Influence of El Niño on Midtropospheric CO2 from Atmospheric Infrared Sounder and Model

Jiang, Xun; Wang, Jingqian; Olsen, E. T.; Liang, Mao‐Chang; Pagano, Thomas S.; Chen, Luke L.; Licata, S. J.; Yung, Yuk L.

doi:10.1175/jas-d-11-0282.1

Cited by 19 publications

(16 citation statements)

References 23 publications

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“…El Niño Southern Oscillation (ENSO) signals have been removed from the precipitation time series at each location by a multiple regression method to avoid large biases in the trend due to significant interannual variability. We first regress the original time series on first, second, and third Legendre polynomials, annual cycle, semiannual cycle, and ENSO signal [30]. Then we subtract the ENSO signal from the original time series.…”

Section: Resultsmentioning

confidence: 99%

Investigation of Precipitation Variations over Wet and Dry Areas from Observation and Model

Trammell

Jiang

et al. 2015

Advances in Meteorology

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Our observational study revealed that the precipitation increased over the wet area and decreased over the dry area during the past two decades. Here, we further investigate whether the current atmospheric models can quantitatively capture the characteristics of precipitation from the observation. The NASA Goddard Institute for Space Studies (GISS) model is used to examine the historic simulation of the precipitation, in which the historic greenhouse gases and aerosols are included in the radiative forcing. The consistency between the historic GISS simulation and the Global Precipitation Climatology Project (GPCP) precipitation suggests that the model can qualitatively capture the temporal trends of precipitation over the wet and dry areas. However, the precipitation trends are weaker in the model than in the observation. The observed trends of precipitation do not appear in the control simulation with the fixed concentrations of greenhouse gases and aerosols, which suggests that the global warming due to anthropogenic forcing can influence the temporal variations of precipitation over the wet and dry areas. Diagnostic studies of other variables from the model further suggest that enhanced rising air can increase the precipitation over the wet area.

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Section: Resultsmentioning

confidence: 99%

Investigation of Precipitation Variations over Wet and Dry Areas from Observation and Model

Trammell

Jiang

et al. 2015

Advances in Meteorology

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“…[] with a nadir footprint of 90 by 90 km 2 [ Chahine et al ., ]. AIRS CO 2 observations have been used to study temporal [e.g., Jiang et al ., ; Li et al ., ] and spatial [e.g., Ruzmaikin et al ., ; Bai et al ., ] variability in midtropospheric CO 2 , to evaluate atmospheric CO 2 simulations [e.g., Feng et al ., ], and for data assimilation studies [e.g., Liu et al ., ; Engelen et al ., ].…”

Section: Comparison With Co2 Observational Recordsmentioning

confidence: 99%

Assessing the magnitude of CO₂ flux uncertainty in atmospheric CO₂ records using products from NASA's Carbon Monitoring Flux Pilot Project

et al. 2015

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NASA's Carbon Monitoring System Flux Pilot Project (FPP) was designed to better understand contemporary carbon fluxes by bringing together state-of-the art models with remote sensing data sets. Here we report on simulations using NASA's Goddard Earth Observing System Model, version 5 (GEOS-5) which was used to evaluate the consistency of two different sets of observationally informed land and ocean fluxes with atmospheric CO 2 records. Despite the observation inputs, the average difference in annual terrestrial biosphere flux between the two land (NASA Ames Carnegie-Ames-Stanford-Approach (CASA) and CASA-Global Fire Emissions Database version 3 (GFED)) models is 1.7 Pg C for 2009-2010. Ocean models (NASA's Ocean Biogeochemical Model (NOBM) and Estimating the Circulation and Climate of the Ocean Phase II (ECCO2)-Darwin) differ by 35% in their global estimates of carbon flux with particularly strong disagreement in high latitudes. Based upon combinations of terrestrial and ocean fluxes, GEOS-5 reasonably simulated the seasonal cycle observed at Northern Hemisphere surface sites and by the Greenhouse gases Observing SATellite (GOSAT) while the model struggled to simulate the seasonal cycle at Southern Hemisphere surface locations. Though GEOS-5 was able to reasonably reproduce the patterns of XCO 2 observed by GOSAT, it struggled to reproduce these aspects of Atmospheric Infrared Sounder observations. Despite large differences between land and ocean flux estimates, resulting differences in atmospheric mixing ratio were small, typically less than 5 ppm at the surface and 3 ppm in the XCO 2 column. A statistical analysis based on the variability of observations shows that flux differences of these magnitudes are difficult to distinguish from inherent measurement variability, regardless of the measurement platform.

