Decadal Variability of Great Lakes Ice Cover in Response to AMO and PDO, 1963–2017

2018 ◽  
Vol 31 (18) ◽  
pp. 7249-7268 ◽  
Author(s):  
Jia Wang ◽  
James Kessler ◽  
Xuezhi Bai ◽  
Anne Clites ◽  
Brent Lofgren ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Great Lakes ◽  
Regression Model ◽  
Decadal Variability ◽  
Ice Cover ◽  
Lake Surface ◽  
Lake Ice ◽  
Relationship Of ◽  
The Relationship ◽  
Lake Ice Cover

Abstract In this study, decadal variability of ice cover in the Great Lakes is investigated using historical airborne and satellite measurements from 1963 to 2017. It was found that Great Lakes ice cover has 1) a linear relationship with the Atlantic multidecadal oscillation (AMO), similar to the relationship of lake ice cover with the North Atlantic Oscillation (NAO), but with stronger impact than NAO; 2) a quadratic relationship with the Pacific decadal oscillation (PDO), which is similar to the relationship of lake ice cover to Niño-3.4, but with opposite curvature; and 3) decadal variability with a positive (warming) trend in AMO contributes to the decreasing trend in lake ice cover. Composite analyses show that during the positive (negative) phase of AMO, the Great Lakes experience a warm (cold) anomaly in surface air temperature (SAT) and lake surface temperature (LST), leading to less (more) ice cover. During the positive (negative) phase of PDO, the Great Lakes experience a cold (warm) anomaly in SAT and LST, leading to more (less) ice cover. Based on these statistical relationships, the original multiple variable regression model established using the indices of NAO and Niño-3.4 only was improved by adding both AMO and PDO, as well as their interference (interacting or competing) mechanism. With the AMO and PDO added, the correlation between the model and observation increases to 0.69, compared to 0.48 using NAO and Niño-3.4 only. When November lake surface temperature was further added to the regression model, the prediction skill of the coming winter ice cover increased even more.

scholarly journals Sensitivity of Lake-Effect Snowfall to Lake Ice Cover and Temperature in the Great Lakes Region

2013 ◽  
Vol 141 (2) ◽  
pp. 670-689 ◽  
Author(s):  
David M. Wright ◽  
Derek J. Posselt ◽  
Allison L. Steiner
Keyword(s):  
Great Lakes ◽  
Large Scale ◽  
Ice Cover ◽  
Surface Fluxes ◽  
Lake Surface ◽  
Lake Ice ◽  
Lake Shore ◽  
Lake Effect ◽  
Spatial Coverage ◽  
Lake Ice Cover

Abstract High-resolution Weather Research and Forecasting Model (WRF) simulations are used to explore the sensitivity of Great Lakes lake-effect snowfall (LES) to changes in lake ice cover and surface temperature. A control simulation with observed ice cover is compared with three sensitivity tests: complete ice cover, no lake ice, and warmer lake surface temperatures. The spatial pattern of unfrozen lake surfaces determines the placement of LES, and complete ice cover eliminates it. Removal of ice cover and an increase in lake temperatures result in an expansion of the LES area both along and downwind of the lake shore, as well as an increase in snowfall amount. While lake temperatures and phase determine the amount and spatial coverage of LES, the finescale distribution of LES is strongly affected by the interaction between lake surface fluxes, the large-scale flow, and the local lake shore geography and inland topography. As a consequence, the sensitivity of LES to topography and shore geometry differs for lakes with short versus long overwater fetch. These simulations indicate that coarse-resolution models may be able to realistically reproduce the gross features of LES in future climates, but will miss the important local-scale interactions that determine the location and intensity of LES.

scholarly journals Simulation of Heavy Lake-Effect Snowstorms across the Great Lakes Basin by RegCM4: Synoptic Climatology and Variability*,+

2013 ◽  
Vol 141 (6) ◽  
pp. 1990-2014 ◽  
Author(s):  
Michael Notaro ◽  
Azar Zarrin ◽  
Steve Vavrus ◽  
Val Bennington
Keyword(s):  
Great Lakes ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Cover ◽  
Synoptic Climatology ◽  
Great Lakes Basin ◽  
Lake Ice ◽  
Lake Effect ◽  
Lake Ice Cover

