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Vladimir A. Zubov, Eugene V. Rozanov, and Michael E. Schlesinger

Abstract

A 3D hybrid (H) transport scheme has been developed that consists of the Prather (P) scheme for vertical transport and a semi-Lagrangian (SL) scheme for horizontal transport on a spherical surface. Two tests have also been developed to permit evaluation of the performance of any numerical transport scheme for flows similar to those found in the earth’s atmosphere. In the first test, the 2D distributions of the wind field and the 3D distribution of the chemical species concentration are prescribed analytically and the consistent analytical expression for the species sources and sinks is determined from the constituent continuity equation. The analytical expressions for the winds and source and sink are then used by a numerical scheme to calculate the 3D distribution of the species concentration. Comparison of the numerical distribution with the analytical distribution then allows evaluation of the performance of the numerical scheme. This test has been used to compare the P, SL, and H schemes. The test shows that the SL scheme produces errors up to 6% in species concentration. The P scheme has high accuracy (about 1%) but requires substantial amounts of computer CPU time and memory. The accuracy of the H scheme is higher (better than 1.6%) than that of the SL scheme and is close to that of the P scheme. The H scheme is about nine times faster than the P scheme but does require about three times more memory than the SL scheme. In another test, the P, H, and SL schemes are tested for 2D zonally averaged transport of the conservative species “cloud” by analytically calculated wind velocities. Comparison of the results shows that the H scheme is superior to the SL scheme. It is concluded that the H scheme is a computationally efficient, accurate scheme for simulating the 3D global transport of both conservative and nonconservative species.

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G. Chiodo, L. M. Polvani, D. R. Marsh, A. Stenke, W. Ball, E. Rozanov, S. Muthers, and K. Tsigaridis

Abstract

An accurate quantification of the stratospheric ozone feedback in climate change simulations requires knowledge of the ozone response to increased greenhouse gases. Here, an analysis is presented of the ozone layer response to an abrupt quadrupling of CO2 concentrations in four chemistry–climate models. The authors show that increased CO2 levels lead to a decrease in ozone concentrations in the tropical lower stratosphere, and an increase over the high latitudes and throughout the upper stratosphere. This pattern is robust across all models examined here, although important intermodel differences in the magnitude of the response are found. As a result of the cancellation between the upper- and lower-stratospheric ozone, the total column ozone response in the tropics is small, and appears to be model dependent. A substantial portion of the spread in the tropical column ozone is tied to intermodel spread in upwelling. The high-latitude ozone response is strongly seasonally dependent, and shows increases peaking in late winter and spring of each hemisphere, with prominent longitudinal asymmetries. The range of ozone responses to CO2 reported in this paper has the potential to induce significant radiative and dynamical effects on the simulated climate. Hence, these results highlight the need of using an ozone dataset consistent with CO2 forcing in models involved in climate sensitivity studies.

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Zoe E. Gillett, Julie M. Arblaster, Andrea J. Dittus, Makoto Deushi, Patrick Jöckel, Douglas E. Kinnison, Olaf Morgenstern, David A. Plummer, Laura E. Revell, Eugene Rozanov, Robyn Schofield, Andrea Stenke, Kane A. Stone, and Simone Tilmes

Abstract

Studies have recently reported statistically significant relationships between observed year-to-year spring Antarctic ozone variability and the Southern Hemisphere annular mode and surface temperatures in spring–summer. This study investigates whether current chemistry–climate models (CCMs) can capture these relationships, in particular, the connection between November total column ozone (TCO) and Australian summer surface temperatures, where years with anomalously high TCO over the Antarctic polar cap tend to be followed by warmer summers. The interannual ozone–temperature teleconnection is examined over the historical period in the observations and simulations from the Whole Atmosphere Community Climate Model (WACCM) and nine other models participating in the Chemistry–Climate Model Initiative (CCMI). There is a systematic difference between the WACCM experiments forced with prescribed observed sea surface temperatures (SSTs) and those with an interactive ocean. Strong correlations between TCO and Australian temperatures are only obtained for the uncoupled experiment, suggesting that the SSTs could be important for driving both variations in Australian temperatures and the ozone hole, with no causal link between the two. Other CCMI models also tend to capture this relationship with more fidelity when driven by observed SSTs, although additional research and targeted modeling experiments are required to determine causality and further explore the role of model biases and observational uncertainty. The results indicate that CCMs can reproduce the relationship between spring ozone and summer Australian climate reported in observational studies, suggesting that incorporating ozone variability could improve seasonal predictions; however, more work is required to understand the difference between the coupled and uncoupled simulations.

