scholarly journals Doppler Weather Radar analysis of short term cyclonic storm

MAUSAM ◽  
2022 ◽  
Vol 63 (3) ◽  
pp. 459-468
Author(s):  
D. PRADHAN ◽  
U.K. DE
Keyword(s):  
Heavy Rainfall ◽  
Rapid Change ◽  
Weather Radar ◽  
Doppler Weather Radar ◽  
Wall Region ◽  
Short Term ◽  
Cyclonic Storm ◽  
South West Monsoon ◽  
Strong Winds ◽  
Severe Cyclonic Storm

On the east coast of India, during South-West monsoon period severe cyclonic storms are very rare and if they are short term cyclones then their prediction becomes very difficult due to rapid change in the intensity of the system. Though synoptic observations failed and satellite observations also cannot give decisive picture about such systems, in that case timely warning can not be issued by the weather agencies. Such a system was formed on 19 September, 2006 at about 250 km South-East of Kolkata (India). Very heavy rainfall associated with the system caused several human casualties and extensive damage to the property. According to news agencies, more than 100 people died and a million people became homeless due to heavy rainfall and strong winds associated with the cyclone during 19 September -21, 2006. At 0600 UTC, Doppler Weather radar (DWR) at Kolkata observed initial signatures of the system like a depression. Subsequently at 0900 UTC the observations indicated that the intensification of the system has taken place to a higher stage of deep depression and at about 1200 UTC clear spiral bands with a circular eye recorded by DWR confirmed for a fully developed severe cyclonic storm. The system weakened in to a deep depression at 1630 UTC after the landfall but again became a cyclonic storm at 2100 UTC of 19 September, 2006. Present study establishes that DWR is very useful for prediction of this short term cyclonic storm, its direction of movement and heavy rainfall associated. The maximum radial winds of the magnitude 32 m/s (64 knots/115 km/h) were also recorded by DWR at an altitude of 2.5 km in the eye wall region of the system. The high wind speed and the well defined structure of the cyclone observed by DWR confirmed that the system was a Severe Cyclonic Storm of T number 3.5. Records are available with surface observatories in the region for strong winds of the order of 110 km/h. This study also revealed that an early warning for strong winds and heavy rainfall could have been issued for development of such a short duration tropical cyclone using DWR data well in advance.

scholarly journals Rainfall-runoff modeling using Doppler weather radar data for Adyar watershed, India

MAUSAM ◽  
2021 ◽  
Vol 65 (1) ◽  
pp. 49-56
Author(s):  
S.JOSEPHINE VANAJA ◽  
B.V. MUDGAL ◽  
S.B. THAMPI
Keyword(s):  
Weather Radar ◽  
Radar Data ◽  
Rain Gauge ◽  
Hydrologic Model ◽  
Rainfall Data ◽  
Doppler Weather Radar ◽  
Rainfall Runoff ◽  
Cyclonic Storm ◽  
Rain Gauges ◽  
Runoff Modeling

Precipitation is a significant input for hydrologic models; so, it needs to be quantified precisely. The measurement with rain gauges gives the rainfall at a particular location, whereas the radar obtains instantaneous snapshots of electromagnetic backscatter from rain volumes that are then converted into rainfall via algorithms. It has been proved that the radar measurement of areal rainfall can outperform rain gauge network measurements, especially in remote areas where rain gauges are sparse, and remotely sensed satellite rainfall data are too inaccurate. The research focuses on a technique to improve rainfall-runoff modeling based on radar derived rainfall data for Adyar watershed, Chennai, India. A hydrologic model called ‘Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS)’ is used for simulating rainfall-runoff processes. CARTOSAT 30 m DEM is used for watershed delineation using HEC-GeoHMS. The Adyar watershed is within 100 km radius circle from the Doppler Weather Radar station, hence it has been chosen as the study area. The cyclonic storm Jal event from 4-8 November, 2010 period is selected for the study. The data for this period are collected from the Statistical Department, and the Cyclone Detection Radar Centre, Chennai, India. The results show that the runoff is over predicted using calibrated Doppler radar data in comparison with the point rainfall from rain gauge stations.

