Category: Weather

Introduction

One of the most important thing for humankind it to plan their day, to plan their day human need to know about the weather forecasting so they can plan their day or even their month accordingly, as said wiki: “Weather forecasting is the application of science and technology to predict the conditions of the atmosphere for a given place and time’. from a long way back weather forecasting always play a big role in humanity. Before to predict the weather we have to measure the weather, to predict tomorrow weather, we must know what is the weather today and what was the weather yesterday, but the knowledge of the average weather in a specific day of the year is also important, to predict the weather we will these data, to predict the weather we have to collect everyday data so we can see the patterns and trends, and we will understand how our atmosphere behave. Those data will help us to predict the weather condition by using machine learning and some of his algorithm to make an accuracy prediction.

Weather change continuously and rapidly (wind speed, temperature, humidity, rain or snow, pressure); an accurate forecasting is important for daily life. For this project we are going to use a Data collected by a GHCND station data democratic Republic of Congo from 2010 to 2015.

DR Congo it’s located in the equatorial line, it has an extreme weather and climate variability, that’s cause high risk to droughts and floods. Using the data of GHCND station in machine learning to predict the weather so we can avoid more damage than before from a natural cause.

Objectives

The earth it’s a very complex place suffering of the climate change, It’s significant to predict an accurate weather without any error, to make sure of the security and mobility, as well a safe daily operation.

Weather forecasting it’s build by collecting huge amount of data, that’s make machine learning an essential tool, by using some backtesting method and some algorithms to make an accurate prediction of weather.

We are going to evaluate the methods with a set of experiments that highlight the performance and value of the methods. With ML add in weather forecasting bring an enormous advantage for the prediction make it more accurate.

Weather forecasting it’s a very powerful application of science for the benefits of the society it’s can be used for Aerospatiale; agriculture; sport; musical event; marine; renewable energy; aviation and forestry, it’s very important to know what’s the weather going to be. Finding out the maximum and minimum temperature, it’s one of the method of linear regression that’s reach a precise result.

• Collecting data;
• Exploring and preparing data;
• Data preparation- creating random training and test data;
• Training model on data;
• Evaluating model performance;
• Improving model performance.

Tools used for analyses

• Excel
• R x64.3.6.2
• R i386.6.2
• radar
• Data collection
• Microsoft word 2016
• IDLE python

SWOT

Strength

Weather forecasting it’s a very important application of science for human, making its more accuracy by using machine learning so we can anticipate some naturel problem floods, hurricanes so on.

Machine learning change the weather forecasting for more accurate result of weather, now we can use big data and rise in climate change patterns by knowing what exactly temperature will be in the future or how the weather it’s changing according, it’s can help to anticipate a Global warming to the worst.

Weather forecasting in machine learning its growing very fast according to marketstandmarkets.com “weather forecasting system market its projecting to grow from usd 2.3 billion in 2019 to usd 3.3 billion in 2025”.

Weaknesses

Weather forecasting it’s a very complex science. Not matter how many data we collect or how precise the algorithm is, weather cannot be exact.

Weather forecasting in machine learning need a big amount of dataset so it’s can learn from, more data we introduce to the system more accurate the result are, and if the result are different to the weather, the weather forecaster we be blamed. Because it’s cause a damage in field like airline for example.

Opportunities

The accuracy is higher than it was century ago, and with billions of smart phone users the forecast can reach everyone around the globe. Using machine learning, Weather model can better have performed for prediction mistakes, such as rainfall and produce more accurate prediction.

With the algorithm of ML to prevent any errors that come from traditional weather forecasting.

Threats

Not control of the climate change not matter how many data collected the result it’s not hundred percent sure, that’s can cause a lot of damage in certain area as agriculture loss of product cause weather forecasting algorithm predicted a rain, airplane company allowed a plan to take off but the weather change and caused a crash. It’s a challenging task to predict a weather because as storm and natural events that can happen on hourly time scale.

The huge amount of data that’s request cannot be executed by a normal computer, its require a super computer to execute all the algorithm in a record time, the supercomputer is very costly.

Outcome

In this project we explain how machine learning can improve the accuracy of weather forecasting by introducing some algorithm and historical data so win the future we can prevent any disaster as natural disaster as hurricane, cyclone or floods.

Introduction

“Weather” is defined as the the condition of the atmosphere at a specific space and time as regards heat, dryness, wind, rain, etc. over a short time frame, whereas “climate” refers to the weather data of a place over a longer period to yield meaningful averages.”Global Change” means alterations in the Earth.

A Brief History

Man has always aspired to predict about the weather conditions. In the past, astrologers studied stars and dreams to predict weather and much more. It is mentioned in the Holy Qur’an that Hazrat Yusuf (S.A.W.) predicted the dream to save Egypt from famine. In a nutshell, prediction about weather, climate and global change grew more and more in the respect of science over the course of time.

Daily Life Affects

The weather affects all of us as an unexpected rain can ruin a picnic and snowfalls can block road. Fine weather across the farmlands produce heavy yield but the weather does not only affect the yield but also an abundant yield can make food cheaper and vice-versa. Mild weather conditions can lower our utility bills like gas, water and electricity.

