scholarly journals Impacts of the Madden–Julian Oscillation on Storm-Track Activity, Surface Air Temperature, and Precipitation over North America

2018 ◽  
Vol 31 (15) ◽  
pp. 6113-6134 ◽  
Author(s):  
Cheng Zheng ◽  
Edmund Kar-Man Chang ◽  
Hye-Mi Kim ◽  
Minghua Zhang ◽  
Wanqiu Wang
Keyword(s):  
United States ◽  
North America ◽  
Air Temperature ◽  
West Coast ◽  
Storm Track ◽  
Surface Air Temperature ◽  
Madden Julian Oscillation ◽  
Temperature And Precipitation ◽  
Storm Track Activity ◽  
Wave Trains

In this study, the intraseasonal variations in storm-track activity, surface air temperature, and precipitation over North America associated with the Madden–Julian oscillation (MJO) in boreal winter (November–April) are investigated. A lag composite strategy that considers different MJO phases and different lag days is developed. The results highlight regions over which the MJO has significant impacts on surface weather on intraseasonal time scales. A north–south shift of storm-track activity associated with the MJO is found over North America. The shift is consistent with the MJO-related surface air temperature anomaly over the eastern United States. In many regions over the western, central, and southeastern United States, the MJO-related precipitation signal is also consistent with nearby storm-track activity. An MJO-related north–south shift of precipitation is also found near the west coast of North America, with the precipitation over California being consistent with the MJO-related storm-track activity over the eastern Pacific. MJO-related temperature and storm-track anomalies are also found near Alaska. Further analyses of streamfunction anomalies and wave activity flux show clear signatures of Rossby wave trains excited by convection anomalies related to MJO phases 3 and 8. These wave trains propagate across the Pacific and North America, bringing an anticyclonic (cyclonic) anomaly to the eastern part of North America, shifting the westerly jet to the north (south), thereby modulating the surface air temperature and storm-track activity over the continent. Rossby waves associated with phases 2 and 6 are also found to impact the U.S. West Coast.

scholarly journals Seasonal Variation and Spatial Patterns of the Atmospheric Component of the Pacific Decadal Oscillation

2013 ◽  
Vol 26 (5) ◽  
pp. 1575-1594 ◽  
Author(s):  
Catrin M. Mills ◽  
John E. Walsh
Keyword(s):  
United States ◽  
North America ◽  
Air Temperature ◽  
Pacific Decadal Oscillation ◽  
Southern Oscillation ◽  
Grid Point ◽  
Southeastern United States ◽  
Surface Air Temperature ◽  
The Pacific ◽  
Difference Fields

Abstract The Pacific decadal oscillation (PDO) is an El Niño–Southern Oscillation (ENSO)-like climate oscillation that varies on multidecadal and higher-frequency scales, with a sea surface temperature (SST) dipole in the Pacific. This study addresses the seasonality, vertical structure, and across-variable relationships of the local North Pacific and downstream North American atmospheric signal of the PDO. The PDO-based composite difference fields of 500-mb geopotential height, surface air temperature, sea level pressure, and precipitation vary not only across seasons, but also from one calendar month to another within a season, although month-to-month continuity is apparent. The most significant signals occur in western North America and in the southeastern United States, where a positive PDO is associated with negative heights, consistent with underlying temperatures in the winter. In summer, a negative precipitation signal in the southeastern United States associated with a positive PDO phase is consistent with a ridge over the region. When an annual harmonic is fit to the 12 monthly surface air temperature differences at each grid point, the PDO temperature signal peaks in winter in most of North America, while a peak in summer occurs in the southeastern United States. Approximately 25% of the variance of the PDO index is accounted for by ENSO. Atmospheric composite differences based on a residual (ENSO linearly removed) PDO index have many similarities to those of the full PDO signal.

