Weather - Science topic

Climate change adaptation requires changes in what we grow. Because of weather challenges, most exotic fruits and vegetables are grown outside the UK. Will the rise in temperatures in Britain provide an opportunity to grow such crops? How can black women get involved in this opportunity?

Sabemos que mexico es un pais privilegiado en cuanto a sus recursos naturales, con una ubicacion y clima excepcionales, esto sin mencionar el enorme potencial de capital humano y expertos en diversas areas del conocimiento, asi como Instituciones educativas muy reconocidas con excelentes avances e investigacion en cuanto al cultivo de peces marinos, sin embargo parece no ser suficiente para lograr el despegue y desarrolo del cultivo de peces marinos; que consideras que haria falta para este fin ?

I need a scientific articles about Camelus bactrianus specifically about their behaviour and adaptation to the cold weather as well all know camel belongs to the desert but this time the situation is differen.

Often in many articles we come across this confusing terminology.

greenhouse gases, such as mathen, co2, and others affect weather conditions

The population is growing exponentially and demands food, fiber, services, etc. And on the other hand, the weather goes every time unpredictable. Technology and innovation seem to be an alternative as long as it is possible to reuse and add value to the residues and waste from the production units. This leads to asking a question that perhaps starts this discussion. What is the country's agenda on the issue of Bioeconomy?

For my own research, I use LSTM and MLP algorithms, where weather data is part of the input data. Unfortunately, data related to temperature and precipitation have not been recorded in many time periods, and the number of empty data is high. What is the solution to manage this missing data?

How does climate change affect weather patterns and the environment in different parts of the world?

I need to compute vapour pressure deficit (VPD) from ECMWF ERA-5 data set.

Can anyone help me to select appropriate ERA-5 parameters and corresponding equations ?

You can get the list of available parameters here: https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=form

My first guess would be:

VPD = SVP – AVP

with AVP = actual vapor pressure

SVP = saturation vapor pressure

using formulation of Bougeault (1982):

SVP = 610.78 x e^(17.2694 x (Td-273.16) / (Td-35.86))

AVP = 610.78 x e^(17.2694 x (T -273.16) / (T -35.86))

With T = air temperature ("2m temperature" ERA5 parameter)

Td = dewpoint temperature ("2m dewpoint temperature " ERA5 parameter)

if correct, VPD is thus derived from T and Td

Thanks for helping

Polymers undergo degradation by weathering ( UV-light, oxygen & moisture effects outdoors low temperatures ) hence the use of stabilizers.

But i could not find studies on this problem or solutions for the case of biodegradable polymers. Are the solutions known for PBS, TPS & PHA and their blends ?

Dear Colleagues,

We invite you to submit your valuable articles to the Special Issue "Recent and Future Cyclonic Activity and Associated Weather Extremes"

The aim of this Special Issue is to provide recent advances in the field of study on cyclonic activity change encompassing issues of changes in the past, revealing current tendencies and scenarios of changes in the near future. A key task for SI is gathering high-quality papers concerning seasonal- interannual-to-decadal variability of synoptic patterns that drive cyclones evolution; studies on extraction and interpretation of multidecadal trends are also welcomed. Expected future trends of cyclones frequency and intensity associated with the anthropogenic factors is the second task of SI. Besides, it is well-known that cyclones can cause extreme weather conditions and may trigger natural disasters. Therefore, special attention should be paid to study of extremes associated with cyclones, and this is the third task of SI. Actually, these problems should be solved using both various probabilistic and interdisciplinary methods of experimental data analysis, as well as numerical, stochastic and statistical modeling including outputs of CORDEX, CMIP6 etc.

Above tasks are very important not only from academic point of view, but also for a high number of applications which are also in the focus of the SI. Among them are sustainable agriculture, social infrastructure and recreational potential, optimal design and use of wind power plants, transport and maritime safety etc. The scope of these problems covers an essential part of issues to be resolved to attain optimal regional strategies for adaptation and sustainable planning all over the World.

