Hail—pieces of ice that form and fall from clouds instead of snow or rain—has always been a problem for farmers in some areas of the United States. Hail pellets can fall with great force and destroy crops in the field. Over the last few decades, a method of reducing hail, called “cloud seeding,” has been tried. In cloud seeding, the chemical silver iodide is sprayed on storm clouds from an airplane. This makes the clouds produce harmless rain or snow instead of hail. Several pieces of evidence suggest that cloud seeding has been effective in protecting crops from hail.
Laboratory experiments
Experiments in the laboratory support the idea that cloud seeding is effective. Hail usually forms in water vapor that is close to the freezing point. However, when experimenters added silver iodide to cold water vapor in the laboratory, they often observed light snow forming instead of hail pellets.
Evidence from Asia
There is evidence about the effectiveness of cloud seeding from several countries around the world. In some Asian countries, for example, cloud seeding has been successfully used to control precipitation in urban areas. These positive results suggest that cloud seeding should also be effective in protecting fields and farms in the United States.
Local studies
A few local studies also support the value of cloud seeding. One study conducted in a farming region in the central United States, for example, directly monitored crop damage due to hail. The study found that in an area where cloud seeding was used there was reduced hail damage compared to previous years.
Whether cloud seeding is believed to be effective of preventing crop damage from hail is still surrounded by controversy. According to the reading passage, the author mentions three pieces of evidence to support the theory; nonetheless, the professor in the listening considers the evidence indefensible.
First, the author claims that laboratory experiment showed that cloud seeding forms light snow instead of hail pellet that cause the damage of crops, while the professor demonstrates a squarely different idea. He points out that in laboratory condition, cloud seeding produce snow instead of hail, whereas cloud seeding can form any precipitation, such as snow, rain or hail, in nature condition. So if cloud seeding were put in places that do not rain often, it might cause drought. As a result, it brings about another damage to the crop due to the lack of water.
Second, the professor disputes the reading passage that the success of cloud seeding implementation in Asian city can indicate the success of which in American farm and field. He illustrates that the measure was conduct in urban area and cannot be duplicated to farming area. In addition, air pollution particles in the city interact with cloud seeding. Therefore, the experience in Asia could not infer that cloud seeding will work out in the unpolluted area of American.
Finally, the author cited local studies that the crop damage has declined in a conducting region due to the reduction of hail. However, the professor repudiates the research by explaining that hail decreased not only in that region but also in nearby area. Hence, because the declination occurred in the whole region, it could only be contributed to the natural local weather change in that year.
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Grammar and spelling errors:
Line 1, column 1, Rule ID: SENTENCE_FRAGMENT[1]
Message: “Whether” at the beginning of a sentence requires a 2nd clause. Maybe a comma, question or exclamation mark is missing, or the sentence is incomplete and should be joined with the following sentence.
Whether cloud seeding is believed to be effecti...
^^^^^^^
Line 3, column 449, Rule ID: ADVERB_WORD_ORDER[9]
Message: The adverb 'often' is usually put before the verb 'rain'.
Suggestion: often rain
... seeding were put in places that do not rain often, it might cause drought. As a result, i...
^^^^^^^^^^
Transition Words or Phrases used:
also, but, finally, first, hence, however, if, nonetheless, second, so, still, therefore, whereas, while, in addition, such as, as a result
Attributes: Values AverageValues Percentages(Values/AverageValues)% => Comments
Performance on Part of Speech:
To be verbs : 7.0 10.4613686534 67% => OK
Auxiliary verbs: 7.0 5.04856512141 139% => OK
Conjunction : 4.0 7.30242825607 55% => More conjunction wanted.
Relative clauses : 13.0 12.0772626932 108% => OK
Pronoun: 17.0 22.412803532 76% => OK
Preposition: 41.0 30.3222958057 135% => OK
Nominalization: 12.0 5.01324503311 239% => Less nominalizations (nouns with a suffix like: tion ment ence ance) wanted.
Performance on vocabulary words:
No of characters: 1471.0 1373.03311258 107% => OK
No of words: 284.0 270.72406181 105% => OK
Chars per words: 5.17957746479 5.08290768461 102% => OK
Fourth root words length: 4.10515524023 4.04702891845 101% => OK
Word Length SD: 2.71678376121 2.5805825403 105% => OK
Unique words: 159.0 145.348785872 109% => OK
Unique words percentage: 0.55985915493 0.540411800872 104% => OK
syllable_count: 451.8 419.366225166 108% => OK
avg_syllables_per_word: 1.6 1.55342163355 103% => OK
A sentence (or a clause, phrase) starts by:
Pronoun: 5.0 3.25607064018 154% => OK
Article: 7.0 8.23620309051 85% => OK
Subordination: 3.0 1.25165562914 240% => Less adverbial clause wanted.
Conjunction: 0.0 1.51434878587 0% => OK
Preposition: 3.0 2.5761589404 116% => OK
Performance on sentences:
How many sentences: 13.0 13.0662251656 99% => OK
Sentence length: 21.0 21.2450331126 99% => OK
Sentence length SD: 41.5330480803 49.2860985944 84% => OK
Chars per sentence: 113.153846154 110.228320801 103% => OK
Words per sentence: 21.8461538462 21.698381199 101% => OK
Discourse Markers: 10.6923076923 7.06452816374 151% => OK
Paragraphs: 4.0 4.09492273731 98% => OK
Language errors: 2.0 4.19205298013 48% => OK
Sentences with positive sentiment : 6.0 4.33554083885 138% => OK
Sentences with negative sentiment : 3.0 4.45695364238 67% => OK
Sentences with neutral sentiment: 4.0 4.27373068433 94% => OK
What are sentences with positive/Negative/neutral sentiment?
Coherence and Cohesion:
Essay topic to essay body coherence: 0.212795496177 0.272083759551 78% => OK
Sentence topic coherence: 0.0714681395819 0.0996497079465 72% => OK
Sentence topic coherence SD: 0.0532926991198 0.0662205650399 80% => OK
Paragraph topic coherence: 0.116620014572 0.162205337803 72% => OK
Paragraph topic coherence SD: 0.0508463907208 0.0443174109184 115% => OK
Essay readability:
automated_readability_index: 13.9 13.3589403974 104% => OK
flesch_reading_ease: 50.16 53.8541721854 93% => OK
smog_index: 8.8 5.55761589404 158% => OK
flesch_kincaid_grade: 11.5 11.0289183223 104% => OK
coleman_liau_index: 12.76 12.2367328918 104% => OK
dale_chall_readability_score: 9.01 8.42419426049 107% => OK
difficult_words: 78.0 63.6247240618 123% => OK
linsear_write_formula: 14.5 10.7273730684 135% => OK
gunning_fog: 10.4 10.498013245 99% => OK
text_standard: 10.0 11.2008830022 89% => OK
What are above readability scores?
---------------------
Rates: 80.0 out of 100
Scores by essay e-grader: 24.0 Out of 30
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Note: the e-grader does NOT examine the meaning of words and ideas. VIP users will receive further evaluations by advanced module of e-grader and human graders.