Propagation of cloud base to higher levels during Covid-19-Lockdown.
Identifieur interne : 000210 ( Main/Exploration ); précédent : 000209; suivant : 000211Propagation of cloud base to higher levels during Covid-19-Lockdown.
Auteurs : Latha R [Inde] ; Murthy B S [Inde] ; Sandeepan B S [Inde] ; Vinayak Bhanage [Inde] ; Aditi Rathod [Inde] ; Arpit Tiwari [Inde] ; Gufran Beig [Inde] ; Siddhartha Singh [Inde]Source :
- The Science of the total environment [ 1879-1026 ] ; 2021.
Descripteurs français
- KwdFr :
- MESH :
- Wicri :
- geographic : Inde.
English descriptors
- KwdEn :
- MESH :
- geographic : India.
- Atmosphere, COVID-19, Communicable Disease Control, Humans, Pandemics, SARS-CoV-2.
Abstract
Aerosol-cloud interactions and feedbacks play an important role in modulating cloud development, microphysical and optical properties thus enhancing or reducing precipitation over polluted/pristine regions. The lockdown enforced on account of Covid-19 pandemic is a unique opportunity to verify the influence of drastic reduction in aerosols on cloud development and its vertical distribution embedded in identical synoptic conditions. Cloud bases measured by ceilometer in Delhi, the capital of India, are observed to propagate from low level to higher levels as the lockdown progresses. It is explained in terms of trends in temporal variation of cloud condensation nuclei (CCN) and precursor gases to secondary hygroscopic aerosols. The large reduction (47%) in CCN estimated from aerosol extinction coefficient during the lockdown results in upward shift of cloud bases. Low clouds with bases located below 3 km are found to have reduced significantly from 63% (of total clouds distributed in the vertical) during pre-lockdown to 12% in lockdown period (less polluted). Cloud base height is found to have an inverse correlation with CCN (r = -0.64) and NO2/NH3 concentrations (r = -0.7). The role of meteorology and CCN in modulating the cloud vertical profiles is discussed in terms of anomalies of various controlling factors like lifting condensation level (LCL), precipitable water content (PWC) and mixing layer height (MLH).
DOI: 10.1016/j.scitotenv.2020.144299
PubMed: 33341515
Affiliations:
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Electronic address: murthy@tropmet.res.in.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune</wicri:regionArea><wicri:noRegion>Pune</wicri:noRegion></affiliation></author><author><name sortKey="B S, Sandeepan" sort="B S, Sandeepan" uniqKey="B S S" first="Sandeepan" last="B S">Sandeepan B S</name><affiliation wicri:level="1"><nlm:affiliation>Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune</wicri:regionArea><wicri:noRegion>Pune</wicri:noRegion></affiliation></author><author><name sortKey="Bhanage, Vinayak" sort="Bhanage, Vinayak" uniqKey="Bhanage V" first="Vinayak" last="Bhanage">Vinayak Bhanage</name><affiliation wicri:level="1"><nlm:affiliation>Indian Institute of Technology, Mumbai, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Indian Institute of Technology, Mumbai</wicri:regionArea><wicri:noRegion>Mumbai</wicri:noRegion></affiliation></author><author><name sortKey="Rathod, Aditi" sort="Rathod, Aditi" uniqKey="Rathod A" first="Aditi" last="Rathod">Aditi Rathod</name><affiliation wicri:level="1"><nlm:affiliation>Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune</wicri:regionArea><wicri:noRegion>Pune</wicri:noRegion></affiliation></author><author><name sortKey="Tiwari, Arpit" sort="Tiwari, Arpit" uniqKey="Tiwari A" first="Arpit" last="Tiwari">Arpit Tiwari</name><affiliation wicri:level="1"><nlm:affiliation>India Meteorological Department, Ministry of Earth Sciences, New Delhi, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>India Meteorological Department, Ministry of Earth Sciences, New Delhi</wicri:regionArea><wicri:noRegion>New Delhi</wicri:noRegion></affiliation></author><author><name sortKey="Beig, Gufran" sort="Beig, Gufran" uniqKey="Beig G" first="Gufran" last="Beig">Gufran Beig</name><affiliation wicri:level="1"><nlm:affiliation>Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune</wicri:regionArea><wicri:noRegion>Pune</wicri:noRegion></affiliation></author><author><name sortKey="Singh, Siddhartha" sort="Singh, Siddhartha" uniqKey="Singh S" first="Siddhartha" last="Singh">Siddhartha Singh</name><affiliation wicri:level="1"><nlm:affiliation>India Meteorological Department, Ministry of Earth Sciences, New Delhi, India.