Abstract A historical simulation (1976–2002) of the Abdus Salam International Centre for Theoretical Physics Regional Climate Model, version 4 (ICTP RegCM4), coupled to a one-dimensional lake model, is validated against observed lake ice cover and snowfall across the Great Lakes Basin. The model reproduces the broad temporal and spatial features of both variables in terms of spatial distribution, seasonal cycle, and interannual variability, including climatological characteristics of lake-effect snowfall, although the simulated ice cover is overly extensive largely due to the absence of lake circulations. A definition is introduced for identifying heavy lake-effect snowstorms in regional climate model output for all grid cells in the Great Lakes Basin, using criteria based on location, wind direction, lake ice cover, and snowfall. Simulated heavy lake-effect snowstorms occur most frequently downwind of the Great Lakes, particularly to the east of Lake Ontario and to the east and south of Lake Superior, and are most frequent in December–January. The mechanism for these events is attributed to an anticyclone over the central United States and related cold-air outbreak for areas downwind of Lakes Ontario and Erie, in contrast to a nearby cyclone over the Great Lakes Basin and associated cold front for areas downwind of Lakes Superior, Huron, and Michigan.

Using The Fully Modified M Method In Estimating The Effect Of Cultivated Area On Barley Production In Iraq For The Period 1970-2018

2020 ◽  
Vol 2020 (66) ◽  
pp. 101-110
Author(s):  
. Azhar Kadhim Jbarah ◽  
Prof Dr. Ahmed Shaker Mohammed
Keyword(s):  
Regression Model ◽  
Moving Average ◽  
Estimation Method ◽  
Estimation Methods ◽  
Autoregressive Moving Average ◽  
Moving Average Models ◽  
Error Terms ◽  
Relationship Of ◽  
The Relationship ◽  
Barley Crop

The research is concerned with estimating the effect of the cultivated area of barley crop on the production of that crop by estimating the regression model representing the relationship of these two variables. The results of the tests indicated that the time series of the response variable values is stationary and the series of values of the explanatory variable were nonstationary and that they were integrated of order one ( I(1) ), these tests also indicate that the random error terms are auto correlated and can be modeled according to the mixed autoregressive-moving average models ARMA(p,q), for these results we cannot use the classical estimation method to estimate our regression model, therefore, a fully modified M method was adopted, which is a robust estimation methods, The estimated results indicate a positive significant relation between the production of barley crop and cultivated area.

scholarly journals Calving Seasonality Associated With Melt‐Undercutting and Lake Ice Cover

2020 ◽  
Vol 47 (8) ◽  
Author(s):  
Joseph Mallalieu ◽  
Jonathan L. Carrivick ◽  
Duncan J. Quincey ◽  
Mark W. Smith
Keyword(s):  
Ice Cover ◽  
Lake Ice ◽  
Lake Ice Cover

The Settlement Prediction of Pile Foundation Based on Grey Linear Regression Model

2012 ◽  
Vol 204-208 ◽  
pp. 320-325
Author(s):  
Jia Kun Liu ◽  
Jian Ping Wang ◽  
Min Zhu ◽  
Xiao Jie Hou
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Pile Foundation ◽  
Load Test ◽  
Static Load Test ◽  
Combined Model ◽  
Actual Meaning ◽  
Relationship Of ◽  
The Relationship

Grey linear regression model is a covert grey combined model that is built based on GM(1,1) model and linear regression model. It improves undervaluation of linear regression model which can not in press the exponential growth and come to deficiency of grey GM (1, 1) model which has not linear factor. This paper briefly introduces the establishment and precision examination method of the grey linearity regression model and establishes the grey linear regression model to predict the relationship of load and settlement. Based on the data of static load test, the load-settlement curve is simulated and analyzed. The result of study shows that Grey Linear regression Model can effectively predict the settlement of pile foundation, and be of the theoretical and actual meaning for further analyzing the bearing capability of pile foundation.

