scholarly journals Impact Assessment of Block Level Agro Advisories for Saving Input Cost of Farmers under Old Gangetic Plains of West Bengal - A Case Study in Malda

2020 ◽  
pp. 86-96
Author(s):  
Debjyoti Majumder ◽  
Rakesh Roy ◽  
F. H. Rahman ◽  
B. C. Rudra
Keyword(s):  
West Bengal ◽  
Monsoon Season ◽  
India Meteorological Department ◽  
Weather Forecast ◽  
Economic Benefits ◽  
Weather Data ◽  
New Delhi ◽  
Medium Range Weather Forecast ◽  
Net Returns ◽  
Block Level

Biweekly block level Agromet bulletins were disseminated based on medium range weather forecast with an objective to assess the effectiveness and usefulness of Block level Agro Advisory Services (AAS) and quantify the economic benefits through adopting the micro scale agromet advisory in their day to day agricultural operations at Malda, West Bengal. Two farmers groups were considered for the study on the basis of adoption and non-adoption of the agro-met advisories. Crop situation of these farmers were compared with nearby fields having the same crops where forecast were not adopted among non AAS farmers. The entire cost incurred along with yield and net returns were calculated from sowing to marketing of goods. Similarly, the weather forecast and actual weather data received from India Meteorological Department, New Delhi were compared to verify the accuracy of rainfall forecast for the year 2019-20 at GKMS centre, Malda KVK, West Bengal. It was apparent that the value of ratio score was higher during winter (84%) than pre-monsoon (80%), post-monsoon (79%) and monsoon (74%). However, the value of threat score was also found maximum during pre-monsoon season (79%). Statistical analysis like correlation coefficient, RMSE values of wind direction were found too high in all the four seasons to accept any homogeneity in the predicted and observed values. Blockwise verification of rainfall over the year showed the range of accuracy forecast for rainfall in between 67–76%. This forecast directly had a significant role in profit generation among the AAS adaptive farmers whose additional profit enhancement for maize cultivation was between 12% and 19% only towards cost of irrigation as compared to non-adaptive farmers. The study also showcased that the AAS adaptive farmers had a better livelihood as compared to non-AAS adaptive farmers.

scholarly journals Improving efficiency of block-level agrometeorological advisory system by exploiting reuse: A study in Telangana

2021 ◽  
Vol 23 (3) ◽  
pp. 330-339
Author(s):  
MAMATHA ALUGUBELLY ◽  
KRISHNA REDDY POLEPALLI ◽  
BALAJINAIK BANOTH ◽  
SREENIVAS GADE ◽  
ANIRBAN MONDAL ◽  
...  
Keyword(s):  
Weather Condition ◽  
India Meteorological Department ◽  
Weather Forecast ◽  
Weather Data ◽  
Spatial Reuse ◽  
Medium Range Weather Forecast ◽  
Weather Situation ◽  
Block Level ◽  
Block Based ◽  
Level Medium

India Meteorological Department (IMD) has started block-level level agromet advisory (AA) service from the year 2015 and is currently operating in a few blocks of each state across India. In a block-level AA service, on every Tuesday and Friday, AA is being prepared for each block based on the block-level Medium Range weather Forecast (MRF). In this paper, we propose a framework to improve the preparation of blocklevel AA by modeling a weather situation as “Category-based Weather Condition (CWC)” and exploiting both “temporal reuse” and “spatial reuse” of AA based on the similarity among CWCs. The weather data analysis for 12 blocks of Telangana by considering the phenophase-specific CWCs of Rice crop showed that there is a scope to improve the efficiency of block-level AA bulletin preparation process by exploiting reuse.

scholarly journals Statistical interpretation of general circulation model: A prospect for automation of medium range local weather forecast in India

