A neural-network-based cluster technique, the so-called self-organizing map (SOM), was performed to extract distinct sea surface temperature (SST) anomaly patterns during boreal winter. The SOM technique has advantages in nonlinear feature extraction compared to the commonly used empirical orthogonal function analysis and is widely used in meteorology. The eight distinguishable SOM patterns so identified represent three La Niña–like patterns, two near-normal patterns, and three El Niño–like patterns. These patterns show the varied amplitude and location of the SST anomalies associated with El Niño and La Niña, such as the central Pacific (CP) and eastern Pacific (EP) El Niño. The impact of each distinctive SOM pattern on winter-mean surface temperature and precipitation changes over North America was examined. Based on composite maps with observational data, each SOM pattern corresponds to a distinguishable spatial structure of temperature and precipitation anomaly over North America, which seems to result from differing wave train patterns, extending from the tropics to mid–high latitudes induced by longitudinally shifted tropical heating. The corresponding teleconnection as represented by the National Center for Atmospheric Research Community Atmospheric Model, version 4 (CAM4), was compared with the observational results. It was found that the 16-member ensemble average of the CAM4 experiments with prescribed SST can reproduce the observed atmospheric circulation responses to the different SST SOM patterns, which suggests that the circulation differences are largely SST driven rather than due to internal atmospheric variability.

Knowing the freeze-thaw (FT) state of the land surface is essential for many aspects of weather forecasting, climate, hydrology, and agriculture. Microwave L-band emission contains rather direct information about the FT-state because of its impact on the soil dielectric constant, which determines microwave emissivity and the optical depth profile. However, current L-band-based FT algorithms need reference values to distinguish between frozen and thawed soil, which are often not well known. We present a new FT-state-detection algorithm based on the daily variation of the H-polarized brightness temperature of the SMAP L3c FT global product for the northern hemisphere, which is available from 2015 to 2021. Exploiting the daily variation signal allows for a more reliable state detection, particularly during the transition periods, when the near-surface soil layer may freeze and thaw on sub-daily time scales. The new algorithm requires no reference values; its results agree with the SMAP FT state product by up to 98% in summer and up to 75% in winter. Compared to the FT state inferred indirectly from the 2-m air temperature and collocated soil temperature at 0–7 cm of the ERA5-land reanalysis, the new FT algorithm has a similar performance to the SMAP FT product. The most significant differences occur over the midlatitudes, including the Tibetan plateau and its downstream area. Here, daytime surface heating may lead to daily FT transitions, which are not considered by the SMAP FT state product but are correctly identified by the new algorithm. The new FT algorithm suggests a 15 days earlier start of the frozen-soil period than the ERA5-land’s estimate. This study is expected to extend the L-band microwave remote sensing data for improved FT detection.

The sea‐ice extent (SIE) in the Weddell Sea plays a crucial role in the Antarctic climate system. Many studies have examined its long‐term trend, however whether its year‐to‐year variation has changed remains unclear. We found an amplified year‐to‐year variance of the Weddell Sea SIE in austral summer since 1998/1999 in observational datasets. Analyses of sea‐ice concentration budget and surface fluxes indicate that it is the thermodynamic process that drives the amplification of SIE variations, rather than the sea‐ice‐drift‐related dynamic process. Compared to 1979–1998, the Southern Annular Mode in the preceding spring shows a closer linkage with the Weddell Sea SIE in 1999–2021 through a stronger and more prolonged impact on sea surface temperature, which thermodynamically modulates local sea ice via changing surface heat and radiation fluxes. Our study helps advance the understanding of extreme low Antarctic‐SIE records occurring in recent decades and improve future projections of the Antarctic sea‐ice variability.

Tropical sea surface temperature (SST) and associated precipitation, acting as diabatic heat forcing, has far-reaching climatic impacts across the globe through exciting poleward-propagating Rossby waves. It is found that the leading mode of tropical Pacific forcing in austral autumn experiences a significant interdecadal shift from an eastern Pacific (EP) to a central Pacific (CP) type around the late 1990s. More specifically, the EP-type precipitation anomaly mode before 1998 drives a quadrupole-like teleconnection pathway emanating from the tropical Pacific to the Ross Sea and Amundsen–Bellingshausen Seas (ABS) region, whereas the CP-type mode after 1999 excites a Pacific–South American (PSA)-like teleconnection orienting along a great circle. Divergent flows induced by different precipitation anomaly modes primarily determine the generation of Rossby waves by means of the vortex stretching and vorticity advection processes. Furthermore, the synoptic high-frequency transient eddy activity along with its dynamic forcing effect differs greatly before and after 1998/99, contributing to different locations of the teleconnection lobes at mid- to high latitudes. In contrast, the subseasonal low-frequency transient eddy activity exerts a limited influence. Our findings also indicate that the EP-type (CP-type) tropical forcing mode could significantly modulate the zonal displacement (strength) of the Amundsen Sea low, which could lead to distinct climate responses of West Antarctica and the Antarctic Peninsula in austral autumn.