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181 results on '"Dubey, M K"'

2. Detonation Soot: A New Class of Ice Nucleating Particle.

Author

Thompson, S. A., Aiken, A. C., Huber, R. C., Dubey, M. K., and Brooks, S. D.

Subjects
RATE of nucleation, SOOT, COLD regions, WEATHER, LOW temperatures, ICE nuclei, ATMOSPHERIC nucleation
Abstract

Temperatures and pressures from high explosive detonations far exceed atmospheric conditions in typical combustion reactions, and consequently, detonation soot forms with physiochemical properties distinct from soot formed by combustion. In this study, samples of detonation soot from two high explosives, PBX 9502 and Composition B‐3, were analyzed. Ice nucleation experiments on soot collected after controlled detonations were conducted in the laboratory to probe immersion and contact mode freezing. Samples nucleated ice at temperatures warmer than commercially available nanodiamonds, which has a mean nucleation temperature of −20.7°C. Ice nucleation rate coefficients increase rapidly by two to three orders of magnitude below −20°C for every sample. Size‐selected 137 μm diameter particles produced during detonation in an ambient air atmosphere yield bimodal distributions of freezing temperature with primary and secondary nucleation modes centered at −20°C and −13°C, respectively. The presence of a secondary mode allows for enhanced ice nucleation rate coefficients (one to two orders of magnitude greater than samples without a secondary mode) at temperatures outside the influence of the primary mode (>−17°C). Given the observed onset nucleation temperatures of −9.2°C, our results imply that detonation soot of the type studied here would only need to reach an altitude of approximately 4 km to facilitate ice formation. Plain Language Summary: Tiny suspended particles can modify the earth's energy balance. Some of these particles influence cloud formation through a process called the indirect effect of aerosol. One aspect of the indirect effect involves a subset of aerosol known as ice nucleating particles (INPs) that enhance ice formation in cold regions of the atmosphere. Because of the impact of INPs on climate, it is important to identify the types of aerosols that efficiently form ice. One understudied aerosol is a unique soot with distinct properties that is formed by the extreme temperatures and pressures achieved within high explosive detonations. This detonation soot can be lofted high into the atmosphere where it could impact ice formation. The ice nucleation activity of detonation soot is examined here for the first time. Through experimentation, we measured the freezing temperature of detonation soot originating from two different high explosives, PBX‐9502 and Composition B‐3. Detonation soot does act as an INP with a small portion of efficient particles. Our results indicate that detonation soot lofted into the atmosphere could increase the number of INPs around the globe and promote ice nucleation at warmer temperatures and lower altitudes in regions lacking more efficient INPs. Key Points: High explosive detonation soot particles act as ice nucleating particles with a small percentage activating as warm as −9.2°CDetonations in oxygen‐rich environments generate more effective ice nucleating particles than those generated in oxygen‐poor environmentsCuprous oxide and diamond are moderately effective ice nucleating particles but less effective than the detonation soot samples [ABSTRACT FROM AUTHOR]

Published
2024
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3. Minimal Realization of an Input–Output L-fuzzy Multiset Behavior.

Author

Dhingra, Mallika and Dubey, M. K.

Abstract

This research aims to introduce and study the minimal realization problem of a new class of automaton with input and output as multisets. We begin by introducing the concrete categories N M A S e t (Ω ⊕) and L M A S e t (Ω ⊕) of non-deterministic and L -fuzzy multiset automata over category Set and determine the functorial relationship between them, in which L is a distributive lattice. Next, we introduce other concrete categories L M A O S e t (Ω ⊕ , ℧ ⊕) and D L M A O S e t (Ω ⊕ , ℧ ⊕) of L -fuzzy (crisp deterministic L -fuzzy) multiset automata with output over category Set and their input–output L -fuzzy multiset behavior. Further, we minimize the introduced category D L M A O S e t (Ω ⊕ , ℧ ⊕) using functorial maps. Finally, we introduce the concept of realization of an input–output L -fuzzy multiset behavior and using Myhill–Nerode's theory, we construct a minimal crisp deterministic L -fuzzy multiset automata with output in Set which realizes the given input–output L -fuzzy multiset behavior. [ABSTRACT FROM AUTHOR]

Published
2024
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4. Algebraic Characterization of IF-Automata

Author

Yadav, Vijay K., Yadav, Swati, Dubey, M. K., Tiwari, S. P., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Panigrahi, Chhabi Rani, editor, Pujari, Arun K., editor, Misra, Sudip, editor, Pati, Bibudhendu, editor, and Li, Kuan-Ching, editor

Published
2019
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5. On the Category of Quantale-Semimodules

Author

Dubey, M. K., Yadav, Vijay K., Tiwari, S. P., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Panigrahi, Chhabi Rani, editor, Pujari, Arun K., editor, Misra, Sudip, editor, Pati, Bibudhendu, editor, and Li, Kuan-Ching, editor

Published
2019
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9. FASER128: Cryptanalysis and Its Countermeasure

Author

Dubey, M. K., Gaba, Navneet, Bedi, S. S., Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Giri, Debasis, editor, Mohapatra, Ram N., editor, Begehr, Heinrich, editor, and Obaidat, Mohammad S., editor

Published
2017
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13. Global consortium for the classification of fungi and fungus-like taxa