MAUSAM ◽  
2021 ◽  
Vol 47 (3) ◽  
pp. 229-236
Author(s):  
ASHOK KUMAR ◽  
PARVINDER MAINI
Keyword(s):  
General Circulation ◽  
Weather Forecasting ◽  
Monsoon Season ◽  
Circulation Model ◽  
Weather Forecast ◽  
General Circulation Models ◽  
Statistical Interpretation ◽  
Medium Range Weather Forecast ◽  
Medium Range ◽  
Local Weather

The General Circulation Models (GCM), though able to provide reasonably good medium range weather forecast. have comparatively less skill in forecasting location-specific weather. This is mainly due to the poor representation of 16cal topography and other features in these models. Statistical interpretation (SI) of GCM is very essential in order to improve the location-specific medium range local weather forecast. An attempt has been made at the National Centre for Medium Range Weather Forecasting (NCMRWF), New Delhi to do this type of objective forecasting. Hence location-specific SI models are developed and a bias free forecast is obtained. One of the techniques for accomplishing this, is the Perfect Prog. Method (PPM). PPM models for precipitation (quantitative, probability, yes/no) and maximum minimum temperature are developed for monsoon season (June to August) for 10 stations in lndia. These PPM models and the output from the GCM (R-40) operational at NCMRWF, are then used to obtain the SI forecast. An indirect method based upon SI forecast and observed values of previous one or two seasons, for getting bias free forecast is explained. A comparative study of skill of bias free SI and final forecast, with the observed, issued from NCMRWF to 10 Agromet Field Units (AMFU) during monsoon season 1993, has indicated that automation of medium range local weather forecast can be achieved with the help of SI forecast.

scholarly journals Seasonal forecasting of green water components and crop yield of summer crops in Serbia and Austria

2018 ◽  
Vol 156 (5) ◽  
pp. 658-672 ◽  
Author(s):  
B. Lalić ◽  
A. Firanj Sremac ◽  
J. Eitzinger ◽  
R. Stričević ◽  
S. Thaler ◽  
...  
Keyword(s):  
Crop Yield ◽  
Spring Barley ◽  
Water Productivity ◽  
Weather Forecast ◽  
Seasonal Forecasting ◽  
Green Water ◽  
Weather Data ◽  
Medium Range Weather Forecast ◽  
Probabilistic Forecasts ◽  
Aquacrop Model

AbstractA probabilistic crop forecast based on ensembles of crop model output estimates, presented here, offers an ensemble of possible realizations and probabilistic forecasts of green water components, crop yield and green water footprints (WFs) on seasonal scales for selected summer crops. The present paper presents results of an ongoing study related to the application of ensemble forecasting concepts in crop production. Seasonal forecasting of crop water use indicators (evapotranspiration (ET), water productivity, green WF) and yield of rainfed summer crops (maize, spring barley and sunflower), was performed using the AquaCrop model and ensemble weather forecast, provided by The European Centre for Medium-range Weather Forecast. The ensemble of estimates obtained was tested with observation-based simulations to assess the ability of seasonal weather forecasts to ensure that accuracy of the simulation results was the same as for those obtained using observed weather data. Best results are obtained for ensemble forecast for yield, ET, water productivity and green WF for sunflower in Novi Sad (Serbia) and maize in Groß-Enzersdorf (Austria) – average root mean square error (2006–2014) was <10% of observation-based values of selected variables. For variables yielding a probability distribution, capacity to reflect the distribution from which their outcomes will be drawn was tested using an Ignorance score. Average Ignorance score, for all locations, crops and variables varied from 1.49 (spring barley ET in Groß-Enzersdorf) to 3.35 (sunflower water productivity in Groß-Enzersdorf).

scholarly journals Preliminary results from the total lightning detector-cum-mini weather station installed at the Calcutta University

2018 ◽  
Author(s):  
Subrata Kumar Midya ◽  
Sujay Pal ◽  
Reetambhara Dutta ◽  
Prabir Kumar Gole ◽  
Upal Saha ◽  
...  
Keyword(s):  
West Bengal ◽  
Monsoon Season ◽  
Severe Weather ◽  
Lightning Activity ◽  
Weather Data ◽  
Weather Station ◽  
Withdrawal Time ◽  
Preliminary Results ◽  
Daily Weather Data ◽  
Total Lightning

