Ecosystem modelling of the cycling of marine dimethylsulfide: a review of current approaches and of the potential for extrapolation to global scales

2004 ◽  
Vol 61 (5) ◽  
pp. 845-856 ◽  
Author(s):  
Alain F Vézina

There is rising interest from oceanic and atmospheric scientists in the potential role of dimethylsulphide (DMS) in regulating global climate. The increased availability of field observations of DMS and related compounds (DMS(P)) and of their transformation rates in the ocean has stimulated the development of ecosystem models of marine sulfur cycling. The models cover a wide range of complexity levels and spatial/temporal scales, from zero-dimensional local simulations spanning a few days to regional/global simulations driven by ocean general circulation models. The degree of complexity required to model DMS(P) dynamics, particularly the differentiation into phyto plankton species or groups, remains an important open question. First attempts to drive these models with vertically resolved turbulence models suggest interesting interactions between DMS(P) dynamics and fine-scale ocean mixing that can modify fluxes of DMS to the atmosphere. Recent models also bring into focus the strong affinities between the cycling of DMS(P) and that of dissolved organic carbon in the surface ocean. Formal parameter estimation techniques, which are increasingly used in ecosystem modelling of carbon and nitrogen dynamics, should play a stronger role in the development of DMS sulfur modelling. Extrapolation of DMS cycling and fluxes to the global scale presently relies largely on empirical approach. A semiempirical approach, based on a simple ecosystem model, is shown to reproduce gross features of the global distribution of DMS in the surface ocean. This shows promise for the continuing development of ecosystem models for global modelling of marine sulfur fluxes to the atmosphere.

2009 ◽  
Vol 66 (1) ◽  
pp. 105-115 ◽  
Author(s):  
Alexandru Rap ◽  
Satyajit Ghosh ◽  
Michael H. Smith

Abstract This paper presents a novel method based on the application of interpolation techniques to the multicomponent aerosol–cloud parameterization for global climate modeling. Quantifying the aerosol indirect effect still remains a difficult task, and thus developing parameterizations for general circulation models (GCMs) of the microphysics of clouds and their interactions with aerosols is a major challenge for climate modelers. Three aerosol species are considered in this paper—namely sulfate, sea salt, and biomass smoke—and a detailed microphysical chemical parcel model is used to obtain a dataset of points relating the cloud droplet number concentration (CDNC) to the three aerosol input masses. The resulting variation of CDNC with the aerosol mass has some nonlinear features that require a complex but efficient parameterization to be easily incorporated into GCMs. In bicomponent systems, simple interpolation techniques may be sufficient to relate the CDNC to the aerosol mass, but with increasing components, simple methods fail. The parameterization technique proposed in this study employs either the modified Shepard interpolation method or the Hardy multiquadrics interpolation method, and the numerical results obtained show that both methods provide realistic results for a wide range of aerosol mass loadings. This is the first application of these two interpolation techniques to aerosol–cloud interaction studies.


Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1509
Author(s):  
Mengru Zhang ◽  
Xiaoli Yang ◽  
Liliang Ren ◽  
Ming Pan ◽  
Shanhu Jiang ◽  
...  

In the context of global climate change, it is important to monitor abnormal changes in extreme precipitation events that lead to frequent floods. This research used precipitation indices to describe variations in extreme precipitation and analyzed the characteristics of extreme precipitation in four climatic (arid, semi-arid, semi-humid and humid) regions across China. The equidistant cumulative distribution function (EDCDF) method was used to downscale and bias-correct daily precipitation in eight Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs). From 1961 to 2005, the humid region had stronger and longer extreme precipitation compared with the other regions. In the future, the projected extreme precipitation is mainly concentrated in summer, and there will be large areas with substantial changes in maximum consecutive 5-day precipitation (Rx5) and precipitation intensity (SDII). The greatest differences between two scenarios (RCP4.5 and RCP8.5) are in semi-arid and semi-humid areas for summer precipitation anomalies. However, the area of the four regions with an increasing trend of extreme precipitation is larger under the RCP8.5 scenario than that under the RCP4.5 scenario. The increasing trend of extreme precipitation in the future is relatively pronounced, especially in humid areas, implying a potential heightened flood risk in these areas.


