Impact of Changing Winds on the Mauna Loa CO2 Seasonal Cycle in Relation to the Pacific Decadal Oscillation

Long-term measurements at the Mauna Loa Observatory (MLO) show that the CO₂ seasonal cycle amplitude (SCA) increased from 1959 to 2019 at an overall rate of 0.22  ±  0.034 ppm decade^-1 while also varying on interannual to decadal time scales. These SCA changes are a signature of changes in land ecological CO₂ fluxes as well as shifting winds. Simulations with the TM3 tracer transport model and CO₂ fluxes from the Jena CarboScope CO₂ Inversion suggest that shifting winds alone have contributed to a decrease in SCA of -0.10  ±  0.022 ppm decade^-1 from 1959 to 2019, partly offsetting the observed long-term SCA increase associated with enhanced ecosystem net primary production. According to these simulations and MIROC-ACTM simulations, the shorter-term variability of MLO SCA is nearly equally driven by varying ecological CO₂ fluxes (49%) and varying winds (51%). We also show that the MLO SCA is strongly correlated with the Pacific Decadal Oscillation (PDO) due to varying winds, as well as with a closely related wind index (U-PDO). Since 1980, 44% of the wind-driven SCA decrease has been tied to a secular trend in the U-PDO, which is associated with a progressive weakening of westerly winds at 700 mbar over the central Pacific from 20°N to 40°N. Similar impacts of varying winds on the SCA are seen in simulations at other low-latitude Pacific stations, illustrating the difficulty of constraining trend and variability of land CO₂ fluxes using observations from low latitudes due to the complexity of circulation changes.

Causes of slowing-down seasonal CO2 amplitude at Mauna Loa

Changing amplitude of the seasonal cycle of atmospheric CO₂ (SCA) in the northern hemisphere is an emerging carbon cycle property. Mauna Loa (MLO) station (20°N, 156°W), which has the longest continuous northern hemisphere CO₂ record, shows an increasing SCA before the 1980s (p < .01), followed by no significant change thereafter. We analyzed the potential driving factors of SCA slowing-down, with an ensemble of dynamic global vegetation models (DGVMs) coupled with an atmospheric transport model. We found that slowing-down of SCA at MLO is primarily explained by response of net biome productivity (NBP) to climate change, and by changes in atmospheric circulations. Through NBP, climate change increases SCA at MLO before the 1980s and decreases it afterwards. The effect of climate change on the slowing-down of SCA at MLO is mainly exerted by intensified drought stress acting to offset the acceleration driven by CO₂ fertilization. This challenges the view that CO₂ fertilization is the dominant cause of emergent SCA trends at northern sites south of 40°N. The contribution of agricultural intensification on the deceleration of SCA at MLO was elusive according to land-atmosphere CO₂ flux estimated by DGVMs and atmospheric inversions. Our results also show the necessity to adequately account for changing circulation patterns in understanding carbon cycle dynamics observed from atmospheric observations and in using these observations to benchmark DGVMs.

Scaling Properties of Atmospheric Wind Speed in Mesoscale Range

The scaling properties of turbulent flows are well established in the inertial sub-range. However, those of the synoptic-scale motions are less known, also because of the difficult analysis of data presenting nonstationary and periodic features. Extensive analysis of experimental wind speed data, collected at the Mauna Loa Observatory of Hawaii, is performed using different methods. Empirical Mode Decomposition, interoccurrence times statistics, and arbitrary-order Hilbert spectral analysis allow to eliminate effects of large-scale modulations, and provide scaling properties of the field fluctuations (Hurst exponent, interoccurrence distribution, and intermittency correction). The obtained results suggest that the mesoscale wind dynamics owns features which are typical of the inertial sub-range turbulence, thus extending the validity of the turbulent cascade phenomenology to scales larger than observed before.

Seven years of observational atmospheric CO2 at a maritime site in northernmost Japan and its implications

Surface atmospheric CO2 mixing ratio reflects both natural fluctuation of the carbon cycle and the effect of anthropogenic activities. Long-term observation of atmospheric CO2 forms the basis for model simulations of the carbon cycle both in the straightforward and the inversion ways. Atmospheric CO2 has been measured on Rishiri Island (45.1°N, 141.2°E) in the western North Pacific since May 2006. We report the first 7-year temporal CO2 variations from diurnal to inter-annual scales and the implications on the vegetation phenology. Diurnally, an obvious cycle appeared as a minimum in the afternoon and maximum at midnight in the summer months, caused by local vegetation. Seasonally, the maximum CO2 concentration appeared around the beginning of April, while the minimum appeared around the middle of August. This seasonal variation implied the natural cycle of terrestrial biological activities of the boreal forest, mostly in the east Eurasia. A mean growing season length of ~126 days was estimated. In the period from 2007 to 2012, the peak-to-peak amplitude increased until 2009 and decreased thereafter, with a mean value of 19.7 ppm. Inter-annually, atmospheric CO2 is increasing by a mean growth rate of 2.1 ppm year(-1). The study provides invaluable dataset and useful information to better understand the carbon cycle and its interaction with climate change.

Observational evidence for interhemispheric hydroxyl-radical parity

The hydroxyl radical (OH) is a key oxidant involved in the removal of air pollutants and greenhouse gases from the atmosphere. The ratio of Northern Hemispheric to Southern Hemispheric (NH/SH) OH concentration is important for our understanding of emission estimates of atmospheric species such as nitrogen oxides and methane. It remains poorly constrained, however, with a range of estimates from 0.85 to 1.4 (refs 4, 7-10). Here we determine the NH/SH ratio of OH with the help of methyl chloroform data (a proxy for OH concentrations) and an atmospheric transport model that accurately describes interhemispheric transport and modelled emissions. We find that for the years 2004-2011 the model predicts an annual mean NH-SH gradient of methyl chloroform that is a tight linear function of the modelled NH/SH ratio in annual mean OH. We estimate a NH/SH OH ratio of 0.97 ± 0.12 during this time period by optimizing global total emissions and mean OH abundance to fit methyl chloroform data from two surface-measurement networks and aircraft campaigns. Our findings suggest that top-down emission estimates of reactive species such as nitrogen oxides in key emitting countries in the NH that are based on a NH/SH OH ratio larger than 1 may be overestimated.