Abstract. We report preliminary results derived from the total lightning detector-cum-mini weather station installed at the Calcutta University during 2016. This detector is a part of Earth Networks Total Lightning Network (ENTLN) operated globally for ground-based monitoring of total lightning activity and forecasting of localized storm alert and severe weather conditions. This set up provides improved measurement of in-cloud (IC) lightning as well as cloud-to-ground (CG) lightning in addition to daily weather data. Severe weather such as thunder squall, Nor'wester, hailstorm, cyclone over the Gangetic West Bengal can be studied in details based on total lightning activity along with other atmospheric and meteorological research using the weather data. Here we present some initial results from the analysis of total lightning measurements during the recent Nor'wester events occurred in and around Kolkata. We also present variation of wet component of atmospheric refractivity index during the monsoon season which can be used to declare the onset and withdrawal time of monsoon over Gangetic West Bengal.

scholarly journals VERIFICATION OF MEDIUM RANGE WEATHER FORECAST IN NORTH GUJARAT

2018 ◽  
Vol 6 (1) ◽  
pp. 102-106
Author(s):  
Sevak Das ◽  
A. I. Desai
Keyword(s):  
Wind Speed ◽  
Minimum Temperature ◽  
Monsoon Season ◽  
Winter Season ◽  
Weather Forecast ◽  
Maximum Temperature ◽  
Medium Range Weather Forecast ◽  
Temperature Forecast ◽  
Lower Accuracy ◽  
Medium Range

The medium range weather forecast issued from NCMRWF, Noida on rainfall, maximum temperature, minimum temperature and wind speed for the last 18 years (1999-2016) has been verified with observed weather parameters recorded at agrometeorological observatory, Sardarkrushinagar to known its accuracy. The results revealed that the usability of rainfall was higher in pre monsoon, post monsoon and winter seasons. However, during monsoon, the accuracy of rainfall forecast was 78 percent with RMSE value of 15.3 that indicated the lower accuracy. The maximum temperature forecast accuracy was very good varied from 76 to 88% in different seasons. Similarly, minimum temperature forecast was excellent in monsoon season (88%), and poor in winter season (57%). The wind speed forecast was excellent in all the seasons.

scholarly journals Modeling the effect of planting date on Maize (Zea mays L.) crop in Sabour region of Bihar using DSSATv3.5 crop simulation model

MAUSAM ◽  
2021 ◽  
Vol 61 (1) ◽  
pp. 75-80
Author(s):  
P. K. SINGH ◽  
L. S. RATHORE ◽  
K. K. SINGH ◽  
A. K. BAXLA ◽  
R. K. MALL
Keyword(s):  
Grain Yield ◽  
Weather Forecast ◽  
Sowing Date ◽  
Weather Data ◽  
Maximum Temperature ◽  
Local Conditions ◽  
Medium Range Weather Forecast ◽  
Physiological Maturity ◽  
Grain Yields ◽  
Medium Range

CERES-Maize model calibrated for local conditions of Sabour has been used to evaluate the relevance medium range weather forecast relative to the maize crop growth period. The procedure is to place the reference year's daily weather into the model up to the time the yield prediction is to be made and sequences of historical data (one sequence per year) after that time until the end of growing season to give yield estimates. A procedure that makes use of historical weather data, medium range weather forecast (mrwf) and current weather data in conjunction with the CERES-Maize model was developed to arrive at a probable distribution of predicted yields. The lower temperature and more solar radiation in tassel emergence to dough stage silk emergence to physiological maturity phase and lower maximum temperature are found favorable to contribute more in increasing the grain yields. The CERES- Maize model correlated for the genetic coefficient predicts the silking dates and physiological maturity very well. Kharif maize gave the highest grain yield of 3490 kg/ha in 1999 and the lowest of 2474 kg/ha in 1979. Among eight different sowing dates the lowest average grain yield was 3190 kg/ha for the last sowing date and the highest average grain yield was 3313 kg/ha in 2nd sowing date. The 25 percentiles were less than the mean grain yields and also 75 percentiles.  

