Effect of convection on the thermal structure of the troposphere and lower stratosphere including the tropical tropopause layer in the South Asian monsoon region

2018 ◽  
Vol 169 ◽  
pp. 52-65 ◽  
Author(s):  
M. Muhsin ◽  
S.V. Sunilkumar ◽  
M. Venkat Ratnam ◽  
K. Parameswaran ◽  
B.V. Krishna Murthy ◽  
...  
2018 ◽  
Vol 123 (11) ◽  
pp. 5927-5946 ◽  
Author(s):  
Clay R. Tabor ◽  
Bette L. Otto-Bliesner ◽  
Esther C. Brady ◽  
Jesse Nusbaumer ◽  
Jiang Zhu ◽  
...  

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1462
Author(s):  
Birgit Hassler ◽  
Axel Lauer

Precipitation is a key component of the hydrological cycle and one of the most important variables in weather and climate studies. Accurate and reliable precipitation data are crucial for determining climate trends and variability. In this study, eleven different precipitation datasets are compared, six reanalysis and five observational datasets, including the reanalysis datasets ERA5 and WFDE5 from the ECMWF family, to quantify the differences between the widely used precipitation datasets and to identify their particular strengths and shortcomings. The comparisons are focused on the common time period 1983 through 2016 and on monthly, seasonal, and inter-annual times scales in regions representing different precipitation regimes, i.e., the Tropics, the Pacific Inter Tropical Convergence Zone (ITCZ), Central Europe, and the South Asian Monsoon region. For the analysis, satellite-gauge precipitation data from the Global Precipitation Climatology Project (GPCP-SG) are used as a reference. The comparison shows that ERA5 and ERA5-Land are a clear improvement over ERA-Interim and show in most cases smaller biases than the other reanalysis datasets (e.g., around 13% high bias in the Tropics compared to 17% for MERRA-2 and 36% for JRA-55). ERA5 agrees well with observations for Central Europe and the South Asian Monsoon region but underestimates very low precipitation rates in the Tropics. In particular, the tropical ocean remains challenging for reanalyses with three out of four products overestimating precipitation rates over the Atlantic and Indian Ocean.


2016 ◽  
Vol 16 (5) ◽  
pp. 3383-3398 ◽  
Author(s):  
Ann-Sophie Tissier ◽  
Bernard Legras

Abstract. Transit properties across the tropical tropopause layer are studied using extensive forward and backward Lagrangian diabatic trajectories between cloud tops and the reference surface 380 K. After dividing the tropical domain into 11 subregions according to the distribution of land and convection, we estimate the contribution of each region to the upward mass flux across the 380 K surface and to the vertical distribution of convective sources and transit times over the period 2005–2008. The good agreement between forward and backward statistics is the basis of the results presented here. It is found that about 85 % of the tropical parcels at 380 K originate from convective sources throughout the year. From November to April, the sources are dominated by the warm pool which accounts for up to 70 % of the upward flux. During boreal summer, the Asian monsoon region is the largest contributor with similar contributions from the maritime and continental parts of the region; however, the vertical distributions and transit times associated with these two subregions are very different. Convective sources are generally higher over the continental part of the Asian monsoon region, with shorter transit times. We estimate the monthly averaged upward mass flux on the 380 K surface and show that the contribution from convective outflow accounts for 80 % on average and explains most of its seasonal variations. The largest contributor to the convective flux is the South Asian Pacific region (warm pool) at 39 % throughout the year followed by oceanic regions surrounding continental Asia at 18 % and Africa at 10.8 %. Continental Asian lowlands account for 8 %. The Tibetan Plateau is a minor overall contributor (0.8 %), but transport from convective sources in this region is very efficient due to its central location beneath the Asian upper level anticyclone. The core results are robust to uncertainties in data and methods, but the vertical source distributions and transit times exhibit some sensitivity to the representations of cloud tops and heating rates. The main sensitivity is to the radiative heating rates which vary among reanalyses.


2014 ◽  
Vol 27 (17) ◽  
pp. 6612-6626 ◽  
Author(s):  
Xiushu Qie ◽  
Xueke Wu ◽  
Tie Yuan ◽  
Jianchun Bian ◽  
Daren Lu

Abstract Diurnal and seasonal variation, intensity, and structure of deep convective systems (DCSs; with 20-dBZ echo tops exceeding 14 km) over the Tibetan Plateau–South Asian monsoon region from the Tibetan Plateau (TP) to the ocean are investigated using 14 yr of Tropical Rainfall Measuring Mission (TRMM) data. Four unique regions characterized by different orography are selected for comparison, including the TP, the southern Himalayan front (SHF), the South Asian subcontinent (SAS), and the ocean. DCSs and intense DCSs (IDCSs; with 40-dBZ echo tops exceeding 10 km) occur more frequently over the continent than over the ocean. About 23% of total DCSs develop into IDCSs in the SHF, followed by the TP (21%) and the SAS (15%), with the least over the ocean (2%). The average 20-dBZ echo-top height of IDCSs exceeds 16 km and 9% of them even exceed 18 km. DCSs and IDCSs are the most frequent over the SHF, especially in the westernmost SHF, where the intensity—in terms of strong radar echo-top (viz., 40 dBZ) height, ice-particle content, and lightning flash rate—is the strongest. DCSs over the TP are relatively weak in convective intensity and small in size but occur frequently. Oceanic DCSs possess the tallest cloud top (which mainly reflects small ice particles) and the largest size, but their convective intensity is markedly weaker. DCSs and IDCSs show a similar diurnal variation, mainly occurring in the afternoon with a peak at 1600 local time over land. Although most of both DCSs and IDCSs occur between April and October, DCSs have a peak in August, whereas IDCSs have a peak in May.


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