Summer Nonconvective Severe Wind Frequency over Ontario and Its Correlation with Tropical Pacific Sea Surface Temperature

2014 ◽  
Vol 53 (5) ◽  
pp. 1170-1182 ◽  
Author(s):  
Da-Lin Zhang ◽  
Zuohao Cao ◽  
Jianmin Ma ◽  
Aiming Wu
Keyword(s):  
Air Temperature ◽  
Large Scale ◽  
Regional Climate ◽  
Surface Wind ◽  
Surface Air Temperature ◽  
Kendall Test ◽  
Tropical Pacific ◽  
Sea Surface ◽  
Positive Trend ◽  
Climate Conditions

AbstractThe summer nonconvective severe surface wind (NCSSW) frequency over Ontario, Canada, in relation to regional climate conditions and tropical Pacific Ocean sea surface temperatures (SSTs) during the period of 1979–2006 is examined using surface wind reports and large-scale analysis data. A statistically robust positive trend in Ontario summer NCSSW frequency is identified using three independent statistical approaches, which include the conventional linear regression that has little disturbance to the original time series, the Mann–Kendall test without a lag-1 autoregressive process, and the Monte Carlo simulation. A composite analysis of the large-scale monthly mean data reveals that the high- (low-) NCSSW occurrence years are linked to stronger (weaker) large-scale horizontal pressure gradients and more (less) intensive vector wind anomalies in the upper troposphere. Unlike the low-event years, anomalous anticyclonic circulations are found at 500 and 250 hPa in the high-event years, which are conducive to downward momentum transport and favorable for severe surface wind development. It is also found that the summer NCSSW occurs more frequently under the conditions of warmer surface air temperature over Ontario. Further analyses indicate that an increase in the summer NCSSW frequency is well correlated with an increase in the previous winter SSTs over the eastern equatorial Pacific, namely, in the Niño-1+2 and Niño-3 areas, through a decrease in sea level pressure over northern Ontario and an increase in surface air temperature over central and southern Ontario.

Trends and variability of climate and river flow in the region of Costa das Baleias, Brazil

2013 ◽  
Vol 67 (1) ◽  
pp. 47-54 ◽  
Author(s):  
F. Genz ◽  
C. A. S. Tanajura
Keyword(s):  
River Discharge ◽  
Large Scale ◽  
River Flow ◽  
Local Development ◽  
Global Climate ◽  
Surface Air Temperature ◽  
Kendall Test ◽  
Positive Trend ◽  
Area Of Interest ◽  
Discharge Rates

There is an ongoing effort by the scientific community to regionalize climate studies to support local development plans. The area of interest is the Costa das Baleias on the east coast of northeast Brazil. It is located in a transition region of precipitation trends, and so assessing the local signal and magnitude is necessary. A series of annual anomalies of surface air temperature, precipitation and river discharge were analyzed from 1946 to 2010. The modified Mann–Kendall test was applied to detect trends. Temperature anomalies showed a consistent positive trend since 1950. Precipitation anomalies tended to decrease, though not significantly. River discharge rates showed a consistent positive trend. However, from the 1980s onwards, both the precipitation and the river discharge anomalies had the same decreasing tendency. The precipitation and discharge behavior are likely due to the combined effect of human interventions in the river basins including local, synoptic and global climate effects. The inter-annual variability was characterized by spectral analysis. Cycles were identified for the precipitation and the river discharge with periods of 2–3 years, 3–4 years, 7–8 years and 11–12 years. The decadal frequency is consistent with the South Atlantic and El Niño indices. This work strongly indicates that climate is changing in Costa das Baleias and further work is needed to investigate the mechanisms that link local to large-scale variability.

