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Journal articles on the topic 'Model Seasonal Cycle'
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1
Stein, Karl, Niklas Schneider, Axel Timmermann, and Fei-Fei Jin. "Seasonal Synchronization of ENSO Events in a Linear Stochastic Model*." Journal of Climate 23, no. 21 (November 1, 2010): 5629–43. http://dx.doi.org/10.1175/2010jcli3292.1.
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Abstract A simple model of ENSO is developed to examine the effects of the seasonally varying background state of the equatorial Pacific on the seasonal synchronization of ENSO event peaks. The model is based on the stochastically forced recharge oscillator, extended to include periodic variations of the two main model parameters, which represent ENSO’s growth rate and angular frequency. Idealized experiments show that the seasonal cycle of the growth rate parameter sets the seasonal cycle of ENSO variance; the inclusion of the time dependence of the angular frequency parameter has a negligible effect. Event peaks occur toward the end of the season with the most unstable growth rate. Realistic values of the parameters are estimated from a linearized upper-ocean heat budget with output from a high-resolution general circulation model hindcast. Analysis of the hindcast output suggests that the damping by the mean flow field dominates the seasonal cycle of ENSO’s growth rate and, thereby, seasonal ENSO variance. The combination of advective, Ekman pumping, and thermocline feedbacks plays a secondary role and acts to enhance the seasonal cycle of the ENSO growth rate.
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Jucker, M., S. Fueglistaler, and G. K. Vallis. "Maintenance of the Stratospheric Structure in an Idealized General Circulation Model." Journal of the Atmospheric Sciences 70, no. 11 (October 31, 2013): 3341–58. http://dx.doi.org/10.1175/jas-d-12-0305.1.
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Abstract This work explores the maintenance of the stratospheric structure in a primitive equation model that is forced by a Newtonian cooling with a prescribed radiative equilibrium temperature field. Models such as this are well suited to analyze and address questions regarding the nature of wave propagation and troposphere–stratosphere interactions. The focus lies on the lower to midstratosphere and the mean annual cycle, with its large interhemispheric variations in the radiative background state and forcing, is taken as a benchmark to be simulated with reasonable verisimilitude. A reasonably realistic basic stratospheric temperature structure is a necessary first step in understanding stratospheric dynamics. It is first shown that using a realistic radiative background temperature field based on radiative transfer calculations substantially improves the basic structure of the model stratosphere compared to previously used setups. Then, the physical processes that are needed to maintain the seasonal cycle of temperature in the lower stratosphere are explored. It is found that an improved stratosphere and seasonally varying topographically forced stationary waves are, in themselves, insufficient to produce a seasonal cycle of sufficient amplitude in the tropics, even if the topographic forcing is large. Upwelling associated with baroclinic wave activity is an important influence on the tropical lower stratosphere and the seasonal variation of tropospheric baroclinic activity contributes significantly to the seasonal cycle of the lower tropical stratosphere. Given a reasonably realistic basic stratospheric structure and a seasonal cycle in both stationary wave activity and tropospheric baroclinic instability, it is possible to obtain a seasonal cycle in the lower stratosphere of amplitude comparable to the observations.
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Cubadda, Gianluca, Giovanni Savio, and Roberto Zelli. "SEASONALITY, PRODUCTIVITY SHOCKS, AND SECTORAL COMOVEMENTS IN A REAL BUSINESS CYCLE MODEL FOR ITALY." Macroeconomic Dynamics 6, no. 3 (June 2002): 337–56. http://dx.doi.org/10.1017/s1365100500000316.
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This paper investigates the degree of comovements in quarterly Italian time series of sectoral output. A recently developed multivariate technique for the empirical analysis of long-run, cyclical and seasonal comovements is used in the context of a multisectoral real-business-cycle model augmented with persistent seasonal shocks in productivity. Our empirical results emphasize the role of input–output relations in the propagation mechanism and indicate that sectoral outputs have a relatively low number of common stochastic trends, in conflict with the hypothesis of independent productivity shocks. In contrast, stochastic seasonals seem to move idiosyncratically. Furthermore, our findings suggest that the theoretical model should be extended to allow for deterministic seasonal shifts in preferences.
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Gilford, Daniel M., and Susan Solomon. "Radiative Effects of Stratospheric Seasonal Cycles in the Tropical Upper Troposphere and Lower Stratosphere." Journal of Climate 30, no. 8 (April 2017): 2769–83. http://dx.doi.org/10.1175/jcli-d-16-0633.1.
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Water vapor and ozone are powerful radiative constituents in the tropical lower stratosphere, impacting the local heating budget and nonlocally forcing the troposphere below. Their near-tropopause seasonal cycle structures imply associated “radiative seasonal cycles” in heating rates that could affect the amplitude and phase of the local temperature seasonal cycle. Overlying stratospheric seasonal cycles of water vapor and ozone could also play a role in the lower stratosphere and upper troposphere heat budgets through nonlocal propagation of radiation. Previous studies suggest that the tropical lower stratospheric ozone seasonal cycle radiatively amplifies the local temperature seasonal cycle by up to 35%, while water vapor is thought to have a damping effect an order of magnitude smaller. This study uses Aura Microwave Limb Sounder observations and an offline radiative transfer model to examine ozone, water vapor, and temperature seasonal cycles and their radiative linkages in the lower stratosphere and upper troposphere. Radiative sensitivities to ozone and water vapor vertical structures are explicitly calculated, which has not been previously done in a seasonal cycle context. Results show that the water vapor radiative seasonal cycle in the lower stratosphere is not sensitive to the overlying water vapor structure. In contrast, about one-third of ozone’s radiative seasonal cycle amplitude at 85 hPa is associated with longwave emission above 85 hPa. Ozone’s radiative effects are not spatially homogenous: for example, the Northern Hemisphere tropics have a seasonal cycle of radiative temperature adjustments with an amplitude 0.8 K larger than the Southern Hemisphere tropics.
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Giese, Benjamin S., and James A. Carton. "The Seasonal Cycle in Coupled Ocean-Atmosphere Model." Journal of Climate 7, no. 8 (August 1994): 1208–17. http://dx.doi.org/10.1175/1520-0442(1994)007<1208:tscico>2.0.co;2.
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Chen, Gang, and Lantao Sun. "Mechanisms of the Tropical Upwelling Branch of the Brewer–Dobson Circulation: The Role of Extratropical Waves." Journal of the Atmospheric Sciences 68, no. 12 (December 1, 2011): 2878–92. http://dx.doi.org/10.1175/jas-d-11-044.1.
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Abstract The role of extratropical waves in the tropical upwelling branch of the Brewer–Dobson circulation is investigated in an idealized model of the stratosphere and troposphere. To simulate different stratospheric seasonal cycles of planetary waves in the two hemispheres, seasonally varying radiative heating is imposed only in the stratosphere, and surface topographic forcing is prescribed only in the Northern Hemisphere (NH). A zonally symmetric version of the same model is used to diagnose the effects of different wavenumbers and different regions of the total forcing on tropical stratospheric upwelling. The simple configuration can simulate a reasonable seasonal cycle of the tropical upwelling in the lower stratosphere with a stronger amplitude in January (NH midwinter) than in July (NH midsummer), as in the observations. It is shown that the seasonal cycle of stratospheric planetary waves and tropical upwelling responds nonlinearly to the strength of the tropospheric forcing, with a midwinter maximum under strong NH-like tropospheric forcing and double peaks in the fall and spring under weak Southern Hemisphere (SH)-like forcing. The planetary wave component of the total forcing can approximately reproduce the seasonal cycle of tropical stratospheric upwelling in the zonally symmetric model. The zonally symmetric model further demonstrates that the planetary wave forcing in the winter tropical and subtropical stratosphere contributes most to the seasonal cycle of tropical stratospheric upwelling, rather than the high-latitude wave forcing. This suggests that the planetary wave forcing, prescribed mostly in the extratropics in the model, has to propagate equatorward into the subtropical latitudes to induce sufficient tropical upwelling. Another interesting finding is that the planetary waves in the summer lower stratosphere can drive a shallow residual circulation rising in the subtropics and subsiding in the extratropics.
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Hindrayanto, Irma, Jan P. A. M. Jacobs, Denise R. Osborn, and Jing Tian. "TREND–CYCLE–SEASONAL INTERACTIONS: IDENTIFICATION AND ESTIMATION." Macroeconomic Dynamics 23, no. 8 (February 6, 2018): 3163–88. http://dx.doi.org/10.1017/s1365100517001092.
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Economists typically use seasonally adjusted data in which the assumption is imposed that seasonality is uncorrelated with trend and cycle. The importance of this assumption has been highlighted by the Great Recession. The paper examines an unobserved components model that permits nonzero correlations between seasonal and nonseasonal shocks. Identification conditions for estimation of the parameters are discussed from the perspectives of both analytical and simulation results. Applications to UK household consumption expenditures and US employment reject the zero correlation restrictions and also show that the correlation assumptions imposed have important implications about the evolution of the trend and cycle in the post-Great Recession period.
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Stein, Karl, Axel Timmermann, Niklas Schneider, Fei-Fei Jin, and Malte F. Stuecker. "ENSO Seasonal Synchronization Theory." Journal of Climate 27, no. 14 (July 10, 2014): 5285–310. http://dx.doi.org/10.1175/jcli-d-13-00525.1.