Significance of Prediction

It is crucial to know about the weather after a few hours in some cases. Fishermen and sailors must when it will be safe for them in the sea. Similarly, Pilots must know the wind velocity for a safer travel. Climate change is inevitable, but today, it is noticed that this change is taking place quite faster compared to the past due to increment of human activity in the natural system so we are more concerned about the environment than our ancestors. Thus, we look at the ways of how the environment works with a powerful scientific approach.

Challenges

When considering all the climate statistics we are always challenged by a certain amount of uncertainty. This uncertainty comes mainly from the huge lack of data. We cannot know the changes in the weather i.e. heat, wind speed, etc. at every instant of time so we take an average of all the values but this approximation changes the forecast. This is coupled by the fact that there is a serious lack of knowledge which makes the data vulnerable. Engineers are challenged to make a computing system which can overcome these problems. Better satellites should be employed for the computation of data. Another challenge is of monetary respect. Low-Budget investment in this sector impedes in the way of development.

Discussion

Prediction about climate change is a huge task at hand. We should collaborate both nationally and internationally to deal with the problems regarding it. Moreover, a general awareness should be given to the local people through seminars and media so change can be made for the better.

Introduction

Aviation has a high level of safety for commercial operations and is considered as one of the safest modes of transport today. Although the aviation industry is considered a safe mode of transport there are accidents that occur due to many different factors. This includes factors such as air traffic control, maintenance and human factors. Another factor that that contributes is the weather, with many different weather phenomenon, weather is a dangerous factor that results in some fatal crashes especially in general aviation.

Crash 1

On the 16th of June 2017, a Cessna 172 was on a private Visual Flight Rules (VFR) flight from Southport Mason Field, Queensland to Ballina Airport in New South Wales. The pilot departed Southport 8:11am, the pilot then tracked towards Stott island at 1500ft Above Mean Sea Level (AMSL) (ATSB, 2019). At 8:28am, whilst over Stott Island the pilot reported the position of the aircraft to ATC, which was the last transmission between ATC and the pilot. After leaving controlled airspace, the pilot continued the flight to Ballina. En-route to Ballina the pilot encountered reduced visibility due to low clouds, fog and drizzle near Bangalow. At 8:44am, the aircraft was approximately 1km north of Bangalow at an altitude of 800ft when radar identification was lost. A minute later at 8:45am, an eyewitness account placed the aircraft 3km further south near the pacific highway flying lower than normal the aircraft turned to the west disappearing into the low-level clouds (ATSB, 2019). Then at 8:47am surveillance data was captured showing the aircraft 6km southwest of the last radar contact heading in a west-south-westerly direction at 700ft with the surrounding terrain ranging from 88ft to 233ft. Following this at 8:50am, several witness account heard near Brooklet the engine noise from the aircraft followed by a loud bang, which indicated the aircraft crashing. The wreckage was later found on a farming property at an elevation of 400ft near Brooklet. All of the witnesses indicated that the weather conditions at the time were low clouds and fog at the time of the accident (ATSB, 2019). 254

At the time of the accident the weather that had contributed to the included low-level clouds, fog and drizzle. The weather conditions were perfect for low-level clouds to form with a humidity of 95% and a temperature of approximately 17.7 degrees Celsius (ATSB, 2019). The clouds that had been forecast in Area 20, which is where Ballina is located, indicated stratus clouds between 1000ft and 2500ft at sea and on the coast with precipitation as well as broken cumulus clouds between 2000ft and 10,000ft with cloud tops above 10,000ft (ATSB, 2019). Stratus clouds are flattened low-level clouds with a grey or white colour that consist of water droplets or ice with a generally grey appearance (Met Office, 2019). They form when moist, warm or cool air blow over colder land or ocean surfaces and can often appear at the surface as mist or fog. The stratus clouds can also be thick and opaque depending on the amount of moisture is in the air and the difference in temperature between the cold and warm air as well as sometimes-producing drizzle (Carr, 2019). Cumulus clouds are puffy cauliflower looking clouds that are the most common cloud produced in fair weather conditions. The cumulus clouds are formed due to convection, when air is heated at the surface lifts up and then water vapour condenses to produce the cumulus cloud. 217

Crash 2

On the 2nd of December 2005, a Piper PA-31-350 Chieftain was on a private Instrument Flight Rules (IFR) flight from Archerfield, Queensland to Griffith, New South Wales with a pilot, and observer-pilot and two passengers. The pilot departed Archerfield at 11:22am, knowing that the weather conditions were going to be patchy with thunderstorms forecasted the pilot then tracked to Moree at 10,000ft and then direct to Coonamble (ATSB, 2005). Then at 1:03pm, the pilot changed the destination to Swan Hill, Victoria via Hillston, New South Wales. Following the change in destination the aircraft passed over Coonamble at 1:12pm still at the altitude of 10,000ft, four minutes later at 1:16pm the pilot advised air traffic control that he was going five nautical miles (NM) to the left of the flight plan due to weather (ATSB, 2005). At 1:37pm, the pilot had to further divert the flight off track by 20NM due to weather followed by another diversion of 29NM off track due to the weather for the third time. That was the last time the aircraft was in contact with air traffic controllers, when at 2pm the police received a call saying an aircraft had crashed on a property. The wreckage of the piper was found 28km north of Condobolin in New South Wales with other debris spread along a trail 4km away from the main wreckage. The damage found was that the right wing along with the right engine, control surfaces and extremities had been separated from the rest of the aircraft during flight (ATSB, 2005). Whilst the fuselage along with the left engine crashed into the ground and were destroyed by a fire which started post impact. 272

