Global Climate Model Performance over Alaska and Greenland

2008 ◽  
Vol 21 (23) ◽  
pp. 6156-6174 ◽  
Author(s):  
John E. Walsh ◽  
William L. Chapman ◽  
Vladimir Romanovsky ◽  
Jens H. Christensen ◽  
Martin Stendel
Keyword(s):  
Sea Level ◽  
Root Mean Square ◽  
Global Climate ◽  
Systematic Errors ◽  
The Arctic ◽  
Future Climate Change ◽  
Mean Square ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Mean Square Errors

Abstract The performance of a set of 15 global climate models used in the Coupled Model Intercomparison Project is evaluated for Alaska and Greenland, and compared with the performance over broader pan-Arctic and Northern Hemisphere extratropical domains. Root-mean-square errors relative to the 1958–2000 climatology of the 40-yr ECMWF Re-Analysis (ERA-40) are summed over the seasonal cycles of three variables: surface air temperature, precipitation, and sea level pressure. The specific models that perform best over the larger domains tend to be the ones that perform best over Alaska and Greenland. The rankings of the models are largely unchanged when the bias of each model’s climatological annual mean is removed prior to the error calculation for the individual models. The annual mean biases typically account for about half of the models’ root-mean-square errors. However, the root-mean-square errors of the models are generally much larger than the biases of the composite output, indicating that the systematic errors differ considerably among the models. There is a tendency for the models with smaller errors to simulate a larger greenhouse warming over the Arctic, as well as larger increases of Arctic precipitation and decreases of Arctic sea level pressure, when greenhouse gas concentrations are increased. Because several models have substantially smaller systematic errors than the other models, the differences in greenhouse projections imply that the choice of a subset of models may offer a viable approach to narrowing the uncertainty and obtaining more robust estimates of future climate change in regions such as Alaska, Greenland, and the broader Arctic.

scholarly journals Simulations of Arctic Temperature and Pressure by Global Coupled Models

2007 ◽  
Vol 20 (4) ◽  
pp. 609-632 ◽  
Author(s):  
William L. Chapman ◽  
John E. Walsh
Keyword(s):  
Sea Level ◽  
Climate Models ◽  
Barents Sea ◽  
Global Climate ◽  
Global Climate Models ◽  
First Century ◽  
The Arctic ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Twenty First Century

Abstract Simulations of Arctic surface air temperature and sea level pressure by 14 global climate models used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change are synthesized in an analysis of biases and trends. Simulated composite GCM surface air temperatures for 1981–2000 are generally 1°–2°C colder than corresponding observations with the exception of a cold bias maximum of 6°–8°C in the Barents Sea. The Barents Sea bias, most prominent in winter and spring, occurs in 12 of the 14 GCMs and corresponds to a region of oversimulated sea ice. All models project a twenty-first-century warming that is largest in the autumn and winter, although the rates of the projected warming vary considerably among the models. The across-model and across-scenario uncertainties in the projected temperatures are comparable through the first half of the twenty-first century, but increases in variability associated with the choice of scenario begin to outpace increases in across-model variability by about the year 2070. By the end of the twenty-first century, the cross-scenario variability is about 50% greater than the across-model variability. The biases of sea level pressure are smaller than in the previous generation of global climate models, although the models still show a positive bias of sea level pressure in the Eurasian sector of the Arctic Ocean, surrounded by an area of negative pressure biases. This bias is consistent with an inability of the North Atlantic storm track to penetrate the Eurasian portion of the Arctic Ocean. The changes of sea level pressure projected for the twenty-first century are negative over essentially the entire Arctic. The most significant decreases of pressure are projected for the Bering Strait region, primarily in autumn and winter.

scholarly journals Prediction of North Atlantic Oscillation Index Associated with the Sea Level Pressure Using DWT-LSTM and DWT-ConvLSTM Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Bin Mu ◽  
Jing Li ◽  
Shijin Yuan ◽  
Xiaodan Luo
Keyword(s):  
North Atlantic Oscillation ◽  
Sea Level ◽  
North Atlantic ◽  
Short Term Memory ◽  
Global Climate ◽  
Time Series Prediction ◽  
Support Vector ◽  
Discrete Wavelet ◽  
Sea Level Pressure ◽  
Level Pressure