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Abstract One of the key characteristics of El Niño–Southern Oscillation (ENSO) is its synchronization to the annual cycle, which manifests in the tendency of ENSO events to peak during boreal winter. Current theory offers two possible mechanisms to account the for ENSO synchronization: frequency locking of ENSO to periodic forcing by the annual cycle, or the effect of the seasonally varying background state of the equatorial Pacific on ENSO’s coupled stability. Using a parametric recharge oscillator (PRO) model of ENSO, the authors test which of these scenarios provides a better explanation of the observed ENSO synchronization. Analytical solutions of the PRO model show that the annual modulation of the growth rate parameter results directly in ENSO’s seasonal variance, amplitude modulation, and 2:1 phase synchronization to the annual cycle. The solutions are shown to be applicable to the long-term behavior of the damped model excited by stochastic noise, which produces synchronization characteristics that agree with the observations and can account for the variety of ENSO synchronization behavior in state-of-the-art coupled general circulation models. The model also predicts spectral peaks at “combination tones” between ENSO and the annual cycle that exist in the observations and many coupled models. In contrast, the nonlinear frequency entrainment scenario predicts the existence of a spectral peak at the biennial frequency corresponding to the observed 2:1 phase synchronization. Such a peak does not exist in the observed ENSO spectrum. Hence, it can be concluded that the seasonal modulation of the coupled stability is responsible for the synchronization of ENSO events to the annual cycle.
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Thum, Tea, Julia E. M. S. Nabel, Aki Tsuruta, Tuula Aalto, Edward J. Dlugokencky, Jari Liski, Ingrid T. Luijkx, et al. "Evaluating two soil carbon models within the global land surface model JSBACH using surface and spaceborne observations of atmospheric CO<sub>2</sub>." Biogeosciences 17, no. 22 (November 23, 2020): 5721–43. http://dx.doi.org/10.5194/bg-17-5721-2020.
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Abstract. The trajectories of soil carbon in our changing climate are of the utmost importance as soil is a substantial carbon reservoir with a large potential to impact the atmospheric carbon dioxide (CO2) burden. Atmospheric CO2 observations integrate all processes affecting carbon exchange between the surface and the atmosphere and therefore are suitable for carbon cycle model evaluation. In this study, we present a framework for how to use atmospheric CO2 observations to evaluate two distinct soil carbon models (CBALANCE, CBA, and Yasso, YAS) that are implemented in a global land surface model (JSBACH). We transported the biospheric carbon fluxes obtained by JSBACH using the atmospheric transport model TM5 to obtain atmospheric CO2. We then compared these results with surface observations from Global Atmosphere Watch stations, as well as with column XCO2 retrievals from GOSAT (Greenhouse Gases Observing Satellite). The seasonal cycles of atmospheric CO2 estimated by the two different soil models differed. The estimates from the CBALANCE soil model were more in line with the surface observations at low latitudes (0–45∘ N) with only a 1 % bias in the seasonal cycle amplitude, whereas Yasso underestimated the seasonal cycle amplitude in this region by 32 %. Yasso, on the other hand, gave more realistic seasonal cycle amplitudes of CO2 at northern boreal sites (north of 45∘ N) with an underestimation of 15 % compared to a 30 % overestimation by CBALANCE. Generally, the estimates from CBALANCE were more successful in capturing the seasonal patterns and seasonal cycle amplitudes of atmospheric CO2 even though it overestimated soil carbon stocks by 225 % (compared to an underestimation of 36 % by Yasso), and its estimations of the global distribution of soil carbon stocks were unrealistic. The reasons for these differences in the results are related to the different environmental drivers and their functional dependencies on the two soil carbon models. In the tropics, heterotrophic respiration in the Yasso model increased earlier in the season since it is driven by precipitation instead of soil moisture, as in CBALANCE. In temperate and boreal regions, the role of temperature is more dominant. There, heterotrophic respiration from the Yasso model had a larger seasonal amplitude, which is driven by air temperature, compared to CBALANCE, which is driven by soil temperature. The results underline the importance of using sub-annual data in the development of soil carbon models when they are used at shorter than annual timescales.
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Mongwe, N. Precious, Marcello Vichi, and Pedro M. S. Monteiro. "The seasonal cycle of <i>p</i>CO<sub>2</sub> and CO<sub>2</sub> fluxes in the Southern Ocean: diagnosing anomalies in CMIP5 Earth system models." Biogeosciences 15, no. 9 (May 15, 2018): 2851–72. http://dx.doi.org/10.5194/bg-15-2851-2018.
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Abstract. The Southern Ocean forms an important component of the Earth system as a major sink of CO2 and heat. Recent studies based on the Coupled Model Intercomparison Project version 5 (CMIP5) Earth system models (ESMs) show that CMIP5 models disagree on the phasing of the seasonal cycle of the CO2 flux (FCO2) and compare poorly with available observation products for the Southern Ocean. Because the seasonal cycle is the dominant mode of CO2 variability in the Southern Ocean, its simulation is a rigorous test for models and their long-term projections. Here we examine the competing roles of temperature and dissolved inorganic carbon (DIC) as drivers of the seasonal cycle of pCO2 in the Southern Ocean to explain the mechanistic basis for the seasonal biases in CMIP5 models. We find that despite significant differences in the spatial characteristics of the mean annual fluxes, the intra-model homogeneity in the seasonal cycle of FCO2 is greater than observational products. FCO2 biases in CMIP5 models can be grouped into two main categories, i.e., group-SST and group-DIC. Group-SST models show an exaggeration of the seasonal rates of change of sea surface temperature (SST) in autumn and spring during the cooling and warming peaks. These higher-than-observed rates of change of SST tip the control of the seasonal cycle of pCO2 and FCO2 towards SST and result in a divergence between the observed and modeled seasonal cycles, particularly in the Sub-Antarctic Zone. While almost all analyzed models (9 out of 10) show these SST-driven biases, 3 out of 10 (namely NorESM1-ME, HadGEM-ES and MPI-ESM, collectively the group-DIC models) compensate for the solubility bias because of their overly exaggerated primary production, such that biologically driven DIC changes mainly regulate the seasonal cycle of FCO2.
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Atkinson, C. P., H. L. Bryden, J. J.-M. Hirschi, and T. Kanzow. "On the seasonal cycles and variability of Florida Straits, Ekman and Sverdrup transports at 26° N in the Atlantic Ocean." Ocean Science 6, no. 4 (October 1, 2010): 837–59. http://dx.doi.org/10.5194/os-6-837-2010.
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Abstract. Since April 2004 the RAPID array has made continuous measurements of the Atlantic Meridional Overturning Circulation (AMOC) at 26° N. Two key components of this system are Ekman transport zonally integrated across 26° N and western boundary current transport in the Florida Straits. Whilst measurements of the AMOC as a whole are somewhat in their infancy, this study investigates what useful information can be extracted on the variability of the Ekman and Florida Straits transports using the decadal timeseries already available. Analysis is also presented for Sverdrup transports zonally integrated across 26° N. The seasonal cycles of Florida Straits, Ekman and Sverdrup transports are quantified at 26° N using harmonic analysis of annual and semi-annual constituents. Whilst Sverdrup transport shows clear semi-annual periodicity, calculations of seasonal Florida Straits and Ekman transports show substantial interannual variability due to contamination by variability at non-seasonal frequencies; the mean seasonal cycle for these transports only emerges from decadal length observations. The Florida Straits and Ekman mean seasonal cycles project on the AMOC with a combined peak-to-peak seasonal range of 3.5 Sv. The combined seasonal range for heat transport is 0.40 PW. The Florida Straits seasonal cycle possesses a smooth annual periodicity in contrast with previous studies suggesting a more asymmetric structure. No clear evidence is found to support significant changes in the Florida Straits seasonal cycle at sub-decadal periods. Whilst evidence of wind driven Florida Straits transport variability is seen at sub-seasonal and annual periods, a model run from the 1/4° eddy-permitting ocean model NEMO is used to identify an important contribution from internal oceanic variability at sub-annual and interannual periods. The Ekman transport seasonal cycle possesses less symmetric structure, due in part to different seasonal transport regimes east and west of 50 to 60° W. Around 60% of non-seasonal Ekman transport variability occurs in phase section-wide at 26° N and is related to the NAO, whilst Sverdrup transport variability is more difficult to decompose.
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Atkinson, C. P., H. L. Bryden, J. J. M. Hirschi, and T. Kanzow. "On the variability of Florida Straits and wind driven transports at 26° N in the Atlantic Ocean." Ocean Science Discussions 7, no. 2 (April 29, 2010): 919–71. http://dx.doi.org/10.5194/osd-7-919-2010.