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Neal Butchart, I. Cionni, V. Eyring, T. G. Shepherd, D. W. Waugh, H. Akiyoshi, J. Austin, C. Brühl, M. P. Chipperfield, E. Cordero, M. Dameris, R. Deckert, S. Dhomse, S. M. Frith, R. R. Garcia, A. Gettelman, M. A. Giorgetta, D. E. Kinnison, F. Li, E. Mancini, C. McLandress, S. Pawson, G. Pitari, D. A. Plummer, E. Rozanov, F. Sassi, J. F. Scinocca, K. Shibata, B. Steil, and W. Tian

Abstract

The response of stratospheric climate and circulation to increasing amounts of greenhouse gases (GHGs) and ozone recovery in the twenty-first century is analyzed in simulations of 11 chemistry–climate models using near-identical forcings and experimental setup. In addition to an overall global cooling of the stratosphere in the simulations (0.59 ± 0.07 K decade−1 at 10 hPa), ozone recovery causes a warming of the Southern Hemisphere polar lower stratosphere in summer with enhanced cooling above. The rate of warming correlates with the rate of ozone recovery projected by the models and, on average, changes from 0.8 to 0.48 K decade−1 at 100 hPa as the rate of recovery declines from the first to the second half of the century. In the winter northern polar lower stratosphere the increased radiative cooling from the growing abundance of GHGs is, in most models, balanced by adiabatic warming from stronger polar downwelling. In the Antarctic lower stratosphere the models simulate an increase in low temperature extremes required for polar stratospheric cloud (PSC) formation, but the positive trend is decreasing over the twenty-first century in all models. In the Arctic, none of the models simulates a statistically significant increase in Arctic PSCs throughout the twenty-first century. The subtropical jets accelerate in response to climate change and the ozone recovery produces a westward acceleration of the lower-stratospheric wind over the Antarctic during summer, though this response is sensitive to the rate of recovery projected by the models. There is a strengthening of the Brewer–Dobson circulation throughout the depth of the stratosphere, which reduces the mean age of air nearly everywhere at a rate of about 0.05 yr decade−1 in those models with this diagnostic. On average, the annual mean tropical upwelling in the lower stratosphere (∼70 hPa) increases by almost 2% decade−1, with 59% of this trend forced by the parameterized orographic gravity wave drag in the models. This is a consequence of the eastward acceleration of the subtropical jets, which increases the upward flux of (parameterized) momentum reaching the lower stratosphere in these latitudes.

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H. W. Barker, G. L. Stephens, P. T. Partain, J. W. Bergman, B. Bonnel, K. Campana, E. E. Clothiaux, S. Clough, S. Cusack, J. Delamere, J. Edwards, K. F. Evans, Y. Fouquart, S. Freidenreich, V. Galin, Y. Hou, S. Kato, J. Li, E. Mlawer, J.-J. Morcrette, W. O'Hirok, P. Räisänen, V. Ramaswamy, B. Ritter, E. Rozanov, M. Schlesinger, K. Shibata, P. Sporyshev, Z. Sun, M. Wendisch, N. Wood, and F. Yang

Abstract

The primary purpose of this study is to assess the performance of 1D solar radiative transfer codes that are used currently both for research and in weather and climate models. Emphasis is on interpretation and handling of unresolved clouds. Answers are sought to the following questions: (i) How well do 1D solar codes interpret and handle columns of information pertaining to partly cloudy atmospheres? (ii) Regardless of the adequacy of their assumptions about unresolved clouds, do 1D solar codes perform as intended?

One clear-sky and two plane-parallel, homogeneous (PPH) overcast cloud cases serve to elucidate 1D model differences due to varying treatments of gaseous transmittances, cloud optical properties, and basic radiative transfer. The remaining four cases involve 3D distributions of cloud water and water vapor as simulated by cloud-resolving models. Results for 25 1D codes, which included two line-by-line (LBL) models (clear and overcast only) and four 3D Monte Carlo (MC) photon transport algorithms, were submitted by 22 groups. Benchmark, domain-averaged irradiance profiles were computed by the MC codes. For the clear and overcast cases, all MC estimates of top-of-atmosphere albedo, atmospheric absorptance, and surface absorptance agree with one of the LBL codes to within ±2%. Most 1D codes underestimate atmospheric absorptance by typically 15–25 W m–2 at overhead sun for the standard tropical atmosphere regardless of clouds.

