Role of atmospheric rivers in shaping long term Arctic moisture variability.

Atmospheric rivers (ARs) reaching high-latitudes in summer contribute to the majority of climatological poleward water vapor transport into the Arctic. This transport has exhibited long term changes over the past decades, which cannot be entirely explained by anthropogenic forcing according to ensemble model responses. Here, through observational analyses and model experiments in which winds are adjusted to match observations, we demonstrate that low-frequency, large-scale circulation changes in the Arctic play a decisive role in regulating AR activity and thus inducing the recent upsurge of this activity in the region. It is estimated that the trend in summertime AR activity may contribute to 36% of the increasing trend of atmospheric summer moisture over the entire Arctic since 1979 and account for over half of the humidity trends in certain areas experiencing significant recent warming, such as western Greenland, northern Europe, and eastern Siberia. This indicates that AR activity, mostly driven by strong synoptic weather systems often regarded as stochastic, may serve as a vital mechanism in regulating long term moisture variability in the Arctic.

Roles of anthropogenic forcings in the observed trend of decreasing late-summer precipitation over the East Asian transitional climate zone.

Observations indicate that late-summer precipitation over the East Asian transitional climate zone (TCZ) showed a pronounced decreasing trend during 1951-2005. This study examines the relative contributions of anthropogenic [including anthropogenic aerosol (AA) and greenhouse gas (GHG)] and natural forcings to the drying trend of the East Asian TCZ based on simulations from CMIP5. The results indicate that AA forcing plays a dominant role in contributing to the drying trend of the TCZ. AA forcing weakens the East Asian summer monsoon via reducing the land-sea thermal contrast, which induces strong low-level northerly anomalies over eastern China, suppresses water vapor transport from southern oceans and results in drier conditions over the TCZ. In contrast, GHG forcing leads to a wetting trend in the TCZ by inducing southerly wind anomalies, thereby offsetting the effect of the AA forcing. Natural forcing has a weak impact on the drying trend of the TCZ due to the weak response of atmospheric anomalies.

Potential impact of atmospheric heating over East Europe on the zonal shift in the South Asian high: the role of the Silk Road teleconnection.

It is well recognized that the zonal shift in the South Asian High (SAH) has pronounced influences on weather and climate anomalies over surrounding and teleconnected regions. Hence, it is of great importance to investigate the factors related to the interannual variation in the zonal location of the SAH. This study indicates that the anomalous atmospheric apparent heat source () around East Europe has a close relationship with the interannual variation in the SAH zonal shift during boreal summer. In particular, when above (below) normal exists, the SAH tends to shift westward (eastward). Above-normal over East Europe can trigger an eastward propagating wave train along the subtropical jet stream, resembling the negative phase of the Silk Road teleconnection pattern, with positive geopotential height anomalies around the Iranian Plateau and Northeast Asia and negative anomalies around East Europe and the Tibetan Plateau, which could lead to a westward shift in the SAH. Our model experiments confirm that anomalous around East Europe can exert pronounced impacts on the zonal shift in the SAH by inducing an eastward propagating atmospheric wave train.

Modulation of the relationship between spring AO and the subsequent winter ENSO by the preceding November AO.

Previous studies indicated that the spring Arctic Oscillation (AO) exerts significant influences on the subsequent winter El Niño-Southern Oscillation (ENSO). This analysis suggests that the spring AO-ENSO linkage is highly modulated by its preceding November AO. When November and the subsequent spring AO indices are in phase, the spring AO has a pronounced influence on ENSO. However, when the November and spring AO indices are out of phase, the spring AO-ENSO connection disappears. Modulation of the November AO on the spring AO-ENSO connection is mainly through the constructive and destructive superposition of the November and spring AO associated sea surface temperature (SST) anomalies in the tropical central-eastern Pacific in spring and summer, as well as the SST anomalies developed further in the tropical Pacific via the positive air-sea feedback.

Ballistic targets micro-motion and geometrical shape parameters estimation from sparse decomposition representation of infrared signatures.

Micro-motion dynamics and geometrical shape are considered to be essential evidence for infrared (IR) ballistic target recognition. However, it is usually hard or even impossible to describe the geometrical shape of an unknown target with a finite number of parameters, which results in a very difficult task to estimate target micro-motion parameters from the IR signals. Considering the shapes of ballistic targets are relatively simple, this paper explores a joint optimization technique to estimate micro-motion and dominant geometrical shape parameters from sparse decomposition representation of IR irradiance intensity signatures. By dividing an observed target surface into a number of segmented patches, an IR signature of the target can be approximately modeled as a linear combination of the observation IR signatures from the dominant segmented patches. Given this, a sparse decomposition representation of the IR signature is established with the dictionary elements defined as each segmented patch's IR signature. Then, an iterative optimization method, based on the batch second-order gradient descent algorithm, is proposed to jointly estimate target micro-motion and geometrical shape parameters. Experimental results demonstrate that the micro-motion and geometrical shape parameters can be effectively estimated using the proposed method, when the noise of the IR signature is in an acceptable level, for example, SNR>0 dB.