The North Atlantic Oscillation (NAO), which manifests as an irregular atmospheric fluctuation, has a profound effect on the global climate change. The NAO index (NAOI) is the quantitative indicator that can reflect the intensity of the NAO events, and its traditional definition is the normalized sea level pressure (SLP) difference between Azores and Iceland. From the variation tendency of the NAOI, we found that it is difficult to predict the NAO with the characteristics of variability and complexity. As a data-driven approach, the deep neural network presents great potential in learning the mechanisms of climate forecasting. In this paper, we adopt long short-term memory (LSTM) and ConvLSTM to predict the NAO from two aspects, NAOI and SLP, respectively. In previous studies, LSTM has been regarded as a resultful method for time series prediction. ConvLSTM can capture both the temporal and spatial interdependencies of the SLP field; then, the NAOI can be calculated from the SLP output. In order to improve the prediction reliability, we utilize the discrete wavelet transform (DWT) as a preprocessing technique to decompose original data into different frequencies, considering the local time dependency. It can effectively preserve the features of high-frequency data and forecast extreme events more accurately. The proposed DWT-LSTM and DWT-ConvLSTM models are compared against multiple advanced models, such as LSTM, Holt-Winters, support vector regression (SVR), and gated recurrent unit (GRU). The results indicate that both DWT-LSTM and DWT-ConvLSTM perform better, particularly at peak values. As for the 31 NAO events from 2006 to 2015, our models achieve the lowest prediction error and the best stability. Compared with the forecast products of CPC named Global Forecast System (GFS) and the ensemble forecasts (ENSM), our models are much closer to observation in multistep forecasting.

Outflow of Arctic Ocean Sea Ice into the Greenland and Barents Seas: 1979–2007

2009 ◽  
Vol 22 (9) ◽  
pp. 2438-2457 ◽  
Author(s):  
R. Kwok
Keyword(s):  
Sea Ice ◽  
Sea Level ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Positive Trend ◽  
Fram Strait ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Franz Josef Land ◽  
The Mean

Abstract Twenty-nine years of Arctic sea ice outflow into the Greenland and Barents Seas are summarized. Outflow is computed at three passages: Fram Strait, between Svalbard and Franz Josef Land (S–FJL), and between Franz Josef Land and Severnaya Zemlya (FJL–SZ). Ice drift at the flux gates has been reprocessed using a consistent and updated time series of passive microwave brightness temperature and ice concentration (IC) fields. Over the record, the mean annual area outflow at the Fram Strait is 706(113) × 103 km2; it was highest in 1994/95 (1002 × 103 km2) when the North Atlantic Oscillation (NAO) index was near its 29-yr peak. The strength of the “Transpolar Drift Stream” (TDS) was high during the late 1980s through the mid-1990s. There is no statistically significant trend in the Fram Strait area flux. Even though there is a positive trend in the gradient of cross-strait sea level pressure, the outflow has not increased because of a negative trend in IC. Seasonally, the area outflow during recent summers (in 2005 and 2007) has been higher (> 2σ from the mean) than average, contributing to the decline of summer ice coverage. Without updated ice thickness estimates, the best estimate of mean annual volume flux (between 1991 and 1999) stands at ∼2200 km3 yr−1 (∼0.07 Sv: Sv ≡ 106 m3 s−1). Net annual outflow at the S–FJL passage is 37(39) × 103 km2; the large outflow of multiyear ice in 2002–03, marked by an area and volume outflow of 141 × 103 km2 and ∼300 km3, was unusual over the record. At the FJL–SZ passage, there is a mean annual inflow of 103(93) × 103 km2 of seasonal ice into the Arctic. While the recent pattern of winter Arctic circulation and sea level pressure (SLP) has nearly reverted to its conditions typical of the 1980s, the summer has not. Compared to the 1980s, the recent summer SLP distributions show much lower SLPs (2–3 hPa) over much of the Arctic. Overall, there is a strengthening of the summer TDS. Examination of the exchanges between the Pacific and Atlantic sectors shows a long-term trend that favors the summer advection of sea ice toward the Atlantic associated with a shift in the mean summer circulation patterns.