Enhanced Relationship between Central Tropical Pacific Sea Surface Temperature and Eurasian Surface Air Temperature during Boreal Summers

2021 ◽  
pp. 1-68
Author(s):  
Jing Ming ◽  
Jianqi Sun
Keyword(s):  
Air Temperature ◽  
North Pacific ◽  
Wave Train ◽  
Surface Air Temperature ◽  
Tropical Pacific ◽  
Sea Surface ◽  
The North ◽  
The Relationship ◽  
The North Pacific ◽  
Mean State

AbstractThis study investigates the relationship between the central tropical Pacific (CTP) sea surface temperature (SST) and the surface air temperature (SAT) variability un-related to canonical El Niño-Southern Oscillation (ENSO) over mid-to-high latitude Eurasia during boreal summers over the past half-century. The results show that their relationship experienced a decadal shift around the early 1980s. Before the early 1980s, the Eurasian SAT-CTP SST connection was weak; after that time, the relationship became stronger, and the SAT anomalies exhibited a significant wave-like pattern over Eurasia. Such a decadal change in the Eurasian SAT-CTP SST relationship could be attributed to decadal changes in the mean state and variability of CTP SST. The warmer mean state and enhanced SST variability after the early 1980s reinforced the convective activities over the tropical Pacific, leading to significantly anomalous divergence/convergence and Rossby wave sources over the North Pacific. This outcome further excited the wave train propagating along the Northern Hemisphere zonal jet stream to northern Eurasia and then affected the surface heat fluxes and atmospheric circulations over the region, resulting in wave-like SATs over Eurasia. However, during the period before the early 1980s, the CTP SST had a weak impact on the North Pacific atmospheric circulation and was consequently not able to excite the wave train pattern to impact the Eurasian atmospheric circulation and SATs. The physical processes linking the CTP SST and Eurasian SAT are further confirmed by numerical simulations. The results of this study are valuable to understanding the variability of summer Eurasian SATs.

Analysis of Mean Climate Conditions in Senegal (1971–98)

2006 ◽  
Vol 10 (5) ◽  
pp. 1-40 ◽  
Author(s):  
Souleymane Fall ◽  
Dev Niyogi ◽  
Fredrick H. M. Semazzi
Keyword(s):  
West Africa ◽  
Large Scale ◽  
Regional Climate ◽  
Linear Regression Analysis ◽  
Regional Scale ◽  
Regional Climate Change ◽  
Warming Trend ◽  
Positive Trend ◽  
Local Climate ◽  
Climate Conditions

Abstract This paper presents a GIS-based analysis of climate variability over Senegal, West Africa. It responds to the need for developing a climate atlas that uses local observations instead of gridded global analyses. Monthly readings of observed rainfall (20 stations) and mean temperature (12 stations) were compiled, digitized, and quality assured for a period from 1971 to 1998. The monthly, seasonal, and annual temperature and precipitation distributions were mapped and analyzed using ArcGIS Spatial Analyst. A north–south gradient in rainfall and an east–west gradient in temperature variations were observed. June exhibits the greatest variability for both quantity of rainfall and number of rainy days, especially in the western and northern parts of the country. Trends in precipitation and temperature were studied using a linear regression analysis and interpolation maps. Air temperature showed a positive and significant warming trend throughout the country, except in the southeast. A significant correlation is found between the temperature index for Senegal and the Pacific sea surface temperatures during the January–April period, especially in the El Niño zone. In contrast to earlier regional-scale studies, precipitation does not show a negative trend and has remained largely unchanged, with a few locations showing a positive trend, particularly in the northeastern and southwestern regions. This study reveals a need for more localized climate analyses of the West Africa region because local climate variations are not always captured by large-scale analysis, and such variations can alter conclusions related to regional climate change.

scholarly journals Influence of Forced Large-Scale Atmospheric Patterns on Surface Air Temperature in China

2011 ◽  
Vol 139 (3) ◽  
pp. 830-852 ◽  
Author(s):  
Xiaojing Jia ◽  
Hai Lin
Keyword(s):  
Air Temperature ◽  
General Circulation ◽  
Large Scale ◽  
Statistical Approach ◽  
Surface Air Temperature ◽  
Tropical Pacific ◽  
Second Phase ◽  
Seasonal Forecasts ◽  
The Relationship ◽  
The Tropical Pacific