Author

Hyde, K. D., Abdel-Wahab, M. A., Abdollahzadeh, J., Abeywickrama, P. D., Absalan, S., Afshari, N., Ainsworth, A. M., Akulov, O. Y., Aleoshin, V. V., Al-Sadi, A. M., Alvarado, P., Alves, A., Alves-Silva, G., Amalfi, M., Amira, Y., Amuhenage, T. B., Anderson, J. L., Antonín, V., Aouali, S., Aptroot, A., Apurillo, C. C. S., Araújo, J. P.M., Ariyawansa, H. A., Armand, A., Arumugam, E., Asghari, R., Assis, D. M.A., Atienza, V., Avasthi, S., Azevedo, E., Bahkali, A. H., Bakhshi, M., Banihashemi, Z., Bao, D. F., Baral, H. O., Barata, M., Barbosa, F. R., Barbosa, R. N., Barreto, R. W., Baschien, C., Belamesiatseva, D. B., Reuel, M. Bennett, Bera, I., Bezerra, J. D. P., Bezerra, J. L., Bhat, D. J., Bhunjun, C. S., Bianchinotti, M. V., Błaszkowski, J., Blondelle, A., Boekhout, T., Bonito, G., Boonmee, S., Boonyuen, N., Bregant, C., Buchanan, P., Bundhun, D., Burgaud, G., Burgess, T., Buyck, B., Cabarroi-Hernández, M., Cáceres, M. E. S., Caeiro, M. F., Cai, L., Cai, M. F., Calabon, M. S., Calaça, F. J. S., Callalli, M., Camara, M. P. S., Cano-Lira, J. F., Cantillo, T., Cao, B., Carlavilla, J. R., Carvalho, A., Castañeda-Ruiz, R. F., Castlebury, L., Castro-Jauregui, O., Catania, M. D., Cavalcanti, L. H., Cazabonne, J., Cedeño-Sanchez, M. L., Chaharmiri-Dokhaharani, S., Chaiwan, N., Chakraborty, N., Chaverri, P., Cheewangkoon, R., Chen, C., Chen, C. Y., Chen, K. H., Chen, J., Chen, Q., Chen, W. H., Chen, Y. P., Chethana, K. W. T., Coleine, C., Condé, T. O., Corazon-Guivin, M. A., Cortés-Pérez, A., Costa-Rezende, D. H., Courtecuisse, R., Crouch, J. A., Crous, P. W., Cui, B. K., Cui, Y. Y., da Silva, D. K. A., da Silva, G. A., da Silva, I. R., da Silva, R. M. F., da Silva Santos, A. C., Dai, D. Q., Dai, Y. C., Damm, U., Darmostuk, V., Zoha, Daroodi, Das, K., Davoodian, N., Davydov, E. A., Dayarathne, M. C., Decock, C., de Groot, M. D., De Kesel, A., de la Cruz, T. E. E., De Lange, R., Delgado, G., Denchev, C. M., Denchev, T. T., de Oliveira, N. T., de Silva, N. I., de Souza, F. A., Dentinger, B., Devadatha, B., Dianese, J. C., Dima, B., Diniz, A. G., Dissanayake, A. J., Dissanayake, L. S., Doğan, H. H., Doilom, M., Dolatabadi, S., Dong, W., Dong, Z. Y., Dos Santos, L. A., Drechsler-Santos, E. R., Du, T. Y., Dubey, M. K., Dutta, A. K., Egidi, E., Elliott, T. F., Elshahed, M. S., Erdoğdu, M., Ertz, D., Etayo, J., Evans, H. C., Fan, X. L., Fan, Y. G., Fedosova, A. G., Fell, J., Fernandes, I., Firmino, A. L., Fiuza, P. O., Flakus, A., de Souza, C. A.Fragoso, Frisvad, J. C., Fryar, S. C., Gabaldón, T., Gajanayake, A. J., Galindo, L. J., Gannibal, P. B., García, D., García-Sandoval, S. R., Garrido-Benavent, I., Garzoli, L., Gautam, A. K., Ge, Z. W., Gené, D. J., Gentekaki, E., Ghobad-Nejhad, M., Giachini, A. J., Gibertoni, T. B., Góes-Neto, A., Gomdola, D., de Farias, A. R. Gomes, Gorjón, S. P., Goto, B. T., Granados-Montero, M. M., Griffith, G. W., Groenewald, J. Z., Groenewald, M., Grossart, H. P., Gueidan, C., Gunarathne, A., Gunaseelan, S., Gusmão, L. F.P., Gutierrez, A. C., Guzmán-Dávalos, L., Haelewaters, D., Halling, R., Han, Y. F., Hapuarachchi, K. K., Harder, C. B., Harrington, T. C., Hattori, T., He, M. Q., He, S., He, S. H., Healy, R., Herández-Restrepo, M., Heredia, G., Hodge, K. T., Holgado-Rojas, M., Hongsanan, S., Horak, E., Hosoya, T., Houbraken, J., Huang, S. K., Huanraluek, N., Hur, J. S., Hurdeal, V. G., Hustad, V. P., Iotti, M., Iturriaga, T., Jafar, E., Janik, P., Jany, J. L., Jayalal, R. G.U., Jayasiri, S. C., Jayawardena, R. S., Jeewon, R., Jerônimo, G. H., Jesus, A. L., Jin, J., Johnston, P. R., Jones, E. B.G., Joshi, Y., Justo, A., Kaishian, P., Kakishima, M., Kaliyaperumal, M., Kang, G. P., Kang, J. C., Karakehian, J. M., Karimi, O., Karpov, S. A., Karunarathna, S. C., Kaufmann, M., Kemler, M., Kezo, K., Khyaju, S., Kirchmair, M., Kirk, P. M., Kitaura, M. J., Klawonn, I., Kolarik, M., Kong, A., Kuhar, F., Kukwa, M., Kumar, S., Kušan, I., Lado, C., Larsson, K. H., Latha, K. P.D., Lee, H. B., Leonardi, M., Leontyev, D. L., Lestari, A. S., Li, C. J.Y., Li, D. W., Li, H. Y., Li, L., Li, Q. R., Li, W. L., Li, Y., Li, Y. C., Liao, C. F., Liimatainen, K., Lim, Y. W., Lin, C. G., Linaldeddu, B. T., Linde, C. C., Linn, M. M., Liu, F., Liu, J. K., Liu, N. G., Liu, S., Liu, X. F., Liu, X. Z., Liu, Z. B., Lu, L., Lu, Y. Z., Luangharn, T., Luangsa-ard, J. J., Lumbsch, H. T., Lumyong, S., Luo, L., Luo, M., Luo, Z. L., Ma, J., Machado, A. R., Madagammana, A. D., Madrid, H., Magurno, F., Magyar, D., Mahadevan, N., Maharachchikumbura, S. S.N., Maimaiti, Y., Malosso, E., Manamgoda, D. S., Manawasinghe, I. S., Mapook, A., Marasinghe, D. S., Mardones, M., Marin-Felix, Y., Márquez, R., Masigol, H., Matočec, N., May, T. W., McKenzie, E. H.C., Meiras-Ottoni, A., Melo, R. F.R., Mendes-Alvarenga, R. L., Mendieta, S., Meng, Q. F., Menkis, A., Menolli, N., Mešić, A., Calvo, J. G.Meza, Mikhailov, K. V., Miller, S. L., Moncada, B., Moncalvo, J. M., Monteiro, J. S., Monteiro, M., Mora-Montes, H. M., Moreau, P. A., Mueller, G. M., Mukhopadyay, S., Murugadoss, R., Nagy, L. G., Najafiniya, M., Nanayakkara, C. M., Nascimento, C. C., Nei, Y., Neves, M. A., Neuhauser, S., Niego, A. G.T., Nilsson, R. H., Niskanen, T., Niveiro, N., Noorabadi, M. T., Noordeloos, M. E., Norphanphoun, C., Otaño, N. B.Nuñez, O’Donnell, R. P., Oehl, F., Olariaga, I., Orlando, O. P., Pang, K. L., Papp, V., Pawłowska, J., Peintner, U., Pem, D., Pereira, O. L., Perera, R. H., Perez-Moreno, J., Perez-Ortega, S., Péter, G., Phillips, A. J.L., Phonemany, M., Phukhamsakda, C., Phutthacharoen, K., Piepenbring, M., Pires-Zottarelli, C. L.A., Poinar, G., Pošta, A., Prieto, M., Promputtha, I., Quandt, C. A., Radek, R., Rahnama, K., Raj, K. N.A., Rajeshkumar, K. C., Rämä, T., Rambold, G., Ramírez-Cruz, V., Rasconi, S., Rathnayaka, A. R., Raza, M., Ren, G. C., Robledo, G. L., Rodriguez-Flakus, P., Ronikier, A., Rossi, W., Ryberg, M., Ryvarden, L. R., Salvador-Montoya, C. A., Samant, B., Samarakoon, B. C., Samarakoon, M. C., Sánchez-Castro, I., Sánchez-García, M., Sandoval-Denis, M., Santamaria, B., Santiago, A. L.C.M.A., Sarma, V. V., Savchenko, A., Savchenko, K., Saxena, R. K., Scholler, M., Schoutteten, N., Seifollahi, E., Selbmann, L., Selcuk, F., Senanayake, I. C., Shabashova, T. G., Shen, H. W., Shen, Y. M., Silva-Filho, A. G.S., Simmons, D. R., Singh, R., Sir, E. B., Song, C. G., Souza-Motta, C. M., Sruthi, O. P., Stadler, M., Stchigel, A. M., Stemler, J., Stephenson, S. L., Strassert, J. F.H., Su, H. L., Su, L., Suetrong, S., Sulistyo, B., Sun, Y. R., Svantesson, S., Sysouphanthong, P., Takamatsu, S., Tan, T. H., Tanaka, K., Tang, A. M.C., Tang, X., Tanney, J. B., Tavakol, N. M., Taylor, J. E., Taylor, P. W.J., Tedersoo, L., Tennakoon, D. S., Thamodini, G. K., Thines, M., Thiyagaraja, V., Thongklang, N., Tiago, P. V., Tian, Q., Tian, W. H., Tibell, L., Tibell, S., Tibpromma, S., Tkalčec, Z., Tomšovský, M., Toome-Heller, M., Torruella, G., Tsurykau, A., Udayanga, D., Ulukapi, M., Untereiner, W. A., Uzunov, B. A., Valle, L. G., Van Caenegem, W., Van den Wyngaert, S., Van Vooren, N., Velez, P., Verma, R. K., Vieira, L. C., Vieira, W. A.S., Vizzini, A., Walker, A., Walker, A. K., Wanasinghe, D. N., Wang, C. G., Wang, K., Wang, S. X., Wang, X. Y., Wang, Y., Wannasawang, N., Wartchow, F., Wei, D. P., Wei, X. L., White, J. F., Wijayawardene, N. N., Wijesinghe, S. N., Wijesundara, D. S.A., Wisitrassameewong, K., Worthy, F. R., Wu, F., Wu, G., Wu, H. X., Wu, N., Wu, W. P., Wurzbacher, C., Xiao, Y. P., Xiong, Y. R., Xu, B., Xu, L. J., Xu, R., Xu, T. M., Yakovchenko, L., Yan, J. Y., Yang, H. D., Yang, J., Yang, Z. L., Yang, Y. H., Yapa, N., Yasanthika, E., Youssef, N. H., Yu, F. M., Yu, Q., Yu, X. D., Yu, Y. X., Yu, Z. F., Yuan, H. S., Yuan, Y., Yurkov, A., Zafari, D., Zamora, J. C., Zare, R., Zeng, M., Zeng, N. K., Zeng, X. Y., Zhang, F., Zhang, H., Zhang, J. F., Zhang, J. Y., Zhang, Q. Y., Zhang, S. N., Zhang, W., Zhang, Y., Zhao, C. L., Zhao, H., Zhao, Q., Zhao, R. L., Zhou, L. W., Zhou, M., Zhurbenko, M. P., Zin, H. H., Zucconi, L., Hyde, K. D., Abdel-Wahab, M. A., Abdollahzadeh, J., Abeywickrama, P. D., Absalan, S., Afshari, N., Ainsworth, A. M., Akulov, O. Y., Aleoshin, V. V., Al-Sadi, A. M., Alvarado, P., Alves, A., Alves-Silva, G., Amalfi, M., Amira, Y., Amuhenage, T. B., Anderson, J. L., Antonín, V., Aouali, S., Aptroot, A., Apurillo, C. C. S., Araújo, J. P.M., Ariyawansa, H. A., Armand, A., Arumugam, E., Asghari, R., Assis, D. M.A., Atienza, V., Avasthi, S., Azevedo, E., Bahkali, A. H., Bakhshi, M., Banihashemi, Z., Bao, D. F., Baral, H. O., Barata, M., Barbosa, F. R., Barbosa, R. N., Barreto, R. W., Baschien, C., Belamesiatseva, D. B., Reuel, M. Bennett, Bera, I., Bezerra, J. D. P., Bezerra, J. L., Bhat, D. J., Bhunjun, C. S., Bianchinotti, M. V., Błaszkowski, J., Blondelle, A., Boekhout, T., Bonito, G., Boonmee, S., Boonyuen, N., Bregant, C., Buchanan, P., Bundhun, D., Burgaud, G., Burgess, T., Buyck, B., Cabarroi-Hernández, M., Cáceres, M. E. S., Caeiro, M. F., Cai, L., Cai, M. F., Calabon, M. S., Calaça, F. J. S., Callalli, M., Camara, M. P. S., Cano-Lira, J. F., Cantillo, T., Cao, B., Carlavilla, J. R., Carvalho, A., Castañeda-Ruiz, R. F., Castlebury, L., Castro-Jauregui, O., Catania, M. D., Cavalcanti, L. H., Cazabonne, J., Cedeño-Sanchez, M. L., Chaharmiri-Dokhaharani, S., Chaiwan, N., Chakraborty, N., Chaverri, P., Cheewangkoon, R., Chen, C., Chen, C. Y., Chen, K. H., Chen, J., Chen, Q., Chen, W. H., Chen, Y. P., Chethana, K. W. T., Coleine, C., Condé, T. O., Corazon-Guivin, M. A., Cortés-Pérez, A., Costa-Rezende, D. H., Courtecuisse, R., Crouch, J. A., Crous, P. W., Cui, B. K., Cui, Y. Y., da Silva, D. K. A., da Silva, G. A., da Silva, I. R., da Silva, R. M. F., da Silva Santos, A. C., Dai, D. Q., Dai, Y. C., Damm, U., Darmostuk, V., Zoha, Daroodi, Das, K., Davoodian, N., Davydov, E. A., Dayarathne, M. C., Decock, C., de Groot, M. D., De Kesel, A., de la Cruz, T. E. E., De Lange, R., Delgado, G., Denchev, C. M., Denchev, T. T., de Oliveira, N. T., de Silva, N. I., de Souza, F. A., Dentinger, B., Devadatha, B., Dianese, J. C., Dima, B., Diniz, A. G., Dissanayake, A. J., Dissanayake, L. S., Doğan, H. H., Doilom, M., Dolatabadi, S., Dong, W., Dong, Z. Y., Dos Santos, L. A., Drechsler-Santos, E. R., Du, T. Y., Dubey, M. K., Dutta, A. K., Egidi, E., Elliott, T. F., Elshahed, M. S., Erdoğdu, M., Ertz, D., Etayo, J., Evans, H. C., Fan, X. L., Fan, Y. G., Fedosova, A. G., Fell, J., Fernandes, I., Firmino, A. L., Fiuza, P. O., Flakus, A., de Souza, C. A.Fragoso, Frisvad, J. C., Fryar, S. C., Gabaldón, T., Gajanayake, A. J., Galindo, L. J., Gannibal, P. B., García, D., García-Sandoval, S. R., Garrido-Benavent, I., Garzoli, L., Gautam, A. K., Ge, Z. W., Gené, D. J., Gentekaki, E., Ghobad-Nejhad, M., Giachini, A. J., Gibertoni, T. B., Góes-Neto, A., Gomdola, D., de