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Abstract. Since April 2004 the RAPID array has made continuous measurements of the Atlantic Meridional Overturning Circulation (AMOC) at 26° N. Two key components of this system are Ekman transport zonally integrated across 26° N and western boundary current transport in the Florida Straits. Whilst measurements of the AMOC as a whole are somewhat in their infancy, this study investigates what useful information can be extracted on the variability of the Ekman and Florida Straits transports using the decadal timeseries already available. Analysis is also presented for Sverdrup transports zonally integrated across 26° N. The seasonal cycles of Florida Straits, Ekman and Sverdrup transports are quantified at 26° N using harmonic analysis of annual and semi-annual constituents. Whilst Sverdrup transport shows clear semi-annual periodicity, calculations of seasonal Florida Straits and Ekman transports show substantial interannual variability due to variability at non-seasonal frequencies; the mean seasonal cycle for these transports only emerges from decadal length observations. The Florida Straits and Ekman mean seasonal cycles project on the AMOC with a combined peak-to-peak seasonal range of 3.5 Sv. The combined seasonal range for heat transport is 0.40 PW. The Florida Straits seasonal cycle possesses a smooth annual periodicity in contrast with previous studies suggesting a more asymmetric structure. No clear evidence is found to support significant changes in the Florida Straits seasonal cycle at sub-decadal periods. Whilst evidence of wind driven Florida Straits transport variability is seen at sub-seasonal and annual periods, model runs from the 1/4° eddy-permitting ocean model NEMO are used to identify an important contribution from internal oceanic variability at sub-annual and interannual periods. The Ekman transport seasonal cycle possesses less symmetric structure, due in part to different seasonal transport regimes east and west of 50 to 60° W. Around 60% of non-seasonal Ekman transport variability occurs in phase section-wide at 26° N and is related to the NAO, whilst Sverdrup transport variability is more difficult to decompose.
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Kushner, Paul J., and Lorenzo M. Polvani. "Stratosphere–Troposphere Coupling in a Relatively Simple AGCM: Impact of the Seasonal Cycle." Journal of Climate 19, no. 21 (November 1, 2006): 5721–27. http://dx.doi.org/10.1175/jcli4007.1.
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Abstract The seasonal time dependence of the tropospheric circulation response to polar stratospheric cooling in a simple atmospheric general circulation model is investigated. When the model is run without a seasonal cycle, polar stratospheric cooling induces a positive annular-mode response in the troposphere that takes a remarkably long time—several hundred days—to fully equilibrate. One is thus led to ask whether the tropospheric response would survive in the presence of a seasonal cycle. When a seasonal cycle is introduced into the model stratosphere, the tropospheric response appears with a distinct time lag with respect to the stratospheric cooling, but, in the long-term mean, the pattern of the wind response is very similar to the one that results from stratospheric forcing in the absence of a seasonal cycle.
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Wang, Xun, Andrew E. Dessler, Mark R. Schoeberl, Wandi Yu, and Tao Wang. "Impact of convectively lofted ice on the seasonal cycle of water vapor in the tropical tropopause layer." Atmospheric Chemistry and Physics 19, no. 23 (December 3, 2019): 14621–36. http://dx.doi.org/10.5194/acp-19-14621-2019.
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Abstract. We use a forward Lagrangian trajectory model to diagnose mechanisms that produce the water vapor seasonal cycle observed by the Microwave Limb Sounder (MLS) and reproduced by the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) in the tropical tropopause layer (TTL). We confirm in both the MLS and GEOSCCM that the seasonal cycle of water vapor entering the stratosphere is primarily determined by the seasonal cycle of TTL temperatures. However, we find that the seasonal cycle of temperature predicts a smaller seasonal cycle of TTL water vapor between 10 and 40∘ N than observed by MLS or simulated by the GEOSCCM. Our analysis of the GEOSCCM shows that including evaporation of convective ice in the trajectory model increases both the simulated maximum value of the 100 hPa 10–40∘ N water vapor seasonal cycle and the seasonal-cycle amplitude. We conclude that the moistening effect from convective ice evaporation in the TTL plays a key role in regulating and maintaining the seasonal cycle of water vapor in the TTL. Most of the convective moistening in the 10–40∘ N range comes from convective ice evaporation occurring at the same latitudes. A small contribution to the moistening comes from convective ice evaporation occurring between 10∘ S and 10∘ N. Within the 10–40∘ N band, the Asian monsoon region is the most important region for convective moistening by ice evaporation during boreal summer and autumn.
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Kangasaho, Vilma, Aki Tsuruta, Leif Backman, Pyry Mäkinen, Sander Houweling, Arjo Segers, Maarten Krol, et al. "The Role of Emission Sources and Atmospheric Sink in the Seasonal Cycle of CH4 and δ13-CH4: Analysis Based on the Atmospheric Chemistry Transport Model TM5." Atmosphere 13, no. 6 (May 30, 2022): 888. http://dx.doi.org/10.3390/atmos13060888.
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This study investigates the contribution of different CH4 sources to the seasonal cycle of δ13C during 2000–2012 by using the TM5 atmospheric transport model, including spatially varying information on isotopic signatures. The TM5 model is able to produce the background seasonality of δ13C, but the discrepancies compared to the observations arise from incomplete representation of the emissions and their source-specific signatures. Seasonal cycles of δ13C are found to be an inverse of CH4 cycles in general, but the anti-correlations between CH4 and δ13C are imperfect and experience a large variation (p=−0.35 to −0.91) north of 30° S. We found that wetland emissions are an important driver in the δ13C seasonal cycle in the Northern Hemisphere and Tropics, and in the Southern Hemisphere Tropics, emissions from fires contribute to the enrichment of δ13C in July–October. The comparisons to the observations from 18 stations globally showed that the seasonal cycle of EFMM emissions in the EDGAR v5.0 inventory is more realistic than in v4.3.2. At northern stations (north of 55° N), modeled δ13C amplitudes are generally smaller by 12–68%, mainly because the model could not reproduce the strong depletion in autumn. This indicates that the CH4 emission magnitude and seasonal cycle of wetlands may need to be revised. In addition, results from stations in northern latitudes (19–40° N) indicate that the proportion of biogenic to fossil-based emissions may need to be revised, such that a larger portion of fossil-based emissions is needed during summer.
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Alexandrov, G. A. "Explaining the seasonal cycle of the globally averaged CO<sub>2</sub> with a carbon-cycle model." Earth System Dynamics 5, no. 2 (October 21, 2014): 345–54. http://dx.doi.org/10.5194/esd-5-345-2014.
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Abstract. The seasonal changes in the globally averaged atmospheric carbon-dioxide concentrations reflect an important aspect of the global carbon cycle: the gas exchange between the atmosphere and terrestrial biosphere. The data on the globally averaged atmospheric carbon-dioxide concentrations, which are reported by Earth System Research Laboratory of the US National Oceanic & Atmospheric Administration (NOAA/ESRL), could be used to demonstrate the adequacy of the global carbon-cycle models. However, it was recently found that the observed amplitude of seasonal variations in the atmospheric carbon-dioxide concentrations is higher than simulated. In this paper, the factors that affect the amplitude of seasonal variations are explored using a carbon-cycle model of reduced complexity. The model runs show that the low amplitude of the simulated seasonal variations may result from underestimated effect of substrate limitation on the seasonal pattern of heterotrophic respiration and from an underestimated magnitude of the annual gross primary production (GPP) in the terrestrial ecosystems located to the north of 25° N.
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Ballabrera-Poy, J., R. Murtugudde, R.-H. Zhang, and A. J. Busalacchi. "Coupled Ocean–Atmosphere Response to Seasonal Modulation of Ocean Color: Impact on Interannual Climate Simulations in the Tropical Pacific." Journal of Climate 20, no. 2 (January 15, 2007): 353–74. http://dx.doi.org/10.1175/jcli3958.1.
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Abstract The ability to use remotely sensed ocean color data to parameterize biogenic heating in a coupled ocean–atmosphere model is investigated. The model used is a hybrid coupled model recently developed at the Earth System Science Interdisciplinary Center (ESSIC) by coupling an ocean general circulation model with a statistical atmosphere model for wind stress anomalies. The impact of the seasonal cycle of water turbidity on the annual mean, seasonal cycle, and interannual variability of the coupled system is investigated using three simulations differing in the parameterization of the vertical attenuation of downwelling solar radiation: (i) a control simulation using a constant 17-m attenuation depth, (ii) a simulation with the spatially varying annual mean of the satellite-derived attenuation depth, and (iii) a simulation accounting for the seasonal cycle of the attenuation depth. The results indicate that a more realistic attenuation of solar radiation slightly reduces the cold bias of the model. While a realistic attenuation of solar radiation hardly affects the annual mean and the seasonal cycle due to anomaly coupling, it significantly affects the interannual variability, especially when the seasonal cycle of the attenuation depth is used. The seasonal cycle of the attenuation depth interacts with the low-frequency equatorial dynamics to enhance warm and cold anomalies, which are further amplified via positive air–sea feedbacks. These results also indicate that interannual variability of the attenuation depths is required to capture the asymmetric biological feedbacks during cold and warm ENSO events.
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Donohoe, Aaron, and David S. Battisti. "The Seasonal Cycle of Atmospheric Heating and Temperature." Journal of Climate 26, no. 14 (July 12, 2013): 4962–80. http://dx.doi.org/10.1175/jcli-d-12-00713.1.
