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 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 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 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 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.

THE USE OF WEB APPLICATIONS FOR THE SELECTION OF CROP GROWING TECHNOLOGIES

2018 ◽  
Vol 48 (3) ◽  
pp. 84-90 ◽  
Author(s):  
E. A. Lapchenko ◽  
S. P. Isakova ◽  
T. N. Bobrova ◽  
L. A. Kolpakova
Keyword(s):  
Web Application ◽  
Crop Production ◽  
Web Applications ◽  
Weather Forecast ◽  
Technical Institute ◽  
Software Complex ◽  
Agricultural Enterprise ◽  
Weather Situation ◽  
The Web ◽  
Selection Of

It is shown that the application of the Internet technologies is relevant in the selection of crop production technologies and the formation of a rational composition of the machine-and-tractor fl eet taking into account the conditions and production resources of a particular agricultural enterprise. The work gives a short description of the web applications, namely “ExactFarming”, “Agrivi” and “AgCommand” that provide a possibility to select technologies and technical means of soil treatment, and their functions. “ExactFarming” allows to collect and store information about temperature, precipitation and weather forecast in certain areas, keep records of information about crops and make technological maps using expert templates. “Agrivi” allows to store and provide access to weather information in the fi elds with certain crops. It has algorithms to detect and make warnings about risks related to diseases and pests, as well as provides economic calculations of crop profi tability and crop planning. “AgCommand” allows to track the position of machinery and equipment in the fi elds and provides data on the weather situation in order to plan the use of agricultural machinery in the fi elds. The web applications presented hereabove do not show relation between the technologies applied and agro-climatic features of the farm location zone. They do not take into account the phytosanitary conditions in the previous years, or the relief and contour of the fi elds while drawing up technological maps or selecting the machine-and-tractor fl eet. Siberian Physical-Technical Institute of Agrarian Problems of Siberian Federal Scientifi c Center of AgroBioTechnologies of the Russian Academy of Sciences developed a software complex PIKAT for supporting machine agrotechnologies for production of spring wheat grain at an agricultural enterprise, on the basis of which there is a plan to develop a web application that will consider all the main factors limiting the yield of cultivated crops.

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.

Brazilian aviation nowcasting system: current stage and some results

2021 ◽  
Author(s):  
Vinícius Almeida ◽  
Gutemberg França ◽  
Francisco Albuquerque Neto ◽  
Haroldo Campos Velho ◽  
Manoel Almeida ◽  
...  
Keyword(s):  
Rio De Janeiro ◽  
Remote Sensing Data ◽  
Weather Forecast ◽  
Weather Data ◽  
Vertical Acceleration ◽  
In Situ Data ◽  
Forecasting System ◽  
Under Construction ◽  
Convective Weather

&lt;p&gt;Emphasizes some aspects of the aviation forecasting system under construction for use by the integrated meteorological center (CIMAER) in Brazil. It consists of a set of hybrid models based on determinism and machine learning that use remote sensing data (such as lighting sensor, SODAR, satellite and soon RADAR), in situ data (from the surface weather station and radiosonde) and aircraft data (such as retransmission of aircraft weather data and vertical acceleration). The idea is to gradually operationalize the system to assist CIMAER&amp;#180;s meteorologists in generating their nowcasting, for example, of visibility, ceiling, turbulence, convective weather, ice, etc. with objectivity and precision. Some test results of the developed nowcasting models are highlighted as examples of nowcasting namely: a) visibility and ceiling up to 1h for Santos Dumont airport; b) 6-8h convective weather forecast for the Rio de Janeiro area and the S&amp;#227;o Paulo-Rio de Janeiro route. Finally, the steps in development and the futures are superficially covered.&lt;/p&gt;

scholarly journals Detection and thermal description of medicanes from numerical simulation

2014 ◽  
Vol 14 (5) ◽  
pp. 1059-1070 ◽  
Author(s):  
M. A. Picornell ◽  
J. Campins ◽  
A. Jansà
Keyword(s):  
Numerical Simulation ◽  
Thermal Structure ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Small Scale ◽  
Medium Range Weather Forecast ◽  
Warm Core ◽  
Strong Winds ◽  
Nwp Model ◽  
Ecmwf Model