scholarly journals Impact of the Stratosphere on the Winter Tropospheric Teleconnections between ENSO and the North Atlantic and European Region

2009 ◽  
Vol 22 (5) ◽  
pp. 1223-1238 ◽  
Author(s):  
Chiara Cagnazzo ◽  
Elisa Manzini
Keyword(s):  
Sea Level ◽  
Central Europe ◽  
North Atlantic ◽  
The Arctic ◽  
Stratospheric Warming ◽  
Sudden Stratospheric Warming ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
The North ◽  
The North Atlantic

Abstract The possible role of stratospheric variability on the tropospheric teleconnection between El Niño–Southern Oscillation (ENSO) and the North Atlantic and European (NAE) region is addressed by comparing results from two ensembles of simulations performed with an atmosphere general circulation model fully resolving the stratosphere (with the top at 0.01 hPa) and its low-top version (with the top at 10 hPa). Both ensembles of simulations consist of nine members, covering the 1980–99 period and are forced with prescribed observed sea surface temperatures. It is found that both models capture the sensitivity of the averaged polar winter lower stratosphere to ENSO in the Northern Hemisphere, although with a reduced amplitude for the low-top model. In late winter and spring, the ENSO response at the surface is instead different in the two models. A large-scale coherent pattern in sea level pressure, with high pressures over the Arctic and low pressures over western and central Europe and the North Pacific, is found in the February–March mean of the high-top model. In the low-top model, the Arctic high pressure and the western and central Europe low pressure are very much reduced. The high-top minus low-top model difference in the ENSO temperature and precipitation anomalies is that North Europe is colder and the Northern Atlantic storm track is shifted southward in the high-top model. In addition, it has been found that major sudden stratospheric warming events are virtually lacking in the low-top model, while their frequency of occurrence is broadly realistic in the high-top model. Given that this is a major difference in the dynamical behavior of the stratosphere of the two models and that these events are favored by ENSO, it is concluded that the occurrence of sudden stratospheric warming events affects the reported differences in the tropospheric ENSO–NAE teleconnection. Given that the essence of the high-top minus low-top model difference is a more annular (or zonal) pattern of the anomaly in sea level pressure, relatively larger over the Arctic and the NAE regions, this interpretation is consistent with the observational evidence that sudden stratospheric warmings play a role in giving rise to persistent Arctic Oscillation anomalies at the surface.

A Characterization of the Present-Day Arctic Atmosphere in CCSM4

2012 ◽  
Vol 25 (8) ◽  
pp. 2676-2695 ◽  
Author(s):  
Gijs de Boer ◽  
William Chapman ◽  
Jennifer E. Kay ◽  
Brian Medeiros ◽  
Matthew D. Shupe ◽  
...  
Keyword(s):  
Sea Level ◽  
Energy Budget ◽  
Cloud Cover ◽  
Lower Troposphere ◽  
Surface Fluxes ◽  
The Arctic ◽  
Sea Level Pressure ◽  
Climate System Model ◽  
Level Pressure ◽  
Arctic Atmosphere

Abstract Simulation of key features of the Arctic atmosphere in the Community Climate System Model, version 4 (CCSM4) is evaluated against observational and reanalysis datasets for the present-day (1981–2005). Surface air temperature, sea level pressure, cloud cover and phase, precipitation and evaporation, the atmospheric energy budget, and lower-tropospheric stability are evaluated. Simulated surface air temperatures are found to be slightly too cold when compared with the 40-yr ECMWF Re-Analysis (ERA-40). Spatial patterns and temporal variability are well simulated. Evaluation of the sea level pressure demonstrates some large biases, most noticeably an under simulation of the Beaufort High during spring and autumn. Monthly Arctic-wide biases of up to 13 mb are reported. Cloud cover is underpredicted for all but summer months, and cloud phase is demonstrated to be different from observations. Despite low cloud cover, simulated all-sky liquid water paths are too high, while ice water path was generally too low. Precipitation is found to be excessive over much of the Arctic compared to ERA-40 and the Global Precipitation Climatology Project (GPCP) estimates. With some exceptions, evaporation is well captured by CCSM4, resulting in P − E estimates that are too high. CCSM4 energy budget terms show promising agreement with estimates from several sources. The most noticeable exception to this is the top of the atmosphere (TOA) fluxes that are found to be too low while surface fluxes are found to be too high during summer months. Finally, the lower troposphere is found to be too stable when compared to ERA-40 during all times of year but particularly during spring and summer months.