Abstract The seasonality of the influence of the tropical Pacific sea surface temperature (SST)-forced large-scale atmospheric patterns on the surface air temperature (SAT) over China is investigated for the period from 1969 to 2001. Both observations and output from four atmospheric general circulation models (GCMs) involved in the second phase of the Canadian Historical Forecasting Project (HFP) are used. The large-scale atmospheric patterns are obtained by applying a singular value decomposition (SVD) analysis between 500-hPa geopotential height (Z500) in the Northern Hemisphere and SST in the tropical Pacific Ocean. Temporal correlations between the SAT over China and the expansion coefficients of the leading SVD modes show that SAT over China can be significantly influenced by these large-scale atmospheric patterns, especially by the second SVD mode. The relationship between the SAT over China and the leading atmospheric patterns in the observations is partly captured by the HFP models. Furthermore, seasonal forecasts of SAT over China are postprocessed using a statistical approach. This statistical approach is designed based on the relationship between the forecast Z500 and the observed SST to calibrate the SAT forecasts. Results show that the forecast skill of the postprocessed SAT over China can be improved in all seasons to some extent, with that in fall having the most significant improvement. Possible mechanisms behind the improvement of the forecast are investigated.

Impact of high-resolution sea surface temperature and urban data on estimations of surface air temperature in a regional climate

2016 ◽  
Vol 121 (18) ◽  
pp. 10,486-10,504 ◽  
Author(s):  
Sachiho A. Adachi ◽  
Fujio Kimura ◽  
Hiroshi G. Takahashi ◽  
Masayuki Hara ◽  
Xieyao Ma ◽  
...  
Keyword(s):  
High Resolution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Air Temperature ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Sea Surface ◽  
Urban Data

Diagnosing Sources of U.S. Seasonal Forecast Skill

2006 ◽  
Vol 19 (13) ◽  
pp. 3279-3293 ◽  
Author(s):  
X. Quan ◽  
M. Hoerling ◽  
J. Whitaker ◽  
G. Bates ◽  
T. Xu
Keyword(s):  
Air Temperature ◽  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Diagnostic Methods ◽  
Sea Surface ◽  
Empirical Methods ◽  
Spatial Coverage ◽  
Sst Anomalies

Abstract In this study the authors diagnose the sources for the contiguous U.S. seasonal forecast skill that are related to sea surface temperature (SST) variations using a combination of dynamical and empirical methods. The dynamical methods include ensemble simulations with four atmospheric general circulation models (AGCMs) forced by observed monthly global SSTs from 1950 to 1999, and ensemble AGCM experiments forced by idealized SST anomalies. The empirical methods involve a suite of reductions of the AGCM simulations. These include uni- and multivariate regression models that encapsulate the simultaneous and one-season lag linear connections between seasonal mean tropical SST anomalies and U.S. precipitation and surface air temperature. Nearly all of the AGCM skill in U.S. precipitation and surface air temperature, arising from global SST influences, can be explained by a single degree of freedom in the tropical SST field—that associated with the linear atmospheric signal of El Niño–Southern Oscillation (ENSO). The results support previous findings regarding the preeminence of ENSO as a U.S. skill source. The diagnostic methods used here exposed another skill source that appeared to be of non-ENSO origins. In late autumn, when the AGCM simulation skill of U.S. temperatures peaked in absolute value and in spatial coverage, the majority of that originated from SST variability in the subtropical west Pacific Ocean and the South China Sea. Hindcast experiments were performed for 1950–99 that revealed most of the simulation skill of the U.S. seasonal climate to be recoverable at one-season lag. The skill attributable to the AGCMs was shown to achieve parity with that attributable to empirical models derived purely from observational data. The diagnostics promote the interpretation that only limited advances in U.S. seasonal prediction skill should be expected from methods seeking to capitalize on sea surface predictors alone, and that advances that may occur in future decades could be readily masked by inherent multidecadal fluctuations in skill of coupled ocean–atmosphere systems.

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