A New Dynamical Index for India-Burma Trough

Abstract

Based on the vertical velocity field of reanalysis datasets, this study defines a new dynamical index for the India-Burma trough and supports this index's advantages by analyzing reanalysis and observational datasets. For a convenient understanding, the vertical velocities of 5 levels ranging from 700 hPa to 500 hPa within the area of 15.625 ∘ N-24.375 ∘ N and 90.625 ∘ E-100.625 ∘ E are multiplied by −1 and summed up into a time series involving each year from 1979 to 2012. The standardized value of the time series is defined as the index of India-Burma trough (IIBT). IIBT can reflect the characteristics of the annual strength and the interdecadal variation of the India-Burma trough. IIBT can also well reveal the relationship between the India-Burma trough and its upstream teleconnection. What is more, through a correlation analysis on the grid point precipitation field, respectively, with the IIBT and the India-Burma trough indices defined with vorticity and geopotential height, over southern Asia the correlation pattern between the IIBT and the precipitation field is found to nearly be the sum of the correlation patterns of the latter 2 indices with the precipitation. To the south of the TP, the correlation field between the IIBT and the grid point precipitation shows dipolar distribution, which is consistent with the correlation patterns of the IIBT with the vertical velocity, specific humidity, and the mid-level geopotential height in the same spatial location. IIBT is beneficial for more accurate study of the impact of the India-Burma trough on the associated weather and climate.

Assessment of the impact of soil moisture on spring surface air temperature over the low‐latitude highlands of China

“…Additionally, correlation coefficient between SATI and spring precipitation in East Asia is displayed in Figure 7. A significant negative relationship between SATI and precipitation dominates the LLH, while a significant positive relationship exists over the middle and lower reaches of the Yangtze River valley, which is similar to the result of Liu et al (2018). Correlation coefficient between SATI and the IBT index (standardized area-mean vertical velocity defined by Liu et al (2018)) is −0.38 (exceeding the 95% confidence level based on the Student's t test), thereby indicating that the IBT may have a potential impact on SAT and precipitation in the LLH.…”

“…Correlation coefficient between SATI and the IBT index (standardized area‐mean vertical velocity defined by Liu et al . (2018)) is −0.38 (exceeding the 95% confidence level based on the Student's t test), thereby indicating that the IBT may have a potential impact on SAT and precipitation in the LLH. Therefore, SM‐SAT coupling might be potentially modulated by the IBT.…”

“…A significant negative relationship between SATI and precipitation dominates the LLH, while a significant positive relationship exists over the middle and lower reaches of the Yangtze River valley, which is similar to the result of Liu et al . (2018). Correlation coefficient between SATI and the IBT index (standardized area‐mean vertical velocity defined by Liu et al .…”

“…Wang et al (2011 demonstrated that the relationships between the IBT and SAT as well as precipitation over southern and eastern Asia in winter were enhanced after 1978. For the LLH, the southwesterly wind in front of the IBT transports water vapour from the BOB to the LLH, and the water vapour transportation of the IBT is the primary moisture source for the LLH during the boreal winter half year, hence the IBT is considered as one of the major factors that has significant effects on weather and climate in the LLH (Qin et al, 1991;Duan et al, 2012;Li and Zhou, 2016;Liu et al, 2018). Figure 6b suggests that higher (lower) spring SAT in the LLH is corresponding to a weakened (intensified) IBT, which may be caused by the surface cooling (warming) effect of increased (decreased) precipitation in the LLH.…”

Connection between Two Leading Modes of Autumn Rainfall Interannual Variability in Southeast China and Two Types of ENSO-Like SSTA

“…In the winter of 2008, severe freezing rain and snow disasters occurred, with an enormous loss in economically prosperous SEC [21,22]. e interannual variation of precipitation in SEC is affected by many factors, such as western Pacific subtropical high, India-Burma trough, subtropical westerly jet, typhoon activity, monsoon, North Atlantic oscillation (NAO), and even black carbon aerosol, very important one of which is the key region sea surface temperature (SST) [23][24][25][26]. So the relationship between SEC rainfall and SST has attracted a lot of attention [22,27,28].…”