Multivariate data assimilation in a seamless sea ice prediction system based on AWI-CM

2020 ◽  
Author(s):  
Longjiang Mu ◽  
Lars Nerger ◽  
Qi Tang ◽  
Svetlana N. Losa ◽  
Dmitry Sidorenko ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Multivariate Data ◽  
Reanalysis Data ◽  
Sea Surface ◽  
The Arctic ◽  
Prediction System ◽  
Wide Range

<p>We implement multivariate data assimilation in a seamless sea ice prediction system based on the fully-coupled AWI Climate Model (AWI-CM, v1.1). AWI-CM has an ocean/ice component with unstructured-mesh discretization and smoothly varying spatial resolution, which aims for seamless sea ice prediction across a wide range of space and time scales. The assimilation uses a Local Error Subspace Transform Kalman Filter coded in the Parallel Data Assimilation Framework. To test the robustness of the assimilation system, a perfect-model experiment is configured to assimilate synthetic observations. Real observations from sea ice concentration, thickness, drift, and sea surface temperature are further assimilated in the system. The analysis results are evaluated against independent in-situ observations and reanalysis data. Further experiments that assimilate different combinations of variables are conducted to understand their individual impacts on the analysis step. Particularly we find that assimilating sea ice drift improves the sea ice thickness estimate in the Antarctic, and assimilating sea surface temperature is able to avert a circulation bias of the free-running model in the Arctic Ocean at mid-depth. We also test the performance of an extended experiment where the atmosphere is constrained by nudging toward reanalysis data. The second version of the system assimilating more observations also with a new atmospheric model is currently under development.</p>

scholarly journals Interannual Variability and Trends in Sea Surface Temperature, Lower and Middle Atmosphere Temperature at Different Latitudes for 1980–2019

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 454
Author(s):  
Andrew R. Jakovlev ◽  
Sergei P. Smyshlyaev ◽  
Vener Y. Galin
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Lower Stratosphere ◽  
Middle Atmosphere ◽  
Southern Oscillation ◽  
Lower Troposphere ◽  
Reanalysis Data ◽  
Sea Surface ◽  
The Arctic ◽  
The Impact

The influence of sea-surface temperature (SST) on the lower troposphere and lower stratosphere temperature in the tropical, middle, and polar latitudes is studied for 1980–2019 based on the MERRA2, ERA5, and Met Office reanalysis data, and numerical modeling with a chemistry-climate model (CCM) of the lower and middle atmosphere. The variability of SST is analyzed according to Met Office and ERA5 data, while the variability of atmospheric temperature is investigated according to MERRA2 and ERA5 data. Analysis of sea surface temperature trends based on reanalysis data revealed that a significant positive SST trend of about 0.1 degrees per decade is observed over the globe. In the middle latitudes of the Northern Hemisphere, the trend (about 0.2 degrees per decade) is 2 times higher than the global average, and 5 times higher than in the Southern Hemisphere (about 0.04 degrees per decade). At polar latitudes, opposite SST trends are observed in the Arctic (positive) and Antarctic (negative). The impact of the El Niño Southern Oscillation phenomenon on the temperature of the lower and middle atmosphere in the middle and polar latitudes of the Northern and Southern Hemispheres is discussed. To assess the relative influence of SST, CO2, and other greenhouse gases’ variability on the temperature of the lower troposphere and lower stratosphere, numerical calculations with a CCM were performed for several scenarios of accounting for the SST and carbon dioxide variability. The results of numerical experiments with a CCM demonstrated that the influence of SST prevails in the troposphere, while for the stratosphere, an increase in the CO2 content plays the most important role.

scholarly journals Variations of the Mid-Pacific Trough and Their Relations to the Asian–Pacific–North American Climate: Roles of Tropical Sea Surface Temperature and Arctic Sea Ice

2018 ◽  
Vol 31 (6) ◽  
pp. 2233-2252 ◽  
Author(s):  
Kaiqiang Deng ◽  
Song Yang ◽  
Mingfang Ting ◽  
Chundi Hu ◽  
Mengmeng Lu
Keyword(s):  
United States ◽  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Arctic Sea Ice ◽  
Sea Surface ◽  
The Arctic ◽  
Boreal Summer ◽  
Arctic Sea ◽  
Second Mode

The mid-Pacific trough (MPT), occurring in the upper troposphere during boreal summer, acts as an atmospheric bridge connecting the climate variations over Asia, the Pacific, and North America. The first (second) mode of empirical orthogonal function analysis of the MPT, which accounts for 20.3% (13.4%) of the total variance, reflects a change in its intensity on the southwestern (northeastern) portion of the trough. Both modes are significantly correlated with the variability of tropical Pacific sea surface temperature (SST). Moreover, the first mode is affected by Atlantic SST via planetary waves that originate from the North Atlantic and propagate eastward across the Eurasian continent, and the second mode is influenced by the Arctic sea ice near the Bering Strait by triggering an equatorward wave train over the northeast Pacific. A stronger MPT shown in the first mode is significantly linked to drier and warmer conditions in the Yangtze River basin, southern Japan, and the northern United States and wetter conditions in South Asia and northern China, while a stronger MPT shown in the second mode is associated with a drier and warmer southwestern United States. In addition, an intensified MPT (no matter whether in the southwestern or the northeastern portion) corresponds to more tropical cyclones (TCs) over the western North Pacific (WNP) and fewer TCs over the eastern Pacific (EP) in summer, which is associated with the MPT-induced ascending and descending motions over the WNP and the EP, respectively.