scholarly journals Block level weather forecast using direct model output from NWP models during monsoon season in India

MAUSAM ◽  
2021 ◽  
Vol 68 (1) ◽  
pp. 23-40
Author(s):  
ASHOK KUMAR ◽  
NABANSU CHATTOPADHAYAY ◽  
Y. V. RAMARAO ◽  
K. K. SINGH ◽  
V. R. DURAI ◽  
...  
Keyword(s):  
Monsoon Season ◽  
Wrf Model ◽  
Weather Forecast ◽  
Oceanic Islands ◽  
Ratio Score ◽  
Rainfall Forecast ◽  
Skill Scores ◽  
Direct Model ◽  
Block Level ◽  
Weather Parameters

The forecast for 655 districts and 6500 blocks had been prepared and implemented on 1st June, 2014. The procedure for getting forecast for the districts  and  blocks in India including altitude corrections is based upon regular (0.25 × 0.25) grid output from the T-574 Model and output from  9 km WRF model. A verification study for rainfall forecast at 0.25 × 0.25 degree grid for Indian Window (0-40° N and 60-100° N) is also conducted, which had indicated that skill of the rainfall forecast is good for all parts of the country except oceanic islands and high terrain regions and one can down scale to any level, down to the blocks, the skill scores will not differ much. A detailed verification study for the skill of the forecast at block level for all the eight weather parameters for which the forecast was issued is conducted. The skill of the rainfall forecast is obtained for categorical forecast and as well as for yes/no forecast. The skill scores for rainfall had indicated that highest value of Hanssen and Kuiper (HK) score is 0.44, Hanssen and Kuiper score for quantitative rainfall (HKQ) is 0.18, Ratio score for yes/no forecast is 90 percent and Hit rate (HR) is 0.83. The detailed verification study for the block level weather forecast for monsoon 2014 is presented in the paper and the skill found is good. The study indicates that model forecast has the potential to be used for the block level forecast after making the quick value additions for which hints are given in the conclusion part.  

scholarly journals Agrometeorological Advisory Service: A Key to Enhance the Farmers’ Income in Red and Lateritic Zone of Purulia District of West Bengal

2020 ◽  
pp. 55-60
Author(s):  
S. Thakur ◽  
F. H. Rahman ◽  
S. K. Bhattacharjya ◽  
A. Chakraborty ◽  
B. Mahato ◽  
...  
Keyword(s):  
Management Practices ◽  
West Bengal ◽  
Weather Condition ◽  
India Meteorological Department ◽  
Statistical Technique ◽  
Agricultural System ◽  
Net Income ◽  
Advisory Service ◽  
Block Level ◽  
Purulia District

Weather and climate affect the production of an agricultural system as it influences growth and development of crops before and during the cropping season. The Agro-meteorological Advisory Service (AAS) rendered by India Meteorological Department implemented through establishment of District Agromet Unit (DAMU) in different Krishi Vigyan Kendras across the country mainly aims to enhance the farmers’ income by proper utilization of inputs and adopting suitable management practices according to the weather condition. The present study was undertaken to know the usefulness of AAS and assessing the economic benefit through its adoption in day to day farming operation by the farmers. The study was conducted at Jambad village of Purulia district under Red and Lateritic Zone of West Bengal for Kharif rice, groundnut and mustard crop which are predominantly grown in the region during 2019 Kharif and 2019-20 Rabi season. A group of farmers following AAS regularly provided through DAMU were selected randomly from the target village and farmers not following the same were also identified for the study. The economic impact and usefulness of block level AAS has been assessed through analysing the data collected from the selected farmers using suitable statistical technique. The result showed from the study that most of the cases forecasted data is well matched with actual data and hence those farmers who have adopted AAS timely in their farming operation realized more net income as compared to non AAS farmers having the same crop grown in the target village. Thus it can be concluded from the study that AAS is an effective tool for minimizing the crop losses caused due to aberrant weather and played a significant role in enhancing the production and farmers’ income.

