3 results
Search Results
Now showing 1 - 3 of 3
- ItemPolar middle atmosphere temperature climatology from Rayleigh lidar measurements at ALOMAR (69° N)(München : European Geopyhsical Union, 2008) Schöch, A.; Baumgarten, G.; Fiedler, J.Rayleigh lidar temperature profiles have been derived in the polar middle atmosphere from 834 measurements with the ALOMAR Rayleigh/Mie/Raman lidar (69.3° N, 16.0° E) in the years 1997–2005. Since our instrument is able to operate under full daylight conditions, the unique data set presented here extends over the entire year and covers the altitude region 30 km–85 km in winter and 30 km–65 km in summer. Comparisons of our lidar data set to reference atmospheres and ECMWF analyses show agreement within a few Kelvin in summer but in winter higher temperatures below 55 km and lower temperatures above by as much as 25 K, due likely to superior resolution of stratospheric warming and associated mesospheric cooling events. We also present a temperature climatology for the entire lower and middle atmosphere at 69° N obtained from a combination of lidar measurements, falling sphere measurements and ECMWF analyses. Day to day temperature variability in the lidar data is found to be largest in winter and smallest in summer.
- ItemValidation of the Atmospheric Chemistry Experiment (ACE) version 2.2 temperature using ground-based and space-borne measurements(München : European Geopyhsical Union, 2008) Sica, R.J.; Izawa, M.R.M.; Walker, K.A.; Boone, C.; Petelina, S.V.; Argall, P.S.; Bernath, P.; Burns, G.B.; Catoire, V.; Collins, R.L.; Daffer, W.H.; De Clercq, C.; Fan, Z.Y.; Firanski, B.J.; French, W.J.R.; Gerard, P.; Gerding, M.; Granville, J.; Innis, J.L.; Keckhut, P.; Kerzenmacher, T.; Klekociuk, A.R.; Kyrö, E.; Lambert, J.C.; Llewellyn, E.J.; Manney, G.L.; McDermid, I.S.; Mizutani, K.; Murayama, Y.; Piccolo, C.; Raspollini, P.; Ridolfi, M.; Robert, C.; Steinbrecht, W.; Strawbridge, K.B.; Strong, K.; Stübi, R.; Thurairajah, B.An ensemble of space-borne and ground-based instruments has been used to evaluate the quality of the version 2.2 temperature retrievals from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS). The agreement of ACE-FTS temperatures with other sensors is typically better than 2 K in the stratosphere and upper troposphere and 5 K in the lower mesosphere. There is evidence of a systematic high bias (roughly 3–6 K) in the ACE-FTS temperatures in the mesosphere, and a possible systematic low bias (roughly 2 K) in ACE-FTS temperatures near 23 km. Some ACE-FTS temperature profiles exhibit unphysical oscillations, a problem fixed in preliminary comparisons with temperatures derived using the next version of the ACE-FTS retrieval software. Though these relatively large oscillations in temperature can be on the order of 10 K in the mesosphere, retrieved volume mixing ratio profiles typically vary by less than a percent or so. Statistical comparisons suggest these oscillations occur in about 10% of the retrieved profiles. Analysis from a set of coincident lidar measurements suggests that the random error in ACE-FTS version 2.2 temperatures has a lower limit of about ±2 K.
- ItemHistorical and idealized climate model experiments: An intercomparison of Earth system models of intermediate complexity(München : European Geopyhsical Union, 2013) Eby, M.; Weaver, A.J.; Alexander, K.; Zickfeld, K.; Abe-Ouchi, A.; Cimatoribus, A.A.; Crespin, E.; Drijfhout, S.S.; Edwards, N.R.; Eliseev, A.V.; Feulner, G.; Fichefet, T.; Forest, C.E.; Goosse, H.; Holden, P.B.; Joos, F.; Kawamiya, M.; Kicklighter, D.; Kienert, H.; Matsumoto, K.; Mokhov, I.I.; Monier, E.; Olsen, S.M.; Pedersen, J.O.P.; Perrette, M.; Philippon-Berthier, G.; Ridgwell, A.; Schlosser, A.; Schneider von Deimling, T.; Shaffer, G.; Smith, R.S.; Spahni, R.; Sokolov, A.P.; Steinacher, M.; Tachiiri, K.; Tokos, K.; Yoshimori, M.; Zeng, N.; Zhao, F.Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.