Topics of interest for the Special Issue include but are not limited to:

Prof. Dr. Elena Nikolaevna Voskresenskaya Dr. Vladislav Evstigneev Guest Editors

The question of whether deep learning models can outperform traditional numerical weather prediction (NWP) systems is increasingly relevant in meteorology. NWP relies on complex physical models and equations to simulate atmospheric processes, but it can be computationally expensive and slow. In contrast, deep learning models, those utilizing neural networks like LSTM, CNN, and Transformer architectures, offer the potential for faster and more data-driven predictions by learning complex patterns directly from historical weather data. While deep learning shows promise in specific applications such as short-term forecasting, its ability to consistently surpass NWP remains an active area of research requiring further validation.

Weathering of metallic surfaces affect the solar/light reflectance properties but also its emissivity. According to a manufacturer of copper plates the emissivity measured between 2000 and 50000 nm increases from below 0,02 for a new surface to approximately 0,70 when is has been exposed to outdoor elements for a certain time. What causes this substantial shift and can it be predicted for typical exposure conditions?

I need to estimate the LAI of a wheat crop using only weather and soil parameters. Can anyone please help me?

If hydrosphere is (fluid) mass conserved, then,

Is it NOT about the

" Reallocated Distribution of Water Resources on this earth"?

Whether Global Warming really matters on a larger continental scale?

Of course, we do have extreme weathers resulting from global warming at few specific locations. But on the whole, the total fluid mass needs to be conserved. Right?

The entire global system has to be in "Dynamic Equilibrium" - Right?

The British Premier league has 20 teams, they play 380 games in a season, each team plays with each one game at home and one game away. 17 out of these 20 teams were playing in the previous season and all results are available. 3 teams are new, we ignore them and only predict for those that played previous season.

How to predict outcomes in a new season for these 17 teams using historic records and newly obtained results. For example, when several games already played in a new seasons, they can be taken on account. We need to predict the exact score, not only a winner. Winners are obvious in most games. When predicting scores we need predict them as vectors, so if it is 3:2 that does not mean we can predict 3 by one model and 2 by another, it is clear that both numbers are related. Also the model must be probabilistic. So we have to predict probabilities of multiple possible outcomes.

I'm not trying to get quick rich. Bookmakers disallow to use AI and disqualify those who, may use them. Also, it is already known that AI predicts better than humans. Also, bookmakers are simply exclude those who win too much without any explanation, so it is not a money making method, but a research.

The prediction must use only the scores from the previous seasons and not any other insider information, such as traumas, new players, new trainers, weather, rain, wind and so on. These factors are considered as random noise and expressed indirectly in probabilities.

We are doing a student-run project outlining climate influences on a small watershed, and were hoping to access historical, localized data from the Weather Underground network (there are currently about 6 registered sites in the watershed). Any attempts to gain access to the data have been frustrating and we were wondering if anyone has found a good work-around for this? We do not want AI-generated data or forecasts, but actual observations within the watershed.

Thanks in advance for your thoughts on this!

especially in extreme weather regions

Hello,

i am writing an assigment about endurance, where i am cycling for 1 month (cca. 16 tranings 2 day training successively; 1 day rest) and as a bonus i am trying to find colleration with weather and my cylcling time, avg., max. heart rate... (For example when the temperature was above 25 degrees my avg. HR was incereased...) Sadly weather isnt as simple as saying 20 degrees celcius is hot and 10 is cold and it becomes complicated with humiditity, wind, sun... The lap i am cyciling basically negates the effect of wind (for example if wind is blowing one way it helps me in the first half and its harder the second half) and geting accurate wind measurments is basically impossible. Still i want to know if there is an index, a formula that would accurately portray the effect of temperature and humidity? 30 degrees in 90% humidity with the sun out is not the same as 30 degrees with 30% humidity, so i was personally thinking of just putting this into "weather" units meaning 30 degrees and 90% would be 120 weather units, while the latter would be 60 weather units, in this case i would atleast have a more accurate scale. Maybe something like sun being out and shining on me for the whole ride would be a (multiplier)*2. I dont know, so i am askig if there is a formula that already connects atleast temperature and humidity. Thank you.

I am currently doing my post-graduate, and for my research thesis, I needed weather data from the wet zone in Sri Lanka( Matara, Galle, Kalutara, Colombo, Gampaha, Kegalle, Ratnapura, Nuwara Eliya, Nuwara and Matale districts). Here the data of annual rainfall, maximum temperature and minimum temperature are required from 1961 to 2023. How can I get this data and what is the suitable way for that?

