Moisture Budget of the Tropical Cyclones Formed over the Bay of Bengal: Role of Soil Moisture After Landfall

The role of EI-Nino in modulating tropical cyclone motion over Bay of Bengal during post monsoon season has been examined. Storms which formed during the years 1901-1987 have been classified into recuriving or those of which crossing north of 17° N and non-recurving or those of which crossing south of 17° N the east coast of India. It has been found that in most of the cases (87 %) during EI-Nino years, the tropical cyclones which formed over Bay of Bengal crossed south of 17° N, i.e. south Andhra Pradesh Tamil Nadu coast, whereas tropical cyclones, ed during the year prior to the EI-Nino years [El- Nino (-1 ) year] are seen crossing mostly (in 79% of cases) either h of 17°N or recurving m northeastward direction. In other years this kind of behaviour is not generally onseerved. The correlation between southern oscillation indices and the fractional values of storms crossing south of 170 N for the period 1901-1987 (n=87) is found to be ---0.63 which is significant at 1 per cent level.

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THE ROLE OF SOIL MOISTURE REGIME IN ENHANCING BIOFUMIGATION EFFICACY AGAINST Meloidogyne Incognita (KOFOID ET WHITE) CHITW. ON TOMATO

Sinai Journal of Applied Sciences ◽

10.21608/sinjas.2020.88765 ◽

2020 ◽

Vol 0 (0) ◽

pp. 0-0

Author(s):

Shimaa Hassan ◽

Salah AbdEl-kareem ◽

Samia Massoud ◽

Mohamed Abdallah

Keyword(s):

Soil Moisture ◽

Meloidogyne Incognita ◽

Moisture Regime ◽

Soil Moisture Regime

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A numerical study on the role of atmospheric forcing on mixed layer depth variability in the Bay of Bengal using a regional ocean model

Ocean Dynamics ◽

10.1007/s10236-021-01475-8 ◽

2021 ◽

Author(s):

Sumit Dandapat ◽

Arun Chakraborty ◽

Jayanarayanan Kuttippurath ◽

Chirantan Bhagawati ◽

Radharani Sen

Keyword(s):

Mixed Layer ◽

Bay Of Bengal ◽

Numerical Study ◽

Mixed Layer Depth ◽

Ocean Model ◽

Atmospheric Forcing ◽

Layer Depth ◽

Regional Ocean Model

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Impact of SAPHIR radiances on the simulation of tropical cyclones over the Bay of Bengal using NCMRWF hybrid-4DVAR assimilation and forecast system

Journal of Earth System Science ◽

10.1007/s12040-020-01473-2 ◽

2020 ◽

Vol 129 (1) ◽

Author(s):

Devanil Choudhury ◽

Ankur Gupta ◽

S Indira Rani ◽

John P George

Keyword(s):

Tropical Cyclones ◽

Bay Of Bengal ◽

Forecast System

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The Role of Averaging for Improving Sea Surface Salinity Retrieval from the Soil Moisture and Ocean Salinity (SMOS) Satellite and Impact of Auxiliary Data

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech1954.1 ◽

2007 ◽

Vol 24 (2) ◽

pp. 255-269 ◽

Cited By ~ 10

Author(s):

Sabine Philipps ◽

Christine Boone ◽

Estelle Obligis

Keyword(s):

Soil Moisture ◽

Sensitivity Study ◽

Sea Surface ◽

Sea Surface Salinity ◽

Global Ocean ◽

Surface Salinity ◽

Auxiliary Data ◽

Additional Information ◽

Ocean Salinity

Abstract Soil Moisture and Ocean Salinity (SMOS) was chosen as the European Space Agency’s second Earth Explorer Opportunity mission. One of the objectives is to retrieve sea surface salinity (SSS) from measured brightness temperatures (TBs) at L band with a precision of 0.2 practical salinity units (psu) with averages taken over 200 km by 200 km areas and 10 days [as suggested in the requirements of the Global Ocean Data Assimilation Experiment (GODAE)]. The retrieval is performed here by an inverse model and additional information of auxiliary SSS, sea surface temperature (SST), and wind speed (W). A sensitivity study is done to observe the influence of the TBs and auxiliary data on the SSS retrieval. The key role of TB and W accuracy on SSS retrieval is verified. Retrieval is then done over the Atlantic for two cases. In case A, auxiliary data are simulated from two model outputs by adding white noise. The more realistic case B uses independent databases for reference and auxiliary ocean parameters. For these cases, the RMS error of retrieved SSS on pixel scale is around 1 psu (1.2 for case B). Averaging over GODAE scales reduces the SSS error by a factor of 12 (4 for case B). The weaker error reduction in case B is most likely due to the correlation of errors in auxiliary data. This study shows that SSS retrieval will be very sensitive to errors on auxiliary data. Specific efforts should be devoted to improving the quality of auxiliary data.

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A MOISTURE STRESS INDEX FOR WHEAT BY MEANS OF A MODULATED SOIL MOISTURE BUDGET

Canadian Journal of Plant Science ◽

10.4141/cjps68-101 ◽

1968 ◽

Vol 48 (5) ◽

pp. 535-544 ◽

Cited By ~ 2

Author(s):

A. R. Mack ◽

W. S. Ferguson

Keyword(s):

Soil Moisture ◽

Stress Function ◽

Potential Evapotranspiration ◽

Moisture Stress ◽

Moisture Distribution ◽

Stress Index ◽

Wheat Crop ◽

Moisture Budget ◽

Dough Stage ◽

Soil Moisture Budget

Actual evapotranspiration (AE), soil moisture distribution, and moisture stress for a wheat crop (PE-AE) were estimated by the modulated soil moisture budget of Holmes and Robertson. The estimated soil moisture was reasonably well correlated with soil moisture measured weekly by means of gypsum blocks. Wheat yields from experimental plots in the corresponding area were related more closely to the moisture stress function (PE-AE: r = − 0.83), than to the seasonal precipitation (r = 0.62), the potential evapotranspiration (PE) or the evapotranspiration ratio (AE/PE). Regression analyses showed that the grain yields were reduced by an average of 156 (±sb = 40) kg/ha per cm of moisture stress from emergence to harvest, or by 311 and 69 kg/ha per cm of stress, from the fifth-leaf to the soft-dough stage and from the soft-dough stage to maturity, respectively. The moisture stress function may be used to characterize the soil–plant–atmosphere environment for the growing season of a crop. Precipitation and evapotranspiration data are presented annually for three standardized growing periods at Brandon from 1921 to 1963.

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