scholarly journals An Inter-Comparison of Arctic Synoptic Scale Storms between Four Global Reanalysis Datasets

2020 ◽  
Author(s):  
Alexander Vessey ◽  
Kevin Hodges ◽  
Len Shaffrey ◽  
Jonathan Day
Keyword(s):  
Sea Level ◽  
Relative Vorticity ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Level Pressure ◽  
Mean Sea Level ◽  
Tracking Method ◽  
Level Pressure ◽  
Storm Tracking ◽  
Storm Characteristics

<p>Arctic sea ice has reduced significantly over recent decades and is projected to reduce further over this century. This has made the Arctic more accessible and increased opportunities for the expansion of business and industrial activities.  As a result, the exposure and risk of humans and infrastructure to extreme storms will increase in the Arctic.</p><p>Our understanding of the current risk from storms comes from analysing the past, for example, by using storm tracking algorithms to detect storms in reanalysis datasets.  However, there are multiple reanalysis datasets available from different institutions and there are multiple storm tracking methods.  Previous studies have found that there can be differences between reanalysis datasets and between storm tracking methods in the climatology of storms, particularly in mid-latitude regions rather than the Arctic.  In this study, we aimed to improve the understanding of Arctic storms by assessing their characteristics in multiple global reanalyses, the ECMWF-Interim Reanalysis (ERA-Interim), the 55-Year Japanese Reanalysis (JRA-55), the NASA-Modern Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2), and the NCEP-Climate Forecast System Reanalysis (NCEP-CFSR), using the same storm tracking method based on 850 hPa relative vorticity and mean sea level pressure.</p><p>The results from this study show that there are no significant trends in Arctic storm characteristics between 1980-2017, even though the Arctic has undergone rapid change.  Although some similar Arctic storm characteristics are found between the reanalysis datasets, there are generally higher differences between the reanalyses in winter (DJF) than in summer (JJA).  In addition, substantial differences can arise between using the same storm tracking method based on 850 hPa relative vorticity or mean sea level pressure, which adds to the uncertainty associated with current Arctic storm characteristics.</p>

scholarly journals The Arctic sea ice extent change connected to Pacific decadal variability

2020 ◽  
Vol 14 (2) ◽  
pp. 693-708
Author(s):  
Xiao-Yi Yang ◽  
Guihua Wang ◽  
Noel Keenlyside
Keyword(s):  
Sea Ice ◽  
Sea Level ◽  
Annual Cycle ◽  
Bering Sea ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Arctic Sea

Abstract. After an unprecedented retreat, the total Arctic sea ice cover for the post-2007 period is characterized by low extent and a remarkable increase in annual cycle amplitude. We have identified the leading role of spring Bering Sea ice in explaining the changes in the amplitude of the annual cycle of total Arctic sea ice. In particular, these changes are related to the recent occurrence of multiyear variability in spring Bering Sea ice extent. This is due to the phase-locking of the North Pacific Gyre Oscillation (NPGO) and the Pacific Decadal Oscillation (PDO) after about 2007, with a correlation coefficient reaching −0.6. Furthermore, there emerge notable changes in the sea level pressure and sea surface temperature patterns associated with the NPGO in the recent decade. After 2007, the NPGO is related to a quadrupole of sea level pressure (SLP) anomalies that is associated with the wind stress curl and Ekman pumping rate anomalies in the Bering deep basin; these account for the change in Bering Sea subsurface variability that contribute to the decadal oscillation of the spring Bering Sea ice extent.