A composite study of the MJO influence on the surface air temperature and precipitation over the Continental United States

2011 ◽  
Vol 38 (7-8) ◽  
pp. 1459-1471 ◽  
Author(s):  
Shuntai Zhou ◽  
Michelle L’Heureux ◽  
Scott Weaver ◽  
Arun Kumar
Keyword(s):  
United States ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Temperature And Precipitation ◽  
Composite Study

scholarly journals Mapping the Relationship between Northern Hemisphere Winter Surface Air Temperature and the Madden–Julian Oscillation

2011 ◽  
Vol 139 (8) ◽  
pp. 2439-2454 ◽  
Author(s):  
Yang Zhou ◽  
Keith R. Thompson ◽  
Youyu Lu
Keyword(s):  
North America ◽  
Linear Model ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Boreal Winter ◽  
Eastern North America ◽  
Madden Julian Oscillation ◽  
State Variables ◽  
Normal Surface ◽  
The Tropics

AbstractA regression-based modeling approach is described for mapping the dependence of atmospheric state variables such as surface air temperature (SAT) on the Madden–Julian oscillation (MJO). For the special case of a linear model the dependence can be described by two maps corresponding to the amplitude and lag of the mean atmospheric response with respect to the MJO. In this sense the method leads to a more parsimonious description than traditional compositing, which usually results in eight maps, one for each MJO phase. Another advantage of the amplitude and phase maps is that they clearly identify propagating signals, and also regions where the response is strongly amplified or attenuated. A straightforward extension of the linear model is proposed to allow the amplitude and phase of the response to vary with the amplitude of the MJO or indices that define the background state of the atmosphere–ocean system. Application of the approach to global SAT for boreal winter clearly shows the propagation of MJO-related signals in both the tropics and extratropics and an enhanced response over eastern North America and Alaska (further enhanced during La Niña years). The SAT response over Alaska and eastern North America is caused mainly by horizontal advection related to variations in shore-normal surface winds that, in turn, can be traced (via signals in the 500-hPa geopotential height) back to MJO-related disturbances in the tropics.

scholarly journals The Influence of the Madden–Julian Oscillation on Canadian Wintertime Surface Air Temperature

2009 ◽  
Vol 137 (7) ◽  
pp. 2250-2262 ◽  
Author(s):  
Hai Lin ◽  
Gilbert Brunet
Keyword(s):  
Air Temperature ◽  
Wave Train ◽  
Winter Season ◽  
Surface Air Temperature ◽  
Madden Julian Oscillation ◽  
Eastern Canada ◽  
Central Pacific ◽  
Sea Level Pressure ◽  
The Indian Ocean ◽  
Rossby Wave Train

Using the homogenized Canadian historical daily surface air temperature (SAT) for 210 relatively evenly distributed stations across Canada, the lagged composites and probability of the above- and below-normal SAT in Canada for different phases of the Madden–Julian oscillation (MJO) in the winter season are analyzed. Significant positive SAT anomalies and high probability of above-normal events in the central and eastern Canada are found 5–15 days following MJO phase 3, which corresponds to an enhanced precipitation over the Indian Ocean and Maritime Continent and a reduced convective activity near the tropical central Pacific. On the other hand, a positive SAT anomaly appears over a large part of northern and northeastern Canada about 5–15 days after the MJO is detected in phase 7. An analysis of the evolution of the 500-hPa geopotential height and sea level pressure anomalies indicates that the Canadian SAT anomaly is a result of a Rossby wave train associated with the tropical convection anomaly of the MJO. Hence, the MJO phase provides useful information for the extended-range forecast of Canadian winter surface air temperature. This result also provides an important reference for numerical model verifications.

scholarly journals Seasonal Surface Air Temperature and Precipitation in the FSU Climate Model Coupled to the CLM2

2005 ◽  
Vol 18 (16) ◽  
pp. 3217-3228 ◽  
Author(s):  
D. W. Shin ◽  
S. Cocke ◽  
T. E. LaRow ◽  
James J. O’Brien
Keyword(s):  
Heat Flux ◽  
Air Temperature ◽  
Climate Model ◽  
Initial Conditions ◽  
Sensible Heat Flux ◽  
Surface Air Temperature ◽  
Community Land Model ◽  
Temperature And Precipitation ◽  
The Impact ◽  
Convective Scheme

Abstract The current Florida State University (FSU) climate model is upgraded by coupling the National Center for Atmospheric Research (NCAR) Community Land Model Version 2 (CLM2) as its land component in order to make a better simulation of surface air temperature and precipitation on the seasonal time scale, which is important for crop model application. Climatological and seasonal simulations with the FSU climate model coupled to the CLM2 (hereafter FSUCLM) are compared to those of the control (the FSU model with the original simple land surface treatment). The current version of the FSU model is known to have a cold bias in the temperature field and a wet bias in precipitation. The implementation of FSUCLM has reduced or eliminated this bias due to reduced latent heat flux and increased sensible heat flux. The role of the land model in seasonal simulations is shown to be more important during summertime than wintertime. An additional experiment that assimilates atmospheric forcings produces improved land-model initial conditions, which in turn reduces the biases further. The impact of various deep convective parameterizations is examined as well to further assess model performance. The land scheme plays a more important role than the convective scheme in simulations of surface air temperature. However, each convective scheme shows its own advantage over different geophysical locations in precipitation simulations.