</nlm:affiliation><country xml:lang="fr">Inde</country><wicri:regionArea>India Meteorological Department, Ministry of Earth Sciences, New Delhi</wicri:regionArea><wicri:noRegion>New Delhi</wicri:noRegion></affiliation></author></analytic><series><title level="j">The Science of the total environment</title><idno type="eISSN">1879-1026</idno><imprint><date when="2021" type="published">2021</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Atmosphere (MeSH)</term><term>COVID-19 (MeSH)</term><term>Communicable Disease Control (MeSH)</term><term>Humans (MeSH)</term><term>India (MeSH)</term><term>Pandemics (MeSH)</term><term>SARS-CoV-2 (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Atmosphère (MeSH)</term><term>Contrôle des maladies transmissibles (MeSH)</term><term>Humains (MeSH)</term><term>Inde (MeSH)</term><term>Pandémies (MeSH)</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>India</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Atmosphere</term><term>COVID-19</term><term>Communicable Disease Control</term><term>Humans</term><term>Pandemics</term><term>SARS-CoV-2</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Atmosphère</term><term>Contrôle des maladies transmissibles</term><term>Humains</term><term>Inde</term><term>Pandémies</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Inde</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Aerosol-cloud interactions and feedbacks play an important role in modulating cloud development, microphysical and optical properties thus enhancing or reducing precipitation over polluted/pristine regions. The lockdown enforced on account of Covid-19 pandemic is a unique opportunity to verify the influence of drastic reduction in aerosols on cloud development and its vertical distribution embedded in identical synoptic conditions. Cloud bases measured by ceilometer in Delhi, the capital of India, are observed to propagate from low level to higher levels as the lockdown progresses. It is explained in terms of trends in temporal variation of cloud condensation nuclei (CCN) and precursor gases to secondary hygroscopic aerosols. The large reduction (47%) in CCN estimated from aerosol extinction coefficient during the lockdown results in upward shift of cloud bases. Low clouds with bases located below 3 km are found to have reduced significantly from 63% (of total clouds distributed in the vertical) during pre-lockdown to 12% in lockdown period (less polluted). Cloud base height is found to have an inverse correlation with CCN (r = -0.64) and NO<sub>2</sub>/NH<sub>3</sub> concentrations (r = -0.7). The role of meteorology and CCN in modulating the cloud vertical profiles is discussed in terms of anomalies of various controlling factors like lifting condensation level (LCL), precipitable water content (PWC) and mixing layer height (MLH).</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Automated" Owner="NLM"><PMID Version="1">33341515</PMID><DateCompleted><Year>2021</Year><Month>01</Month><Day>13</Day></DateCompleted><DateRevised><Year>2021</Year><Month>01</Month><Day>13</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1879-1026</ISSN><JournalIssue CitedMedium="Internet"><Volume>759</Volume><PubDate><Year>2021</Year><Month>Mar</Month><Day>10</Day></PubDate></JournalIssue><Title>The Science of the total environment</Title><ISOAbbreviation>Sci Total Environ</ISOAbbreviation></Journal><ArticleTitle>Propagation of cloud base to higher levels during Covid-19-Lockdown.</ArticleTitle><Pagination><MedlinePgn>144299</MedlinePgn></Pagination><ELocationID EIdType="pii" ValidYN="Y">S0048-9697(20)37830-X</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.scitotenv.2020.144299</ELocationID><Abstract><AbstractText>Aerosol-cloud interactions and feedbacks play an important role in modulating cloud development, microphysical and optical properties thus enhancing or reducing precipitation over polluted/pristine regions. The lockdown enforced on account of Covid-19 pandemic is a unique opportunity to verify the influence of drastic reduction in aerosols on cloud development and its vertical distribution embedded in identical synoptic conditions. Cloud bases measured by ceilometer in Delhi, the capital of India, are observed to propagate from low level to