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Assessment To The Global Air-Sea CO2 Flux In 22 CMIP5 Earth System Models

Posted on:2017-09-18Degree:DoctorType:Dissertation
Country:ChinaCandidate:F DonFull Text:PDF
GTID:1310330533955227Subject:Environmental Science and Engineering
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Ocean is an important carbon sink of atmosphere.Model results of the air-sea CO2 flux affect the future climate simulation directly.To assess the capability of latest Earth System Models?ESMs?in representing historical global air-sea CO2 flux,results associated with ocean carbon in 22 models from Phase 5 of the Coupled Model Intercomparision Project?CMIP5?are analyzed,with focuses on the spatial distribution of multiyear mean,the air-sea CO2 flux interannual variability over the global ocean and tropical Pacific.The response of tropical Pacific air-sea CO2 flux to El Ni?o–Southern Oscillation?ENSO?events was further investigated.Simulated biases of air-sea CO2 flux were analyzed according to associated physical and biogeochemical factors.The influences of biological activity and the sea surface wind speed on the interannual variability of air-sea CO2 flux were investigated through an ocean carbon cycle model developed by Chinese researchers.The main results and conclusions are as follows.?1?More than half of CMIP5-ESMs?Earth System Models in CMIP5?capture the distribution of air-sea CO2 flux well and four models have poor performance.The differences in model-model and biases between models and observational results mainly exist in regions with strong vertical movement.Biases of the simulated carbon flux were mainly caused by the physical biases?for example,the colder SST in the Northwest Pacific;the weaker AMOC;unrealistic deep convection over the South Ocean?in most models.The annual mean flux in the 18-member multimodel ensemble?MME;four models were excluded because of their poor performances?mean during 1996-2004 is 1.95 Pg C yr-1?1 Pg = 1015 g;positive means into the ocean?,which is close to the observational results.?2?The first mode of the global air-sea CO2 flux variability in six of the models represents the ENSO mode.The remaining 12 models fail to represent this important character for following reasons: in five models,the tropical Pacific does not play a dominant role in the interannual variability of global air-sea CO2 flux due to stronger interannual variability in the Southern Ocean;two models poorly represent the interannual fluctuation of dissolved inorganic carbon?DIC?in the surface ocean of the tropical Pacific;and four models have shorter periods of the air-sea CO2 flux,which are out of the period range of ENSO events.?3?Over the tropical Pacific,although the contributions of gas exchange coefficient?K?and difference of CO2 partial pressure between air and sea??pCO2?to the interannual variability of air-sea CO2 flux are nearly equal,the main factor leading to the unreasonable interannual variability of air-sea CO2 flux stems form partial pressure of CO2 in the surface sea water?pCO2sea?.Reasons to models not being able to represent the reasonable interannual variation of the tropical Pacific air-sea CO2 flux are determined through an improved quantitative analysis method.?4?Results based on the ocean carbon cycle model?IAP-OBM?show that biological activity has obvious influence on nutrient and productivity in the sea surface,which furthermore affects the climatic mean state of air-sea CO2 flux.However,the biological activity plays a small role in regulating the interannual variability of the air-sea CO2 flux.In our study,we found that the variation of sea surface wind speed mainly affects the interannual variability of air-sea CO2 flux over the central tropical Pacific.This study investigated model biases and the underlying causes from aspects of coupled physical field and ocean carbon,and found the the dominating role of biases form physical processes in the air-sea CO2 flux biases.These results have important scienctific significance and application value for climate change research and improvement of coupled model.
Keywords/Search Tags:CMIP5 models, Air-sea CO2 flux, Multiyear mean, Interannual variability
PDF Full Text Request
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