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Abstract The seasonal cycle of the heating of the atmosphere is divided into a component due to direct solar absorption in the atmosphere and a component due to the flux of energy from the surface to the atmosphere via latent, sensible, and radiative heat fluxes. Both observations and coupled climate models are analyzed. The vast majority of the seasonal heating of the northern extratropics (78% in the observations and 67% in the model average) is due to atmospheric shortwave absorption. In the southern extratropics, the seasonal heating of the atmosphere is entirely due to atmospheric shortwave absorption in both the observations and the models, and the surface heat flux opposes the seasonal heating of the atmosphere. The seasonal cycle of atmospheric temperature is surface amplified in the northern extratropics and nearly barotropic in the Southern Hemisphere; in both cases, the vertical profile of temperature reflects the source of the seasonal heating. In the northern extratropics, the seasonal cycle of atmospheric heating over land differs markedly from that over the ocean. Over the land, the surface energy fluxes complement the driving absorbed shortwave flux; over the ocean, they oppose the absorbed shortwave flux. This gives rise to large seasonal differences in the temperature of the atmosphere over land and ocean. Downgradient temperature advection by the mean westerly winds damps the seasonal cycle of heating of the atmosphere over the land and amplifies it over the ocean. The seasonal cycle in the zonal energy transport is 4.1 PW. Finally, the authors examine the change in the seasonal cycle of atmospheric heating in 11 models from phase 3 of the Coupled Model Intercomparison Project (CMIP3) due to a doubling of atmospheric carbon dioxide from preindustrial concentrations. The seasonal heating of the troposphere is everywhere enhanced by increased shortwave absorption by water vapor; it is reduced where sea ice has been replaced by ocean, which increases the effective heat storage reservoir of the climate system and thereby reduces the seasonal magnitude of energy fluxes between the surface and the atmosphere. As a result, the seasonal amplitude of temperature increases in the upper troposphere (where atmospheric shortwave absorption increases) and decreases at the surface (where the ice melts).
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Hansen, Candice J., and David A. Paige. "A thermal model for the seasonal nitrogen cycle on Triton." Icarus 99, no. 2 (October 1992): 273–88. http://dx.doi.org/10.1016/0019-1035(92)90146-x.
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Bowman, Henry, Steven Turnock, Susanne E. Bauer, Kostas Tsigaridis, Makoto Deushi, Naga Oshima, Fiona M. O'Connor, et al. "Changes in anthropogenic precursor emissions drive shifts in the ozone seasonal cycle throughout the northern midlatitude troposphere." Atmospheric Chemistry and Physics 22, no. 5 (March 16, 2022): 3507–24. http://dx.doi.org/10.5194/acp-22-3507-2022.
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Abstract. Simulations by six Coupled Model Intercomparison Project Phase 6 (CMIP6) Earth system models indicate that the seasonal cycle of baseline tropospheric ozone at northern midlatitudes has been shifting since the mid-20th century. Beginning in ∼ 1940, the magnitude of the seasonal cycle increased by ∼10 ppb (measured from seasonal minimum to maximum), and the seasonal maximum shifted to later in the year by about 3 weeks. This shift maximized in the mid-1980s, followed by a reversal – the seasonal cycle decreased in amplitude and the maximum shifted back to earlier in the year. Similar changes are seen in measurements collected from the 1970s to the present. The timing of the seasonal cycle changes is generally concurrent with the rise and fall of anthropogenic emissions that followed industrialization and the subsequent implementation of air quality emission controls. A quantitative comparison of the temporal changes in the ozone seasonal cycle at sites in both Europe and North America with the temporal changes in ozone precursor emissions across the northern midlatitudes found a high degree of similarity between these two temporal patterns. We hypothesize that changing precursor emissions are responsible for the shift in the ozone seasonal cycle; this is supported by the absence of such seasonal shifts in southern midlatitudes where anthropogenic emissions are much smaller. We also suggest a mechanism by which changing emissions drive the changing seasonal cycle: increasing emissions of NOx allow summertime photochemical production of ozone to become more important than ozone transported from the stratosphere, and increasing volatile organic compounds (VOCs) lead to progressively greater photochemical ozone production in the summer months, thereby increasing the amplitude of the seasonal ozone cycle. Decreasing emissions of both precursor classes then reverse these changes. The quantitative parameter values that characterize the seasonal shifts provide useful benchmarks for evaluating model simulations, both against observations and between models.
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Vergara, Oscar, Boris Dewitte, Ivonne Montes, Veronique Garçon, Marcel Ramos, Aurélien Paulmier, and Oscar Pizarro. "Seasonal variability of the oxygen minimum zone off Peru in a high-resolution regional coupled model." Biogeosciences 13, no. 15 (August 8, 2016): 4389–410. http://dx.doi.org/10.5194/bg-13-4389-2016.
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Abstract. In addition to being one of the most productive upwelling systems, the oceanic region off Peru is embedded in one of the most extensive oxygen minimum zones (OMZs) of the world ocean. The dynamics of the OMZ off Peru remain uncertain, partly due to the scarcity of data and to the ubiquitous role of mesoscale activity on the circulation and biogeochemistry. Here we use a high-resolution coupled physical/biogeochemical model simulation to investigate the seasonal variability of the OMZ off Peru. The focus is on characterizing the seasonal cycle in dissolved O2 (DO) eddy flux at the OMZ boundaries, including the coastal domain, viewed here as the eastern boundary of the OMZ, considering that the mean DO eddy flux in these zones has a significant contribution to the total DO flux. The results indicate that the seasonal variations of the OMZ can be interpreted as resulting from the seasonal modulation of the mesoscale activity. Along the coast, despite the increased seasonal low DO water upwelling, the DO peaks homogeneously over the water column and within the Peru Undercurrent (PUC) in austral winter, which results from mixing associated with the increase in both the intraseasonal wind variability and baroclinic instability of the PUC. The coastal ocean acts therefore as a source of DO in austral winter for the OMZ core, through eddy-induced offshore transport that is also shown to peak in austral winter. In the open ocean, the OMZ can be divided vertically into two zones: an upper zone above 400 m, where the mean DO eddy flux is larger on average than the mean seasonal DO flux and varies seasonally, and a lower part, where the mean seasonal DO flux exhibits vertical–zonal propagating features that share similar characteristics than those of the energy flux associated with the annual extratropical Rossby waves. At the OMZ meridional boundaries where the mean DO eddy flux is large, the DO eddy flux has also a marked seasonal cycle that peaks in austral winter (spring) at the northern (southern) boundary. In the model, the amplitude of the seasonal cycle is 70 % larger at the southern boundary than at the northern boundary. Our results suggest the existence of distinct seasonal regimes for the ventilation of the OMZ by eddies at its boundaries. Implications for understanding the OMZ variability at longer timescales are discussed.
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Kawaguchi, So, Toshihiro Yoshida, Luke Finley, Paul Cramp, and Stephen Nicol. "The krill maturity cycle: a conceptual model of the seasonal cycle in Antarctic krill." Polar Biology 30, no. 6 (November 8, 2006): 689–98. http://dx.doi.org/10.1007/s00300-006-0226-2.
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Achatz, Ulrich, and J. D. Opsteegh. "Primitive-Equation-Based Low-Order Models with Seasonal Cycle. Part I: Model Construction." Journal of the Atmospheric Sciences 60, no. 3 (February 2003): 465–77. http://dx.doi.org/10.1175/1520-0469(2003)060<0465:peblom>2.0.co;2.
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Luan, Xiaohan, and Leilei Han. "Prediction Model of Dynamic Resilient Modulus of Unsaturated Modified Subgrade under Multi-Factor Combination." Applied Sciences 12, no. 18 (September 13, 2022): 9185. http://dx.doi.org/10.3390/app12189185.
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The objective of this research is to solve the problem of the lack of prediction methods and basis for the long-term road performance of oil shale residue-modified soil in seasonally frozen regions. This paper summarizes and expands the resilient modulus prediction methods in the related literature. Based on the measured soil–water characteristic curve (SWCC) of the compacted modified soil and the trend characteristics of dynamic resilient modulus under freeze–thaw cycles, a semi-empirical prediction model is proposed. This model was used to quantitatively forecast the resilient modulus of unsaturated modified subgrade soil after the freeze–thaw cycle in a seasonal permafrost region. The applicability and accuracy of the method were verified by dynamic resilient modulus tests of the oil shale residue-modified soil under various freeze–thaw cycles and moisture content. The results show that the model has a high degree of fit to the experimental data and is more suitable for predicting the dynamic resilient modulus of modified soil under the change of moisture and the freeze–thaw cycle compared to the existing models.
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Anav, A., P. Friedlingstein, M. Kidston, L. Bopp, P. Ciais, P. Cox, C. Jones, M. Jung, R. Myneni, and Z. Zhu. "Evaluating the Land and Ocean Components of the Global Carbon Cycle in the CMIP5 Earth System Models." Journal of Climate 26, no. 18 (September 9, 2013): 6801–43. http://dx.doi.org/10.1175/jcli-d-12-00417.1.
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Abstract The authors assess the ability of 18 Earth system models to simulate the land and ocean carbon cycle for the present climate. These models will be used in the next Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) for climate projections, and such evaluation allows identification of the strengths and weaknesses of individual coupled carbon–climate models as well as identification of systematic biases of the models. Results show that models correctly reproduce the main climatic variables controlling the spatial and temporal characteristics of the carbon cycle. The seasonal evolution of the variables under examination is well captured. However, weaknesses appear when reproducing specific fields: in particular, considering the land carbon cycle, a general overestimation of photosynthesis and leaf area index is found for most of the models, while the ocean evaluation shows that quite a few models underestimate the primary production.The authors also propose climate and carbon cycle performance metrics in order to assess whether there is a set of consistently better models for reproducing the carbon cycle. Averaged seasonal cycles and probability density functions (PDFs) calculated from model simulations are compared with the corresponding seasonal cycles and PDFs from different observed datasets. Although the metrics used in this study allow identification of some models as better or worse than the average, the ranking of this study is partially subjective because of the choice of the variables under examination and also can be sensitive to the choice of reference data. In addition, it was found that the model performances show significant regional variations.