Farias, A. R. Gomes, Gorjón, S. P., Goto, B. T., Granados-Montero, M. M., Griffith, G. W., Groenewald, J. Z., Groenewald, M., Grossart, H. P., Gueidan, C., Gunarathne, A., Gunaseelan, S., Gusmão, L. F.P., Gutierrez, A. C., Guzmán-Dávalos, L., Haelewaters, D., Halling, R., Han, Y. F., Hapuarachchi, K. K., Harder, C. B., Harrington, T. C., Hattori, T., He, M. Q., He, S., He, S. H., Healy, R., Herández-Restrepo, M., Heredia, G., Hodge, K. T., Holgado-Rojas, M., Hongsanan, S., Horak, E., Hosoya, T., Houbraken, J., Huang, S. K., Huanraluek, N., Hur, J. S., Hurdeal, V. G., Hustad, V. P., Iotti, M., Iturriaga, T., Jafar, E., Janik, P., Jany, J. L., Jayalal, R. G.U., Jayasiri, S. C., Jayawardena, R. S., Jeewon, R., Jerônimo, G. H., Jesus, A. L., Jin, J., Johnston, P. R., Jones, E. B.G., Joshi, Y., Justo, A., Kaishian, P., Kakishima, M., Kaliyaperumal, M., Kang, G. P., Kang, J. C., Karakehian, J. M., Karimi, O., Karpov, S. A., Karunarathna, S. C., Kaufmann, M., Kemler, M., Kezo, K., Khyaju, S., Kirchmair, M., Kirk, P. M., Kitaura, M. J., Klawonn, I., Kolarik, M., Kong, A., Kuhar, F., Kukwa, M., Kumar, S., Kušan, I., Lado, C., Larsson, K. H., Latha, K. P.D., Lee, H. B., Leonardi, M., Leontyev, D. L., Lestari, A. S., Li, C. J.Y., Li, D. W., Li, H. Y., Li, L., Li, Q. R., Li, W. L., Li, Y., Li, Y. C., Liao, C. F., Liimatainen, K., Lim, Y. W., Lin, C. G., Linaldeddu, B. T., Linde, C. C., Linn, M. M., Liu, F., Liu, J. K., Liu, N. G., Liu, S., Liu, X. F., Liu, X. Z., Liu, Z. B., Lu, L., Lu, Y. Z., Luangharn, T., Luangsa-ard, J. J., Lumbsch, H. T., Lumyong, S., Luo, L., Luo, M., Luo, Z. L., Ma, J., Machado, A. R., Madagammana, A. D., Madrid, H., Magurno, F., Magyar, D., Mahadevan, N., Maharachchikumbura, S. S.N., Maimaiti, Y., Malosso, E., Manamgoda, D. S., Manawasinghe, I. S., Mapook, A., Marasinghe, D. S., Mardones, M., Marin-Felix, Y., Márquez, R., Masigol, H., Matočec, N., May, T. W., McKenzie, E. H.C., Meiras-Ottoni, A., Melo, R. F.R., Mendes-Alvarenga, R. L., Mendieta, S., Meng, Q. F., Menkis, A., Menolli, N., Mešić, A., Calvo, J. G.Meza, Mikhailov, K. V., Miller, S. L., Moncada, B., Moncalvo, J. M., Monteiro, J. S., Monteiro, M., Mora-Montes, H. M., Moreau, P. A., Mueller, G. M., Mukhopadyay, S., Murugadoss, R., Nagy, L. G., Najafiniya, M., Nanayakkara, C. M., Nascimento, C. C., Nei, Y., Neves, M. A., Neuhauser, S., Niego, A. G.T., Nilsson, R. H., Niskanen, T., Niveiro, N., Noorabadi, M. T., Noordeloos, M. E., Norphanphoun, C., Otaño, N. B.Nuñez, O’Donnell, R. P., Oehl, F., Olariaga, I., Orlando, O. P., Pang, K. L., Papp, V., Pawłowska, J., Peintner, U., Pem, D., Pereira, O. L., Perera, R. H., Perez-Moreno, J., Perez-Ortega, S., Péter, G., Phillips, A. J.L., Phonemany, M., Phukhamsakda, C., Phutthacharoen, K., Piepenbring, M., Pires-Zottarelli, C. L.A., Poinar, G., Pošta, A., Prieto, M., Promputtha, I., Quandt, C. A., Radek, R., Rahnama, K., Raj, K. N.A., Rajeshkumar, K. C., Rämä, T., Rambold, G., Ramírez-Cruz, V., Rasconi, S., Rathnayaka, A. R., Raza, M., Ren, G. C., Robledo, G. L., Rodriguez-Flakus, P., Ronikier, A., Rossi, W., Ryberg, M., Ryvarden, L. R., Salvador-Montoya, C. A., Samant, B., Samarakoon, B. C., Samarakoon, M. C., Sánchez-Castro, I., Sánchez-García, M., Sandoval-Denis, M., Santamaria, B., Santiago, A. L.C.M.A., Sarma, V. V., Savchenko, A., Savchenko, K., Saxena, R. K., Scholler, M., Schoutteten, N., Seifollahi, E., Selbmann, L., Selcuk, F., Senanayake, I. C., Shabashova, T. G., Shen, H. W., Shen, Y. M., Silva-Filho, A. G.S., Simmons, D. R., Singh, R., Sir, E. B., Song, C. G., Souza-Motta, C. M., Sruthi, O. P., Stadler, M., Stchigel, A. M., Stemler, J., Stephenson, S. L., Strassert, J. F.H., Su, H. L., Su, L., Suetrong, S., Sulistyo, B., Sun, Y. R., Svantesson, S., Sysouphanthong, P., Takamatsu, S., Tan, T. H., Tanaka, K., Tang, A. M.C., Tang, X., Tanney, J. B., Tavakol, N. M., Taylor, J. E., Taylor, P. W.J., Tedersoo, L., Tennakoon, D. S., Thamodini, G. K., Thines, M., Thiyagaraja, V., Thongklang, N., Tiago, P. V., Tian, Q., Tian, W. H., Tibell, L., Tibell, S., Tibpromma, S., Tkalčec, Z., Tomšovský, M., Toome-Heller, M., Torruella, G., Tsurykau, A., Udayanga, D., Ulukapi, M., Untereiner, W. A., Uzunov, B. A., Valle, L. G., Van Caenegem, W., Van den Wyngaert, S., Van Vooren, N., Velez, P., Verma, R. K., Vieira, L. C., Vieira, W. A.S., Vizzini, A., Walker, A., Walker, A. K., Wanasinghe, D. N., Wang, C. G., Wang, K., Wang, S. X., Wang, X. Y., Wang, Y., Wannasawang, N., Wartchow, F., Wei, D. P., Wei, X. L., White, J. F., Wijayawardene, N. N., Wijesinghe, S. N., Wijesundara, D. S.A., Wisitrassameewong, K., Worthy, F. R., Wu, F., Wu, G., Wu, H. X., Wu, N., Wu, W. P., Wurzbacher, C., Xiao, Y. P., Xiong, Y. R., Xu, B., Xu, L. J., Xu, R., Xu, T. M., Yakovchenko, L., Yan, J. Y., Yang, H. D., Yang, J., Yang, Z. L., Yang, Y. H., Yapa, N., Yasanthika, E., Youssef, N. H., Yu, F. M., Yu, Q., Yu, X. D., Yu, Y. X., Yu, Z. F., Yuan, H. S., Yuan, Y., Yurkov, A., Zafari, D., Zamora, J. C., Zare, R., Zeng, M., Zeng, N. K., Zeng, X. Y., Zhang, F., Zhang, H., Zhang, J. F., Zhang, J. Y., Zhang, Q. Y., Zhang, S. N., Zhang, W., Zhang, Y., Zhao, C. L., Zhao, H., Zhao, Q., Zhao, R. L., Zhou, L. W., Zhou, M., Zhurbenko, M. P., Zin, H. H., and Zucconi, L.

