climate Prediction Center morphing technique (CMORPH) observations examined by Vincent and Lane (2016) over New Guinea contradicted their modeling results by showing a similar DCP amplitude just prior to and during the most active MJO conditions over the MC. Several papers based on
; Wijesekera et al. 2016 ) aims to understand the upper-ocean dynamics in the Bay of Bengal by extensive high-resolution measurements and modeling to eventually improve the monsoon forecasts. Fig . 1. (a) AVISO-derived sea level anomaly in the northern Bay of Bengal on the day of the drifter release (2 Sep 2015), with the drifter-release location indicated in red and the initial drifter positions overlaid. Trajectories of the (b) observed drifters, (c) AVISO-advected, and (d) stochastic drifters (AVISO
; Wijesekera et al. 2016 ) aims to understand the upper-ocean dynamics in the Bay of Bengal by extensive high-resolution measurements and modeling to eventually improve the monsoon forecasts. Fig . 1. (a) AVISO-derived sea level anomaly in the northern Bay of Bengal on the day of the drifter release (2 Sep 2015), with the drifter-release location indicated in red and the initial drifter positions overlaid. Trajectories of the (b) observed drifters, (c) AVISO-advected, and (d) stochastic drifters (AVISO