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Philander, S. G. H., and R. C. Pacanowski. "A model of the seasonal cycle in the tropical Atlantic Ocean." Journal of Geophysical Research 91, no. C12 (1986): 14192. http://dx.doi.org/10.1029/jc091ic12p14192.
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Beckers, J. M., M. Rixen, P. Brasseur, J. M. Brankart, A. Elmoussaoui, M. Crépon, Ch Herbaut, et al. "Model intercomparison in the Mediterranean: MEDMEX simulations of the seasonal cycle." Journal of Marine Systems 33-34 (June 2002): 215–51. http://dx.doi.org/10.1016/s0924-7963(02)00060-x.
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Miron, Jeffrey A. "Seasonal Fluctuations and the Life Cycle-Permanent Income Model of Consumption." Journal of Political Economy 94, no. 6 (December 1986): 1258–79. http://dx.doi.org/10.1086/261432.
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Browse, J., K. S. Carslaw, S. R. Arnold, K. Pringle, and O. Boucher. "The scavenging processes controlling the seasonal cycle in Arctic sulphate and black carbon aerosol." Atmospheric Chemistry and Physics Discussions 12, no. 1 (January 31, 2012): 3409–65. http://dx.doi.org/10.5194/acpd-12-3409-2012.
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Abstract. The seasonal cycle in Arctic aerosol is typified by high concentrations of large aged anthropogenic particles transported from lower latitudes in the late Arctic winter and early spring followed by a sharp transition to low concentrations of locally sourced smaller particles in the summer. However, multi-model assessments show that many models fail to simulate a realistic cycle. Here, we use a global aerosol microphysics model and surface-level aerosol observations to understand how wet scavenging processes control the seasonal variation in Arctic black carbon (BC) and sulphate aerosol concentrations. We show that the transition from high wintertime to low summertime Arctic aerosol concentrations is caused by the change from inefficient scavenging in ice clouds to the much more efficient scavenging in warm liquid clouds. This seasonal cycle is amplified further by the appearance of warm drizzling cloud in late spring and summer at a time when aerosol transport shifts mainly to low levels. Implementing these processes in a model greatly improves the agreement between the model and observations at the three Arctic ground-stations Alert, Barrow and Zeppelin Mountain on Svalbard. The SO4 model-observation correlation coefficient (R) increases from: −0.33 to 0.71 at Alert (82.5° N), from −0.16 to 0.70 at Point Barrow (71.0° N) and from −0.42 to 0.40 at Zeppelin Mountain (78° N) while, the BC model-observation correlation coefficient increases from −0.68 to 0.72 at Alert and from −0.42 to 0.44 at Barrow. Observations at three marginal Arctic sites (Janiskoski, Oulanka and Karasjok) indicate a far weaker aerosol seasonal cycle, which we show is consistent with the much smaller seasonal changes in ice clouds compared to the higher latitude sites. Our results suggest that the seasonal cycle in Arctic aerosol is driven by temperature-dependent scavenging processes that may be susceptible to modification in a future climate.
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Santer, Benjamin D., Stephen Po-Chedley, Mark D. Zelinka, Ivana Cvijanovic, Céline Bonfils, Paul J. Durack, Qiang Fu, et al. "Human influence on the seasonal cycle of tropospheric temperature." Science 361, no. 6399 (July 19, 2018): eaas8806. http://dx.doi.org/10.1126/science.aas8806.
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We provide scientific evidence that a human-caused signal in the seasonal cycle of tropospheric temperature has emerged from the background noise of natural variability. Satellite data and the anthropogenic “fingerprint” predicted by climate models show common large-scale changes in geographical patterns of seasonal cycle amplitude. These common features include increases in amplitude at mid-latitudes in both hemispheres, amplitude decreases at high latitudes in the Southern Hemisphere, and small changes in the tropics. Simple physical mechanisms explain these features. The model fingerprint of seasonal cycle changes is identifiable with high statistical confidence in five out of six satellite temperature datasets. Our results suggest that attribution studies with the changing seasonal cycle provide powerful evidence for a significant human effect on Earth’s climate.
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Lindqvist, H., C. W. O'Dell, S. Basu, H. Boesch, F. Chevallier, N. Deutscher, L. Feng, et al. "Does GOSAT capture the true seasonal cycle of carbon dioxide?" Atmospheric Chemistry and Physics 15, no. 22 (November 24, 2015): 13023–40. http://dx.doi.org/10.5194/acp-15-13023-2015.
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Abstract. The seasonal cycle accounts for a dominant mode of total column CO2 (XCO2) annual variability and is connected to CO2 uptake and release; it thus represents an important quantity to test the accuracy of the measurements from space. We quantitatively evaluate the XCO2 seasonal cycle of the Greenhouse Gases Observing Satellite (GOSAT) observations from the Atmospheric CO2 Observations from Space (ACOS) retrieval system and compare average regional seasonal cycle features to those directly measured by the Total Carbon Column Observing Network (TCCON). We analyse the mean seasonal cycle amplitude, dates of maximum and minimum XCO2, as well as the regional growth rates in XCO2 through the fitted trend over several years. We find that GOSAT/ACOS captures the seasonal cycle amplitude within 1.0 ppm accuracy compared to TCCON, except in Europe, where the difference exceeds 1.0 ppm at two sites, and the amplitude captured by GOSAT/ACOS is generally shallower compared to TCCON. This bias over Europe is not as large for the other GOSAT retrieval algorithms (NIES v02.21, RemoTeC v2.35, UoL v5.1, and NIES PPDF-S v.02.11), although they have significant biases at other sites. We find that the ACOS bias correction partially explains the shallow amplitude over Europe. The impact of the co-location method and aerosol changes in the ACOS algorithm were also tested and found to be few tenths of a ppm and mostly non-systematic. We find generally good agreement in the date of minimum XCO2 between ACOS and TCCON, but ACOS generally infers a date of maximum XCO2 2–3 weeks later than TCCON. We further analyse the latitudinal dependence of the seasonal cycle amplitude throughout the Northern Hemisphere and compare the dependence to that predicted by current optimized models that assimilate in situ measurements of CO2. In the zonal averages, models are consistent with the GOSAT amplitude to within 1.4 ppm, depending on the model and latitude. We also show that the seasonal cycle of XCO2 depends on longitude especially at the mid-latitudes: the amplitude of GOSAT XCO2 doubles from western USA to East Asia at 45–50° N, which is only partially shown by the models. In general, we find that model-to-model differences can be larger than GOSAT-to-model differences. These results suggest that GOSAT/ACOS retrievals of the XCO2 seasonal cycle may be sufficiently accurate to evaluate land surface models in regions with significant discrepancies between the models.
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Wang, Lei, Yuqing Wang, Axel Lauer, and Shang-Ping Xie. "Simulation of Seasonal Variation of Marine Boundary Layer Clouds over the Eastern Pacific with a Regional Climate Model*." Journal of Climate 24, no. 13 (July 1, 2011): 3190–210. http://dx.doi.org/10.1175/2010jcli3935.1.
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Abstract The seasonal cycle of marine boundary layer (MBL) clouds over the eastern Pacific Ocean is studied with the International Pacific Research Center (IPRC) Regional Atmospheric Model (iRAM). The results show that the model is capable of simulating not only the overall seasonal cycle but also the spatial distribution, cloud regime transition, and vertical structure of MBL clouds over the eastern Pacific. Although the modeled MBL cloud layer is generally too high in altitude over the open ocean when compared with available satellite observations, the model simulated well the westward deepening and decoupling of the MBL, the rise in cloud base and cloud top of the low cloud decks off the Peru and California coasts, and the cloud regime transition from stratocumulus near the coast to trade cumulus farther to the west in both the southeast and northeast Pacific. In particular, the model reproduced major features of the seasonal variations in stratocumulus decks off the Peru and California coasts, including cloud amount, surface latent heat flux, subcloud-layer mixing, and the degree of MBL decoupling. In both observations and the model simulation, in the season with small low-level cloudiness, surface latent heat flux is large and the cloud base is high. This coincides with weak subcloud-layer mixing and strong entrainment at cloud top, characterized by a high degree of MBL decoupling, while the opposite is true for the season with large low-level cloudiness. This seasonal cycle in low-cloud properties resembles the downstream stratocumulus-to-cumulus transition of marine low clouds and can be explained by the “deepening–decoupling” mechanism proposed in previous studies. It is found that the seasonal variations of low-level clouds off the Peru coast are mainly caused by a large seasonal variability in sea surface temperature, whereas those off the California coast are largely attributed to the seasonal cycle in lower-tropospheric temperature.