Abstract

The Global Consortium for the Classification of Fungi and fungus-like taxa is an international initiative of more than 550 mycologists to develop an electronic structure for the classification of these organisms. The members of the Consortium originate from 55 countries/regions worldwide, from a wide range of disciplines, and include senior, mid-career and early-career mycologists and plant pathologists. The Consortium will publish a biannual update of the Outline of Fungi and fungus-like taxa, to act as an international scheme for other scientists. Notes on all newly published taxa at or above the level of species will be prepared and published online on the Outline of Fungi website (https://www.outlineoffungi.org/), and these will be finally published in the biannual edition of the Outline of Fungi and fungus-like taxa. Comments on recent important taxonomic opinions on controversial topics will be included in the biannual outline. For example, 'to promote a more stable taxonomy in Fusarium given the divergences over its generic delimitation', or 'are there too many genera in the Boletales?' and even more importantly, 'what should be done with the tremendously diverse 'dark fungal taxa?' There are undeniable differences in mycologists' perceptions and opinions regarding species classification as well as the establishment of new species. Given the pluralistic nature of fungal taxonomy and its implications for species concepts and the nature of species, this consortium aims to provide a platform to better refine and stabilise fungal classification, taking into consideration views from different parties. In the future, a confidential voting system will be set up to gauge the opinions of all mycologists in the Consortium on important topics. The results of such surveys will be presented to the International Commission on the Taxonomy of Fungi (ICTF) and the Nomenclature Committee

Published
2023

19. Operators associated with lattice-valued multiset finite automata.

Author

Dhingra, Mallika, Dubey, M. K., Singh, Vivek, and Singh, Anand P.

Subjects
*FINITE state machines, *RESIDUATED lattices, *HOMOMORPHISMS
Abstract

The purpose of this work is to introduce different operators related to A-valued multiset finite automata (LMFA), where A is complete residuated lattice. Specially, we introduce (A-valued) source and (A-valued) successor operators associated with LMFA and investigate their properties. Furthermore, we characterize the A-valued subsystems and A-valued operators under a homomorphism. [ABSTRACT FROM AUTHOR]

Published
2023
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20. Nondifferentiable multiobjective semi-infinite programming problems under higher-order convexity.

Author

Singh, Vivek, Shekhawat, Neelima, and Dubey, M. K.