Dear colleagues, I am dealing with a change in the weather. I have monthly precipitation data dating back to around 1950. Can you please advise me on the statistical methods that experts use to evaluate the distribution of rainfall? I have determined from the analysis that the precipitation trends in the areas I am studying are not statistically significant (Mann-Kendall trend test). In some places, the long-term rainfall is slightly decreasing, while in others, it is slightly increasing. However, I know from other articles that their distribution is changing. Periods without rain are becoming longer, and this dry spell is being replaced by heavy rainfall. The rainfall is not uniform; its distribution is different from that in the past.

What method is appropriate for such an analysis?

Thank you very much for your advice.

I am designing a software system for ordering satellite imagery in a way that by entering the specifications of the satellite orbit and its optical sensor, as well as the target ground area, it can determine the required time for the satellite camera to turn on.

To ensure that the weather conditions above the target area are suitable for satellite optical sensor imaging, can I use the PCMODWIN4 software???

In fact, I will perform the following steps:

the judicial influence on the legislature and examples

I used Google Earth Engine to retrieve LST for my research area based on Landsat 7 (for 2001.) and Landsat 8 (for 2019.) by using surface refectance dataset (atmospherically corrected). I'm trying to see how LST changed with newly built-up surfaces.

So, based on slightly different bands wavelengths between satellites, does it also mean LST is varying? For example, if I compare LST from 2001. and 2019. on the same urban surface is the measured LST going to be different? I'm also asking based on this: thermal Band 6 on Landsat 7 is 10.40 - 12.50μm and Band 10 (TIRS1) on Landsat 8 is 10.60 - 11.19 μm.

I am aware of influence of weather during researched time on LST, but aside of that I would like to know if I can compare these two LST's.

Thanks!

Does the concentration of CO2 gas in the atmosphere cause warming of the earth's atmosphere? Or does it lead to less rainfall when it warms up? Or does the warming of the earth's atmosphere lead to an increase in rainfall on the earth's surface?

Equilibrium Climate Sensitivity (ECS) is the global mean change in surface temperature for a doubling of CO2 from the pre-industrial (PI) value. ECS is one of the key metrics used in assessing future global warming, and therefore plays a very important role in climate change related policy-making. One important question in this regard is how ECS changes in a warmer world. Several studies found that ECS increases at higher CO2 concentrations (e.g., Bloch-Johnson et al., 2021; Colman & McAvaney, 2009; Gregory et al., 2015; Meraner et al., 2013). And, more recently, Mitevski et al. (2021) found a non-linear and non-monotonic dependence of ECS on CO2 concentrations. In addition to the surface temperature response, the precipitation response is another critical aspect of climate change. To evaluate precipitation changes, the key metric used is Hydrological Sensitivity (HS). HS is defined as the difference in global mean precipitation per one degree of global mean temperature change from the PI control state. Previous studies have explored the response of the hydrological cycle to global warming by examining HS in terms of the global energy budget, and have described the mechanisms affecting it (e.g., Allen & Ingram, 2002; Held & Soden, 2006; Jeevanjee & Romps, 2018; O'Gorman et al., 2011). The fact that HS is energetically constrained means that the precipitation response can be separated into fast and slow components. The fast response depends only on the CO2 concentrations in the atmosphere, before the surface temperature has time to warm, and results in a decrease in precipitation. The slow response, in contrast, is associated with surface warming, and results in an increase in precipitation (Andrews et al., 2010).

Reply to this discussion

James Garry added a reply:

Mr Kashani,

You have written two rather facile queries, and part of a third.

"Or doe"

Abbas Kashani added a reply:

Does the concentration of CO2 gas in the atmosphere cause warming of the earth's atmosphere? Or does it lead to less rainfall when it warms up? Or does the warming of the earth's atmosphere lead to an increase in rainfall on the earth's surface?

James Garry added a reply:

Abbas,

1) Yes, the rising carbon dioxide content of the atmosphere does lead to an increase in the surface and globally-averaged air temperature.

2) As the partial pressure of water vapour is a strong function of temperature (and that vapour is also a 'greenhouse gas') we expect to see a rise in the global humidity - that in various locales should result in more rainfall.

Neither of these are contentious matters and are well-addressed in the literature.