The weather forecast for the flight was occasional thunderstorms east of a line from Bourke to Griffith after 10am associated with a surface trough that was moving through central NSW. The forecast was later updated at 11:30 am, 8 minutes after the aircraft departed stating that the thunderstorms were now ‘frequently observed’ instead of being ‘occasional’ (ATSB, 2005). The updated forecast known as a SIGMET (Significant Meteorological Information) was not requested by the pilot en-route to Griffith so the pilot did not know of the changing circumstances of the weather they were flying into. The report of the weather after the accident found that there was an active frontal system moving east at 15 to 25 knots through New South Wales with a line of thunderstorms stretching from South East Queensland, through New South Wales into Victoria (ATSB, 2005). The thunderstorms actively highlighted the front that was sweeping through towards the east.

Bibliography

1. ATSB. (2005). In-flight breakup 28 km north of Condobolin, NSW. Australian Transport Safety Bureau. Retrieved from https://www.atsb.gov.au/media/1361529/aair200506266_001.pdf
2. ATSB. (2019). VFR into IMC and loss of control involving Cessna 172, VH-FYN. Australian Transport Safety Bureau. Retrieved from https://www.atsb.gov.au/media/5775758/ao-2017-061_final.pdf
3. Carr, P. K. (2019). Stratus clouds – A blanket of cloud – Weather science. Retrieved from Quatr.us from Professor Carr: https://quatr.us/physics/stratus-clouds-blanket-cloud-weather-science.htm
4. Met Link. (2019). Cumulus Clouds. Retrieved from MetLink Royal Meteorological Society: https://www.metlink.org/other-weather/science-in-the-sky/cumulus-clouds/
5. Met Office. (2019). Cumulus clouds. Retrieved from Met Office: https://www.metoffice.gov.uk/weather/learn-about/weather/types-of-weather/clouds/low-level-clouds/cumulus
6. Met Office. (2019). Stratus Clouds. Retrieved from Met Office: https://www.metoffice.gov.uk/weather/learn-about/weather/types-of-weather/clouds/low-level-clouds/stratus
7. timeanddate.com. (n.d.). Past weather in Ballina, New South Wales, Australia – June 2017. Retrieved from timeanddate.com: https://www.timeanddate.com/weather/australia/ballina/historic?month=6&year=2017

Weather is a short-term climate change. While it is sunny today, it can be rainy, even stormy the next day. There are a lot of weather conditions in the world and these conditions are considered to have some effects on people’s mood. (Widmer, Bill, “Lifehack”) Unlike some people who are the opposite of this idea, I agree with it. The weather has a lot of effects on people’s mood. There is some relationship between life satisfaction and weather conditions, for instance, people living in warmer climates are more satisfied with life than people living in colder climates. It means that when the weather is sunny people are more satisfied with life than when it is cloudy. According to the overall weather conditions in a region, it seems that weather conditions are really related to life satisfaction of people. (Brenner, Laurie, “Sciencing”) There are many possible reasons for this case. It is easier to exercise when it is warm and sunny than when it is cold and rainy. So people who live in warmer climates can do more physical activities than those who live in cold, or rainy climates. As a result, it can be said that weather conditions, including rainfall, sunshine, temperature, and humidity can generally have large effects on people’s mood. (Mercola, Joseph, “Mercola”) Some of these effects are the effects of weather on the clothes that people wear, the transportation ways that people may take to work, and the specific fun activities in which people engage.

Firstly, it can be handled the sunny days to examine. If the weather is sunny, people can feel happy and they can go to the picnics, go to swimming and etc. If the weather is sunny, it can be seen almost all of the people out of their houses, and it can also be seen nearly all of them eat ice cream happily. In addition to these examples, children may play with each other happily. In short, it can be said that almost all people love sunny days. On the contrary to these examples, if the weather is too hot, people cannot feel happy, they can feel depressed and aggressive just the opposite. So it can be really told that it is not only the different weather conditions but also the same weather condition in different temperatures can affect people’s mood. If the weather is too hot, anyone can neither go outside, nor can stay at their house comfortable without air conditioner or anything like that. So it can be concluded from these examples that too hot weather condition has a lot of bad effects on people’s mood.

If it is necessary to give another example of this situation, an example of Muslim’s Ramadan days can be the most . These days can pass more severely and harder and people can be thirsty easier. Especially for children who meet Ramadan new, these days can be extremely excruciating. Despite the fact that bad conditions can be arisen by these extremely hot days, many people love sunny days. Because, if the weather is hot and sunny, everyone can take pleasure by swimming, eating ice- cream, going to the picnic, having a walk, meeting with your friends and going on holiday, which is the best thing to do in these days.

Secondly, it can be mentioned on cloudy days. On one hand, these days can have bad effects on people’s mood. When the weather is cloudy, anyone can feel depressed, sad and even frightened. When the weather is cloudy, it can also be windy and if it is windy, nobody can either go to the picnic or can lick ice cream. If it should be given an example about being depressed on cloudy and windy days, it can be said that when the weather is cloudy, windy or rainy; nobody can go out neither for play with their friends nor for a trip. Instead, they sit in their room and listen to slow music because they feel depressed. Nobody can prevent themselves from thinking the old events and depressing, this is one of the best examples of the effects of the weather on people’ s mood.

