Reviewer has chosen not to be AnonymousOverall Impression:
RejectTechnical Quality of the paper:
Unable to judgePresentation:
Unable to judgeNovelty:
Limited noveltyData availability:
All used and produced data (if any) are FAIR and openly available in established data repositoriesLength of the manuscript:
This manuscript is too long for what it presents and should therefore be considerably shortened (below the general length limit)
Summary of paper in a few sentences:
The authors use a variety of machine learning (ML) methods to predict basic weather variables -- temperature, humidity, wind speed, and rainfall -- in Bangladesh. They compare the ML methods to determine which performs best for each weather variable.
Reasons to accept:
They compare a large number of ML methods, so their results could serve as a valuable guide for those who want to implement similar methods for weather prediction.
Reasons to reject:
The paper is poorly written. Specific complaints are listed below.
 The quality of the English is poor. This makes the paper difficult to follow and makes some parts completely incomprehensible. Some examples from just the first two pages are as follows.
"Nearly 70% of its total population live in rural areas and 60% of them earn their livelihood from tillage stuff." -- What is 'tillage stuff'?
"Weather forecasting is supposed to be a prime factor for Bangladesh’s economy as agriculture plays a vital role in country’s overall Gross Domestic Product (GDP) which accounts for approximately 20% of the total amount. . .Even a significant amount of total annual exports are from farming products which tend to be in the region of 13-18% of the country's total GDP." -- The first sentence seems to claim that 20% of the GDP comes from agriculture, and the second seems to claim that 13-18% of the GDP comes from agriculture -- unless there's a difference between agriculture and 'farming products,' but this is unclear.
"Since the dawn of technological advancement, weather forecasting is that much noteworthy which have been endeavored to predict accurately as much as possible for many years by the experts." -- The second part of this sentence (after the comma) doesn't make sense.
"Intelligent weather prediction techniques can help us to a certain degree that can help us to make effective decisions which can save valuable lives, times and property at a time. With the passage of time, science and technology have advanced to the next level and weather pattern discovery has attracted more attention. It involves the anticipation of how the current circumstance with the air will change in which current climate conditions are taken via ground discernments e.g. boats, radar, satellite, airplanes, etc." -- Although this part is comprehensible, like much of the paper, it is long-winded and full of grammatical errors, which makes it difficult to parse.
 The paper contains 32 figures, which is far too many. I understand that the authors want to show everything, but the paper would be much more effective if they showed only the most interesting/important results. They could relegate other results to an online supplement.
 Most of the figures are ineffective. Figures 1-17 are too grainy; Figures 18, 21, and 30 have three titles that are too small to read; and lines in Figures 19, 23, 25-26, 28-29, and 31-32 cannot be differentiated.
 The paper contains 10 tables, each with 27 numbers. These tables would be better served in a graphical format such as line graphs or bar graphs, as it is difficult to make general conclusions from staring at 27 numbers (especially when one has to do this 10 times).
 In general, the paper contains too many figures/tables and too little interpretation of the data shown in the figures/tables.
Poor presentation and grammar make the paper difficult to read, so I read only the first three pages thoroughly, skimming thereafter. This is why the majority of my comments focus on the presentation and not the science. However, I believe these comments are sufficient to reject. Even if the science were flawless, I can't imagine the paper having a positive impact.