1) https://journals.ametsoc.org/view/journals/atsc/47/4/1520-0469_1990_047_0475_ccatma_2_0_co_2.xml

2)

Article More rain, less soil: Long-term changes in rainfall intensit...

I recommend Google Scholar.

Very useful.

Mrutyunjay Padhiary added a reply:

Through the greenhouse effect, the amount of carbon dioxide (CO2) gas in the atmosphere is a significant contributor to global warming with many other greenhouse gases. Heat from the sun is trapped in the atmosphere when CO2 and other greenhouse gases build up, preventing it from escaping back into space. Global warming is the term for the total rise in temperature that results from this. Rainfall patterns can be impacted by Earth's atmosphere warming, while there is a complex relationship between CO2 concentrations and rainfall that varies based on local climate dynamics. Higher temperatures generally have the potential to alter the rates of evaporation and atmospheric circulation, which in turn can affect the patterns of precipitation. higher moisture can be held by warmer air, which could result in higher evaporation from lakes, oceans, and land surfaces. In certain areas, the increased moisture in the atmosphere may be a factor in the intensity of rainfall events. Higher temperatures, however, can also bring about modifications to weather patterns, including adjustments to air circulation and modifications to precipitation distribution. Also, variables including local geography, atmospheric stability, and variations in cloud cover can all have an impact on changes in rainfall patterns. While some places might have more rainfall than others, other regions might see less rainfall or changes in the frequency and severity of precipitation events. The ecosystems, agricultural practices, water supplies, and human societies may all be significantly impacted by these modifications in rainfall patterns. All things considered, even while the rise in CO2 concentrations in the atmosphere is the main cause of global warming, temperature variations that follow can have an impact on precipitation patterns, which can have complicated and varied impacts on the distribution and intensity of rainfall.

Dea all

Where can I access and download yearly historical weather data (Temperature, Precipitation, and Relative humidity) for countries (ex. Uganda, Senegal,...) from 1960 to 2024?

Thank you all in advance

Hello

Is there anyone who uses the Meteonorm program that can help me find a specific file for a specific site?

I want a file to be used in the TRNSYS program, file name TYPE 9

Location Ma'an/Al-Hussein Bin Talal University, located at coordinates 30.2671° N and 35.6785° E.

Please help, thank you

They don’t always gather even when the weather changes.

During that time iron from weathering will enter the oceans and presumably form soluble compounds.

Hello Everyone,

I'm searching for MRMS raw grid rainfall data across the United States. Can anyone help me with where I can download this data? Additionally, any tips on processing the data would be greatly appreciated

#rainfall #radardata

..

Some studies suggested that herbs are resilient to impacts of CC because they have shorter life span and are adaptive to CC. Other studies suggested that trees are more resilient because of the extensive root system, enabling them to withstand extreme weather events.

Is there any weather data morphing tool (for hourly weather data) to predict climate change for future using the IPCC AR5 (assessment report 5) emission scenarios I.e. rcp 2.5, rcp 4.5, rcp 6 & rcp 8?

name the institutions or the websites to get the local weather data in india

Some volcanoes can send particles and water to the Mesosphere, as Tonga in 2022. The consequences are much more complicated than imagined

this paper is talking about it

Explore the power of AI in crafting adaptive strategies for climate-vulnerable communities and boosting resilience against extreme weather events.

🔍 Key Questions:

🌟 Why Dive In?

🌐 Who's Welcome?

💬 How to Join:

Ready to transform ideas into action? Let's reshape the future together!

I have recently added to a discussion about my fuchsia plants that were out in the first very cold few days in 2022. They are usually out during the winter but looked as if they had died. So, I put them in a porch and gave them words of encouragement. And I have congratulated them about their green shoots.

I then added a piece to another RG discussion asking if any members either talk to their plants or feel that it is helpful (to the plants as well as the RG member!)

The Royal Horticultural Society has done research into this:

and there are other positive thoughts on the subject, just to mention a few:

I would be really interested in your thoughts and will pass the messages on to the fuchsia!

I have measured RWC from drier as well as wetter habitats from high elevations (3000-5000m asl) throughout the growing season. I found some species showing low RWC (%), but the Fv/Fm and PhiPS2 are not too low.

Could there be any other reason to show low RWC?

One study says that non-photochemical quenching can also result in low RWC. Maybe?

