Improvisation in current weather display system

ABSTRACT. Presently the current weather information at four International Airports in India is being provided to air traffic control units through a Close Circuit Television (CCTV) system. The meteorological assistant who sits in the control tower obtains the information from various panels in front of him, prepares the display card by filling values of various parameters and then displays it through CCTV system. This method of display is outdated and lacks quality. Two improved computer based display systems have been developed at Meteorological Office. Palam. These systems greatly improve the quality of display presentation. These can also be used to extend the current weather display system to distant users like, International Airlines offices. One of the system is under test at the Meteorological Office, Palam, Terminal and working satisfactorily. A remote extension of this display system is also working at international Meteorological Office at Terminal II which is 10 km away from the main office at Terminal I.

Weather Forecast Semiotics: Public Interpretation of Common Weather Icons

Weather icons are some of the most frequently used visual tools meteorologists employ to communicate weather information. Previous research has shown a tendency for the public to make inferences about weather forecast information based on the icon shown. For example, people may infer a higher likelihood of precipitation, assume a higher intensity of precipitation, or determine the duration of expected precipitation if the weather icon appears to show heavy rain. It is unknown to what extent these inferences align with what the meteorologist who chose the icon intended to convey. However, previous studies have used simulated weather icons rather than ones currently in use. The goal of our study was to explore how members of the public interpret actual weather icons they see on television or in mobile applications. An online survey distributed by broadcast meteorologists through social media was used to collect 6,253 responses between August and September of 2020. Eleven weather icons currently used by broadcast meteorologists were included in the study. We also tested eight common weather phrases and asked people whether they thought the icons were good illustrators of those phrases. Additionally, people were asked to assign a probability of precipitation (PoP) to the icons. The findings of our study offer new and unique insights that will improve the communication of weather information by giving meteorologists information about how their audiences interpret weather icons.

Progress of Indian summer monsoon onset and convective episodes over Indo-Pacific region observed during 2009-2014

Summer monsoon onset progress from the oceanic region of Southeast Bay of Bengal / Andaman Sea (Oceanr) up to extreme southwestern part of India (Kerala) for the years 2009 to 2014 is investigated. Synoptic weather information, INSAT/KALPANA-1 as well as cloud imageries archived from Dundee Satellite Receiving Station for May and early June for these years are used in the analysis. Upper-air reanalyzed winds from NCEP/NCAR and OLR data archived through NOAA satellites are also used. During the study period, the dates of monsoon onset as well as the time required for the advancement of onset from Oceanr to Kerala have shown a large variation. An attempt is made to investigate the causes for such variations. The results indicate that intense disturbances which formed over north Indian Ocean in 2009, 2010, 2013 and 2014 and over west-north Pacific Oceanic region in 2011 and 2012 have contributed for the same. Analysis is carried out, limiting its focus to bring out the role of these convective events in the observed variation of onset timing and its progress by taking case to case review of these events and bringing out their influence through synoptic analysis. Utility of this information in prediction of the progress of Indian summer monsoon onset is also brought out.

APRS Data Receiver Using Raspberry Pi in LAPAN-A2 Satellite

Lapan-A2 Satellite, also known as LAPAN-ORARI, is the second satellite developed by the Indonesian National Institute of Aeronautics and Space (LAPAN) especially by Satellite Technology Center. This satellite was launched in 2015 which one of the payloads is for amateur radio communication such as VR (Voice Repeater) and APRS (Automatic Packet Reporting System). The APRS is a method of transmitting messages, status and positions using certain range of frequency and often used by Search and Rescue (SAR) team. Due to its function, APRS are not only used for disaster mitigation but also transmit various kind of data such as text message and weather information. In order to receive such information, APRS must be equipped with supporting devices. Formerly, APRS utilize terminal node controller and special hardware to decode its information but those technology is quite expensive. To address that challenge, this paper proposed an alternative way to decode the information send both from satellite APRS and terrestrial APRS by using raspberry Pi to replace those high-cost system.

A statistical study of pre-monsoon weather over south Bengal using descriptive and inferential techniques

Statistical data summarization techniques, curve fitting methods and statistical tests, both parametric and non-parametric, have been applied to form a comprehensive idea about pre-monsoon weather over South Bengal situated in the northeastern part of the Indian sub-continent. The work is based on surface data recorded at 15 major observatories during the period 1969-2000, spread across the western plateau and highlands, Rarh and Gangetic region of South Bengal. The homogeneity of pre-monsoon rainfall and its variability over different stations has been studied using Bartlett`s and Kruskal Wallis tests. For stations with complete weather information for at least 30 consecutive years, time series analysis has been carried out on rainfall data for a climatological overview of long-term behaviour, seasonal and cyclical fluctuations of pre-monsoon rainfall in those areas. This paper, apart from being a regional study, highlights the use of certain parametric and non-parametric tests, not so widely used in the context of climatology.

Assessing the role of short-term weather forecasts in fire manager tactical decision-making: a choice experiment

Background Weather plays an integral role in fire management due to the direct and indirect effects it has on fire behavior. However, fire managers may not use all information available to them during the decision-making process, instead utilizing mental shortcuts that can bias decision-making. Thus, it is important to evaluate if (and how) fire managers use information like weather forecasts when making tactical decisions. We explore USDA Forest Service fire manager confidence in relative humidity, precipitation, and wind models. We then use a choice experiment where key weather attributes were varied to explore how sensitive fire managers were to changes in specific weather variables when choosing to directly or indirectly attack a fire that is transitioning to extended attack. Results Respondents were less confident in the accuracy of wind and precipitation forecasts than relative humidity or weather forecasts more generally. The influence of weather information on the decision depended on the framing used in the choice experiment; specifically, whether respondents were told the initial strategy had been to directly or indirectly attack the fire. Across conditions, fire managers generally preferred to indirectly attack the fire. Decisions about the tactics to apply going forward were more sensitive to time in season when the fire was occurring and wind and precipitation forecasts than to other attributes. Conclusions The results have implications for the design of decision support tools developed to support fire management. Results suggest how fire managers’ use of fire weather information to evaluate forecast conditions and adjust future management decisions may vary depending on the management decision already in place. If fire weather-based decision support tools are to support the use of the best available information to make fire management decisions, careful attention may be needed to debias any effect of prior decisions. For example, decision support tools may encourage users to “consider the opposite,” i.e., consider if they would react differently if different initial decision with similar conditions were in place. The results also highlight the potential importance of either improving wind and precipitation forecast models or improving confidence in existing models.

Automatic Rain Detection System Based on Digital Images of CCTV Cameras Using Convolutional Neural Network Method

The Meteorology, Climatology and Geophysics Agency (BMKG) has a duty to provide weather information including rainfall. BMKG has several types of rainfall gauges, but these are not evenly distributed across regions. The solution to increase the density of rainfall observations is to use existing sources to obtain weather information. This research uses Closed Circuit Television (CCTV) that is spread across the Jakarta area to produce information on rainy conditions. The method used is the Convolutional Neural Network (CNN). The image from CCTV will be used for the training and testing process, so as to get the best accuracy model. The results of this model will be used for rain detection on CCTV digital images. The rain detection process is carried out automatically and in real time. The results of the rain detection process will be displayed on the map according to the location where the CCTV was installed. This research has succeeded in making a CNN model for rain detection with a training accuracy of 98.8% and a testing accuracy of 96.4%, as well as evaluating the BMKG observation data, so it has an evaluation accuracy of 96.7%.