Implications of overestimated anthropogenic CO2 emissions on East Asian and global land CO2 flux inversion

Measurement and modelling of regional or country-level carbon dioxide (CO2) fluxes are becoming critical for verification of the greenhouse gases emission control. One of the commonly adopted approaches is inverse modelling, where CO2 fluxes (emission: positive flux, sink: negative flux) from the terrestrial ecosystems are estimated by combining atmospheric CO2 measurements with atmospheric transport models. The inverse models assume anthropogenic emissions are known, and thus the uncertainties in the emissions introduce systematic bias in estimation of the terrestrial (residual) fluxes by inverse modelling. Here we show that the CO2 sink increase, estimated by the inverse model, over East Asia (China, Japan, Korea and Mongolia), by about 0.26 PgC yr-1 (1 Pg = 1012 g) during 2001-2010, is suggested as an artifact of the anthropogenic CO2 emissions increasing too quickly in China by 1.41 PgC yr-1. Independent results from methane (CH4) inversion suggested about 41% lower rate of East Asian CH4 emission increase during 2002-2012. We apply a scaling factor of 0.59, based on CH4 inversion, to the rate of anthropogenic CO2 emission increase since the anthropogenic emissions of both CO2 and CH4 increase linearly in the emission inventory. We find no systematic increase in land CO2 uptake over East Asia during 1993-2010 or 2000-2009 when scaled anthropogenic CO2 emissions are used, and that there is a need of higher emission increase rate for 2010-2012 compared to those calculated by the inventory methods. High bias in anthropogenic CO2 emissions leads to stronger land sinks in global land-ocean flux partitioning in our inverse model. The corrected anthropogenic CO2 emissions also produce measurable reductions in the rate of global land CO2 sink increase post-2002, leading to a better agreement with the terrestrial biospheric model simulations that include CO2-fertlization and climate effects

Analysis of Meteorological Measurements made over Three Rainy Seasons and Rainfall Simulations in Sinazongwe District, Southern Province, Zambia

Zambia has frequently been affected by abnormal weather and droughts. Our research focused on the type of meteorological data required to assist farmers\u27 efforts to avoid the risks associated with these weather conditions. We conducted local meteorological observations from September 2007 to August 2010 at three sites in Sinazongwe District, Zambia. The three rainy seasons of this period coincided in sequence with La Niña (normal) and El Niño conditions. The mean annual precipitation for the three years of our study exceeded 1200 mm, which was considerably more than the regional annual average rainfall from 1970 to 2000 of a round 800 mm per year. We used detailed analyses of intraseasonal variations in other meteorological elements to attempt to explain the high precipitation.Local circulation dominated in our research area, while heavy rain induced by convection in the afternoon and night might account for precipitation exceeding the norm. We numerically simulated meteorological conditions over the past decade to determine whether the annual precipitation observed since September 2007 indeed exceeded the norm. lntra-seasonal variations in precipitation, such as high rainfall in December during the 2007/2008 rainy season, a gradual increase in cumulative precipitation through 2008/2009, and high rainfall in February in the 2009/2010 rainy season were possibly controlled by El Niño - Southern Oscil lation. Our results suggest that annual variations in precipitation are common in this area and that the precipitation we observed did not necessarilyexceed the norm

What controls the seasonal cycle of columnar methane observed by GOSAT over different regions in India?