scholarly journals Heavy rain at Chennai and its relation to cyclonic disturbances

MAUSAM ◽  
2021 ◽  
Vol 51 (1) ◽  
pp. 17-24
Author(s):  
G. S. GANESAN ◽  
A. MUTHUCHAMI ◽  
A. S. PONNUSWAMY
Keyword(s):  
Bay Of Bengal ◽  
Heavy Rainfall ◽  
Heavy Rain ◽  
Total Rainfall ◽  
Cyclonic Storm ◽  
North East ◽  
The North ◽  
The Mean ◽  
Cyclonic Disturbances ◽  
Severe Cyclonic Storm

In this paper an attempt is made to study the characteristics of Heavy Rainfall (HR) and Very Heavy Rainfall (VHR) over Chennai in the North East Monsoon month of October, November and December and the period considered is 1964 to 19%. It is observed that it is mainly the duration which determines whether rainfall would be heavy or very heavy. Defining a system as Depression or Cyclonic Storm or Severe Cyclonic Storm in the Bay of Bengal, the mean rainfall in a System-affected day is 1.5 times that of Non-system-affected day in October and November. No striking differences could be found in intensity and duration characteristics of rainfall between system- affected days and non-system affected days. Even if system induced. heavy rainfall does not occur other thing being normal, the total rainfall of this season can continue to be normal.

Effects of strategic tillage on short-term erosion, nutrient loss in runoff and greenhouse gas emissions

Soil Research ◽  
2017 ◽  
Vol 55 (3) ◽  
pp. 201 ◽  
Author(s):  
A. R. Melland ◽  
D. L. Antille ◽  
Y. P. Dang
Keyword(s):  
Nitrous Oxide ◽  
Greenhouse Gas ◽  
Heavy Rainfall ◽  
Ghg Emissions ◽  
Nutrient Loss ◽  
Nitrous Oxide Emissions ◽  
Nutrient Losses ◽  
Short Term ◽  
Trade Offs ◽  
Carbon Dioxide Co2

Occasional strategic tillage (ST) of long-term no-tillage (NT) soil to help control weeds may increase the risk of water, erosion and nutrient losses in runoff and of greenhouse gas (GHG) emissions compared with NT soil. The present study examined the short-term effect of ST on runoff and GHG emissions in NT soils under controlled-traffic farming regimes. A rainfall simulator was used to generate runoff from heavy rainfall (70mmh–1) on small plots of NT and ST on a Vertosol, Dermosol and Sodosol. Nitrous oxide (N2O), carbon dioxide (CO2) and methane (CH4) fluxes from the Vertosol and Sodosol were measured before and after the rain using passive chambers. On the Sodosol and Dermosol there was 30% and 70% more runoff, respectively, from ST plots than from NT plots, however, volumes were similar between tillage treatments on the Vertosol. Erosion was highest after ST on the Sodosol (8.3tha–1 suspended sediment) and there were no treatment differences on the other soils. Total nitrogen (N) loads in runoff followed a similar pattern, with 10.2kgha–1 in runoff from the ST treatment on the Sodosol. Total phosphorus loads were higher after ST than NT on both the Sodosol (3.1 and 0.9kgha–1, respectively) and the Dermosol (1.0 and 0.3kgha–1, respectively). Dissolved nutrient forms comprised less than 13% of total losses. Nitrous oxide emissions were low from both NT and ST in these low-input systems. However, ST decreased CH4 absorption from both soils and almost doubled CO2 emissions from the Sodosol. Strategic tillage may increase the susceptibility of Sodosols and Dermosols to water, sediment and nutrient losses in runoff after heavy rainfall. The trade-offs between weed control, erosion and GHG emissions should be considered as part of any tillage strategy.

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