Micro and Macro-level Analysis of Crop Diversification: Evidence from an Agrarian State West Bengal

2020 ◽  
pp. 489-499
Keyword(s):  
Crop Production ◽  
West Bengal ◽  
Farming Systems ◽  
Field Studies ◽  
Farming System ◽  
Structure Questionnaire ◽  
Crop Diversification ◽  
The Status ◽  
Block Level ◽  
Diversified Farming Systems

The farming system in West Bengal is being shifted by integration between the set of cash crops and the main food harvest process. This change in diversified farming systems, where smallholders have a production base in rice can complement production; affect technical efficiency and farm performance. The goal of this study was to investigate the status of crop diversification on smallholders in West Bengal. First, crop diversification regions were developed in West Bengal based on the Herfindahl index, which were categorized into three regions. Three sample districts were studied separately at the block level, and 915 small farmers from 41 sample villages of 9 sample blocks were interviewed through a good structure questionnaire for field studies from the sample districts. West Bengal was gradually moving towards multiple crop production. Furthermore, increasing rice production reduced the marginal use of inputs for the production of other crops. Farming and other vital factors such as HYVs area to GCA, average holding size and per capita income in some districts of West Bengal can be identified as determinants of crop diversification.

scholarly journals A Comparison between One-Step and Two-Step Nesting Strategy in the Dynamical Downscaling of Regional Climate Model COSMO-CLM at 2.2 km Driven by ERA5 Reanalysis

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 260
Author(s):  
Mario Raffa ◽  
Alfredo Reder ◽  
Marianna Adinolfi ◽  
Paola Mercogliano
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Spatial Scales ◽  
Regional Climate ◽  
Weather Forecast ◽  
Medium Range Weather Forecast ◽  
Spatial And Temporal Scales ◽  
Starting Point ◽  
One Step

Recently, the European Centre for Medium Range Weather Forecast (ECMWF) has released a new generation of reanalysis, acknowledged as ERA5, representing at the present the most plausible picture for the current climate. Although ERA5 enhancements, in some cases, its coarse spatial resolution (~31 km) could still discourage a direct use of precipitation fields. Such a gap could be faced dynamically downscaling ERA5 at convection permitting scale (resolution < 4 km). On this regard, the selection of the most appropriate nesting strategy (direct one-step against nested two-step) represents a pivotal issue for saving time and computational resources. Two questions may be raised within this context: (i) may the dynamical downscaling of ERA5 accurately represents past precipitation patterns? and (ii) at what extent may the direct nesting strategy performances be adequately for this scope? This work addresses these questions evaluating two ERA5-driven experiments at ~2.2 km grid spacing over part of the central Europe, run using the regional climate model COSMO-CLM with different nesting strategies, for the period 2007–2011. Precipitation data are analysed at different temporal and spatial scales with respect to gridded observational datasets (i.e., E-OBS and RADKLIM-RW) and existing reanalysis products (i.e., ERA5-Land and UERRA). The present work demonstrates that the one-step experiment tendentially outperforms the two-step one when there is no spectral nudging, providing results at different spatial and temporal scales in line with the other existing reanalysis products. However, the results can be highly model and event dependent as some different aspects might need to be considered (i.e., the nesting strategies) during the configuration phase of the climate experiments. For this reason, a clear and consolidated recommendation on this topic cannot be stated. Such a level of confidence could be achieved in future works by increasing the number of cities and events analysed. Nevertheless, these promising results represent a starting point for the optimal experimental configuration assessment, in the frame of future climate studies.

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