The Years of the Maritime Continent or YMC is a multi-national and multi-year effort, which aims at improving our understanding and prediction skill of the weather-climate systems over the Maritime Continent (MC) as well as its global impact. Its field campaign phase has been started since July 2017 and is scheduled to continue beyond 2020. During the campaign period, many intensive observations have been/will be conducted. YMC data policy requires the campaign participants to provide scientific community with their quality-controlled data in timely manner. Indeed, its first dataset has been released since February 2019 from the YMC website at http://www.jamstec.go.jp/ymc/, and then more data are available now. In particular, since regional meteorological agencies from Indonesia, Philippines, Singapore, Malaysia, and Australia have agreed to provide their original high-resolution operational data such as radiosonde soundings, it is possible to study various temporal and spatial weather-climate phenomena over the MC using intensive observations and such operational high-resolution products.
This special edition on YMC jointly coordinated with Journal of the Meteorological Society of Japan was designed to solicit submission of papers that use those field campaign data. In addition, as this special edition joins a cross-organization special collection on YMC arranged by seven professional organizations including the American Geophysical Union, the American Meteorological Society, the Australian Meteorological and Oceanographic Society, the Chinese Geoscience Union, the European Geosciences Union, the Royal Meteorological Society, and the Meteorological Society of Japan, we believe this edition will not only contribute to new MC sciences but also provide a bridge to those other communities, which may bring a new science interaction.

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Given vigorous mean diurnal variation (MDV) of cumulus convection and surface wind over coastal waters of the Indonesian Maritime Continent, surface sensible and latent heat fluxes (SHF and LHF) are expected to also exhibit significant MDV. However, it is difficult to grasp characteristics of MDV of these fluxes due to lack of surface observation data. Recently, two intensive observation campaigns were conducted off the west coast of Sumatra Island in austral summer, which offer us a unique opportunity to examine the characteristics of convection and the fluxes. This study analyzes these observations to reveal that the MDV of both SHF and LHF has considerable amplitude compared with the average. The MDV of SHF is primarily caused by that in surface air temperature, which is due to the MDV of convection. As for LHF, the MDV is primarily caused by that of surface wind speed, in which both the MDV of convection and sea/land breezes play roles. Furthermore, there are qualitative differences in the MDV of the fluxes between the two campaign periods, which can be explained from the viewpoint of differences in phase and intensity of MDV of convection and the sea/land breezes.

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A shipboard lidar system was examined the capability to retrieve detailed variation of the water vapor mixing ratio in and above the marine atmospheric boundary layer (MABL). The water vapor mixing ratio is retrieved from the ratio of Raman lidar signals by water vapor and by nitrogen, with the help of radiosonde data beside. Data obtained during two special observations, Pre-YMC and YMC-Sumatra, off the west coast of Sumatra island were examined.

The mixing ratio was retrieved in the nighttime over 1 km height with the resolution of 10-minutes in temporal and 120-meters in vertical. The root mean square difference from the radiosonde data is about or less than 1 g/kg in MABL. A case study demonstrates that the retrieved spatiotemporal variation of water vapor mixing ratio captures meso-scale drying and moistening in detail. The capabilities of the retrieved data were well demonstrated, while number of improvements are expected in future work.

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We show that a modification to the latent heat flux (LHF) formulation in Non-hydrostatic Icosahedral Atmospheric Model (NICAM) impacts the representation of a Madden–Julian oscillation (MJO) event during the Pre-Years of the Maritime Continent (Pre-YMC) field campaign in 2015. First, we compare the LHFs computed by the standard NICAM setting with those estimated from the ship observation during Pre-YMC. In this comparison, the NICAM LHF is smaller than observation in the low wind speed region and larger in the high wind speed region. Consequently, the MJO signal weakens when it passes over the Maritime Continent (MC). Next, sensitivity experiments are conducted with a modification to the threshold minimum wind speed in the bulk formula, to enhance the LHFs in the low wind speed region. With this modification, propagation of the MJO is better simulated over the MC, although a bias still remains without corrections in the high wind speed regions. This result indicates that increasing the LHF in the low wind speed region likely contributes to a more effective accumulation of moisture over the eastern MC region and consequently allows the MJO to pass over the MC in the model.

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We report experimental observations of precipitable water vapor (PWV) derived using Global Positioning System/Global Navigation Satellite System (GPS/GNSS) receivers mounted on autonomous surface vehicles (ASVs), which were deployed in the tropical Pacific Ocean from July to September 2018. The GPS atmospheric delay was estimated by precise point positioning and converted to PWV with ASV surface meteorological data. The GPS-PWV was in agreement with the PWV obtained from radiosondes, with a root mean square error of 3.02 mm and a mean difference of 0.16 mm. A similar accuracy was found in a comparison of GPS-PWV with satellite-based microwave measurements. In anticipation of real-time monitoring applications, PWV was also estimated using real-time clock and orbit data. These estimates were in agreement with the post-processing values. High-resolution temporal observations of PWV over the open ocean made possible by ASV technology could greatly improve our understanding of the rapid variations of developing convective systems.

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