The first in-depth hail climatology for the state of New South Wales (NSW), Australia, based on reports of hailstones from 1791 to 2003, is described. The Australian Bureau of Meteorology's severe weather database is extended with a detailed compilation of scientific and newspaper accounts of hail fall for the greater Sydney area for the period 1805 to 1998. Owing to its high exposure to thunderstorm and hail by virtue of population and building density, the greater Sydney area is the focus of the database. Comparisons are drawn between Sydney and the rest of NSW, and between coastal and inland areas of the state. Over the study period, a total of 1570 thunderstorms produced hail. On average, 10 hailstorms per year were recorded in Sydney in the last 50 years. However, there is a statistically significant decrease in the hailstorm frequency during the last 14 years compared with the preceding 36 years. The magnitude of hailstorms, as measured by reports of estimated hailstone size, revealed an average maximum hailstone size per storm that ranged from 3.8 to 4.0 cm for different regions. Hailstorms occur most frequently between October and February (Australian spring and summer) in NSW, with peak activity in November and December. The hail season in Sydney begins 2 months earlier (August to February). However, during the last 14 years there has been a shift to November to March. The majority of NSW hailstorms occur during the late afternoon between 3pm and 7pm, with hailstorms in Sydney occurring about 1 h earlier. The most active hail fall regions are located in the Bureau of Meteorology's northern NSW weather forecast districts of the Northern Tablelands, Northern Rivers and parts of the Northwest Slopes. In Sydney, the most hail-prone suburbs are concentrated over the most densely populated areas and corridors. Copyright © 2005 Royal Meteorological Society

The Murray-Darling Basin (MDB) is Australia’s major agricultural region. The southern MDB receives most of its annual catchment runoff during the cool season (April–September). Focusing on the Murrumbidgee River measurements at Wagga Wagga and further downstream at Hay, cool season river heights are available year to year. The 27-year period April–September Hay and Wagga Wagga river heights exhibit decreases between 1965 and 1991 and 1992–2018 not matched by declining April-September catchment rainfall. However, permutation tests of means and variances of late autumn (April–May) dam catchment precipitation and net inflows, produced p-values indicating a highly significant decline since the early 1990s. Consequently, dry catchments in late autumn, even with average cool season rainfall, have reduced dam inflows and decreased river heights downstream from Wagga Wagga, before water extraction for irrigation. It is concluded that lower April–September mean river heights at Wagga Wagga and decreased river height variability at Hay, since the mid-1990s, are due to combined lower April–May catchment precipitation and increased mean temperatures. Machine learning attribute detection revealed the southern MDB drivers as the southern annular mode (SAM), inter-decadal Pacific oscillation (IPO), Indian Ocean dipole (IOD) and global sea-surface temperature (GlobalSST). Continued catchment drying and warming will drastically reduce future water availability.

When high pressure is located near the Korean peninsula, a diffluent wind regime generally occurs over the Yellow Sea. At night or early morning, diffluent westerly winds occur on the western side of the Korean peninsula near Inchon city and encounter a combined land breeze and katabatic easterly offshore wind, resulting in conditions ranging from calm to a moderate westerly wind near the coast. Nocturnal radiational cooling of the land surface and the moisture laden westerly winds can cause air near the coast to become saturated, resulting in coastal advection fog. During the day, on the other hand, the synoptic‐scale westerly wind is reinforced by a westerly sea breeze and is further reinforced by a westerly valley wind directed upslope towards the mountain top. Even if the resulting intensified onshore wind could transport a large amount of moisture from the sea over the land, it would be very difficult for fog to form because the daytime heat flux from the ground would develop the convective boundary layer inland from Inchon city sufficiently to reduce significantly the moisture content of the air. Therefore, fog does not generally form in situ over the inland coastal basin. When an area of cold sea water (10^°C average) exists approximately 25–50 km offshore and the sea surface temperature increases towards the coast, air parcels over the cool sea surface are cooled sufficiently to saturation, resulting in the formation of advection sea fog. However, at the coast, nocturnal cooling of the ground further cools the advected moist air driven by the westerly wind and causes coastal advection fog to form. Copyright © 2006 John Wiley & Sons, Ltd.

A ten‐year climatology has been prepared of dust days for central eastern Australia, from January 1995 to February 2004, using reports from the Australian Bureau of Meteorology's observational network. It was found that there had been a total of 55 dust days during this ten‐year period. Of these, 43 dust days were associated with cold fronts: 24 were classified as embedded in the zonal westerlies in the Great Australian Bight (GAB) or in westerlies derived from low pressure systems in the GAB, whereas the remaining 19 were associated with cold fronts over eastern Australia where high pressure systems in the GAB generated strong post‐frontal south to southeast winds. Three detailed case studies of dust storm generation and transport were modelled using a sophisticated coupled wind erosion prediction system. The model predictions in all three cases were found to be broadly consistent both with satellite images highlighting dust and the synoptic observations that reported dust. Antecedent land surface conditions are found to be critically important in generating dust, and their representation in the integrated prediction system is subsequently important in providing skilful model predictions of dust transport. Copyright © 2006 Royal Meteorological Society.