It is common during the season to increase the incidence of severe influenza, the symptoms of which are similar to Corona 19. In your opinion, is the weather the main cause, or is it the results of infection with Corona, or is it possible that a new variant is currently developing? Are there recent studies in Iraq on this subject?

Dear Sir,

We all know that the water cement ration 0.45, which may vary due to the Mix-Design. But during the concrete due to changes of weather & materials SSD condition the slump changed (Generally Dropped) in mid time.

So looking the help from experience person, how many water may use for 1mm/5mm slump gaining. The equations also okay, I can check with our mix-design for getting the value.

Thanks in advance for your assistance.

We're proud to introduce the new Weather Station at the American University of Ras Al Khaimah! Get real-time weather data at your fingertips. 🌡️ Check it out here: [https://lnkd.in/duatzcnj ] Stay informed and stay ahead! 🌍🌤️

#WeatherStation #AURAK #RasAlKhaimah #WeatherData #RAK #UAE

Atmospheric Circulation: The movement of air masses and the circulation patterns in the Earth's atmosphere play a significant role in shaping climate. For example, the Hadley, Ferrel, and Polar cells create major wind patterns that influence climate zones and weather patterns.

My question erfers to to knowledge about the coupling of the jet stream, the gulf stream and omega blocks, determining the climate in Europe, Northern Africa and possibly elsewhere on the globe.

Folks who have studied this interplay are welcome to answer my question

Cheers,

Frank

Dear WRF-Chem users,

I am interested in acquiring knowledge regarding the use of the restart functionality inside the Weather Research and Forecasting (WRF) model. There are three domains in a nested structure, with sizes of 9, 3, and 1 km.

The whole duration of the run was allocated to a period of 19 days, with the initial 14 days designated for spin-up.

Could you please provide instructions on how to utilize the restart option? Furthermore, while checking the user guide, I discovered that it was inadequate in providing clear instructions to follow.

Could you kindly provide me with guidance in this matter?

Sincere regards,

Why Prophet Muhammad ordered Muslims to wear white clothes, while the weather in desert is hot and dried?

i have done drought forecasting but i need to proceed the research towards prescriptive analytics so any domain experts in drought can suggest me what are the prescriptive analytics that can be carried out in drought since weather is not under human control

There is nothing worse for curb appearance than chipped and cracked concrete, particularly in steps. But you don’t have to put up with that blight any longer. By the result of weather changes exerted on an existing construction for prolonged time, it causes contraction and expansion those gradually results concrete steps cracks and break up with time.

Dear researchers, I would like to get expert opinions on how to fix this issue with,

prolonged sustainability .

Your answers are highly welcomed.

I need data for historical and fututre projecti0ns using CMIP6 SSP scenarios,anybody know any site please reply

Hello there,

I have seen the website https://cwfis.cfs.nrcan.gc.ca/maps/fw?type=fwi which generates maps of fire weather parameters like DMC, FWI , FFMC etc. based on the date. Is there a way i can get the data in the form of a .nc file or something that contains the continuous historical data of these parameters for canada?

I want to know how we can avoid the effects of climatic changes during stem cutting in crops. I will cut the mature plants' stems from ground level to get new plantlets, but weather changes may affect the growth of new plantlets. Looking for scientific suggestions.

In light of the urban heat island (UHI) effect and variations in urban microclimates, how do researchers account for these localized impacts when analyzing temperature data, especially after weather station relocations? Are there any specific methodologies or correction factors used to ensure that the data truly represents the ambient conditions and isn't skewed by urban developments?

I'm trying to reconstruct the time series of a weather station over the whole 1991-2020 period by using an external model as predictor.

I've successfully used ERA5-Land as predictor for temperature as the correlation with station data is quite high, however I'm struggling to do the same for precipitation.

What is the best alternative to reanalysis in this case? I was thinking about datasets of daily precipitation measured from satellite but the data seems to be quite coarse.

In my case I have the following requirements

You have any suggestions on which dataset I could use?

I am investigating the correlation between climatic variations and conflicts over environmental resources; these are a fe questions that I am interested in researching and would love to discuss with whoever is interested

2. Purpose of the Study:

The study aims to:

a. Identify and quantify the correlation between weather changes and conflicts over environmental resources.

b. Examine specific types of conflicts, focusing on regions or nations that are particularly vulnerable to climate change.

c. Investigate specific environmental resources involved in these conflicts.

