While global mean surface air temperature (SAT) has increased over recent decades, the rate 28 of regional warming has varied markedly 10 , with some of the most rapid SAT increases 29 recorded in the polar regions [11][12][13] . In Antarctica, the largest SAT increases have been 30 observed in the Antarctic Peninsula (AP) and especially on its west coast 1 : in particular, 31Vernadsky (formerly Faraday) station (Fig. 1) experienced an increase in annual mean SAT 32 of 2. 8° C between 1951 and 2000. 33 The AP is a challenging area for the attribution of the causes of climate change 34 because of the shortness of the in-situ records, the large inter-annual circulation variability 14 35 and the sensitivity to local interactions between the atmosphere, ocean and ice. In addition, 36 the atmospheric circulation of the AP and South Pacific are quite different between summer 37 (December -February) and the remainder of the year. 38Since the late 1970s the springtime loss of stratospheric ozone has contributed to the 39 warming of the AP, particularly during summer 7 . However, during the extended winter 40 period of March -September, when teleconnections between the tropics and high southern 41 latitudes are strongest 15 , tropical sea surface temperature (SST) anomalies in the Pacific and 42Atlantic Oceans 16 can strongly modulate the climate of the AP. The teleconnections are 43 further affected by the mid-latitude jet, which influences regional cyclonic activity and AP 44SATs. While the jet is strong for most of the year, during the summer it is weaker, there are 45 fewer cyclones, and tropical forcing plays little part in AP climate variability. 46The annual mean SAT records from six coastal stations located in the northern AP 47 (Fig. 1) show a warming through the second half of the Twentieth Century, followed by little 48 change or a decrease during the first part of the Twenty First Century 17 . We investigate the 49 3 differences in high and low latitude forcing on the climate of the AP during what we 50 henceforth term the 'warming' and 'cooling' periods, focussing particularly on the period 51 since 1979, since this marks the start of the availability of reliable, gridded atmospheric 52 analyses and fields of sea ice concentration (SIC). We use a stacked and normalized SAT 53 anomaly record (Fig. 2a) response to stratospheric ozone depletion and increasing greenhouse gas concentrations 5,18 . 68The trend in the SAM led to a greater flow of mild, north-westerly air onto the AP (Extended 69 Data Fig. 2a), with SAT on the northeastern side increasing most because of amplification 70 through the foehn effect 7 . This atmospheric circulation trend contributed to the large decrease 71 in SIC in summer (Extended Data Fig. 3a) and for the year as a whole (Fig. 3a). However, 72there was no significant trend in annual mean sea level pressure (SLP) across the AP during 73 4 the warming period (Fig. 3b). During the summer, tropical climate variability had little 74 influence on the AP SATs 15 and the trend in the...

During austral spring 2016 Antarctic sea ice extent (SIE) decreased at a record rate of 75 × 103 km2 d−1, which was 46% faster than the mean rate and 18% faster than in any previous spring season during the satellite era. The decrease of sea ice area was also exceptional and 28% greater than the mean. Anomalous negative retreat occurred in all sectors of the Antarctic but was greatest in the Weddell and Ross Seas. Record negative SIE anomalies for the day of year were recorded from 3 November 2016 to 9 April 2017. Rapid ice retreat in the Weddell Sea took place in strong northerly flow after an early maximum ice extent in late August. Rapid ice retreat occurred in November in the Ross Sea when surface pressure was at a record high level, with the Southern Annular Mode at its most negative for that month since 1968.

A better understanding of regional‐scale precipitation patterns in the Himalayan region is required to increase our knowledge of the impacts of climate change on downstream water availability. This study examines the impact of four cloud microphysical schemes (Thompson, Morrison, Weather Research and Forecasting (WRF) single‐moment 5‐class, and WRF double‐moment 6‐class) on summer monsoon precipitation in the Langtang Valley in the central Nepalese Himalayas, as simulated by the WRF model at 1 km grid spacing for a 10 day period in July 2012. The model results are evaluated through a comparison with surface precipitation and radiation measurements made at two observation sites. Additional understanding is gained from a detailed examination of the microphysical characteristics simulated by each scheme, which are compared with measurements using a spaceborne radar/lidar cloud product. Also examined are the roles of large‐ and small‐scale forcings. In general, the schemes are able to capture the timing of surface precipitation better than the actual amounts in the Langtang Valley, which are predominately underestimated, with the Morrison scheme showing the best agreement with the measured values. The schemes all show a large positive bias in incoming radiation. Analysis of the radar/lidar cloud product and hydrometeors from each of the schemes suggests that “cold‐rain” processes are a key precipitation formation mechanism, which is also well represented by the Morrison scheme. As well as microphysical structure, both large‐scale and localized forcings are also important for determining surface precipitation.