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“…The interannual variability of the two time series is further investigated by filtering out high‐frequency oscillations. All high‐frequency oscillations with period smaller than 15 months are removed using a low‐pass filter [ Jiang et al ., ]. As shown in Figure b, the two low‐pass‐filtered time series correlate well, with a correlation coefficient of 0.96 (significance level 1%), which implies a significant correlation for the interannual signals in the two time series (CH 4 differences and SOI).…”

Section: Resultsmentioning

confidence: 99%

“…El Niño-Southern Oscillation (ENSO) has an important influence on large-scale wind patterns, temperature, pressure, precipitation, and trace gases [Gage and Reid, 1987;Jiang et al, 2010Jiang et al, , 2013. It was found that ENSO could influence concentrations of CO 2 and ozone [Jiang et al, 2010;Wang et al, 2011].…”

Section: Introductionmentioning

confidence: 99%

Modulation of midtropospheric methane by El Niño

Corbett

Jiang

Xiong

et al. 2017

Earth and Space Science

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Atmospheric Infrared Sounder (AIRS) midtropospheric methane (CH4) data are utilized to study the variation of methane concentrations over the Pacific Ocean with an emphasis on the correlation to El Niño–Southern Oscillation (ENSO). When El Niño events happen, the rising air over the central Pacific can bring low surface concentrations of CH4 over the ocean into midtroposphere, resulting in a reduction of midtropospheric CH4 over the region. On the contrary, the rising air over the western Pacific brings low surface CH4 to the midtroposphere during the La Nina events, which leads to negative midtropospheric CH4 anomalies over the western Pacific. In the horizontal direction, there are stronger southward winds during El Niño than La Niña months in the region of the western Pacific Ocean. The stronger southward winds during El Niño can enhance the transport of high‐concentration CH4 from the Northern Hemisphere to the tropical western Pacific region and contribute to the positive CH4 anomalies over the region. The difference of midtropospheric CH4 can reach +15 ppb (−15 ppb) over the western (central) Pacific between El Niño and La Niña events. The noteworthy difference of CH4 has a significant correlation to the Southern Oscillation Index with a correlation coefficient of 0.74. The change in the transports associated with the ENSO event is an important factor for CH4 anomalies in the middle troposphere. Results found in this study can help us better understand the spatiotemporal variability of methane.

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Influence of El Niño on Midtropospheric CO2 from Atmospheric Infrared Sounder and Model

Cited by 19 publications

References 23 publications

Investigation of Precipitation Variations over Wet and Dry Areas from Observation and Model

Investigation of Precipitation Variations over Wet and Dry Areas from Observation and Model

Assessing the magnitude of CO₂ flux uncertainty in atmospheric CO₂ records using products from NASA's Carbon Monitoring Flux Pilot Project

Modulation of midtropospheric methane by El Niño

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Influence of El Niño on Midtropospheric CO2 from Atmospheric Infrared Sounder and Model

Cited by 19 publications

References 23 publications

Investigation of Precipitation Variations over Wet and Dry Areas from Observation and Model

Investigation of Precipitation Variations over Wet and Dry Areas from Observation and Model

Assessing the magnitude of CO2 flux uncertainty in atmospheric CO2 records using products from NASA's Carbon Monitoring Flux Pilot Project

Modulation of midtropospheric methane by El Niño

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Product

Resources

About

Assessing the magnitude of CO₂ flux uncertainty in atmospheric CO₂ records using products from NASA's Carbon Monitoring Flux Pilot Project