scholarly journals The neglected Indo‐Gangetic Plains low‐level jet and its importance for moisture transport and precipitation during the peak summer monsoon

2017 ◽  
Vol 44 (16) ◽  
pp. 8601-8610 ◽  
Author(s):  
R. P. Acosta ◽  
M. Huber
2018 ◽  
Author(s):  
Iago Algarra ◽  
Jorge Eiras-Barca ◽  
Gonzalo Miguez-Macho ◽  
Raquel Nieto ◽  
Luis Gimeno

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 160 ◽  
Author(s):  
Fangli Zhang ◽  
Guoping Li ◽  
Jun Yue

A sudden rainstorm that occurred in the northeast Sichuan Basin of China in early May 2017 was associated with a southwest low-level jet (SWLJ) and a mountainous low-level jet (MLLJ). This study investigates the impact of the double low-level jets (LLJs) on rainfall diurnal variation by using the data from ERA5 reanalysis, and explores the characteristics of water vapor transport, including the main paths and sources of moisture, by using the HYSPLIT-driven data of the ERA—interim, GDAS (Global Data Assimilation System), and NCEP/NCAR reanalysis data. The analysis shows that the sudden rainstorm in the mountain terrain was located at the left side of the large-scale SWLJ at 700 hPa, and at the exit region of the meso-scale MLLJ at 850 hPa. The double LLJs provide favorable moisture conditions, and the enhancement (weakening) of the LLJs is ahead of the start (end) of the rainstorm. The capacity of the LLJ at 850 hPa with respect to moisture convergence is superior to that at 700 hPa, especially when the MLLJ and the southerly LLJ at 850 hPa appear at the same time. The HYSPLIT backward trajectory model based on Lagrangian methods has favorable applicability in the event of sudden rainstorms in mountainous terrain, and there is no special path of moisture transport in this precipitation event. The main moisture sources of this process are the East China Sea–South China Sea, the Arabian Sea–Indian Peninsula, the Bay of Bengal, and the Middle East, accounting for 38%, 34%, 17% and 11% of the total moisture transport, respectively. Among them, the moisture transport in the Bay of Bengal and the South China Sea–East China Sea is mainly located in the lower troposphere, which is below 900 hPa, while the moisture transport in the Arabian Sea–Indian Peninsula and the Middle East is mainly in the middle and upper layers of the troposphere. The moisture changes of the transport trajectories are affected by the topography, especially the high mountains around the Sichuan Basin.


2021 ◽  
Vol 248 ◽  
pp. 105243
Author(s):  
Juliet Perdigón-Morales ◽  
Rosario Romero-Centeno ◽  
Paulina Ordoñez ◽  
Raquel Nieto ◽  
Luis Gimeno ◽  
...  

2005 ◽  
Vol 6 (5) ◽  
pp. 710-728 ◽  
Author(s):  
Kingtse C. Mo ◽  
Muthuvel Chelliah ◽  
Marco L. Carrera ◽  
R. Wayne Higgins ◽  
Wesley Ebisuzaki

Abstract The large-scale atmospheric hydrologic cycle over the United States and Mexico derived from the 23-yr NCEP regional reanalysis (RR) was evaluated by comparing the RR products with satellite estimates, independent sounding data, and the operational Eta Model three-dimensional variational data assimilation (3DVAR) system (EDAS). In general, the winter atmospheric transport and precipitation are realistic. The climatology and interannual variability of the Pacific, subtropical jet streams, and low-tropospheric moisture transport are well captured. During the summer season, the basic features and the evolution of the North American monsoon (NAM) revealed by the RR compare favorably with observations. The RR also captures the out-of-phase relationship of precipitation as well as the moisture flux convergence between the central United States and the Southwest. The RR is able to capture the zonal easterly Caribbean low-level jet (CALLJ) and the meridional southerly Great Plains low-level jet (GPLLJ). Together, they transport copious moisture from the Caribbean to the Gulf of Mexico and from the Gulf of Mexico to the Great Plains, respectively. The RR systematically overestimates the meridional southerly Gulf of California low-level jet (GCLLJ). A comparison with observations suggests that the meridional winds from the RR are too strong, with the largest differences centered over the northern Gulf of California. The strongest winds over the Gulf in the RR extend above 700 hPa, while the operational EDAS and station soundings indicate that the GCLLJ is confined to the boundary layer.


2008 ◽  
Vol 136 (10) ◽  
pp. 3781-3795 ◽  
Author(s):  
Edward I. Tollerud ◽  
Fernando Caracena ◽  
Steven E. Koch ◽  
Brian D. Jamison ◽  
R. Michael Hardesty ◽  
...  

Previous studies of the low-level jet (LLJ) over the central Great Plains of the United States have been unable to determine the role that mesoscale and smaller circulations play in the transport of moisture. To address this issue, two aircraft missions during the International H2O Project (IHOP_2002) were designed to observe closely a well-developed LLJ over the Great Plains (primarily Oklahoma and Kansas) with multiple observation platforms. In addition to standard operational platforms (most important, radiosondes and profilers) to provide the large-scale setting, dropsondes released from the aircraft at 55-km intervals and a pair of onboard lidar instruments—High Resolution Doppler Lidar (HRDL) for wind and differential absorption lidar (DIAL) for moisture—observed the moisture transport in the LLJ at greater resolution. Using these observations, the authors describe the multiscalar structure of the LLJ and then focus attention on the bulk properties and effects of scales of motion by computing moisture fluxes through cross sections that bracket the LLJ. From these computations, the Reynolds averages within the cross sections can be computed. This allow an estimate to be made of the bulk effect of integrated estimates of the contribution of small-scale (mesoscale to convective scale) circulations to the overall transport. The performance of the Weather Research and Forecasting (WRF) Model in forecasting the intensity and evolution of the LLJ for this case is briefly examined.


2014 ◽  
Vol 120 (1-2) ◽  
pp. 287-298 ◽  
Author(s):  
Sandhya K. Nair ◽  
Thara V. Prabha ◽  
N. Purushothaman ◽  
S. Sijikumar ◽  
S. Muralidharan ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document