Subjects
SUBDIFFERENTIALS
Abstract

The present paper is framed to focus on a nondifferentiable multiobjective semi-infinite programming problem and to establish sufficient optimality conditions from the standpoint of higher-order convexity and Clarke's subdifferentials assumptions. These optimality conditions are illustrated by a nontrivial example. Subsequently, weak, strong and strict converse duality theorems are established in order to relate the strict minimizer (maximizer) of order m of primal and mixed type multiobjective dual model. [ABSTRACT FROM AUTHOR]

Published
2023
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29. Plankton Diversity in a Fish Pond of Godda District (Santal Pargana), Jharkhand.

Author

KANT, SHASHI, DUBEY, M. K., and MANDAL, N. K.

Subjects
PLANKTON, FISH ponds, CYANOBACTERIA, ZOOPLANKTON, SPECIES diversity
Abstract

The study on seasonal variation of phytoplankton and zooplankton community was conducted in a perennial fish pond of Godda district during January-December 2018. Cyanophyceae constituted dominant group among phytoplankton (66.2-73.7%) during winter months (December-January) with highest species diversity (1.88-2.23 bits/cell) and evenness (1.02-1.06) suggested to be more stable group among phytoplankton. Zooplankton were dominated by Rotifers members (64.2-68.5%) during summer months (April-May) with maximum species diversity (1.29-1.56 bits/cell) and evenness (0.93-0.99). Species diversity showed significant relation with evenness and number of species. Variation in diversity index was mainly due to increase or decrease in number of species in specific group of phyto and zooplankton. The influence of certain physical and chemical factor on plankton distribution has been well established. [ABSTRACT FROM AUTHOR]

Published
2022

30. On the categories of L-Valued and Q-Valued deterministic fuzzy automata

Author

Dubey, M. K., Tiwari, S. P., Kavikumar, J., Dubey, M. K., Tiwari, S. P., and Kavikumar, J.

Abstract

Automata and languages have been studied in the context of different lattice structures by several authors. This paper is toward the categorical study of deterministic lattice-valued (L-valued) fuzzy automata and deterministic quantale-valued (Q-valued) 26 fuzzy automata. The existence of initial and final objects in the subcategory of category of deterministic lattice-valued fuzzy automata is shown. We also show that there is an adjunction between the category of deterministic lattice-valued and quantale-valued fuzzy automata.

Published
2021

31. On the categories of L-Valued and Q-Valued 6 deterministic fuzzy automata

Author

Dubey, M. K., Tiwari, S. P., Kavikumar, J., Dubey, M. K., Tiwari, S. P., and Kavikumar, J.

Abstract

Automata and languages have been studied in the context of different lattice structures by several authors. This paper is toward the categorical study of deterministic lattice-valued (L-valued) fuzzy automata and deterministic quantale-valued (Q-valued) fuzzy automata. The existence of initial and final objects in the subcategory of category of deterministic lattice-valued fuzzy automata is shown. We also show that there is an adjunction between the category of deterministic lattice-valued and quantale-valued fuzzy automata.

Published
2021

34. Overview of the 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES)

Author

Zaveri, R. A, Shaw, W. J, Cahill, J. F, Cairns, Brian, Cappa, C. D, Ottaviani, Matteo, Cziczo, D. J, Ferrare, Richard A, Alexander, M. L, Alexandrov, Mikhail Dmitrievic, Alvarez, R. J, Arnott, W. P, Atkinson, D. B, Schmid, B, Chand, D, China, S, Comstock, J. M, Dubey, M. K, Easter, R. C, Erickson, M. H, Fast, J. D, Flowers, B. A, Fortner, E, Baidar, S, Hair, J, Hostetler, C, Obland, M. D, Rogers, R. R, Floerchinger, C, Banta, R. M, Barnard, J. C, Beranek, J, Berg, L. K, Brechtel, F, and Brewer, W. A

Subjects
Environment Pollution, Meteorology And Climatology
Abstract

Substantial uncertainties still exist in the scientific understanding of the possible interactions between urban and natural (biogenic) emissions in the production and transformation of atmospheric aerosol and the resulting impact on climate change. The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Carbonaceous Aerosol and Radiative Effects Study (CARES) carried out in June 2010 in Central Valley, California, was a comprehensive effort designed to improve this understanding. The primary objective of the field study was to investigate the evolution of secondary organic and black carbon aerosols and their climate-related properties in the Sacramento urban plume as it was routinely transported into the forested Sierra Nevada foothills area. Urban aerosols and trace gases experienced significant physical and chemical transformations as they mixed with the reactive biogenic hydrocarbons emitted from the forest. Two heavily-instrumented ground sites - one within the Sacramento urban area and another about 40 km to the northeast in the foothills area - were set up to characterize the evolution of meteorological variables, trace gases, aerosol precursors, aerosol size, composition, and climaterelated properties in freshly polluted and "aged" urban air. On selected days, the DOE G-1 aircraft was deployed to make similar measurements upwind and across the evolving Sacramento plume in the morning and again in the afternoon. The NASA B-200 aircraft, carrying remote sensing instruments, was also deployed to characterize the vertical and horizontal distribution of aerosols and aerosol optical properties within and around the plume. This overview provides: (a) the scientific background and motivation for the study, (b) the operational and logistical information pertinent to the execution of the study, (c) an overview of key observations and initial findings from the aircraft and ground-based sampling platforms, and (d) a roadmap of planned data analyses and focused modeling efforts that will facilitate the integration of new knowledge into improved representations of key aerosol processes and properties in climate models.

Published
2012
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37. Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) X$_{CO_{2}}$ measurements with TCCON

Author

Wunch, D., Wennberg, P. O., Osterman, G., Fisher, B., Naylor, B., Roehl, M. C., O’Dell, C., Mandrake, L., Viatte, C., Kiel, M., Griffith, D. W. T., Deutscher, N. M., Velazco, V. A., Notholt, J., Warneke, T., Petri, C., Maziere, M. De, Sha, M. K., Sussmann, R., Rettinger, M., Pollard, D., Robinson, J., Morino, I., Uchino, O., Hase, F., Blumenstock, T., Feist, D. G., Arnold, S. G., Strong, K., Mendonca, J., Kivi, R., Heikkinen, P., Iraci, L., Podolske, J., Hillyard, P., Kawakami, S., Dubey, M. K., Parker, H. A., Sepulveda, E., García, O. E., Te, Y., Jeseck, P., Gunson, M. R., Crisp, D., and Eldering, A.