3. Justification:

As climate change becomes an increasingly pressing issue globally, understanding its effects on resource allocation and conflict is crucial for policy-making, international relations, and conflict resolution strategies.

4. Approach:

a. Research Topic: The correlation between climatic variations and conflicts over environmental resources.

b. Contribution Statement: This study will contribute to our understanding of how climate change exacerbates resource-based conflicts.

c. Hypothesis: Significant climatic variations increase the likelihood and intensity of conflicts over environmental resources.

d. Independent Variable: Weather changes (temperature fluctuations, rainfall patterns, extreme weather events).

e. Dependent Variable: Occurrence and intensity of conflicts over environmental resources.

f. Data Collection Methods: Use of historical weather data from meteorological agencies; conflict data from international databases; primary data through interviews or surveys where necessary.

g. Operationalization of Variables: Weather changes will be measured using standard meteorological indices; conflict occurrence/intensity will be quantified using conflict incident reports or indices.

h. Analytical Strategy: Statistical analysis to determine correlation; qualitative analysis for primary data.

5. Limitations & Challenges:

Potential limitations include availability and reliability of conflict data, cultural nuances in conflict reporting, differing definitions of 'conflict', and potential confounding variables such as political instability or economic factors.

6. Projected Results:

The study expects to find a positive correlation between significant weather changes and resource-based conflicts, thereby adding to our understanding of how climate change impacts societal stability and security.

7. Conclusion:

This research proposal offers a comprehensive plan for investigating an increasingly relevant global issue - how climate change influences resource-based conflicts - with potential implications for policy-making, international relations, peacekeeping efforts, and sustainability initiatives.

I want to build a complete weather statistical model to predict the weather.

Where the model is able to predict all atmospheric layers.

And to be able to display the predicted results in the form of interactive weather maps.

Humans are often plagued with extreme weather events e.g. hurricane, heat wave, drought and flood. Is flooding a natural or man-made disaster? Sharing is caring!!!

I am currently working on a model to predict the energy generation of a PV power plant, using historical weather data and power plant generation data. However, I am facing challenges in finding reliable resources that provide hourly power data for PV power plants in any country. I would greatly appreciate any suggestions or recommendations regarding potential sources for such data. Thank you in advance!

What are the most serious problems of civilization development that should be solved as soon as possible? What are the global problems for which research should be developed and solutions to these problems resolved in 2019 and in subsequent years?

One of such research problems, which should not be postponed for an indefinite future, is the need to develop environment-friendly sustainable economic development in order to slow down the adverse process of global warming.

With the warming of the Earth's climate, the risk of more dramatic climate cataclysms, including tsunamis, increases.

Tsunami may be a derivative of the global warming problem. Global warming generates an increase in climate disasters, including more cases of tsunamis.

But not only is the risk of more violent and more dramatic tsunamis rising. Also in recent years, there has been more other types of climate and natural climate catatics, such as droughts, rainstorms, tornadoes and weather anomalies.

At present, it should no longer be asked whether global warming generates an increase in natural disasters only what rate of growth will be recorded in the future? So many data, research centers confirms the progressing process of global warming, that the problem is unquestionable.

More and more data points to the growing risk of climate change, unfavorable for human and life on the Earth, increase of climate disasters, climatic and weather anomalies, which are the result of global warming, rising average annual temperature near the Earth's surface.

Now we should just ask: How can these adverse processes be counteracted? What ecological technologies, renewable energy sources, how to help natural environments, how to rebuild them, such as afforestation, to build natural ecosystems absorbing greenhouse gases?

How to develop ecological business ventures? How to create financing systems for this type of pro-ecological projects? How to dispel international cooperation in this matter? What actions should be taken to move towards the development of a new ecological green economy?

How to develop environmentally sustainable economic development to slow down the unfavorable warming of the Earth's climate?

Please reply. I invite you to the discussion

Are there any researchers or organizations interested in collaborating on enhancing our understanding and modeling of complex natural phenomena, such as ocean currents, atmospheric flows, and geophysical fluid dynamics, with the goal of advancing weather prediction, climate modeling, and promoting environmental sustainability? Please reach out if you are interested in collaborating on this important research area.