Jiye Zeng

Seasonal and interannual variability in the distribution of surface nutrients and dissolved inorganic carbon in the northern North Pacific: Influence of El Niño

The seasonal and interannual changes in surface nutrients, dissolved inorganic carbon (DIC) and total alkalinity (TA) were recorded in the North Pacific (30–54°N) from 1995 to 2001. This study focuses on the region north of the subarctic boundary (∼40°N) where there was extensive monthly coverage of surface properties. The nutrient cycles showed large interannual variations in the eastern and western subarctic gyres. In the Alaska Gyre the seasonal depletion of nitrate (ΔNO3) increased from 8–14 µmol kg−1 in 1995–1999 to 21.5 µmol kg−1 in 2000. In the western subarctic the shifts were similar in amplitude but more frequent. The large ΔNO3 levels were associated with high silicate depletions, indicating enhanced diatom production. The seasonal DIC:NO3 drawdown ratios were elevated in the eastern and central subarctic due to calcification. In the western subarctic and the central Bering Sea calcification was significant only during 1997 and/or 1998, two El Niño years. Regional C/N stoichiometric molar ratios of 5.7 to 7.0 (>40°N) were determined based on the years with negligible or no calcification. The annual new production (NPa) based on ΔNO3 and these C/N ratios showed large interannual variations. NPa was usually higher in the western than in the eastern subarctic. However, values of 84 gC m−2yr−1 were found in the Alaska Gyre in 2000 which is similar to that in the most productive provinces of the northern North Pacific. There were also large increases in NPa around the Alaska Peninsula in 1997 and 1998. Finally, the net removal of carbon by the biological pump was estimated as 0.72 Gt C yr−1 in the North Pacific (>30°N).

Software, Data and Modelling News: METEX - A flexible tool for air trajectory calculation

Air trajectories are often used to study airflow pattern and source-receptor relation in environmental research. We developed the METeorological data EXplorer (METEX) for trajectory calculation with an emphasis on flexibility and ease-of-use.

A Global Surface Ocean fCO2 Climatology Based on a Feed-Forward Neural Network

AbstractA feed-forward neural network is used to create a monthly climatology of the sea surface fugacity of CO2 (fCO2) on a 1° × 1° spatial resolution. Using 127 880 data points from 1990 to 2011 in the track-gridded database of the Surface Ocean CO2 Atlas version 2.0 (Bakker et al.), the model yields a global mean fCO2 increase rate of 1.50 μatm yr−1. The rate was used to normalize multiple years’ fCO2 observations to the reference year of 2000. A total of 73 265 data points from the normalized data were used to model the global fCO2 climatology. The model simulates monthly fCO2 distributions that agree well with observations and yields an anthropogenic CO2 update of −1.9 to −2.3 PgC yr−1. The range reflects the uncertainty related to using different wind products for the flux calculation. This estimate is in good agreement with the recently derived best estimate by Wanninkhof et al. The model product benefits from a finer spatial resolution compared to the product of Lamont–Doherty Earth Observatory (T...

Measurements of Surface Seawater fCO2 from Volunteer Commercial Ships: Techniques and Experiences from Skaugran

Abstract Chemical measurements made in the northern North Pacific from a commercial volunteer observing ship (VOS) program during March 1995–March 1998 are presented. Quasi-continuous measurements of the fugacity of CO2 (fCO2, which takes into account the nonideal nature of the gas; the values are within 0.5–1.5 μatm of the partial pressure in surface water) in seawater were made from two independent systems with different designs, and those results are emphasized here. One system used a fast response bubbling equilibrator with measurements each minute; the other system used a showerhead equilibrator with hourly measurements. Comparison of the results from these side-by-side systems provides useful information about the requirements for making high quality measurements of surface seawater and atmospheric fCO2. From this comparison, the fast response system is deemed to be more stable and potentially more accurate. The utility of this system in waters with high spatial variability is also demonstrated. Fac...

CO emissions from biomass burning in South-east Asia in the 2006 El Nino year: shipboard and AIRS satellite observations

Environmental context Atmospheric carbon monoxide greatly affects the abundance of environmentally important gases, including methane, hydrochlorofluorocarbons and tropospheric ozone. We present evidence for episodes of CO pollution over the tropical Pacific Ocean resulting from intensive biomass burning in South-east Asia and Northern Australia during the 2006 El Nino year. We discuss the locations of the CO emissions and their long-range transport. Abstract Biomass burning is often associated with climate oscillations. For example, biomass burning in South-east Asia is strongly linked to El Nino–southern oscillation activity. During October and November of the 2006 El Nino year, a substantial increase in CO mixing ratios was detected over the Western tropical Pacific Ocean by shipboard observations routinely operated between Japan and Australia and New Zealand. Combining in-situ measurements, satellite observations, and an air trajectory model simulation, two high CO episodes were identified originating from biomass burning in Borneo, Sumatra, New Guinea, and Northern Australia. Between 15°N and the Equator, marked CO enhancements were encountered associated with a significant correlation between CO and CO2 and between CO and O3. The ΔCO/ΔCO2 ratio observed in the fire plume was considerably high (171 ppbv ppmv–1), suggesting substantial contributions from peat soil burning in Indonesia. In contrast, the ΔO3/ΔCO ratio was only 0.05 ppbv ppbv–1, indicating that net photochemical production of O3 in the plume was negligible during long-range transport in the lower troposphere over the Western tropical North Pacific.