2017 ◽  
Author(s):  
Amanda Frigola ◽  
Matthias Prange ◽  
Michael Schulz

Abstract. The Middle Miocene Climate Transition was characterized by major Antarctic ice-sheet expansion and global cooling during the interval ~ 15–13 Ma. Here we present two sets of boundary conditions for global general circulation models characterizing the periods before (Middle Miocene Climatic Optimum; MMCO) and after (Middle Miocene Glaciation; MMG) the transition. These boundary conditions include Middle Miocene global topography, bathymetry and vegetation. Additionally, Antarctic ice volume and geometry, sea-level and atmospheric CO2 concentration estimates for the MMCO and the MMG are reviewed. The boundary-condition files are available for use as input in a wide variety of global climate models and constitute a valuable tool for modeling studies with a focus on the Middle Miocene.


2014 ◽  
Vol 10 (2) ◽  
pp. 697-713 ◽  
Author(s):  
G. Le Hir ◽  
Y. Teitler ◽  
F. Fluteau ◽  
Y. Donnadieu ◽  
P. Philippot

Abstract. During the Archaean, the Sun's luminosity was 18 to 25% lower than the present day. One-dimensional radiative convective models (RCM) generally infer that high concentrations of greenhouse gases (CO2, CH4) are required to prevent the early Earth's surface temperature from dropping below the freezing point of liquid water and satisfying the faint young Sun paradox (FYSP, an Earth temperature at least as warm as today). Using a one-dimensional (1-D) model, it was proposed in 2010 that the association of a reduced albedo and less reflective clouds may have been responsible for the maintenance of a warm climate during the Archaean without requiring high concentrations of atmospheric CO2 (pCO2). More recently, 3-D climate simulations have been performed using atmospheric general circulation models (AGCM) and Earth system models of intermediate complexity (EMIC). These studies were able to solve the FYSP through a large range of carbon dioxide concentrations, from 0.6 bar with an EMIC to several millibars with AGCMs. To better understand this wide range in pCO2, we investigated the early Earth climate using an atmospheric GCM coupled to a slab ocean. Our simulations include the ice-albedo feedback and specific Archaean climatic factors such as a faster Earth rotation rate, high atmospheric concentrations of CO2 and/or CH4, a reduced continental surface, a saltier ocean, and different cloudiness. We estimated full glaciation thresholds for the early Archaean and quantified positive radiative forcing required to solve the FYSP. We also demonstrated why RCM and EMIC tend to overestimate greenhouse gas concentrations required to avoid full glaciations or solve the FYSP. Carbon cycle–climate interplays and conditions for sustaining pCO2 will be discussed in a companion paper.


2018 ◽  
Author(s):  
Duncan Ackerley ◽  
Robin Chadwick ◽  
Dietmar Dommenget ◽  
Paola Petrelli

Abstract. General circulation models (GCMs) are routinely run under Atmospheric Modelling Intercomparison Project (AMIP) conditions with prescribed sea surface temperatures (SSTs) and sea ice concentrations (SICs) from observations. These AMIP simulations are often used to evaluate the role of the land and/or atmosphere in causing the development of systematic errors in such GCMs. Extensions to the original AMIP experiment have also been developed to evaluate the response of the global climate to increased SSTs (prescribed) and carbon-dioxide (CO2) as part of the Cloud Feedback Model Intercomparison Project (CFMIP). None of these international modelling initiatives has undertaken a set of experiments where the land conditions are also prescribed, which is the focus of the work presented in this paper. Experiments are performed initially with freely varying land conditions (surface temperature and, soil temperature and mositure) under five different configurations (AMIP, AMIP with uniform 4 K added to SSTs, AMIP SST with quadrupled CO2, AMIP SST and quadrupled CO2 without the plant stomata response, and increasing the solar constant by 3.3 %). Then, the land surface temperatures from the free-land experiments are used to perform a set of “AMIP-prescribed land” (PL) simulations, which are evaluated against their free-land counterparts. The PL simulations agree well with the free-land experiments, which indicates that the land surface is prescribed in a way that is consistent with the original free-land configuration. Further experiments are also performed with different combinations of SSTs, CO2 concentrations, solar constant and land conditions. For example, SST and land conditions are used from the AMIP simulation with quadrupled CO2 in order to simulate the atmospheric response to increased CO2 concentrations without the surface temperature changing. The results of all these experiments have been made publicly available for further analysis. The main aims of this paper are to provide a description of the method used and an initial validation of these AMIP-prescribed land experiments.