Depending on assumptions about unresolved clouds, the 1D codes were partitioned into four genres: (i) horizontal variability, (ii) exact overlap of PPH clouds, (iii) maximum/random overlap of PPH clouds, and (iv) random overlap of PPH clouds. A single MC code was used to establish conditional benchmarks applicable to each genre, and all MC codes were used to establish the full 3D benchmarks. There is a tendency for 1D codes to cluster near their respective conditional benchmarks, though intragenre variances typically exceed those for the clear and overcast cases. The majority of 1D codes fall into the extreme category of maximum/random overlap of PPH clouds and thus generally disagree with full 3D benchmark values. Given the fairly limited scope of these tests and the inability of any one code to perform extremely well for all cases begs the question that a paradigm shift is due for modeling 1D solar fluxes for cloudy atmospheres.

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M. Ades, R. Adler, Rob Allan, R. P. Allan, J. Anderson, Anthony Argüez, C. Arosio, J. A. Augustine, C. Azorin-Molina, J. Barichivich, J. Barnes, H. E. Beck, Andreas Becker, Nicolas Bellouin, Angela Benedetti, David I. Berry, Stephen Blenkinsop, Olivier. Bock, Michael G. Bosilovich, Olivier. Boucher, S. A. Buehler, Laura. Carrea, Hanne H. Christiansen, F. Chouza, John R. Christy, E.-S. Chung, Melanie Coldewey-Egbers, Gil P. Compo, Owen R. Cooper, Curt Covey, A. Crotwell, Sean M. Davis, Elvira de Eyto, Richard A. M de Jeu, B.V. VanderSat, Curtis L. DeGasperi, Doug Degenstein, Larry Di Girolamo, Martin T. Dokulil, Markus G. Donat, Wouter A. Dorigo, Imke Durre, Geoff S. Dutton, G. Duveiller, James W. Elkins, Vitali E. Fioletov, Johannes Flemming, Michael J. Foster, Richard A. Frey, Stacey M. Frith, Lucien Froidevaux, J. Garforth, S. K. Gupta, Leopold Haimberger, Brad D. Hall, Ian Harris, Andrew K Heidinger, D. L. Hemming, Shu-peng (Ben) Ho, Daan Hubert, Dale F. Hurst, I. Hüser, Antje Inness, K. Isaksen, Viju John, Philip D. Jones, J. W. Kaiser, S. Kelly, S. Khaykin, R. Kidd, Hyungiun Kim, Z. Kipling, B. M. Kraemer, D. P. Kratz, R. S. La Fuente, Xin Lan, Kathleen O. Lantz, T. Leblanc, Bailing Li, Norman G Loeb, Craig S. Long, Diego Loyola, Wlodzimierz Marszelewski, B. Martens, Linda May, Michael Mayer, M. F. McCabe, Tim R. McVicar, Carl A. Mears, W. Paul Menzel, Christopher J. Merchant, Ben R. Miller, Diego G. Miralles, Stephen A. Montzka, Colin Morice, Jens Mühle, R. Myneni, Julien P. Nicolas, Jeannette Noetzli, Tim J. Osborn, T. Park, A. Pasik, Andrew M. Paterson, Mauri S. Pelto, S. Perkins-Kirkpatrick, G. Pétron, C. Phillips, Bernard Pinty, S. Po-Chedley, L. Polvani, W. Preimesberger, M. Pulkkanen, W. J. Randel, Samuel Rémy, L. Ricciardulli, A. D. Richardson, L. Rieger, David A. Robinson, Matthew Rodell, Karen H. Rosenlof, Chris Roth, A. Rozanov, James A. Rusak, O. Rusanovskaya, T. Rutishäuser, Ahira Sánchez-Lugo, P. Sawaengphokhai, T. Scanlon, Verena Schenzinger, S. Geoffey Schladow, R. W Schlegel, Eawag Schmid, Martin, H. B. Selkirk, S. Sharma, Lei Shi, S. V. Shimaraeva, E. A. Silow, Adrian J. Simmons, C. A. Smith, Sharon L Smith, B. J. Soden, Viktoria Sofieva, T. H. Sparks, Paul W. Stackhouse Jr., Wolfgang Steinbrecht, Dimitri A. Streletskiy, G. Taha, Hagen Telg, S. J. Thackeray, M. A. Timofeyev, Kleareti Tourpali, Mari R. Tye, Ronald J. van der A, Robin, VanderSat B.V. van der Schalie, Gerard van der SchrierW. Paul, Guido R. van der Werf, Piet Verburg, Jean-Paul Vernier, Holger Vömel, Russell S. Vose, Ray Wang, Shohei G. Watanabe, Mark Weber, Gesa A. Weyhenmeyer, David Wiese, Anne C. Wilber, Jeanette D. Wild, Takmeng Wong, R. Iestyn Woolway, Xungang Yin, Lin Zhao, Guanguo Zhao, Xinjia Zhou, Jerry R. Ziemke, and Markus Ziese
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