Subjects
Earth sciences, ddc:550
Abstract

NASA's Orbiting Carbon Observatory-2 (OCO-2) has been measuring carbon dioxide column-averaged dry-air mole fraction, X$_{CO_{2}}$, in the Earth's atmosphere for over 2 years. In this paper, we describe the comparisons between the first major release of the OCO-2 retrieval algorithm (B7r) and X$_{CO_{2}}$ from OCO-2's primary ground-based validation network: the Total Carbon Column Observing Network (TCCON). The OCO-2 X$_{CO_{2}}$ retrievals, after filtering and bias correction, agree well when aggregated around and coincident with TCCON data in nadir, glint, and target observation modes, with absolute median differences less than 0.4 ppm and RMS differences less than 1.5 ppm. After bias correction, residual biases remain. These biases appear to depend on latitude, surface properties, and scattering by aerosols. It is thus crucial to continue measurement comparisons with TCCON to monitor and evaluate the OCO-2 X$_{CO_{2}}$ data quality throughout its mission.

Published
2017
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39. Ability of the 4-D-Var analysis of the GOSAT BESD XCO₂ retrievals to characterize atmospheric CO₂ at large and synoptic scales

Author

Massart, S., Agusti-Panareda, A., Heymann, J., Buchwitz, M., Chevallier, F., Reuter, M., Hilker, M., Burrows, J. P., Deutscher, N. M., Feist, D. G., Hase, F., Sussmann, R., Desmet, F., Dubey, M. K., Griffith, D. W. T., Kivi, R., Petri, C., Schneider, M., and Velazco, V. A.

Subjects
Earth sciences, ddc:550
Abstract

This study presents results from the European Centre for Medium-Range Weather Forecasts (ECMWF) carbon dioxide (CO₂) analysis system where the atmospheric CO₂ is controlled through the assimilation of column-averaged dry-air mole fractions of CO₂ (XCO₂) from the Greenhouse gases Observing Satellite (GOSAT). The analysis is compared to a free-run simulation (without assimilation of XCO₂), and they are both evaluated against XCO₂ data from the Total Carbon Column Observing Network (TCCON). We show that the assimilation of the GOSAT XCO₂ product from the Bremen Optimal Estimation Differential Optical Absorption Spectroscopy (BESD) algorithm during the year 2013 provides XCO₂ fields with an improved mean absolute error of 0.6 parts per million (ppm) and an improved station-to-station bias deviation of 0.7 ppm compared to the free run (1.1 and 1.4 ppm, respectively) and an improved estimated precision of 1 ppm compared to the GOSAT BESD data (3.3 ppm). We also show that the analysis has skill for synoptic situations in the vicinity of frontal systems, where the GOSAT retrievals are sparse due to cloud contamination. We finally computed the 10-day forecast from each analysis at 00:00 UTC, and we demonstrate that the CO₂ forecast shows synoptic skill for the largest-scale weather patterns (of the order of 1000 km) even up to day 5 compared to its own analysis.

Published
2016

40. Consistent satellite XCO₂ retrievals from SCIAMACHY and GOSAT using the BESD algorithm

Author

Heymann, J., Reuter, M., Hilker, M., Buchwitz, M., Schneising, O., Bovensmann, H., Burrows, J. P., Kuze, A., Suto, H., Deutscher, N. M., Dubey, M. K., Griffith, D. W. T., Hase, F., Kawakami, S., Kivi, R., Morino, I., Petri, C., Roehl, C., Schneider, M., Sherlock, V., Sussmann, R., Velazco, V. A., Warneke, T., and Wunsch, D.

Subjects
Earth sciences, ddc:550
Published
2015

42. Study of the footprints of short-term variation in XCO2 observed by TCCON sites using NIES and FLEXPART atmospheric transport models

Author

Belikov, D. A., primary, Maksyutov, S., additional, Ganshin, A., additional, Zhuravlev, R., additional, Deutscher, N. M., additional, Wunch, D., additional, Feist, D. G., additional, Morino, I., additional, Parker, R. J., additional, Strong, K., additional, Yoshida, Y., additional, Bril, A., additional, Oshchepkov, S., additional, Boesch, H., additional, Dubey, M. K., additional, Griffith, D., additional, Hewson, W., additional, Kivi, R., additional, Mendonca, J., additional, Notholt, J., additional, Schneider, M., additional, Sussmann, R., additional, Velazco, V., additional, and Aoki, S., additional

Published
2016
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43. Wintertime aerosol chemical composition, volatility, and spatial variability in the greater London area

Author

Xu, L., primary, Williams, L. R., additional, Young, D. E., additional, Allan, J. D., additional, Coe, H., additional, Massoli, P., additional, Fortner, E., additional, Chhabra, P., additional, Herndon, S., additional, Brooks, W. A., additional, Jayne, J. T., additional, Worsnop, D. R., additional, Aiken, A. C., additional, Liu, S., additional, Gorkowski, K., additional, Dubey, M. K., additional, Fleming, Z. L., additional, Visser, S., additional, Prévôt, A. S. H., additional, and Ng, N. L., additional

Published
2016
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44. Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data

Author

Turner, A J, Jacob, Daniel J, Wecht, K J, Maasakkers, J D, Lundgren, E, Andrews, A E, Biraud, S C, Boesch, Hartmut, Bowman, K W, Deutscher, Nicholas M, Dubey, M K, Griffith, David W. T, Hase, Frank, Kuze, A, Notholt, Justus, Ohyama, H, Parker, Robert J, Payne, V H, Sussmann, Ralf, Sweeney, C, Velazco, Voltaire A, Warneke, Thorsten, Wennberg, Paul O, Wunch, Debra, Turner, A J, Jacob, Daniel J, Wecht, K J, Maasakkers, J D, Lundgren, E, Andrews, A E, Biraud, S C, Boesch, Hartmut, Bowman, K W, Deutscher, Nicholas M, Dubey, M K, Griffith, David W. T, Hase, Frank, Kuze, A, Notholt, Justus, Ohyama, H, Parker, Robert J, Payne, V H, Sussmann, Ralf, Sweeney, C, Velazco, Voltaire A, Warneke, Thorsten, Wennberg, Paul O, and Wunch, Debra

Abstract

We use 2009-2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to estimate global and North American methane emissions with 4° x 5° and up to 50 km x 50 km spatial resolution, respectively. GEOS-Chem and GOSAT data are first evaluated with atmospheric methane observations from surface and tower networks (NOAA/ESRL, TCCON) and aircraft (NOAA/ESRL, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. Our global adjoint-based inversion yields a total methane source of 539 Tg a−1 with some important regional corrections to the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide error characterization. We infer a US anthropogenic methane source of 40.2-42.7 Tg a−1, as compared to 24.9-27.0 Tg a−1 in the EDGAR and EPA bottom-up inventories, and 30.0-44.5 Tg a−1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the southern-central US, the Central Valley of California, and Florida wetlands; large isolated point sources such as the US Four Corners also contribute. Using prior information on source locations, we attribute 29-44 % of US anthropogenic methane emissions to livestock, 22-31 % to oil/gas, 20 % to landfills/wastewater, and 11-15 % to coal. Wetlands contribute an additional 9.0-10.1 Tg a−1.