Abstract. Tropical-like cyclones rarely affect the Mediterranean region but they can produce strong winds and heavy precipitations. These warm-core cyclones, called MEDICANES (MEDIterranean hurriCANES), are small in size, develop over the sea and are infrequent. For these reasons, the detection and forecast of medicanes are a difficult task and many efforts have been devoted to identify them. The goals of this work are to contribute to a proper description of these structures and to develop some criteria to identify medicanes from numerical weather prediction (NWP) model outputs. To do that, existing methodologies for detecting, characterizating and tracking cyclones have been adapted to small-scale intense cyclonic perturbations. First, a mesocyclone detection and tracking algorithm has been modified to select intense cyclones. Next, the parameters that define the Hart's cyclone phase diagram are tuned and calculated to examine their thermal structure. Four well-known medicane events have been described from numerical simulation outputs of the European Centre for Medium-Range Weather Forecast (ECMWF) model. The predicted cyclones and their evolution have been validated against available observational data and numerical analyses from the literature.

scholarly journals Two decades of in-situ temperature measurements in the upper troposphere and lowermost stratosphere from IAGOS long-term routine observation

2017 ◽  
Author(s):  
Florian Berkes ◽  
Patrick Neis ◽  
Martin G. Schultz ◽  
Ulrich Bundke ◽  
Susanne Rohs ◽  
...  
Keyword(s):  
Weather Forecast ◽  
Global Scale ◽  
Temperature Trend ◽  
Data Set ◽  
Medium Range Weather Forecast ◽  
Upper Troposphere ◽  
Temperature Trends ◽  
Geographical Regions

Abstract. Despite several studies on temperature trends in the tropopause region, a comprehensive understanding of the evolution of temperatures in this climate-sensitive region of the atmosphere remains elusive. Here we present a unique global-scale, long-term data set of high-resolution in-situ temperature data measured aboard passenger aircraft within the European Research Infrastructure IAGOS (In-service Aircraft for a Global Observing System, www.iagos.org). This data set is used to investigate temperature trends within the global upper troposphere and lowermost stratosphere (UTLS) for the period 1995 to 2012 in different geographical regions and vertical layers of the UTLS. The largest amount of observations is available over the North Atlantic. Here, a neutral temperature trend is found within the lowermost stratosphere. This contradicts the temperature trend in the European Centre for Medium Range Weather Forecast (ECMWF) ERA-Interim reanalysis, where a significant (95 % confidence) temperature increase of +0.56 K/decade is obtained. Differences between trends derived from observations and reanalysis data can be traced back to changes in the temperature bias between observation and model data over the studied period. This study demonstrates the value of the IAGOS temperature observations as anchor point for the evaluation of reanalyses and its suitability for independent trend analyses.

scholarly journals Examining the Impact of Adverse Weather on Travel Time Reliability of Urban Corridors in Shanghai

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yajie Zou ◽  
Ting Zhu ◽  
Yifan Xie ◽  
Linbo Li ◽  
Ying Chen
Keyword(s):  
Travel Time ◽  
Weather Condition ◽  
Time Of Day ◽  
Weather Data ◽  
Time Variability ◽  
Travel Time Reliability ◽  
Time Data ◽  
Adverse Weather Condition ◽  
Adverse Weather ◽  
The Impact

Travel time reliability (TTR) is widely used to evaluate transportation system performance. Adverse weather condition is an important factor for affecting TTR, which can cause traffic congestions and crashes. Considering the traffic characteristics under different traffic conditions, it is necessary to explore the impact of adverse weather on TTR under different conditions. This study conducted an empirical travel time analysis using traffic data and weather data collected on Yanan corridor in Shanghai. The travel time distributions were analysed under different roadway types, weather, and time of day. Four typical scenarios (i.e., peak hours and off-peak hours on elevated expressway, peak hours and off-peak hours on arterial road) were considered in the TTR analysis. Four measures were calculated to evaluate the impact of adverse weather on TTR. The results indicated that the lognormal distribution is preferred for describing the travel time data. Compared with off-peak hours, the impact of adverse weather is more significant for peak hours. The travel time variability, buffer time index, misery index, and frequency of congestion increased by an average of 29%, 19%, 22%, and 63%, respectively, under the adverse weather condition. The findings in this study are useful for transportation management agencies to design traffic control strategies when adverse weather occurs.

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