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King, J. C., P. S. Anderson, and G. W. Mann. "The seasonal cycle of sublimation at Halley, Antarctica." Journal of Glaciology 47, no. 156 (2001): 1–8. http://dx.doi.org/10.3189/172756501781832548.
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AbstractWe have used micrometeorological data collected at Hailey Research Station, Antarctica, to estimate monthly totals of snow sublimation. Direct sublimation from the snow surface is calculated using bulk-transfer formulae, while the sublimation of blowing snow is estimated using a model for suspended-particle number density and individual particle sublimation rates. During the winter months, sublimation losses are negligible, but between November and March sublimation removes around 25% of the snowfall. Surface sublimation and sublimation of blowing snow make roughly equal contributions to this total. Estimates of sublimation using micrometeorological data agree well with estimates made from daily snow-stake measurements.
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Browse, J., K. S. Carslaw, S. R. Arnold, K. Pringle, and O. Boucher. "The scavenging processes controlling the seasonal cycle in Arctic sulphate and black carbon aerosol." Atmospheric Chemistry and Physics 12, no. 15 (August 1, 2012): 6775–98. http://dx.doi.org/10.5194/acp-12-6775-2012.
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Abstract. The seasonal cycle in Arctic aerosol is typified by high concentrations of large aged anthropogenic particles transported from lower latitudes in the late Arctic winter and early spring followed by a sharp transition to low concentrations of locally sourced smaller particles in the summer. However, multi-model assessments show that many models fail to simulate a realistic cycle. Here, we use a global aerosol microphysics model (GLOMAP) and surface-level aerosol observations to understand how wet scavenging processes control the seasonal variation in Arctic black carbon (BC) and sulphate aerosol. We show that the transition from high wintertime concentrations to low concentrations in the summer is controlled by the transition from ice-phase cloud scavenging to the much more efficient warm cloud scavenging in the late spring troposphere. This seasonal cycle is amplified further by the appearance of warm drizzling cloud in the late spring and summer boundary layer. Implementing these processes in GLOMAP greatly improves the agreement between the model and observations at the three Arctic ground-stations Alert, Barrow and Zeppelin Mountain on Svalbard. The SO4 model-observation correlation coefficient (R) increases from: −0.33 to 0.71 at Alert (82.5° N), from −0.16 to 0.70 at Point Barrow (71.0° N) and from −0.42 to 0.40 at Zeppelin Mountain (78° N). The BC model-observation correlation coefficient increases from −0.68 to 0.72 at Alert and from −0.42 to 0.44 at Barrow. Observations at three marginal Arctic sites (Janiskoski, Oulanka and Karasjok) indicate a far weaker aerosol seasonal cycle, which we show is consistent with the much smaller seasonal change in the frequency of ice clouds compared to higher latitude sites. Our results suggest that the seasonal cycle in Arctic aerosol is driven by temperature-dependent scavenging processes that may be susceptible to modification in a future climate.
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Holmes, Ryan M., Jan D. Zika, and Matthew H. England. "Diathermal Heat Transport in a Global Ocean Model." Journal of Physical Oceanography 49, no. 1 (January 2019): 141–61. http://dx.doi.org/10.1175/jpo-d-18-0098.1.
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AbstractThe rate at which the ocean moves heat from the tropics toward the poles, and from the surface into the interior, depends on diabatic surface forcing and diffusive mixing. These diabatic processes can be isolated by analyzing heat transport in a temperature coordinate (the diathermal heat transport). This framework is applied to a global ocean sea ice model at two horizontal resolutions (1/4° and 1/10°) to evaluate the partioning of the diathermal heat transport between different mixing processes and their spatial and seasonal structure. The diathermal heat transport peaks around 22°C at 1.6 PW, similar to the peak meridional heat transport. Diffusive mixing transfers this heat from waters above 22°C, where surface forcing warms the tropical ocean, to temperatures below 22°C where midlatitude waters are cooled. In the control 1/4° simulation, half of the parameterized vertical mixing is achieved by background diffusion, to which sensitivity is explored. The remainder is associated with parameterizations for surface boundary layer, shear instability, and tidal mixing. Nearly half of the seasonal cycle in the peak vertical mixing heat flux is associated with shear instability in the tropical Pacific cold tongue, highlighting this region’s global importance. The framework presented also allows for quantification of numerical mixing associated with the model’s advection scheme. Numerical mixing has a substantial seasonal cycle and increases to compensate for reduced explicit vertical mixing. Finally, applied to Argo observations the diathermal framework reveals a heat content seasonal cycle consistent with the simulations. These results highlight the utility of the diathermal framework for understanding the role of diabatic processes in ocean circulation and climate.
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Lindsay, Keith, Gordon B. Bonan, Scott C. Doney, Forrest M. Hoffman, David M. Lawrence, Matthew C. Long, Natalie M. Mahowald, J. Keith Moore, James T. Randerson, and Peter E. Thornton. "Preindustrial-Control and Twentieth-Century Carbon Cycle Experiments with the Earth System Model CESM1(BGC)." Journal of Climate 27, no. 24 (December 10, 2014): 8981–9005. http://dx.doi.org/10.1175/jcli-d-12-00565.1.
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Abstract Version 1 of the Community Earth System Model, in the configuration where its full carbon cycle is enabled, is introduced and documented. In this configuration, the terrestrial biogeochemical model, which includes carbon–nitrogen dynamics and is present in earlier model versions, is coupled to an ocean biogeochemical model and atmospheric CO2 tracers. The authors provide a description of the model, detail how preindustrial-control and twentieth-century experiments were initialized and forced, and examine the behavior of the carbon cycle in those experiments. They examine how sea- and land-to-air CO2 fluxes contribute to the increase of atmospheric CO2 in the twentieth century, analyze how atmospheric CO2 and its surface fluxes vary on interannual time scales, including how they respond to ENSO, and describe the seasonal cycle of atmospheric CO2 and its surface fluxes. While the model broadly reproduces observed aspects of the carbon cycle, there are several notable biases, including having too large of an increase in atmospheric CO2 over the twentieth century and too small of a seasonal cycle of atmospheric CO2 in the Northern Hemisphere. The biases are related to a weak response of the carbon cycle to climatic variations on interannual and seasonal time scales and to twentieth-century anthropogenic forcings, including rising CO2, land-use change, and atmospheric deposition of nitrogen.
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Davy, Richard. "The Climatology of the Atmospheric Boundary Layer in Contemporary Global Climate Models." Journal of Climate 31, no. 22 (November 2018): 9151–73. http://dx.doi.org/10.1175/jcli-d-17-0498.1.
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Here, we present the climatology of the planetary boundary layer depth in 18 contemporary general circulation models (GCMs) in simulations of the late-twentieth-century climate that were part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). We used a bulk Richardson methodology to establish the boundary layer depth from the 6-hourly synoptic-snapshot data available in the CMIP5 archives. We present an ensemble analysis of the climatological mean, diurnal cycle, and seasonal cycle of the boundary layer depth in these models and compare it to the climatologies from the ECMWF ERA-Interim reanalysis. Overall, we find that the CMIP5 models do a reasonably good job of reproducing the distribution of mean boundary layer depth, although the geographical patterns vary considerably between models. However, the models are biased toward weaker diurnal and seasonal cycles in the boundary layer depth and generally produce much deeper boundary layers at night and during the winter than are found in the reanalysis. These biases are likely to reduce the ability of these models to accurately represent other properties of the diurnal and seasonal cycles, and the sensitivity of these cycles to climate change.
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Lindqvist, H., C. W. O'Dell, S. Basu, H. Boesch, F. Chevallier, N. Deutscher, L. Feng, et al. "Does GOSAT capture the true seasonal cycle of XCO<sub>2</sub>?" Atmospheric Chemistry and Physics Discussions 15, no. 12 (June 17, 2015): 16461–503. http://dx.doi.org/10.5194/acpd-15-16461-2015.
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Abstract. The seasonal cycle accounts for a dominant mode of total column CO2 (XCO2) annual variability and is connected to CO2 uptake and release; it thus represents an important variable to accurately measure from space. We quantitatively evaluate the XCO2 seasonal cycle of the Greenhouse Gases Observing Satellite (GOSAT) observations from the Atmospheric CO2 Observations from Space (ACOS) retrieval system, and compare average regional seasonal cycle features to those directly measured by the Total Carbon Column Observing Network (TCCON). We analyze the mean seasonal cycle amplitude, dates of maximum and minimum XCO2, as well as the regional growth rates in XCO2 through the fitted trend over several years. We find that GOSAT generally captures the seasonal cycle amplitude within 1.0 ppm accuracy compared to TCCON, except in Europe, where the difference exceeds 1.0 ppm at two sites, and the amplitude captured by GOSAT is generally shallower compared to TCCON. This bias over Europe is not as large for the other GOSAT retrieval algorithms (NIES v02.21, RemoTeC v2.35, UoL v5.1, and NIES PPDF-S v.02.11), although they have significant biases at other sites. The ACOS bias correction was found to partially explain the shallow amplitude over Europe. The impact of the TCCON retrieval version, co-location method, and aerosol changes in the ACOS algorithm were also tested, and found to be few tenths-of-a-ppm and mostly non-systematic. We find generally good agreement in the date of minimum XCO2 between ACOS and TCCON, but ACOS generally infers a date of maximum XCO2 2–3 weeks later than TCCON. We further analyze the latitudinal dependence of the seasonal cycle amplitude throughout the Northern Hemisphere, and compare the dependence to that predicted by current optimized models that assimilate in-situ measurements of CO2. In the zonal averages, GOSAT agrees with the models to within 1.4 ppm, depending on the model and latitude. We also show that the seasonal cycle of XCO2 depends on longitude especially at the mid-latitudes: the amplitude of GOSAT XCO2 doubles from West US to East Asia at 45–50° N, which is only partially shown by the models. In general, we find that model-to-model differences can be larger than GOSAT-to-model differences. These results suggest that GOSAT retrievals of the XCO2 seasonal cycle may be sufficiently accurate to evaluate land surface models in regions with significant discrepancies between the models.