Published
2015

45. Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm

Author

Heymann, J, Reuter, Markus, Hilker, M, Buchwitz, M, Schneising, O, Bovensmann, H, Burrows, J P, Kuze, A, Suto, H, Deutscher, Nicholas M, Dubey, M K, Griffith, David W. T, Hase, Frank, Kawakami, S, Kivi, Rigel, Morino, Isamu, Petri, Christof, Roehl, Coleen M, Schneider, Matthias, Sherlock, Vanessa, Sussmann, Ralf, Velazco, Voltaire A, Warneke, Thorsten, Wunch, Debra, Heymann, J, Reuter, Markus, Hilker, M, Buchwitz, M, Schneising, O, Bovensmann, H, Burrows, J P, Kuze, A, Suto, H, Deutscher, Nicholas M, Dubey, M K, Griffith, David W. T, Hase, Frank, Kawakami, S, Kivi, Rigel, Morino, Isamu, Petri, Christof, Roehl, Coleen M, Schneider, Matthias, Sherlock, Vanessa, Sussmann, Ralf, Velazco, Voltaire A, Warneke, Thorsten, and Wunch, Debra

Abstract

Consistent and accurate long-term data sets of global atmospheric concentrations of carbon dioxide (CO2) are required for carbon cycle and climate-related research. However, global data sets based on satellite observations may suffer from inconsistencies originating from the use of products derived from different satellites as needed to cover a long enough time period. One reason for inconsistencies can be the use of different retrieval algorithms. We address this potential issue by applying the same algorithm, the Bremen Optimal Estimation DOAS (BESD) algorithm, to different satellite instruments, SCIAMACHY on-board ENVISAT (March 2002-April 2012) and TANSO-FTS on-board GOSAT (launched in January 2009), to retrieve XCO2, the column-averaged dry-air mole fraction of CO2. BESD has been initially developed for SCIAMACHY XCO2 retrievals. Here, we present the first detailed assessment of the new GOSAT BESD XCO2 product. GOSAT BESD XCO2 is a product generated and delivered to the MACC project for assimilation into ECMWF's Integrated Forecasting System. We describe the modifications of the BESD algorithm needed in order to retrieve XCO2 from GOSAT and present detailed comparisons with ground-based observations of XCO2 from the Total Carbon Column Observing Network (TCCON). We discuss detailed comparison results between all three XCO2 data sets (SCIAMACHY, GOSAT and TCCON). The comparison results demonstrate the good consistency between SCIAMACHY and GOSAT XCO2. For example, we found a mean difference for daily averages of −0.60 ± 1.56 ppm (mean difference ± standard deviation) for GOSAT-SCIAMACHY (linear correlation coefficient r=0.82), −0.34 ± 1.37 ppm (r = 0.86) for GOSAT-TCCON and 0.10 ± 1.79 ppm (r = 0.75) for SCIAMACHY-TCCON. The remaining differences between GOSAT and SCIAMACHY are likely due to non-perfect collocation (± 2 h, 10° x 10° around TCCON sites), i.e. the observed air masses are not exactly identical but likely also due to a still non-perfect BESD retriev

Published
2015

46. Signature of a tropical Pacific cyclone in the composition of the upper troposphere over Socorro, NM

Author

Minschwaner, K., primary, Manney, G. L., additional, Petropavlovskikh, I., additional, Torres, L. A., additional, Lawrence, Z. D., additional, Sutherland, B., additional, Thompson, A. M., additional, Johnson, B. J., additional, Butterfield, Z., additional, Dubey, M. K., additional, Froidevaux, L., additional, Lambert, A., additional, Read, W. G., additional, and Schwartz, M. J., additional

Published
2015
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47. Wintertime aerosol chemical composition, volatility, and spatial variability in the greater London area

Author

Xu, L., primary, Williams, L. R., additional, Young, D. E., additional, Allan, J. D., additional, Coe, H., additional, Massoli, P., additional, Fortner, E., additional, Chhabra, P., additional, Herndon, S., additional, Brooks, W. A., additional, Jayne, J. T., additional, Worsnop, D. R., additional, Aiken, A. C., additional, Liu, S., additional, Gorkowski, K., additional, Dubey, M. K., additional, Fleming, Z. L., additional, Visser, S., additional, Prevot, A. S. H., additional, and Ng, N. L., additional

Published
2015
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48. Supplementary material to "Wintertime aerosol chemical composition, volatility, and spatial variability in the greater London area"

Author

Xu, L., primary, Williams, L. R., additional, Young, D. E., additional, Allan, J. D., additional, Coe, H., additional, Massoli, P., additional, Fortner, E., additional, Chhabra, P., additional, Herndon, S., additional, Brooks, W. A., additional, Jayne, J. T., additional, Worsnop, D. R., additional, Aiken, A. C., additional, Liu, S., additional, Gorkowski, K., additional, Dubey, M. K., additional, Fleming, Z. L., additional, Visser, S., additional, Prevot, A. S. H., additional, and Ng, N. L., additional

Published
2015
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50. Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data

Author

Turner, A. J., primary, Jacob, D. J., additional, Wecht, K. J., additional, Maasakkers, J. D., additional, Lundgren, E., additional, Andrews, A. E., additional, Biraud, S. C., additional, Boesch, H., additional, Bowman, K. W., additional, Deutscher, N. M., additional, Dubey, M. K., additional, Griffith, D. W. T., additional, Hase, F., additional, Kuze, A., additional, Notholt, J., additional, Ohyama, H., additional, Parker, R., additional, Payne, V. H., additional, Sussmann, R., additional, Sweeney, C., additional, Velazco, V. A., additional, Warneke, T., additional, Wennberg, P. O., additional, and Wunch, D., additional

Published
2015
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