scholarly journals Changes in sea-surface temperature and atmospheric circulation patterns associated with reductions in Arctic sea ice cover in recent decades

2018 ◽  
Vol 18 (19) ◽  
pp. 14149-14159 ◽  
Author(s):  
Lejiang Yu ◽  
Shiyuan Zhong
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Arctic Sea Ice ◽  
Sea Surface ◽  
The Arctic ◽  
Atmospheric Circulation Patterns ◽  
Arctic Sea

Abstract. In recent decades, the Arctic sea ice has been declining at a rapid pace as the Arctic warms at a rate of twice the global average. The underlying physical mechanisms for the Arctic warming and accelerated sea ice retreat are not fully understood. In this study, we apply a relatively novel statistical method called self-organizing maps (SOM) along with composite analysis to examine the trend and variability of autumn Arctic sea ice in the past three decades and their relationships to large-scale atmospheric circulation changes. Our statistical results show that the anomalous autumn Arctic dipole (AD) (Node 1) and the Arctic Oscillation (AO) (Node 9) could explain in a statistical sense as much as 50 % of autumn sea ice decline between 1979 and 2016. The Arctic atmospheric circulation anomalies associated with anomalous sea-surface temperature (SST) patterns over the North Pacific and North Atlantic influence Arctic sea ice primarily through anomalous temperature and water vapor advection and associated radiative feedback.

scholarly journals How does sea ice influence <i>δ</i><sup>18</sup>O of Arctic precipitation?

2017 ◽  
Vol 17 (9) ◽  
pp. 5865-5876 ◽  
Author(s):  
Anne-Katrine Faber ◽  
Bo Møllesøe Vinther ◽  
Jesper Sjolte ◽  
Rasmus Anker Pedersen
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Water Vapour ◽  
Arctic Sea Ice ◽  
Sea Surface ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Surface Conditions ◽  
Arctic Sea

Abstract. This study investigates how variations in Arctic sea ice and sea surface conditions influence δ18O of present-day Arctic precipitation. This is done using the model isoCAM3, an isotope-equipped version of the National Center for Atmospheric Research Community Atmosphere Model version 3. Four sensitivity experiments and one control simulation are performed with prescribed sea surface temperature (SST) and sea ice. Each of the four experiments simulates the atmospheric and isotopic response to Arctic oceanic conditions for selected years after the beginning of the satellite era in 1979. Changes in sea ice extent and SSTs have different impacts in Greenland and the rest of the Arctic. The simulated changes in central Arctic sea ice do not influence δ18O of Greenland precipitation, only anomalies of Baffin Bay sea ice. However, this does not exclude the fact that simulations based on other sea ice and sea surface temperature distributions might yield changes in the δ18O of precipitation in Greenland. For the Arctic, δ18O of precipitation and water vapour is sensitive to local changes in sea ice and sea surface temperature and the changes in water vapour are surface based. Reduced sea ice extent yields more enriched isotope values, whereas increased sea ice extent yields more depleted isotope values. The distribution of the sea ice and sea surface conditions is found to be essential for the spatial distribution of the simulated changes in δ18O.

scholarly journals Assessing bias corrections of oceanic surface conditions for atmospheric models

2019 ◽  
Vol 12 (1) ◽  
pp. 321-342 ◽  
Author(s):  
Julien Beaumet ◽  
Gerhard Krinner ◽  
Michel Déqué ◽  
Rein Haarsma ◽  
Laurent Li
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
General Circulation Models ◽  
Substantial Improvement ◽  
Sea Surface ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
Analogue Method

Abstract. Future sea surface temperature and sea-ice concentration from coupled ocean–atmosphere general circulation models such as those from the CMIP5 experiment are often used as boundary forcings for the downscaling of future climate experiments. Yet, these models show some considerable biases when compared to the observations over present climate. In this paper, existing methods such as an absolute anomaly method and a quantile–quantile method for sea surface temperature (SST) as well as a look-up table and a relative anomaly method for sea-ice concentration (SIC) are presented. For SIC, we also propose a new analogue method. Each method is objectively evaluated with a perfect model test using CMIP5 model experiments and some real-case applications using observations. We find that with respect to other previously existing methods, the analogue method is a substantial improvement for the bias correction of future SIC. Consistency between the constructed SST and SIC fields is an important constraint to consider, as is consistency between the prescribed sea-ice concentration and thickness; we show that the latter can be ensured by using a simple parameterisation of sea-ice thickness as a function of instantaneous and annual minimum SIC.

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