Large-Scale Precipitation and Outgoing Longwave Radiation from INSAT-1B during the 1986 Southwest Monsoon Season

This paper studies the summer monsoon 2017 and examines the number of parameters which we believe were important in understanding why monsoon failed in second half over India. The list of parameters includes monthly mean or anomalies of the following fields : sea surface temperature, outgoing longwave radiation, stream function of lower and upper atmosphere, velocity potential and monthly and seasonal precipitation. ENSO conditions were mainly neutral with warm ENSO neutral conditions observed in the first half and cool ENSO neutral conditions observed in the second half. As a result, influence on the monsoon from the large scale SST forcing from Pacific Ocean was nearly absent during the season. However, Positive IOD conditions over the Indian Ocean during the monsoon season, particularly during first half of the monsoon were prominent. The transition of warmer than normal SSTs (June and July) to normal SSTs (August) and then becoming cooler than normal SSTs (September) in the equatorial Indian Ocean had a significant influence which lead monsoon to fail in second half.

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Estimating the Earth’s Outgoing Longwave Radiation Measured from a Moon-Based Platform

Remote Sensing ◽

10.3390/rs13112201 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2201

Author(s):

Hanlin Ye ◽

Huadong Guo ◽

Guang Liu ◽

Jinsong Ping ◽

Lu Zhang ◽

...

Keyword(s):

Outgoing Longwave Radiation ◽

Large Scale ◽

Single Point ◽

Longwave Radiation ◽

Earth Observation ◽

Artificial Satellites ◽

Earth Observations ◽

The Earth ◽

Observation Geometry ◽

Global Mean

Moon-based Earth observations have attracted significant attention across many large-scale phenomena. As the only natural satellite of the Earth, and having a stable lunar surface as well as a particular orbit, Moon-based Earth observations allow the Earth to be viewed as a single point. Furthermore, in contrast with artificial satellites, the varied inclination of Moon-based observations can improve angular samplings of specific locations on Earth. However, the potential for estimating the global outgoing longwave radiation (OLR) from the Earth with such a platform has not yet been fully explored. To evaluate the possibility of calculating OLR using specific Earth observation geometry, we constructed a model to estimate Moon-based OLR measurements and investigated the potential of a Moon-based platform to acquire the necessary data to estimate global mean OLR. The primary method of our study is the discretization of the observational scope into various elements and the consequent integration of the OLR of all elements. Our results indicate that a Moon-based platform is suitable for global sampling related to the calculation of global mean OLR. By separating the geometric and anisotropic factors from the measurement calculations, we ensured that measured values include the effects of the Moon-based Earth observation geometry and the anisotropy of the scenes in the observational scope. Although our results indicate that higher measured values can be achieved if the platform is located near the center of the lunar disk, a maximum difference between locations of approximately 9 × 10−4 W m−2 indicates that the effect of location is too small to remarkably improve observation performance of the platform. In conclusion, our analysis demonstrates that a Moon-based platform has the potential to provide continuous, adequate, and long-term data for estimating global mean OLR.

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Beaching patterns of plastic debris along the Indian Ocean rim

10.5194/os-2020-50 ◽

2020 ◽

Author(s):

Mirjam van der Mheen ◽

Erik van Sebille ◽

Charitha Pattiaratchi

Keyword(s):

Indian Ocean ◽

Bay Of Bengal ◽

Plastic Material ◽

Monsoon Season ◽

Southwest Monsoon ◽

Plastic Waste ◽

Ocean Dynamics ◽

Global Ocean ◽

The Indian Ocean ◽

Southwest Monsoon Season

Abstract. A large percentage of global ocean plastic waste enters the northern hemisphere Indian Ocean (NIO). Despite this, it is unclear what happens to buoyant plastics in the NIO. Because the subtropics in the NIO is blocked by landmass, there is no subtropical gyre and no associated subtropical garbage patch in this region. We therefore hypothesise that plastics "beach" and end up on coastlines along the Indian Ocean rim. In this paper, we determine the influence of beaching plastics by applying different beaching conditions to Lagrangian particle tracking simulation results. Our results show that a large amount of plastic likely ends up on coastlines in the NIO, while some crosses the equator into the southern hemisphere Indian Ocean (SIO). In the NIO, the transport of plastics is dominated by seasonally reversing monsoonal currents, which transport plastics back and forth between the Arabian Sea and the Bay of Bengal. All buoyant plastic material in this region beaches within a few years in our simulations. Countries bordering the Bay of Bengal are particularly heavily affected by plastics beaching on coastlines. This is a result of both the large sources of plastic waste in the region, as well as ocean dynamics which concentrate plastics in the Bay of Bengal. During the intermonsoon period following the southwest monsoon season (September, October, November), plastics can cross the equator on the eastern side of the NIO basin into the SIO. Plastics that escape from the NIO into the SIO beach on eastern African coastlines and islands in the SIO or enter the subtropical SIO garbage patch.