scholarly journals Patterns of Sea Ice Retreat in the Transition to a Seasonally Ice-Free Arctic

2016 ◽  
Vol 29 (19) ◽  
pp. 6993-7008 ◽  
Author(s):  
Patricia DeRepentigny ◽  
L. Bruno Tremblay ◽  
Robert Newton ◽  
Stephanie Pfirman
Keyword(s):  
Sea Ice ◽  
Sea Level ◽  
Large Scale ◽  
System Model ◽  
The Arctic ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
The Pacific ◽  
Ice Retreat ◽  
Sea Ice Retreat

Abstract The patterns of sea ice retreat in the Arctic Ocean are investigated using two global climate models (GCMs) that have profound differences in their large-scale mean winter atmospheric circulation and sea ice drift patterns. The Community Earth System Model Large Ensemble (CESM-LE) presents a mean sea level pressure pattern that is in general agreement with observations for the late twentieth century. The Community Climate System Model, version 4 (CCSM4), exhibits a low bias in its mean sea level pressure over the Arctic region with a deeper Icelandic low. A dynamical mechanism is presented in which large-scale mean winter atmospheric circulation has significant effect on the following September sea ice extent anomaly by influencing ice divergence in specific areas. A Lagrangian model is used to backtrack the 80°N line from the approximate time of the melt onset to its prior positions throughout the previous winter and quantify the divergence across the Pacific and Eurasian sectors of the Arctic. It is found that CCSM4 simulates more sea ice divergence in the Beaufort and Chukchi Seas and less divergence in the Eurasian seas when compared to CESM-LE, leading to a Pacific-centric sea ice retreat. On the other hand, CESM-LE shows a more symmetrical retreat between the Pacific, Eurasian, and Atlantic sectors of the Arctic. Given that a positive trend in the Arctic Oscillation (AO) index, associated with low sea level pressure anomalies in the Arctic, is a robust feature of GCMs participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5), these results suggest that the sea ice retreat in the Pacific sector could be amplified during the transition to a seasonal ice cover.

scholarly journals Decadal changes in the leading patterns of sea level pressure in the Arctic and their impacts on the sea ice variability in boreal summer

2019 ◽  
Vol 13 (11) ◽  
pp. 3007-3021
Author(s):  
Nakbin Choi ◽  
Kyu-Myong Kim ◽  
Young-Kwon Lim ◽  
Myong-In Lee
Keyword(s):  
Sea Ice ◽  
Sea Level ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Boreal Summer ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
The Pacific ◽  
Circulation Change ◽  
Arctic Sea

Abstract. Besides its negative trend, the interannual and the interdecadal changes in the Arctic sea ice have also been pronounced in recent decades. The three leading modes in the sea level pressure (SLP) variability in the Arctic (70–90∘ N) – the Arctic Oscillation (AO), the Arctic Dipole (AD), and the third mode (A3) – are analyzed to understand the linkage between sea ice variability and large-scale atmospheric circulation in boreal summer (June–August). This study also compares the decadal changes of the modes between the early (1982–1997) and the recent (1998–2017) periods and their influences on the Arctic sea ice extent (SIE). Only the AD mode shows a significant correlation increase with SIE in summer (JJA) from −0.05 in the early period to 0.57 in the recent period. The AO and the A3 modes show a less significant relationship with SIE for the two periods. The AD is characterized by a dipole pattern of SLP, which modulates the strength of meridional surface winds and the Transpolar Drift Stream (TDS). The major circulation change in the late 1990s is that the direction of the wind has been changed more meridionally over the exit region of the Fram Strait, which causes sea ice drift and discharge through that region. In addition, the response of surface albedo and the net surface heat flux becomes larger and much clearer, suggesting a positive sea-ice–albedo feedback in the sea ice variability associated with the AD. The analysis also reveals that the zonal shift of the centers of SLP anomalies and associated circulation change affects a significant reduction in sea ice concentration over the Pacific sector of the Arctic Ocean. This study further suggests that the Pacific Decadal Oscillation (PDO) phase change could influence the spatial pattern change in the AD.

Sign in / Sign up

Export Citation Format

Share Document