scholarly journals Panama’s Current Climate Replicability in a Non-Hydrostatic Regional Climate Model Nested in an Atmospheric General Circulation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1543
Author(s):  
Reinhardt Pinzón ◽  
Noriko N. Ishizaki ◽  
Hidetaka Sasaki ◽  
Tosiyuki Nakaegawa
Keyword(s):  
Regional Climate Model ◽  
Air Temperature ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Horizontal Resolution ◽  
Temperature And Precipitation ◽  
Current Climate

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation.

scholarly journals Influence of ENSO on North American subseasonal surface air temperature variability

2021 ◽  
Vol 2 (2) ◽  
pp. 395-412
Author(s):  
Patrick Martineau ◽  
Hisashi Nakamura ◽  
Yu Kosaka
Keyword(s):  
North America ◽  
Air Temperature ◽  
North American ◽  
Surface Air Temperature ◽  
Tropical Pacific ◽  
La Niña ◽  
Western North America ◽  
The North ◽  
Subseasonal Variability ◽  
La Nina

Abstract. The wintertime influence of tropical Pacific sea surface temperature (SST) variability on subseasonal variability is revisited by identifying the dominant mode of covariability between 10–60 d band-pass-filtered surface air temperature (SAT) variability over the North American continent and winter-mean SST over the tropical Pacific. We find that the El Niño–Southern Oscillation (ENSO) explains a dominant fraction of the year-to-year changes in subseasonal SAT variability that are covarying with SST and thus likely more predictable. In agreement with previous studies, we find a tendency for La Niña conditions to enhance the subseasonal SAT variability over western North America. This modulation of subseasonal variability is achieved through interactions between subseasonal eddies and La Niña-related changes in the winter-mean circulation. Specifically, eastward-propagating quasi-stationary eddies over the North Pacific are more efficient in extracting energy from the mean flow through the baroclinic conversion during La Niña. Structural changes of these eddies are crucial to enhance the efficiency of the energy conversion via amplified downgradient heat fluxes that energize subseasonal eddy thermal anomalies. The enhanced likelihood of cold extremes over western North America is associated with both an increased subseasonal SAT variability and the cold winter-mean response to La Niña.

scholarly journals Diagnosis of Multiyear Predictability on Continental Scales

2011 ◽  
Vol 24 (19) ◽  
pp. 5108-5124 ◽  
Author(s):  
Liwei Jia ◽  
Timothy DelSole
Keyword(s):  
Time Scales ◽  
Air Temperature ◽  
Climate Models ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Optimization Method ◽  
First Year ◽  
Temperature And Precipitation ◽  
Regional Prediction ◽  
Intercomparison Project

A new statistical optimization method is used to identify components of surface air temperature and precipitation on six continents that are predictable in multiple climate models on multiyear time scales. The components are identified from unforced “control runs” of the Coupled Model Intercomparison Project phase 3 dataset. The leading predictable components can be calculated in independent control runs with statistically significant skill for 3–6 yr for surface air temperature and 1–3 yr for precipitation, depending on the continent, using a linear regression model with global sea surface temperature (SST) as a predictor. Typically, lag-correlation maps reveal that the leading predictable components of surface air temperature are related to two types of SST patterns: persistent patterns near the continent itself and an oscillatory ENSO-like pattern. The only exception is Europe, which has no significant ENSO relation. The leading predictable components of precipitation are significantly correlated with an ENSO-like SST pattern. No multiyear predictability of land precipitation could be verified in Europe. The squared multiple correlations of surface air temperature and precipitation for nonzero lags on each continent are less than 0.4 in the first year, implying that less than 40% of variations of the leading predictable component can be predicted from global SST. The predictable components describe the spatial structures that can be predicted on multiyear time scales in the absence of anthropogenic and natural forcing, and thus provide a scientific rationale for regional prediction on multiyear time scales.

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