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Intra-seasonal oscfffations of radio refractive index during southwest monsoon over India

MAUSAM ◽

10.54302/mausam.v44i3.3862 ◽

2022 ◽

Vol 44 (3) ◽

pp. 271-276

Author(s):

H. N. SRIVASTAVA ◽

K. C. SINHARAY ◽

R. K. MUKHOPADHYAY

Keyword(s):

Refractive Index ◽

Monsoon Season ◽

Temporal Variations ◽

Southwest Monsoon ◽

The Individual ◽

Southwest Monsoon Season ◽

Seasonal Oscillations ◽

Refractive Index Data ◽

Indian Seas ◽

Variance Explained

The study deals with the spatial and temporal variations of intra-seasonal oscillations in radio refractive index during southwest monsoon season over India and islands over Indian seas. Average daily radio refractive index data from 1 June to 30 September and that of the individual years for the period 1969-1986 were subjected to harmonic analysis to investigate the contributions of various periodicities in monsoon radio refractive index. The inter-annual variability of various intra-seasonal oscillations have been studied for each 5° latitudinal strip from 50 oN to 30° N with the help of variance explained by various frequency modes for different years. Variance explained by 30-60 day and 10-20 day modes were studied in relation to monsoon performance. The northward and eastward propagation of30.60 day mod~ was noticed. The 10.20 day mode and seasonal mode dominate at latitudinal belts 5°N.10oN and 25°N-30°N respectively. Between 10°N and 25°N, both 30-60 day and 10-20 day modes occur.

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Soil Quality Near Indian Oil Corporation Limited Pol Depot Ahmednagar, Maharashtra, State of India

Advances in Environmental Engineering and Green Technologies - Amelioration Technology for Soil Sustainability ◽

10.4018/978-1-5225-7940-3.ch010 ◽

2019 ◽

pp. 168-178

Author(s):

Kanchan P. Rathoure

Keyword(s):

Water Quality ◽

Soil Quality ◽

Monsoon Season ◽

Southwest Monsoon ◽

Soil Types ◽

Central Position ◽

The West ◽

Deccan Plateau ◽

Southwest Monsoon Season ◽

Godavari Basin

The area in question has diversified relief and amount of rainfall and soil types. It is dry region lies in east, irrigated region in north and tribal-dominant population dominant in the west. Ahmednagar district is situated partly in the upper Godavari basin and partly in the Bhīma basin occupying a somewhat central position in Maharashtra state. The climate of the district is characterized by a hot summer and general dryness throughout the year except during the southwest monsoon season (i.e., June to September). Physiographically the district forms part of Deccan Plateau. Part of Sahayadri hill ranges fall in the district. Here in this chapter, the author has elaborated about soil quality and ground water quality near IOCL Terminal Ahmednagar, Maharashtra, India.

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Season-ahead forecasting of water storage and irrigation requirements – an application to the southwest monsoon in India

Hydrology and Earth System Sciences ◽

10.5194/hess-22-5125-2018 ◽

2018 ◽

Vol 22 (10) ◽

pp. 5125-5141 ◽

Cited By ~ 3

Author(s):

Arun Ravindranath ◽

Naresh Devineni ◽

Upmanu Lall ◽

Paulina Concha Larrauri

Keyword(s):

Water Stress ◽

Large Scale ◽

Agricultural Sector ◽

Mean Squared Error ◽

Monsoon Season ◽

Water Storage ◽

Skill Score ◽

Southwest Monsoon ◽

False Alarms ◽

K Nearest Neighbors

Abstract. Water risk management is a ubiquitous challenge faced by stakeholders in the water or agricultural sector. We present a methodological framework for forecasting water storage requirements and present an application of this methodology to risk assessment in India. The application focused on forecasting crop water stress for potatoes grown during the monsoon season in the Satara district of Maharashtra. Pre-season large-scale climate predictors used to forecast water stress were selected based on an exhaustive search method that evaluates for highest ranked probability skill score and lowest root-mean-squared error in a leave-one-out cross-validation mode. Adaptive forecasts were made in the years 2001 to 2013 using the identified predictors and a non-parametric k-nearest neighbors approach. The accuracy of the adaptive forecasts (2001–2013) was judged based on directional concordance and contingency metrics such as hit/miss rate and false alarms. Based on these criteria, our forecasts were correct 9 out of 13 times, with two misses and two false alarms. The results of these drought forecasts were compared with precipitation forecasts from the Indian Meteorological Department (IMD). We assert that it is necessary to couple informative water stress indices with an effective forecasting methodology to maximize the utility of such indices, thereby optimizing water management decisions.

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