Observation-based trends of the southern ocean carbon sink

The Southern Ocean (SO) carbon sink has strengthened substantially since the year 2000, following a decade of a weakening trend. However, the surface ocean pCO2 data underlying this trend reversal are sparse, requiring a substantial amount of extrapolation to map the data. Here we use nine different pCO2 mapping products to investigate the SO trends and their sensitivity to the mapping procedure. We find a robust temporal coherence for the entire SO, with eight of the nine products agreeing on the sign of the decadal trends, that is, a weakening CO2 sink trend in the 1990s (on average 0.22 ± 0.24 pg C yr−1 decade−1), and a strengthening sink trend during the 2000s (−0.35 ± 0.23 pg C yr−1 decade−1). Spatially, the multiproduct mean reveals rather uniform trends, but the confidence is limited, given the small number of statistically significant trends from the individual products, particularly during the data-sparse 1990–1999 period. Plain Language Summary The Southern Ocean plays an important role in regulating Earth’s climate as it takes up a substantial amount of carbon dioxide from the atmosphere, thereby limiting the effect of global warming. However, this part of the global ocean is also the least well observed and observational data are sparse. Therefore, to study Southern Ocean carbon uptake, data interpolation methods are used to estimate the variability of the carbon uptake from the few existing observations. This poses the question on how reliable these estimates are. The Surface Ocean CO2 Mapping intercomparison project aims to do exactly that, that is, test how reliable current estimates are by comparing results from different methods. Here we compare the results from nine data interpolation methods in the Southern Ocean from 1990 to 2010 and find a broad and encouraging agreement regarding decadal carbon uptake signals, whereas a spatially more refined analysis reveals much less agreement locally, illustrating the need to continue the measurement effort in the Southern Ocean.

Extraordinary halocarbon emissions initiated by the 2011 Tohoku earthquake

The Tohoku earthquake of 11 March 2011, with moment magnitude Mw = 9.0, and subsequent tsunami caused catastrophic structural damage in east Japan. Using high-frequency atmospheric monitoring data, we show that emissions of halocarbons, potent greenhouse gases and stratospheric ozone-depleting substances, dramatically increased shortly after the earthquake and that annual emissions were significantly higher in 2011 than in other years. We estimate that the sum of earthquake-related emissions of the six studied halocarbon species (CFC-11, HCFC-22, HCFC-141b, HFC-134a, HFC-32, and SF6) was 6.6 (5.2–8.0) Gg, which is equivalent to ozone depletion potential-weighted emissions of 1.3 (1.1–1.6) Gg with a global warming potential equivalent to 19.2 (15.8–22.5) Tg of carbon dioxide. These extraordinary halocarbon emissions are likely due to destruction of building components containing halocarbons, such as air conditioners, foam insulation, and electrical equipment.

Sustained acceleration of soil carbon decomposition observed in a 6-year warming experiment in a warm-temperate forest in southern Japan

To examine global warming’s effect on soil organic carbon (SOC) decomposition in Asian monsoon forests, we conducted a soil warming experiment with a multichannel automated chamber system in a 55-year-old warm-temperate evergreen broadleaved forest in southern Japan. We established three treatments: control chambers for total soil respiration, trenched chambers for heterotrophic respiration (Rh), and warmed trenched chambers to examine warming effect on Rh. The soil was warmed with an infrared heater above each chamber to increase soil temperature at 5 cm depth by about 2.5 °C. The warming treatment lasted from January 2009 to the end of 2014. The annual warming effect on Rh (an increase per °C) ranged from 7.1 to17.8% °C−1. Although the warming effect varied among the years, it averaged 9.4% °C−1 over 6 years, which was close to the value of 10.1 to 10.9% °C−1 that we calculated using the annual temperature–efflux response model of Lloyd and Taylor. The interannual warming effect was positively related to the total precipitation in the summer period, indicating that summer precipitation and the resulting soil moisture level also strongly influenced the soil warming effect in this forest.

High-resolution data on the impact of warming on soil CO 2 efflux from an Asian monsoon forest

This paper describes a project for evaluation of global warming’s impacts on soil carbon dynamics in Japanese forest ecosystems. We started a soil warming experiment in late 2008 in a 55-year-old evergreen broad-leaved forest at the boundary between the subtropical and warm-temperate biomes in southern Japan. We used infrared carbon-filament heat lamps to increase soil temperature by about 2.5 °C at a depth of 5 cm and continuously recorded CO2 emission from the soil surface using a multichannel automated chamber system. Here, we present details of the experimental processes and datasets for the CO2 emission rate, soil temperature, and soil moisture from control, trenched, and warmed trenched plots. The long term of the study and its high resolution make the datasets meaningful for use in or development of coupled climate-ecosystem models to tune their dynamic behaviour as well as to provide mean parameters for decomposition of soil organic carbon to support future predictions of soil carbon sequestration.

Reconstructing the Carbon Dioxide Absorption Patterns of World Oceans Using a Feed-Forward Neural Network: Software Implementation and Employment Techniques

Oceans play a major role in the global carbon budget, absorbing approximately 27% of anthropogenic carbon dioxide (CO2). As the degree to which an ocean can serve as a carbon sink is determined by the partial pressure of CO2 in the surface water, it is critical to obtain an accurate estimate of the spatial distributions of CO2 and its temporal variation on a global scale. However, this is extremely challenging due to insufficient measurements, large seasonal variability, and short spatial de-correlation scales. This paper presents an open source software package that implements a feed-forward neural network and a back-propagation training algorithm to solve a problem with one output variable and a large number of training patterns. We discuss the employment of the neural network for global ocean CO2 mapping.