higher levels as the lockdown progresses. It is explained in terms of trends in temporal variation of cloud condensation nuclei (CCN) and precursor gases to secondary hygroscopic aerosols. The large reduction (47%) in CCN estimated from aerosol extinction coefficient during the lockdown results in upward shift of cloud bases. Low clouds with bases located below 3 km are found to have reduced significantly from 63% (of total clouds distributed in the vertical) during pre-lockdown to 12% in lockdown period (less polluted). Cloud base height is found to have an inverse correlation with CCN (r = -0.64) and NO<sub>2</sub>/NH<sub>3</sub> concentrations (r = -0.7). The role of meteorology and CCN in modulating the cloud vertical profiles is discussed in terms of anomalies of various controlling factors like lifting condensation level (LCL), precipitable water content (PWC) and mixing layer height (MLH).</AbstractText><CopyrightInformation>Copyright © 2020 Elsevier B.V. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>R</LastName><ForeName>Latha</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>B S</LastName><ForeName>Murthy</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India. Electronic address: murthy@tropmet.res.in.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>B S</LastName><ForeName>Sandeepan</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Bhanage</LastName><ForeName>Vinayak</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>Indian Institute of Technology, Mumbai, India.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Rathod</LastName><ForeName>Aditi</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tiwari</LastName><ForeName>Arpit</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>India Meteorological Department, Ministry of Earth Sciences, New Delhi, India.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Beig</LastName><ForeName>Gufran</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Singh</LastName><ForeName>Siddhartha</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>India Meteorological Department, Ministry of Earth Sciences, New Delhi, India.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>12</Month><Day>09</Day></ArticleDate></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Sci Total Environ</MedlineTA><NlmUniqueID>0330500</NlmUniqueID><ISSNLinking>0048-9697</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D001272" MajorTopicYN="Y">Atmosphere</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000086382" MajorTopicYN="Y">COVID-19</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D003140" MajorTopicYN="N">Communicable Disease Control</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007194" MajorTopicYN="N" Type="Geographic">India</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000086402" MajorTopicYN="N">SARS-CoV-2</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">CCN</Keyword><Keyword MajorTopicYN="N">Ceilometer</Keyword><Keyword MajorTopicYN="N">Cloud profiles</Keyword><Keyword MajorTopicYN="N">Extinction coefficient</Keyword><Keyword MajorTopicYN="N">Trace gases</Keyword></KeywordList><CoiStatement>Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>07</Month><Day>09</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>11</Month><Day>30</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>12</Month><Day>01</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>12</Month><Day>21</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2021</Year><Month>1</Month><Day>14</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>12</Month><Day>20</Day><Hour>20</Hour><Minute>25</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">33341515</ArticleId><ArticleId IdType="pii">S0048-9697(20)37830-X</ArticleId><ArticleId IdType="doi">10.1016/j.scitotenv.2020.144299</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Inde</li></country></list><tree><country name="Inde"><noRegion><name sortKey="R, Latha" sort="R, Latha" uniqKey="R L" first="Latha" last="R">Latha R</name></noRegion><name sortKey="B S, Murthy" sort="B S, Murthy" uniqKey="B S M" first="Murthy" last="B S">Murthy B S</name><name sortKey="B S, Sandeepan" sort="B S, Sandeepan" uniqKey="B S S" first="Sandeepan" last="B S">Sandeepan B S</name><name sortKey="Beig, Gufran" sort="Beig, Gufran" 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