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Messerschmidt, J., N. Parazoo, D. Wunch, N. M. Deutscher, C. Roehl, T. Warneke, and P. O. Wennberg. "Evaluation of seasonal atmosphere–biosphere exchange estimations with TCCON measurements." Atmospheric Chemistry and Physics 13, no. 10 (May 17, 2013): 5103–15. http://dx.doi.org/10.5194/acp-13-5103-2013.
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Abstract. We evaluate three estimates of the atmosphere-biosphere exchange against total column CO2 observations from the Total Carbon Column Observing Network (TCCON). Using the GEOS-Chem transport model, we produce forward simulations of atmospheric CO2 concentrations for the 2006–2010 time period using the Carnegie-Ames-Stanford Approach (CASA), the Simple Biosphere (SiB) and the GBiome-BGC models. Large differences in the CO2 simulations result from the choice of the atmosphere-biosphere model. We evaluate the seasonal cycle phase, amplitude and shape of the simulations. The version of CASA currently used as the a priori model by the GEOS-Chem carbon cycle community poorly represents the season cycle in total column CO2. Consistent with earlier studies, enhancing the CO2 uptake in the boreal forest and shifting the onset of the growing season earlier significantly improve the simulated seasonal CO2 cycle using CASA estimates. The SiB model gives a better representation of the seasonal cycle dynamics. The difference in the seasonality of net ecosystem exchange (NEE) between these models is not the absolute gross primary productivity (GPP), but rather the differential phasing of ecosystem respiration (RE) with respect to GPP between these models.
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Liu, Liyan, Carlos Lozano, and Dan Iredell. "Time–Space SST Variability in the Atlantic during 2013: Seasonal Cycle." Journal of Atmospheric and Oceanic Technology 32, no. 9 (September 2015): 1689–705. http://dx.doi.org/10.1175/jtech-d-15-0028.1.
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AbstractA 2-yr-long daily gridded field of sea surface temperature (SST) in the Atlantic centered for the year 2013 is projected onto orthogonal components: its mean, six harmonics of the year cycle, the slow-varying contribution, and the fast-varying contribution. The periodic function defined by the year harmonics, referred to here as the seasonal harmonic, contains most of the year variability in 2013. The seasonal harmonic is examined in its spatial and temporal distribution by describing the amplitude and phase of its maxima and minima, and other associated parameters. In the seasonal harmonic, the ratio of the duration of warming period to cooling period ranges from 0.2 to 2.0. There are also differences in the spatial patterns and dominance of the year harmonics—in general associated with regions with different insolation, oceanic, and atmospheric regimes. Empirical orthogonal functions (EOFs) of the seasonal harmonic allow for a succinct description of the seasonal evolution for the Atlantic and its subdomains. The decomposition can be applied to model output, allowing for a more incisive model validation and data assimilation. The decorrelation time scale of the rapidly varying signal is found to be nearly independent of the time of the year once four or more harmonics are used. The decomposition algorithm, here implemented for a single year cycle, can be applied to obtain a multiyear average of the seasonal harmonic.
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Mathiot, P., H. Goosse, T. Fichefet, B. Barnier, and H. Gallée. "Modelling the seasonal variability of the Antarctic Slope Current." Ocean Science 7, no. 4 (July 6, 2011): 455–70. http://dx.doi.org/10.5194/os-7-455-2011.
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Abstract. One of the main features of the oceanic circulation along Antarctica is the Antarctic Slope Current (ASC). This circumpolar current flows westwards and contributes to communication between the three major oceanic basins around Antarctica. The ASC is not very well known due to remote location and the presence of sea ice during several months, allowing in situ studies only during summertime. Moreover, only few modelling studies of this current have been carried out. Here, we investigate the sensitivity of this simulated current to four different resolutions in a coupled ocean-sea ice model and to two different atmospheric forcing sets. Two series of simulations are conducted. For the first series, global model configurations are run at coarse (2°) to eddy-permitting (0.25°) resolutions with the same atmospheric forcing. For the second series, simulations with two different atmospheric forcings are performed using a regional circumpolar configuration (south of 30° S) at 0.5° resolution. The first atmospheric forcing is based on a global atmospheric reanalysis and satellite data, while the second is based on a downscaling of the global atmospheric reanalysis by a regional atmospheric model calibrated to Antarctic meteorological conditions. Sensitivity experiments to resolution indicate that a minimum model resolution of 0.5° is needed to capture the dynamics of the ASC in terms of water mass transport and recirculation. Sensitivity experiments to atmospheric forcing fields shows that the wind speed along the Antarctic coast strongly controls the water mass transport and the seasonal cycle of the ASC. An increase in annual mean of easterlies by about 30 % leads to an increase in the mean ASC transport by about 40 %. Similar effects are obtained on the seasonal cycle: using a wind forcing field with a larger seasonal cycle (+30 %) increases by more than 30 % the amplitude of the seasonal cycle of the ASC. To confirm the importance of wind seasonal cycle, a simulation without wind speed seasonal cycle is carried out. This simulation shows a decrease by more than 50 % of the amplitude of the ASC transport seasonal cycle without changing the mean value of ASC transport.
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Lynch, Amanda, David McGinnis, William L. Chapman, and Jeffrey S. Tilley. "A multivariate comparison of two land-surface models integrated into an Arctic Regional Climate System model." Annals of Glaciology 25 (1997): 127–31. http://dx.doi.org/10.3189/s0260305500013914.
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Different vegetation models impact the atmospheric response of a regional climate model in different ways, and hence have an impact upon the ability of that model to match an observed climatology. Using a multivariate principal-component analysis, we investigate the relationships between several land-surface models (BATS, LSM) coupled to a regional climate model, and observed climate parameters over the North Slope of Alaska. In this application, annual cycle simulations at 20 km spatial resolution are compared with European Centre for Medium-Range Weather Forecasts (ECMWF) climatology. Initial results demonstrate broad agreement between all models; however, small-scale regional variations between land-surface models indicate the strengths and weaknesses of the land-surface treatments in a climate system model. Specifically, we found that the greater surface-moisture availability and temperature-dependent albedo formulation of the LSM model allow for a higher proportion of low-level cloud, and a later, more rapid transition from the winter to the summer regime. Crucial to this transition is the seasonal cycle of incoming solar radiation. These preliminary results indicate the importance of the land-surface hydrologic cycle in modelling the seasonal transitions.
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Lynch, Amanda, David McGinnis, William L. Chapman, and Jeffrey S. Tilley. "A multivariate comparison of two land-surface models integrated into an Arctic Regional Climate System model." Annals of Glaciology 25 (1997): 127–31. http://dx.doi.org/10.1017/s0260305500013914.
Full textAbstract:
Different vegetation models impact the atmospheric response of a regional climate model in different ways, and hence have an impact upon the ability of that model to match an observed climatology. Using a multivariate principal-component analysis, we investigate the relationships between several land-surface models (BATS, LSM) coupled to a regional climate model, and observed climate parameters over the North Slope of Alaska. In this application, annual cycle simulations at 20 km spatial resolution are compared with European Centre for Medium-Range Weather Forecasts (ECMWF) climatology. Initial results demonstrate broad agreement between all models; however, small-scale regional variations between land-surface models indicate the strengths and weaknesses of the land-surface treatments in a climate system model. Specifically, we found that the greater surface-moisture availability and temperature-dependent albedo formulation of the LSM model allow for a higher proportion of low-level cloud, and a later, more rapid transition from the winter to the summer regime. Crucial to this transition is the seasonal cycle of incoming solar radiation. These preliminary results indicate the importance of the land-surface hydrologic cycle in modelling the seasonal transitions.
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Cholette, Pierre A. "La désaisonnalisation pour le non-spécialiste." L'Actualité économique 59, no. 1 (January 19, 2009): 144–52. http://dx.doi.org/10.7202/601049ar.
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Abstract This paper provides simple descriptions and interpretations of the components found in time series: the trend, the cycle, the seasonal, the trading-day and the irregular components. Furthermore, the necessity and the justification ofseasonal adjustment are explained. It is however reminded the seasonally adjusted series should not be used for model building.
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Boersma, K. F., D. J. Jacob, M. Trainic, Y. Rudich, I. DeSmedt, R. Dirksen, and H. J. Eskes. "Validation of urban NO<sub>2</sub> concentrations and their diurnal and seasonal variations observed from space (SCIAMACHY and OMI sensors) using in situ measurements in Israeli cities." Atmospheric Chemistry and Physics Discussions 9, no. 1 (February 10, 2009): 4301–33. http://dx.doi.org/10.5194/acpd-9-4301-2009.
