ORCID Profile
0000-0002-1653-7975
Current Organisation
Monash University
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Publisher: American Geophysical Union (AGU)
Date: 12-09-2022
DOI: 10.1029/2022JD036796
Abstract: The persistent Southern Ocean (SO) shortwave radiation biases in climate models and reanalyses have been associated with the poor representation of clouds, precipitation, aerosols, the atmospheric boundary layer, and their intrinsic interactions. Capitalizing on shipborne observations collected during the Clouds Aerosols Precipitation Radiation and atmospheric Composition Over the Southern Ocean 2016 and 2018 field c aigns, this research investigates and characterizes cloud and precipitation processes from synoptic to micro scales. Distinct cloud and precipitation regimes are found to correspond to the seven thermodynamic clusters established using a K‐means clustering technique, while less distinctions are evident using the cyclone and (cold) front compositing methods. Cloud radar and disdrometer data reveal that light precipitation is common over the SO with higher intensities associated with cyclonic and warm frontal regions. Multiple lines of evidence suggest the presence of erse microphysical features in several cloud regimes, including the likely dominance of ice aggregation in deep precipitating clouds. Signatures of mixed phase, and in some cases, riming were detected in shallow convective clouds away from the frontal conditions. Two of the K‐means clusters with contrasting cloud and precipitation properties are observed over the high‐latitude SO and coastal Antarctica, suggesting distinct physical processes therein. Through a single case study, in‐situ and remote‐sensing data collected by an overflight of the Southern Ocean Clouds Radiation Aerosol Transport Experimental Study were also evaluated and complement the ship‐based analysis.
Publisher: American Meteorological Society
Date: 11-2022
Abstract: This work examines the diurnal and seasonal variability of near-surface temperature and humidity at several large areas with high population density within the Maritime Continent using the Bureau of Meteorology Atmospheric Regional Reanalysis (BARRA) 12-km-resolution dataset that covers the period 1990–2019. The diurnal cycle is examined in detail, with a key feature being the relatively small diurnal variation of the wet-bulb temperature T WB when compared with the temperature and dewpoint temperature T D . The diurnal variability is strongly modulated by the monsoons with their increased rainfall and cloud cover. The near-surface signals associated with the Madden–Julian oscillation across the domains are relatively weak. Dry and humid temperature extremes are examined for regional and seasonal variability. The dry and moist variable extremes occur at different times of year, but each have spatially coherent structure. This paper examines the climatological variations of near-surface temperature and humidity and their extremes in four locations in the “Maritime Continent.” This is important because there are significant variations potentially affecting human and ecosystem health and its resilience to climate change.
Publisher: CSIRO Publishing
Date: 20-09-2021
DOI: 10.1071/ES21007
Abstract: Reanalyses are important tools for understanding past weather and climate variability, but detailed verification of near surface humidity variables have not been published. This is particularly concerning in tropical regions where humid conditions impact meteorology and human activities. In this study, we used screen level temperature and humidity data from a high-resolution atmospheric regional reanalysis, the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA), validated against automatic weather stations (AWS) data for 32 sites across northern Australia. Overall, the BARRA data was reliable, with the time series from the AWS and BARRA being very highly correlated, but there were some seasonal and diurnally varying biases. The variability of the differences also changed from location to location and as a function of time of day and season, but much less than the biases. This variability was less than the ‘weather signal’ as evidenced by the high correlations. In particular, the litude of the diurnal cycle was overestimated, particularly in the dry (winter) season. In general, the differences in temperature were larger than those of the dew point temperature, and the wet bulb temperature had the least uncertainty. Overall, this study contributes to a better understanding of the effectiveness of reanalyses for examining the impact of moist variables on tropical climate variability.
Publisher: Authorea, Inc.
Date: 27-10-2023
Publisher: Wiley
Date: 22-03-2022
No related grants have been discovered for Peter May.