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Zhiqiang Chen
,
Jiping Liu
,
Mirong Song
,
Qinghua Yang
, and
Shiming Xu

Abstract

Here sea ice concentration derived from the Special Sensor Microwave Imager/Sounder and thickness derived from the Soil Moisture and Ocean Salinity and CryoSat-2 satellites are assimilated in the National Centers for Environmental Prediction Climate Forecast System using a localized error subspace transform ensemble Kalman filter (LESTKF). Three ensemble-based hindcasts are conducted to examine impacts of the assimilation on Arctic sea ice prediction, including CTL (without any assimilation), LESTKF-1 (with initial sea ice assimilation only), and LESTKF-E5 (with every 5-day sea ice assimilation). Assessment with the assimilated satellite products and independent sea ice thickness datasets shows that assimilating sea ice concentration and thickness leads to improved Arctic sea ice prediction. LESTKF-1 improves sea ice forecast initially. The initial improvement gradually diminishes after ~3-week integration for sea ice extent but remains quite steady through the integration for sea ice thickness. Large biases in both the ice extent and thickness in CTL are remarkably reduced through the hindcast in LESTKF-E5. Additional numerical experiments suggest that the hindcast with sea ice thickness assimilation dramatically reduces systematic bias in the predicted ice thickness compared with sea ice concentration assimilation only or without any assimilation, which also benefits the prediction of sea ice extent and concentration due to their covariability. Hence, the corrected state of sea ice thickness would aid in the forecast procedure. Increasing the number of ensemble members or extending the integration period to generate estimates of initial model states and uncertainties seems to have small impacts on sea ice prediction relative to LESTKF-E5.

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Jiping Liu
,
Zhiqiang Chen
,
Jennifer Francis
,
Mirong Song
,
Thomas Mote
, and
Yongyun Hu

Abstract

In recent decades, the Greenland ice sheet has experienced increased surface melt. However, the underlying cause of this increased surface melting and how it relates to cryospheric changes across the Arctic remain unclear. Here it is shown that an important contributing factor is the decreasing Arctic sea ice. Reduced summer sea ice favors stronger and more frequent occurrences of blocking-high pressure events over Greenland. Blocking highs enhance the transport of warm, moist air over Greenland, which increases downwelling infrared radiation, contributes to increased extreme heat events, and accounts for the majority of the observed warming trends. These findings are supported by analyses of observations and reanalysis data, as well as by independent atmospheric model simulations using a state-of-the-art atmospheric model that is forced by varying only the sea ice conditions. Reduced sea ice conditions in the model favor more extensive Greenland surface melting. The authors find a positive feedback between the variability in the extent of summer Arctic sea ice and melt area of the summer Greenland ice sheet, which affects the Greenland ice sheet mass balance. This linkage may improve the projections of changes in the global sea level and thermohaline circulation.

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