On the other hand, these days can have fine effects on people’s mood. If the weather is rainy, this means that it will provide many beneficial effects on the people’s crops and their mood as well. The crops can grow up naturally and healthy thanks to these days and this makes people feel happy. So, it can be concluded that rainy days have different effects on people’ s mood. While some can be happy when there is rain, some can get depressed, can get lazy and just stay in their bed. Personally, some love watching the raindrops and hear them fall on the rooftop and on the ground. Some even love the smell of wet ground and think that it calms them and gives them peace of mind. It is because of that when their mind is cluttered, rain takes it all away and clears their mind. Some people; on the other hand, can think much better when there is rain. As Boby Dylan said, “Some people feel the rain, others just get wet.”

Thirdly, it can be handled the foggy and stormy days. Hardly anyone wants to be outside when the weather is either foggy or stormy as these conditions of the weather are not only depressing but also dangerous ones. While anyone walks on the way and the weather is foggy, a car can hit them as the car driver cannot see them and they cannot blame the driver as it is not only his/her fault. Fourthly, it can be continued with days including hail. When the weather is haily, it is obvious that nobody can be found outside, as nearly no one love this condition of the weather. Hardly anyone can either play, trip or sit outside.

Finally, this essay can be finished with snowy days. These days have both good and bad effects on people’ s mood as well. It is better to start with good ones primarily. Although it does not seem a good idea, nearly all of the people, especially children love these days. These days make almost all of the people happy. People can drink coffee, look at outside and watch their children while playing snowball, make a snowman and skiing happily. And even elder people can play snowball, make a snowman and skiing, after all having fun has no age limit. On the other hand, it can be mentioned bad ones. When the weather is snowy, roads can be closed by snow, can be slippery and these can cause to a traffic accident or can cause people to slip and fall down onto hard ground and this may cause their bones to break.

If you ask me whether the weather has any effect on me, I will absolutely say “yes”. The weather has a lot of effects on me, as well. When I get up, the first thing I do is looking outside in order to know whether the weather is sunny, cloudy, rainy or snowy. I can feel really happy when the weather is sunny but I cannot feel as happy as I am on sunny days if it is cloudy, or rainy.

WORKS CITED

1. Widmer, Bill, “Lifehack”, Web, 03, 14 , 2019 (https://www.lifehack.org/414675/8-ways-weather-can-affect-your-mood-and-behavior-that-you-may-have-never-noticed)
2. Brenner, Laurie, “Sciencing”, 04. 17, 2018, Web, 03, 14, 2019) (http://web2.bilkent.edu.tr/turkce-birimi/wp-content/uploads/sites/4/2018/06/kılavuz.pdf
3. Mercola, Joseph, “Mercola”, 03, 31, 2016, Web, 03, 14, 2019) (https://articles.mercola.com/sites/articles/archive/2016/03/31/weather-affects-mood.aspx

Introduction

Weather is an uncontrollable atmospheric action and often inconsistent. Can the same be said about our moods? Some people’s moods are like the weather, hot, cold and very inconsistent. Studies have been done to see if one is dependent of the other. Weather has for some time been believed to impact a person’s mood but it is very difficult to capture in a study. This could be due to how people describe their mood on self-reporting surveys or weather may not be a direct impact on mood. Yet, self-reports are still the most commonly used research method in measuring mood and weather. For my study, I would like to identify if weather affects mood. Data will be collected from participants by way of self-reporting surveys. Data will then be loaded into SPSS for assessment.

Problem Statement

Often, some of us have heard conversations where people feel weather affects their recreational activities and eventually affecting their moods. We do not need to be a weather forecaster or a scientist to recognize a correlation between weather and mood. With prevailing research and analyzing, several have assumed that the correlation is just the very fact that weather conditions provides us the revelation on views regarding life and also ways to grasp them. Some researchers have developed studies to incorporate variables in determining if weather conditions affect mood. This is a topic of interest for me due to it being psychological, difficult, and something that not many would select. Although several studies have been done on this topic, certain regions should be studied more empirically. As with any shift in weather conditions, our mood is impacted good or bad. If the weather temperature decreases to a cold temperature, does mood increase? To help facilitate this study, several sources from previous studies will be used.

Literature Review

Peng, Tang, Fu, Fan, Hor, and Chan (2016), examined if there was a link between weather and peoples’ happiness on a short-term level. The findings recommend that climate, economic income, and private health behaviors are all related to levels of happiness. Researchers conducted their study using a geospatial approach (applying analytic methods and statistical data) to two major datasets. The study was uniquely conducted on the worldwide representative survey data that aligned with weather data, geographical information on the city and economic history. In developing the study, the researchers advised it was critical and difficult in the data merging.

In collecting the results, the researchers were able to collect enough data even though the study produced limitations from data compatibility. By ordering and rephrasing closed-ended questions on the survey will bridge the gaps in the study. For example, if the closed-ended survey questions were arranged differently, perhaps the results could have yielded better compatibility.

Construct validity posed an issue from the research design using the survey questions. Although there were disadvantages from the design method and mistranslation on the survey questions, the study still had criterion validity by linking temperature and personal happiness.