Methane (CH4) is one of the most important short-lived climate forcers for its critical roles in greenhouse warming and air pollution chemistry in the troposphere, and the water vapor budget in the stratosphere. It is estimated that up to about 8% of global CH4 emissions occur from South Asia, covering less than 1% of the global land. With the availability of satellite observations from space, variability in CH4 has been captured for most parts of the global land with major emissions, which were otherwise not covered by the surface observation network. The satellite observation of the columnar dry-air mole fractions of methane (XCH4) is an integrated measure of CH4 densities at all altitudes from the surface to the top of the atmosphere. Here, we present an analysis of XCH4 variability over different parts of India and the surrounding cleaner oceanic regions as measured by the Greenhouse gases Observation SATellite (GOSAT) and simulated by an atmospheric chemistry-transport model (ACTM). Distinct seasonal variations of XCH4 have been observed over the northern (north of 15°N) and southern (south of 15°N) parts of India, corresponding to the peak during the southwestern monsoon (July-September) and early autumn (October-December) seasons, respectively. Analysis of the transport, emission, and chemistry contributions to XCH4 using ACTM suggests that a distinct XCH4 seasonal cycle over northern and southern regions of India is governed by both the heterogeneous distributions of surface emissions and a contribution of the partial CH4 column in the upper troposphere. Over most of the northern Indian Gangetic Plain regions, up to 40% of the peak-to-trough amplitude during the southwestern (SW) monsoon season is attributed to the lower troposphere ( ? 1000-600hPa), and ? 40% to uplifted high-CH4 air masses in the upper troposphere ( ? 600-200hPa). In contrast, the XCH4 seasonal enhancement over semi-arid western India is attributed mainly ( ? 70%) to the upper troposphere. The lower tropospheric region contributes up to 60% in the XCH4 seasonal enhancement over the Southern Peninsula and oceanic region. These differences arise due to the complex atmospheric transport mechanisms caused by the seasonally varying monsoon. The CH4 enriched air mass is uplifted from a high-emission region of the Gangetic Plain by the SW monsoon circulation and deep cumulus convection and then confined by anticyclonic wind in the upper tropospheric heights ( ? 200hPa). The anticyclonic confinement of surface emission over a wider South Asia region leads to a strong contribution of the upper troposphere in the formation of the XCH4 peak over northern India, including the semi-arid regions with extremely low CH4 emissions. Based on this analysis, we suggest that a link between surface emissions and higher levels of XCH4 is not always valid over Asian monsoon regions, although there is often a fair correlation between surface emissions and XCH4. The overall validity of ACTM simulation for capturing GOSAT observed seasonal and spatial XCH4 variability will allow us to perform inverse modeling of XCH4 emissions in the future using XCH4 data.CC-BY 3.

Indigenous Climate Information and Modern Meteorological Records in Sinazongwe District, Southern Province, Zambia

In 2007, we conducted field research in Sinazongwe District in Southern Province, Zambia, focusing on collecting indigenous information concerning the local climate, which was often embodied in proverbs involving weather forecasts. The indigenous information was compared with recently collected meteorological records and a relationship between popular folk knowledge, local climate, and global climate factors such as ENSO (El Nino and the Southern Oscillation) was suggested. Proverbs related to agriculture and climate were categorized into four types of indicators used to forecast rain: the emergence of butterflies; tree characteristics (producing shoots, flowering, and dropping water); wind direction, wind speed, and temperature; and wind sound. The first two types are based on sea sonal changes in life forms, and the latter two use wind variations produced by synoptic pattern changes

Global atmospheric CO₂ inverse models converging on neutral tropical land exchange, but disagreeing on fossil fuel and atmospheric growth rate

We have compared a suite of recent global CO₂ atmospheric inversion results to independent airborne observations and to each other, to assess their dependence on differences in northern extratropical (NET) vertical transport and to identify some of the drivers of model spread. We evaluate posterior CO₂ concentration profiles against observations from the High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observations (HIPPO) aircraft campaigns over the mid-Pacific in 2009–2011. Although the models differ in inverse approaches, assimilated observations, prior fluxes, and transport models, their broad latitudinal separation of land fluxes has converged significantly since the Atmospheric Carbon Cycle Inversion Intercomparison (TransCom 3) and the REgional Carbon Cycle Assessment and Processes (RECCAP) projects, with model spread reduced by 80 % since TransCom 3 and 70 % since RECCAP. Most modeled CO₂ fields agree reasonably well with the HIPPO observations, specifically for the annual mean vertical gradients in the Northern Hemisphere. Northern Hemisphere vertical mixing no longer appears to be a dominant driver of northern versus tropical (T) annual flux differences. Our newer suite of models still gives northern extratropical land uptake that is modest relative to previous estimates (Gurney et al., 2002; Peylin et al., 2013) and near-neutral tropical land uptake for 2009–2011. Given estimates of emissions from deforestation, this implies a continued uptake in intact tropical forests that is strong relative to historical estimates (Gurney et al., 2002; Peylin et al., 2013). The results from these models for other time periods (2004–2014, 2001–2004, 1992–1996) and re-evaluation of the TransCom 3 Level 2 and RECCAP results confirm that tropical land carbon fluxes including deforestation have been near neutral for several decades. However, models still have large disagreements on ocean–land partitioning. The fossil fuel (FF) and the atmospheric growth rate terms have been thought to be the best-known terms in the global carbon budget, but we show that they currently limit our ability to assess regional-scale terrestrial fluxes and ocean–land partitioning from the model ensemble

The Orbiting Carbon Observatory (OCO-2) Tracks 2-3 Peta-Gram Increase in Carbon Release to the Atmosphere During the 2014-2016 El Nino