2013 ◽  
Vol 6 (5) ◽  
pp. 8371-8411 ◽  
Author(s):  
S. Zeng ◽  
J. Riedi ◽  
F. Parol ◽  
C. Cornet ◽  
F. Thieuleux

Abstract. The A-Train observations provide an unprecedented opportunity for the production of high quality dataset describing cloud properties. We illustrate in this study the use of one year of coincident POLDER (Polarization and Directionality of the Earth Reflectance), MODIS (MODerate Resolution Imaging Spectroradiometer) and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) observations to establish a reference dataset for the description of cloud top thermodynamic phase at global scale. We present the results of an extensive comparison between POLDER and MODIS cloud top phase products and discuss those in view of cloud vertical structure and optical properties derived simultaneously from collocated CALIOP active measurements. These results allow to identify and quantify potential biases present in the 3 considered dataset. Among those, we discuss the impacts of observation geometry, thin cirrus in multilayered and single layered cloud systems, supercooled liquid droplets, aerosols, fractional cloud cover and snow/ice or bright surfaces on global statistics of cloud phase derived from POLDER and MODIS passive measurements. Based on these analysis we define criteria for the selection of high confidence cloud phase retrievals which in turn can serve for the establishment of a reference cloud phase product. This high confidence joint product derived from POLDER/PARASOL and MODIS/Aqua can be used in the future as a benchmark for the evaluation of other cloud climatologies, for the assessment of cloud phase representation in models and the development of better cloud phase parametrization in the general circulation models (GCMs).


Author(s):  
Paul D. Williams ◽  
Michael J. P. Cullen ◽  
Michael K. Davey ◽  
John M. Huthnance

The societal need for reliable climate predictions and a proper assessment of their uncertainties is pressing. Uncertainties arise not only from initial conditions and forcing scenarios, but also from model formulation. Here, we identify and document three broad classes of problems, each representing what we regard to be an outstanding challenge in the area of mathematics applied to the climate system. First, there is the problem of the development and evaluation of simple physically based models of the global climate. Second, there is the problem of the development and evaluation of the components of complex models such as general circulation models. Third, there is the problem of the development and evaluation of appropriate statistical frameworks. We discuss these problems in turn, emphasizing the recent progress made by the papers presented in this Theme Issue. Many pressing challenges in climate science require closer collaboration between climate scientists, mathematicians and statisticians. We hope the papers contained in this Theme Issue will act as inspiration for such collaborations and for setting future research directions.


2018 ◽  
Vol 75 (7) ◽  
pp. 2217-2233 ◽  
Author(s):  
Guanglin Tang ◽  
Ping Yang ◽  
George W. Kattawar ◽  
Xianglei Huang ◽  
Eli J. Mlawer ◽  
...  