Wagner, Keusch, Yan & Clarke (2019), examined if people are physically active indoors or outdoors in extreme temperature conditions. Their independent variable in the study was based upon questions regarding different weather conditions “which of the following conditions is most likely to change the way you go about day to day activities” (Wagner., Keusch, Yan & Clarke, 2019). The researchers used a survey design with common questions. Collecting data from 502 respondents, older adults (≥65 years of age) would choose exercising indoors (in a gym) if temperature conditions are not favorable outdoors as opposed to the younger adults.

As opposed to the previous article from Wagner., Keusch, Yan and Clarke (2019) on recreational activities indoors or outdoors being a personal preference, Hansen, Pisaniello, and Xiang (2013), focused on characteristics of work environments where workers are exposed to extreme heat temperatures beyond working health code requirements. They also aimed to summarize findings from published studies, and ultimately strategize ways for the work environment heat exposure reduction, diversification, and additional research analysis.

Blue collar employees working in extremely hot conditions are also in danger of heat strokes, particularly for those working for low wages in countries in tropic regions. The study was conducted from 1997 to 2012. The researchers analyzed data from 55 articles to determine what are the effects on health from working in extremely hot conditions.

The results yielded minimal limitations. The authors feel they may have understudied work-related injuries which may be challenging to data. If this is true, then this will affect the reliability of the results. There was also not enough data to analyze the relationship between temperatures and heat-work related injuries.

In this article by Guzman, Tonelli, Roberts, Stiller, Jackson, Soriano, Yousufi, Rohan, Komarow and Postolache (2007), aimed to find a relationship between weather, severe allergies and mood. The researchers felt that pollen can turn into inflammation in the respiratory system airways and inflammation triggers depression in vulnerable people. The researchers hypothesized that mood sensitivity to pollen, the foremost seasonal pollen, are related to a larger seasonality of mood. A Mann Whitney study was used to compare GSS between participants having or not having mood worsening throughout high pollen counts. Results showed that the potential of mood worsening with high pollen counts, age, ethnicity, and gender of mild conditions were analyzed with supply regressions.

The average age was 29 years for individual’s reportage sensitivity to pollen and 30 for people who failed to report sensitivity to pollen. The common length of residence within the study space was 20 years for those not reportage sensitivity and 20 years for those coverage sensitivities to pollen, with simple fraction of the respondents living within the space for over ten years.

Timmermans, van der Pas, Schaap, Sánchez-Martínez, Zambon, Peter, Pedersen, Dennison, Denkinger, Castell, Siviero, Herbolsheimer, Edwards, Otero and Deeg (2014), study aimed to look at whether or not there are variations in perceived joint pain between older individuals with OA who rumored to be weather-sensitive versus those that failed to in six European countries with totally different climates and to spot characteristics of older persons with OA that are most prognostic of perceived weather sensitivity.

Baseline information from the Project on degenerative arthritis were used. ACR classification criteria were used to confirm OA. Participants with OA were asked concerning their perception of weather as influencing their pain. Employing a two-week follow-up pain calendar, average self-reported joint pain was assessed range: zero -10. Simple regression analyses, logistical regression analyses and an independent t-test were used. Analyses were adjusted for many confounders.

The majority of participants with OA perceived the weather as affecting their pain. Weather-sensitive participants reported additional pain than non-weather-sensitive participants.

The study resulted in a limitation that should be taken in consideration. If subjects noted that their joint pain wasn’t suffering from one in all this weather, they were thought of as non-weather-sensitive persons. The method employed to conduct the study failed to take into consideration whether or not participants’ joint pain might be suffering from different weather, like changes in air pressure. Moreover, it’s necessary to acknowledge some caveats with relevance the utilization of 3 local climate varieties.

Advantages and Disadvantages

Advantages and disadvantages will also be in reference to the research question. They are supported by previous studies regarding productivity in certain weather conditions. This will be supported by findings from various studies from researchers focusing on how temperature and weather can influence mood that affect productivity.

Peng, Tang, Fu, Fan, Hor, and Chan (2016), incorporated the geospatial approach to the statistical regression to expand and elevate people’s mood was a major advantage to the study. The disadvantage to the design method was that it caused too many loopholes with collecting data. The context of the survey questions did not translate well to some cultures; thus, causing social desirability.

Wagner, Keusch, Yan & Clarke (2019), An advantage to using the study design of the questionnaire was the rigor in which the survey questions were constructed that derived from literature reviews. The results did not produce many limitations. For example, if the sample size had been increased, it could have yielded precision results in the categories of age, education, income and race; thus, bridging the gap in the study.

A disadvantage to the design method was that it did not account for the neighborhoods in which people live in. For example, is there a walking trail or park in the neighborhood? If not, could this pose an issue why some are not physically active outdoors? In advantage to the design method was that the rigor in the survey question deriving from literature reviews decreased any bias responses from participants. In relation to Peng, Tang, Fu, Fan, Hor, and Chan (2016), concluding people are less happy if unable to do physical activity outdoors, Wagner, Keusch, Yan & Clarke (2019), concluded exercising is much labeled as a personal preference whether indoors or outdoors.