Simulation of North American lake-ice cover characteristics under contemporary and future climate conditions

2011 ◽  
Vol 32 (5) ◽  
pp. 695-709 ◽  
Author(s):  
Yonas Dibike ◽  
Terry Prowse ◽  
Barrie Bonsal ◽  
Laurent de Rham ◽  
Tuomo Saloranta
Keyword(s):  
North American ◽  
Ice Cover ◽  
Future Climate ◽  
Lake Ice ◽  
Climate Conditions ◽  
Lake Ice Cover

scholarly journals Changes in Lake Ice Cover on the Morskie Oko Lake in Poland (1971-2007)

2013 ◽  
Vol 1 (2) ◽  
pp. 71-75
Author(s):  
Choiński Adam ◽  
Kolendowicz Leszek ◽  
Pociask-Karteczka Joanna ◽  
Sobkowiak Leszek
Keyword(s):  
Ice Cover ◽  
Lake Ice ◽  
Lake Ice Cover

scholarly journals Decay of a High Arctic lake-ice cover: observations and modelling

1994 ◽  
Vol 40 (135) ◽  
pp. 283-292 ◽  
Author(s):  
Richard Heron ◽  
Ming-Ko Woo
Keyword(s):  
Energy Balance ◽  
Ice Cover ◽  
High Arctic ◽  
Shortwave Radiation ◽  
Balance Model ◽  
Lake Ice ◽  
Ice Melt ◽  
Density Reduction ◽  
Ice Water ◽  
Lake Ice Cover

AbstractThe decay of a lake-ice cover in the Canadian High Arctic was studied for 2 years. Melt at the upper surface accounted for 75% of the decrease in ice thickness, while 25% occurred at the ice–water interface. An energy-balance model, incorporating density reduction due to internal ice melt, was used to simulate the decay of the ice cover. The overall performance of the model was satisfactory despite periods when computed results differed from the observed ice decay. Energy-balance calculations indicated that the absorption of shortwave radiation within the ice provided 52% of the melt energy while 33 and 15% came from the surface-energy balance and heat flux from the water.

scholarly journals Relationship of the Arctic and Antarctic Oscillations to the Outgoing Longwave Radiation

2003 ◽  
Vol 16 (10) ◽  
pp. 1583-1592 ◽  
Author(s):  
A. J. Miller ◽  
S. Zhou ◽  
S-K. Yang
Keyword(s):  
Numerical Model ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Outgoing Longwave Radiation ◽  
Longwave Radiation ◽  
Sea Surface ◽  
Radiation Budget ◽  
The Arctic ◽  
Relationship Of ◽  
The Relationship

Abstract While several mechanisms have been suggested to account for the association of the Arctic and Antarctic Oscillations (AO/AAO) with atmospheric parameters, this paper focuses on the relationship with the atmospheric outgoing longwave radiation (OLR). The main objective of this paper is to demonstrate through AO/AAO composite analysis that the NCEP–NCAR reanalysis OLR agrees with the independent observations of the NASA Earth Radiation Budget Experiment (ERBE) broadband satellite instruments both in zonal averages and in geographically mapped space, and to verify AO/AAO characterized general circulations derived from models and analyses. The results indicate several pronounced areas of storminess that are AO/AAO dependent. One is the well-known variation over the North Atlantic Ocean toward Europe. Also, several major areas are indicated in the tropical region—one in the Indian Ocean and the others in the west and central Pacific Ocean. In addition to demonstrating that the signals are statistically significant, also tested is the relationship of the features to other well-known tropical forcing mechanisms: the Madden–Julian oscillation (MJO) and the El Niño–La Niña sea surface temperature variations. It is shown that the tropical features do, in fact, have a strong relationship to the MJO, which indicates an additional tropical–extratropical interaction. With regard to the sea surface temperature, no correlation associated with the AO/AAO variability is seen. These associations with the cloudiness and atmospheric radiation budget suggest that if there is to be improvement of numerical model forecasts to an extended time period that numerical model radiation physics will have to be taken into consideration and improved.

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