Abstract Cloud longwave scattering is generally neglected in general circulation models (GCMs), but it plays a significant and highly uncertain role in the atmospheric energy budget as demonstrated in recent studies. To reduce the errors caused by neglecting cloud longwave scattering, two new radiance adjustment methods are developed that retain the computational efficiency of broadband radiative transfer simulations. In particular, two existing scaling methods and the two new adjustment methods are implemented in the Rapid Radiative Transfer Model (RRTM). The results are then compared with those based on the Discrete Ordinate Radiative Transfer model (DISORT) that explicitly accounts for multiple scattering by clouds. The two scaling methods are shown to improve the accuracy of radiative transfer simulations for optically thin clouds but not effectively for optically thick clouds. However, the adjustment methods reduce computational errors over a wide range, from optically thin to thick clouds. With the adjustment methods, the errors resulting from neglecting cloud longwave scattering are reduced to less than 2 W m−2 for the upward irradiance at the top of the atmosphere and less than 0.5 W m−2 for the surface downward irradiance. The adjustment schemes prove to be more accurate and efficient than a four-stream approximation that explicitly accounts for multiple scattering. The neglect of cloud longwave scattering results in an underestimate of the surface downward irradiance (cooling effect), but the errors are almost eliminated by the adjustment methods (warming effect).


2019 ◽  
Vol 32 (10) ◽  
pp. 2869-2885
Author(s):  
Paolo Ruggieri ◽  
Fred Kucharski ◽  
Lenka Novak

Abstract Given the recent changes in the Arctic sea ice, understanding the effects of the resultant polar warming on the global climate is of great importance. However, the interaction between the Arctic and midlatitude circulation involves a complex chain of mechanisms, which leaves state-of-the-art general circulation models unable to represent this interaction unambiguously. This study uses an idealized general circulation model to provide a process-based understanding of the sensitivity of the midlatitude circulation to the location of high-latitude warming. A simplified atmosphere is simulated with a single zonally localized midlatitude storm track, which is analogous to the storm tracks in the Northern Hemisphere. It is found that even small changes in the position of the forcing relative to that storm track can lead to very different responses in the midlatitude circulation. More specifically, it is found that heating concentrated in one region may cause a substantially stronger global response compared to when the same amount of heating is distributed across all longitudes at the same latitude. Linear interference between climatological and anomalous flow is an important component of the response, but it does not explain differences between different longitudes of the forcing. Feedbacks from atmospheric transient eddies are found to be associated with this strong response. A dependence between the climatological jet latitude and the jet response to polar surface heating is found. These results can be used to design and interpret experiments with complex state-of-the-art models targeted at Arctic–midlatitude interactions.


2012 ◽  
Vol 25 (17) ◽  
pp. 6036-6056 ◽  
Author(s):  
Minghong Zhang ◽  
Shuanglin Li ◽  
Jian Lu ◽  
Renguang Wu

Abstract This study examines the skills in simulating interannual variability of northwestern Pacific (NWP) summer climate in 12 atmospheric general circulation models (AGCMs) attending the Atmospheric Model Intercomparison Project phase 2 (AMIP II). The models show a wide range of skills, among those version 1 of the Hadley Centre Global Atmosphere Model (HadGAM1) showed the highest fidelity and thus may be a better choice for studying East Asian–NWP summer climate. To understand the possible causes for the difference among the models, five models {HadGAM1; ECHAM5; the Geophysical Fluid Dynamics Laboratory Atmosphere Model, version 2.1 (AM2.1); Model for Interdisciplinary Research on Climate 3.2, high-resolution version [MIROC3.2(hires)]; and the fourth-generation National Center for Atmospheric Research Community Atmosphere Model (CAM3)} that have various skill levels, ranging from the highest to the moderate to the minor, were selected for analyses. The simulated teleconnection of NWP summer climate with sea surface temperatures (SSTs) in the tropical Indian and Pacific Oceans was first compared. HadGAM1 reproduces suppressed (intensified) rainfall during El Niño (La Niña) events and captures well the remote connection with the tropical Indian Ocean, while the other models either underestimate [ECHAM5, AM2.1, MIROC3.2(hires)] or fail to reproduce (CAM3) these teleconnections. The Walker cell and diabatic heating were further compared to shed light on the underlying physical mechanisms for the difference. Consistent with the best performance in simulating interannual rainfall, HadGAM1 exhibits the highest-level skill in capturing the observed climatology of the Walker cell and diabatic heating. These results highlight the key roles of the model’s background climatology in the Walker cell and diabatic heating, thus providing important clues to improving the model’s ability.


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