A disadvantage to Guzman, Tonelli, Roberts, Stiller, Jackson, Soriano, Yousufi, Rohan, Komarow and Postolache (2007), study was they only studied black communities. By using a small sample size, results might not be generalizable to the whole population. The researchers also did not directly measure depression scores or pollen counts. They also did not collect information on allergies. Results from the study are an expression of circular reasoning. Thus, additional refined epidemiologic, empirical and experimental work is important to verify our hypothesis. On a clinical level, there’s a necessity for more studies concentrating on longitudinally evaluate depression, allergic reaction symptoms, inflammation markers, and pollen counts. The researchers concluded their study be a preliminary.

The method applied in Timmermans, van der Pas, Schaap, Sánchez-Martínez, Zambon, Peter, Pedersen, Dennison, Denkinger, Castell, Siviero, Herbolsheimer, Edwards, Otero and Deeg (2014) study worked to their advantage. The researchers’ greatest data was that the initial large-scale study that examined self-perceived weather sensitivity and joint pain in older individuals with OA in Europe, corrected for a large vary of contradictory factors. Previous studies were performed within the USA and Australasia were primarily centered on self-perceived weather-sensitivity and pain in less specific teams. This study used a population-based approach and centered on one illness cluster and it magnified insight into the characteristics profile of weather-sensitive individuals with OA during a general population of older persons across Europe. This could assist distinguishing weather-sensitive older individuals with OA.

A major disadvantage to these studies would be that weather and mood can be difficult to capture. It can be difficult due to a person’s medical condition or the temperament of a person to conclude that weather influences mood. Researches put their best method of study to the test to identify the link between both weather and mood, yet none of the designs accounted for age and gender of the participants. It is hypothesized that weather affects mood. Creating strategic questions focused on weather conditions, this study may yield better results on concluding weather affecting mood. Although the sample size is small, the data should still give results to if the temperature decreases to a colder degree, does mood increase?

Materials

An online survey program, Qualtrics will hold all materials needed for participants to complete the online survey. This program is used for research purposes is exclusive to Southern New Hampshire University. Participants will need internet access, computer and 20 minutes of time to complete a 15 self-reporting survey regarding personality and weather conditions. The questionnaire will employ a Likert Scale as an ordered category scale.

Procedure

To test the hypothesis, graduates will answer a questionnaire on how does weather influence their mood. Prior to the questionnaire, each respondent will be given an informed consent form. This is because participants will be providing information on the demographics consisting of age, gender, city and state.

The self-reporting questionnaire will be related to three sections. The initial section is the demographic information. This will be a generic Likert Scale asking for age range , gender, temperament, allergy/sinus or joint pain sufferer and geographical information. This is general information regarding the participant’s s temperament prior to weather conditions. The next section will list different the seasons where they will scale 1 for like, 2 for dislike, 3 for neutral. The last section will list types of weather conditions (rain, sunny, hot and cold) and they will select their mood (happy, sad, neutral) associated with the weather condition.

Ethical Concerns

An informed consent explaining the purpose of the research, duration of study and procedures will be provided to all participants. Participants will also be informed of their rights to decline to participate and can withdraw from the analysis once it’s started. They will also be informed of anticipated consequences of withdrawing. The informed consent form is vital to research because participants will be providing demographic information such as age, male/female, city and state. The form will also advise of confidentiality and security measures. Providing this form will cut down all any ethical issues that may arise from the study if not provided.

Results

Reviewing the literature reviews, my anticipated results will identify if conditions of weather can affect your mood. I anticipate sunny days will be highly preferable. I also anticipate some female participants may not report the majority of their mood from conditions of weather; whereas male participants’ mood will have a neutral response from conditions of weather. Anticipated results will give a clear distinction if weather affects mood.

The anticipated results will be exhibited as actual views and not as explanations of cause. Results will be cautiously taken in consideration to guarantee that there are no ethical issues with deceiving anyone with the outcomes.

Because of the small sample size with the sample being enrollees from Southern New Hampshire University, limitations are expected. Normal distribution may not be normal due to the limited population; thus, will be harder for a larger population to be generalized.

Reference

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Agriculture is one field of the human activity which is extremely sensitive to weather and climate. The study of these two aspects in relation to agriculture is referred as agricultural meteorology and is a multidisciplinary science. Agricultural meteorology when properly applied by plant scientists can achieve the sustainability of agricultural production system through efficient management of agro-climatic resources and crop microclimate modification. Each and every plant developmental phase is decided by meteorological parameters. Every genotype has its own optimum climatic requirements for expression of its full potential. Therefore, the knowledge of meteorological parameters and their influence on crop growth and yield is very important for plant scientists (Niwas, Singh, Singh, Khichar & Singh, 2006).

Agricultural meteorology is an applied science which deals with the relationship between weather or climatic conditions and agricultural production. More than ever, agricultural meteorological services have become necessary because of the challenges provided to many forms of agricultural production by increasing climate variability and associated extreme events as well as climate change, all of which affecting the socio-economic conditions. Some of the importance of agricultural meteorology to plant scientists are; it helps in planning cropping systems, selecting of sowing dates and crop varieties, reduce losses of applied chemicals and fertilizers, in season cultivation and irrigation, eliminating outbreak of pests and diseases, efficient harvesting of crops and pre-season crop marketing decisions and managing weather abnormalities such as cyclones, forest fire, dust storm, heavy rainfall, floods, drought etc. achieved by weather forecasting (Eilts, 2018).