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Abstract. We compare a full-year (2006) record of surface air NO2 concentrations measured in Israeli cities to coinciding retrievals of tropospheric NO2 columns from satellite sensors (SCIAMACHY aboard ENVISAT and OMI aboard Aura). This provides a large statistical data set for validation of NO2 satellite measurements in urban air, where validation is difficult yet crucial for using these measurements to infer NOx emissions by inverse modeling. Assuming that NO2 is well-mixed throughout the boundary layer (BL), and using observed average seasonal boundary layer heights, near-surface NO2 concentrations are converted into BL NO2 columns. The agreement between OMI and (13:45) BL NO2 columns (slope=0.93, n=542), and the comparable results at 10:00 h for SCIAMACHY, allow a validation of the seasonal, weekly, and diurnal cycles in satellite-derived NO2. OMI and BL NO2 columns show consistent seasonal cycles (winter NO2 1.6–2.7× higher than summer). BL and coinciding OMI columns both show a strong weekly cycle with 45–50% smaller NO2 columns on Saturday relative to the weekday mean, reflecting the reduced weekend activity, and validating the weekly cycle observed from space. The diurnal difference between SCIAMACHY (10:00) and OMI (13:45) NO2 is maximum in summer when SCIAMACHY is up to 40% higher than OMI, and minimum in winter when OMI slightly exceeds SCIAMACHY. A similar seasonal variation in the diurnal difference is found in the source region of Cairo. The surface measurements in Israel cities confirm this seasonal variation in the diurnal cycle. Using simulations from a global 3-D chemical transport model (GEOS-Chem), we show that this seasonal cycle can be explained by a much stronger photochemical loss of NO2 in summer than in winter.
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Boersma, K. F., D. J. Jacob, M. Trainic, Y. Rudich, I. DeSmedt, R. Dirksen, and H. J. Eskes. "Validation of urban NO<sub>2</sub> concentrations and their diurnal and seasonal variations observed from the SCIAMACHY and OMI sensors using in situ surface measurements in Israeli cities." Atmospheric Chemistry and Physics 9, no. 12 (June 15, 2009): 3867–79. http://dx.doi.org/10.5194/acp-9-3867-2009.
Full textAbstract:
Abstract. We compare a full-year (2006) record of surface air NO2 concentrations measured in Israeli cities to coinciding retrievals of tropospheric NO2 columns from satellite sensors (SCIAMACHY aboard ENVISAT and OMI aboard Aura). This provides a large statistical data set for validation of NO2 satellite measurements in urban air, where validation is difficult yet crucial for using these measurements to infer NOx emissions by inverse modeling. Assuming that NO2 is well-mixed throughout the boundary layer (BL), and using observed average seasonal boundary layer heights, near-surface NO2 concentrations are converted into BL NO2 columns. The agreement between OMI and (13:45) BL NO2 columns (slope=0.93, n=542), and the comparable results at 10:00 h for SCIAMACHY, allow a validation of the seasonal, weekly, and diurnal cycles in satellite-derived NO2. OMI and BL NO2 columns show consistent seasonal cycles (winter NO2 1.6–2.7× higher than summer). BL and coinciding OMI columns both show a strong weekly cycle with 45–50% smaller NO2 columns on Saturday relative to the weekday mean, reflecting the reduced weekend activity, and validating the weekly cycle observed from space. The diurnal difference between SCIAMACHY (10:00) and OMI (13:45) NO2 is maximum in summer when SCIAMACHY is up to 40% higher than OMI, and minimum in winter when OMI slightly exceeds SCIAMACHY. A similar seasonal variation in the diurnal difference is found in the source region of Cairo. The surface measurements in Israel cities confirm this seasonal variation in the diurnal cycle. Using simulations from a global 3-D chemical transport model (GEOS-Chem), we show that this seasonal cycle can be explained by a much stronger photochemical loss of NO2 in summer than in winter.
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Behrens, L. K., T. Martin, V. A. Semenov, and M. Latif. "The Arctic Sea ice in the CMIP3 climate model ensemble – variability and anthropogenic change." Cryosphere Discussions 6, no. 6 (December 19, 2012): 5317–44. http://dx.doi.org/10.5194/tcd-6-5317-2012.
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Abstract. The strongest manifestation of global warming is observed in the Arctic. The warming in the Arctic during the recent decades is about twice as strong as in the global average and has been accompanied by a summer sea ice decline that is very likely unprecedented during the last millennium. Here, Arctic sea ice variability is analyzed in the ensemble of CMIP3 models. Complementary to several previous studies, we focus on regional aspects, in particular on the Barents Sea. We also investigate the changes in the seasonal cycle and interannual variability. In all regions, the models predict a reduction in sea ice area and sea ice volume during 1900–2100. Toward the end of the 21st century, the models simulate higher sea ice area variability in September than in March, whereas the variability in the preindustrial control runs is higher in March. Furthermore, the amplitude and phase of the sea ice seasonal cycle change in response to enhanced greenhouse warming. The amplitude of the sea ice area seasonal cycle increases due to the very strong sea ice area decline in September. The seasonal cycle amplitude of the sea ice volume decreases due to the stronger reduction of sea ice volume in March. Multi-model mean estimates for the late 20th century are comparable with observational data only for the entire Arctic and the Central Arctic. In the Barents Sea, differences between the multi-model mean and the observational data are more pronounced. Regional sea ice sensitivity to Northern Hemisphere average surface warming has been investigated.
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Jun, Li, and H. Jay Zwally. "Modeled seasonal variations of firn density induced by steady-state surface air-temperature cycle." Annals of Glaciology 34 (2002): 299–302. http://dx.doi.org/10.3189/172756402781817707.
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AbstractSeasonal variations of firn density in ice-sheet firn layers have been attributed to variations in deposition processes or other processes within the upper firn. A recent high-resolution (mm-scale) density profile, measured along a 181 m core from Antarctica, showed small-scale density variations with a clear seasonal cycle that apparently was not related to seasonal variations in deposition or known near-surface processes (Gerland and others, 1999). A recent model of surface elevation changes (Zwally and Li, in press) produced a seasonal variation in firn densification, and explained the seasonal surface elevation changes observed by satellite radar altimeters. In this study, we apply our one-dimensional time-dependent numerical model of firn densification that includes a temperature-dependent formulation of firn densification based on laboratory measurements of grain growth. The model is driven by a steady-state seasonal surface temperature and a constant accumulation rate appropriate for the measured Antarctic ice core. The modeled seasonal variations in firn density show that the layers of snow deposited during spring to mid-summer that have the highest temperature history compress to the highest density, and the layers deposited during later summer to autumn that have the lowest temperature history compress to the lowest density. The initial amplitude of the seasonal difference of about 0.13 reduces to about 0.09 in 5 years and asymptotically to 0.0 at greater depth, which is consistent with the core measurements.
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Spragg, Jon Edward. "Articulating the fashion product life-cycle." Journal of Fashion Marketing and Management: An International Journal 21, no. 4 (September 11, 2017): 499–511. http://dx.doi.org/10.1108/jfmm-03-2017-0029.
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Purpose The purpose of this paper is to describe a framework for predicting the seasonal demand for fashion based on the Bass Diffusion model of demand and the Newsvendor inventory management model. Sales and inventory management simulations based on these models have been implemented in the Julia programming language to demonstrate how theoretical models can be made operational using open-source software for the benefit of small- to medium-scale enterprises with limited resources. Design/methodology/approach The paper employs simulation models implemented in the Julia programming languages to explore the use of theoretical models of demand on the seasonal management of fashion inventory. Findings The research demonstrates that further exploration of the framework described is worth undertaking. Research limitations/implications The paper employs theoretical models and is therefore conceptual in its outlook. Nonetheless it provides insights that could be explored further if real-world sales data would become available. Practical implications The framework provides simple models for predicting the demand for fashion that allows “what-if” scenarios to be constructed based on the manipulation of a few model parameters. Social implications The framework provides low-cost analytical tools that support small fashion enterprises with regards to market understanding and the operational management requirements necessary to support those markets. Originality/value The analytical use of the Bass model of demand with the Newsvendor model of inventory management within a fashion context.
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Liu, Zhengyu, Lei Fan, Sang-Ik Shin, and Qinyu Liu. "Assessing Atmospheric Response to Surface Forcing in the Observations. Part II: Cross Validation of Seasonal Response Using GEFA and LIM." Journal of Climate 25, no. 19 (May 9, 2012): 6817–34. http://dx.doi.org/10.1175/jcli-d-11-00630.1.
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Abstract The authors compared the assessment of the seasonal cycle of the atmospheric response to surface forcing in three statistical methods, generalized equilibrium feedback analysis (GEFA), linear inverse modeling (LIM), and fluctuation–dissipation theorem (FDT). These methods are applied to both a conceptual climate model and the observation. It is found that LIM and GEFA are able to reproduce the major features of the seasonal response consistently, whereas FDT tends to generate a bias of the phase of the seasonal cycle. The success of LIM and GEFA for the assessment of the seasonal response is due to the slowly varying nature of the annual cycle relative to the atmospheric response time. Therefore, the authors recommend GEFA and LIM as two independent methods for the assessment of the seasonal atmospheric response in the observation.