The powerful El Nio event of 2015-2016 - the third most intense since the 1950s - has exerted a large impact on the Earth's natural climate system. The column-averaged CO2 dry-air mole fraction (XCO2) observations from satellites and ground based networks are analyzed together with in situ observations for the period of September 2014 to October 2016. From the differences between satellite (OCO-2) observations and simulations using an atmospheric chemistry-transport model, we estimate that, relative to the mean annual fluxes for 2014, the most recent El Nio has contributed to an excess CO2 emission from the Earth's surface (land+ocean) to the atmosphere in the range of 2.4+/-0.2 PgC (1 Pg = 10(exp 15) g) over the period of July 2015 to June 2016. The excess CO2 flux is resulted primarily from reduction in vegetation uptake due to drought, and to a lesser degree from increased biomass burning. It is about the half of the CO2 flux anomaly (range: 4.4-6.7 PgC) estimated for the 1997/1998 El Nio. The annual total sink is estimated to be 3.9+/-0.2 PgC for the assumed fossil fuel emission of 10.1 PgC. The major uncertainty in attribution arise from error in anthropogenic emission trends, satellite data and atmospheric transport

Regional Methane Emission Estimation Based on Observed Atmospheric Concentrations (2002-2012)

Methane (CH4) plays important roles in atmospheric chemistry and short-term forcing of climate. A clear understanding of atmospheric CH4’s budget of emissions and losses is required to aid sustainable management of Earth’s future environment. We used an atmospheric chemistry-transport model (JAMSTEC’s ACTM) for simulating atmospheric CH4. A global inverse modeling system has been developed for estimating CH4 emissions from 53 land regions for 2002-2012 using measurements at 39 sites. An ensemble of 7 inversions is performed by varying a priori emissions. Global net CH4 emissions varied between 505-509 and 524-545 Tg yr-1 during 2002-2006 and 2008-2012, respectively (ranges based on 7 inversion cases), with a step like increase in 2007 in agreement with atmospheric measurements. The inversion system did not account for interannual variations in OH radicals reacting with CH4 in the atmosphere. Our results suggest that the recent update of the EDGAR inventory (version 4.2FT2010) overestimated the global total emissions by at least 25 Tg yr-1 in 2010. The increase in CH4 emission since 2004 originated in the tropical and southern hemisphere regions, coinciding with an increase in non-dairy cattle stocks by ~10 % from 2002 (with 1056 million heads) to 2012, leading to ~10 Tg yr-1 increase in emissions from enteric fermentation. All 7 ensemble cases robustly estimated the interannual variations in emissions, but poorly constrained the seasonal cycle amplitude or phase consistently for all regions due to the sparse observational network. Forward simulation results using both a priori and a posteriori emissions are compared with independent aircraft measurements for validation. Based on the results of the comparison, we reject the upper limit (545 Tg yr-1) of global total emissions as 14 Tg yr-1 too high during 2008-2012, which allows us to further conclude that the increase in CH4 emissions over the East Asia (mainly China) region was 7-8 Tg yr-1 between the 2002-2006 and 2008-2012 periods, contrary to 1-17 Tg yr-1 in the a priori emissions

The Orbiting Carbon Observatory (OCO-2) tracks 2–3 peta-gram increase in carbon release to the atmosphere during the 2014–2016 El Niño

The powerful El Niño event of 2015–2016 – the third most intense since the 1950s – has exerted a large impact on the Earth’s natural climate system. The column-averaged CO_2 dry-air mole fraction (XCO_2) observations from satellites and ground-based networks are analyzed together with in situ observations for the period of September 2014 to October 2016. From the differences between satellite (OCO-2) observations and simulations using an atmospheric chemistry-transport model, we estimate that, relative to the mean annual fluxes for 2014, the most recent El Niño has contributed to an excess CO_2 emission from the Earth’s surface (land + ocean) to the atmosphere in the range of 2.4 ± 0.2 PgC (1 Pg = 10^(15) g) over the period of July 2015 to June 2016. The excess CO_2 flux is resulted primarily from reduction in vegetation uptake due to drought, and to a lesser degree from increased biomass burning. It is about the half of the CO_2 flux anomaly (range: 4.4–6.7 PgC) estimated for the 1997/1998 El Niño. The annual total sink is estimated to be 3.9 ± 0.2 PgC for the assumed fossil fuel emission of 10.1 PgC. The major uncertainty in attribution arise from error in anthropogenic emission trends, satellite data and atmospheric transport