Despite ongoing improvements in technology and crop varieties, climate is still the main uncontrollable factor affecting agriculture production. Crop growth and yield are affected by variations in climatic factors such as air temperature and precipitation, and the frequency and severity of extreme events such as droughts, floods, windstorms and hail. The losses due to abnormal weather can be minimized to a considerable extent by suitable adjustment of the farming operations according to the probable weather conditions through accurate weather forecasting from meteorological stations. Weather forecasting is foretelling the coming weather in advance. It may be defined as advance information about the probable weather conditions for few days to come. So the time for which weather forecast is made is also important (Hollinger, nd).

Weather is the prime unpredictable factor that controls crop growth and development in agriculture. For instance, when the plant scientists have information on weather forecast and they assume that the weather forecasts are perfect or correct to a useful extent it means, in advance, they can have with the information on the weather such as rainfall, temperature, relative humidity, atmospheric pressure, wind, dew, etc. that is going to affect their crops in the coming days. So, given the weather forecast, plant scientist can foresee in advance the crop growth and development and take necessary measures to increase crop productivity depending on the resource status (Gommes, 2001).

Weather forecasts play a very important role in many farming operations. For instance, weeding is best done in a rainless period, planting requires regular but not too heavy rain, spraying pesticides cannot be done in windy weather, etc. Weather forecasting enables the farmers to manage the whole value chains that is land preparation, planting, management of crops, harvesting etc. under appropriate and optimum conditions for increasing productivity of the crops. Hence weather updates from meteorological stations is essential for the plant scientists and farmers to manage their crops properly and improve their productivity (Griffiths, 1994).

The application of meteorology to agriculture is of high importance, since every facet of agricultural activity depends on the weather. The growth and harvest of plants is a response both to genetics and the surrounding environment. With careful planning and research, agricultural meteorologists help the plant scientists and farmers to meet the world’s demands for food and other agricultural products. Uncertain weather patterns, because of climate change and other meteorological phenomena, has increased the need for accurate weather data (Biswas,2016).

Agricultural meteorology studies meteorological and hydrological factors in relation to agriculture. It also studies the behavior of the weather elements that have direct relevance to agriculture and their effect on crop production. Weather and climate are the factors determining the success or failure of agriculture. It has an important impact in agricultural production as it has a straight influence on crop growth, development and yields, on the incidence of pests and diseases, on water needs and on fertilizer requirements. Extreme and variable weather conditions may cause decline in production, damage to crops and soil erosion, decline in the quality of the final products, problems in the yield transportation (Johnson, 1994).

Plant scientists and farmers cannot fight the weather. However, they can adopt the given situation and take additional farm management practices to minimize crop losses. Therefore, precise information regarding the weather is essential so that farm activities can be planned without adverse events. On the other hand, farming under the open sky is greatly reliant upon the weather and is subject to its moody conditions, especially nowadays, when climate change leads to unpredictable weather which is beyond human control (Hollinger, nd).

Rachita (nd) pointed out that, generally, there is no aspect of crop culture that is immune to the impact of weather. These impacts are particularly strong in countries located in the tropics with low levels of crop management technology, and in most of the cases, exposed to high variability in climate because of regional meteorological systems and phenomena. Considering this context, it is important for plant scientists to use weather and climate information to support the decision making process at various dimensions, at the farm and in agricultural industries. Furthermore, the existence of organized and reliable databases is required to develop studies and research in agricultural meteorology, to generate new knowledge and technological alternatives to minimize the effects of adverse weather and climate conditions for agriculture.

Irrespective of the type of decision, an ever improving understanding of the effects of weather and climate on soils, plants, trees and related production in farming systems, is necessary for decision makers such as plant scientists and farmers, to make timely and efficient use of meteorological and climatological information and of agricultural meteorological services for agriculture production. To these ends choices have to be made of the right mixture and blending of traditional adaptation strategies, contemporary knowledge in science and technology and suitable policy environments. Without policy support systems for agricultural meteorological services, yields with the available production means will remain below optimal (Eilts, 2018).

Agriculture meteorology helps the plant scientist in planning the cropping systems which will be able to take into consideration the environmental concerns. A cropping system is referred to the type and sequence of crops grown and practices used in the production process. Conserving soil and water and maintaining long term soil productivity depends largely on the management of cropping systems, which influence the magnitude of soil erosion and organic matter dynamics. Properly managed cropping system can maintain or even restore moderately degraded lands by improving soil resilience (Wikibooks, 2019).

Field workability refers to the availability of days that are suitable for fieldwork. It’s primarily dependent upon soil moisture and soil temperature. Accurate field-level weather information can help plant scientists and farmers assess the workability of their fields and become more efficient in their day-to-day operations (Eilts, 2018).

Eilts, (2018) emphasized that, timing in fertilizer application is very important and one of the many decisions that plant scientists and farmers have to make is determining the proper time to apply fertilizer, as well as the application rate and fertilizer form to use. A misapplied application caused by weather can wipe away the entire field’s profits. Weather forecasts provided by agricultural meteorologist can be used to ensure that fertilizer is applied in the right conditions. For instance, no urea topdressing before expected heavy rainfall and no topdressing after storm either. In the former case it saves urea from being lost in the environment.

Griffiths (1994) explained that, the application of agricultural meteorology as an aid to the plant scientist and farmer in combating plant disease differs according to the mechanisms by which each pathogen is spread. The pathogen may be a year-round resident that increases and spreads whenever the weather is suitable for the pathogen and the host plant, which is the case with the fungal diseases. In some areas a pathogen may not be capable of surviving the year, and may not reappear unless transported in sufficient quantity from a distant source, for instance, black wheat rust. In recent years the development of crop disease models has focused on crops with high economic value, such as fruit trees, vineyards and vegetables, since the models need meteorological observations in field settings that usually require agricultural meteorology information from weather stations.

Certain weather conditions encourage the development and growth of pests and diseases, which can destroy crops. The application of meteorology to overcome the effects of pests and diseases on plants and animals involves a complete understanding of the complex life cycles of the pathogen and its host, as well as the environmental conditions that influence growth and development. For instance, temperature affects the growth rate of insects, hence their population increases with increase in temperature and vice versa. Temperature has been used in predicting insect pest outbreaks using degree-days concept. Weather forecast guidance incorporated into pest and disease modeling can help plant scientists to determine when it is an appropriate time to apply pesticide or disease controls in older to treat the crops to get the best outcome when it comes to managing pest and diseases (Biswas,2016).

Eilts, (2018) asserts that, in a situation whereby weather forecast indicates that there will be a favorable condition for disease and pest occurrences, the plant scientists will advise farmers to get prepared for preventive and curative measures ahead of damage happening to their crops. Weather forecasts are also important for forecasting the spread of fungal pathogens that are carried on by the wind. This can allow for pretreatment of crops to avoid massive losses. Wind forecasts also play a role in this decision, as crop dusters, aircraft that spray fungicidal or insecticidal chemicals on plants from above, must be utilized when wind conditions are not suitable to cause sprayed chemicals to miss their targets. Besides that, plant scientists can encourage farmers to implement crop diversification in order to reduce the risk of unfavorable weather conditions and damage due to pest and diseases.

Plant scientists and farmers are being helped in decision making due to the access to reliable weather forecast information from agricultural meteorologists. Throughout many months, they make small but frequent decisions about their crops, and the cumulative effect of the financial implications of those decisions can be significant. For example, a forecast of soil moisture for a strategic decision will be made on mean soil moisture conditions at the start of a season and modified based on the historical variance of soil moisture about the mean. In a tactical forecast, the current state of moisture in the soil is known, and based on seasonal climate forecasts the timing of increases or decreases of soil moisture throughout the growing season predicted. Based on this forecast the current planting date of a crop can be adjusted to take advantage of favorable soil moisture during critical growth stages. Forecasting about commencement of rainy season helps the plant scientists to advise farmers to sow crop at the right time (Biswas,2016).

In certain circumstances, when the weather forecast indicates longer dry seasons following short rainy seasons, the plant scientists will encourage farmers to arrange water harvesting or other water supplementary sources of enabling supplementary irrigation to maximize their yields.

Crop growth, or crop yield, requires appropriate amounts of moisture, light, and temperature. Detailed and accurate historical, real-time and forecast weather information can help plant scientists better understand and track the growth status or stage to make informed decisions. Having access to this data can guide them in making significant and potentially costly decisions, such as whether, when and how much to irrigate. Farming mostly depends on rainfall. Too much can overexpose and ruin a crop, whereas too little may cause it to dehydrate and die. By having access to weather forecast data, plant scientists may know when to plant and water a crop. Irrigation planning is a good example. If a farmer relies on a forecast for precipitation that turns out to be accurate, he saves the cost of unnecessary irrigation. And by having a good idea of the expected amount of rain over a period and irrigating just enough to allow crops to thrive, he or she will maximize yield (Eilts, 2018).

Additionally, weather forecast is really very important for the plant scientists to manage their crops. For example, if the weather forecast indicates that there will be rains at the time of harvesting, the plant scientists will advise the farmers to get prepared to harvest their products before being damaged by the rains. If floods are predicted during the harvesting time, better to harvest crop even if 60-75% crop is matured and this will help in averting total loss (Rachita, nd).

Wind and humidity can drastically affect crops through events such as forest fires and by observing these weather issues plant scientists can advise farmers to control the burning and prevent the spread of fire. Moreover, wind can also be measured in less endangering occurrences, such as strong gusts, and in such event fixtures will need to be attached to crops to allow them to stay upright and not damage. Another basic practice which can be initiated by the plant scientists is to advise the farmers to implement the practice of planting crops near shady areas, such as large trees, and by doing so they can ensure their plants are not overly exposed to sunlight and grow to their full capacity. Therefore, by applying this rationale to farming, farmers can increase yield and produce larger, quality harvests (Wikibooks, 2019).

In conclusion, agricultural meteorology is important to plant scientists as it helps in planning cropping systems, selecting of sowing dates and crop varieties, reduce losses of applied chemicals and fertilizers, eliminating outbreak of pests and diseases, in season cultivation and irrigation, efficient harvesting of crops and pre-season crop marketing decisions and managing weather abnormalities like cyclones, forest fire, dust storm, heavy rainfall, floods, drought etc. achieved by weather forecasting.

References

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