Earth System Science Data
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Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies Abstract. This paper presents a new global burned area (BA) product, generated from the Moderate Resolution Imaging Spectroradiometer
(MODIS) red (R) and near-infrared (NIR) reflectances and thermal anomaly
data, thus providing the highest spatial resolution (approx. 250 m) among
the existing global BA datasets. The product includes the full times series
(2001–2016) of the Terra-MODIS archive. The BA detection algorithm was based
on monthly composites of daily images, using temporal and spatial distance
to active fires. The algorithm has two steps, the first one aiming to reduce
commission errors by selecting the most clearly burned pixels (seeds), and
the second one targeting to reduce omission errors by applying contextual
analysis around the seed pixels. This product was developed within the
European Space Agency's (ESA) Climate Change Initiative (CCI) programme, under the
Fire Disturbance project (Fire_cci). The final output
includes two types of BA files: monthly full-resolution continental tiles
and biweekly global grid files at a degraded resolution of 0.25∘.
Each set of products includes several auxiliary variables that were defined
by the climate users to facilitate the ingestion of the product into global
dynamic vegetation and atmospheric emission models. Average annual burned
area from this product was 3.81 Mkm2, with maximum burning in 2011 (4.1 Mkm2)
and minimum in 2013 (3.24 Mkm2). The validation was based on
a stratified random sample of 1200 pairs of Landsat images, covering the
whole globe from 2003 to 2014. The validation indicates an overall accuracy
of 0.9972, with much higher errors for the burned than the unburned category
(global omission error of BA was estimated as 0.7090 and global commission
as 0.5123). These error values are similar to other global BA products, but
slightly higher than the NASA BA product (named MCD64A1, which is produced
at 500 m resolution). However, commission and omission errors are better
compensated in our product, with a tendency towards BA underestimation
(relative bias −0.4033), as most existing global BA products. To understand
the value of this product in detecting small fire patches (<100 ha),
an additional validation sample of 52 Sentinel-2 scenes was generated
specifically over Africa. Analysis of these results indicates a better
detection accuracy of this product for small fire patches (<100 ha)
than the equivalent 500 m MCD64A1 product, although both have high errors for
these small fires. Examples of potential applications of this dataset to
fire modelling based on burned patches analysis are included in this paper.
The datasets are freely downloadable from the Fire_cci
website (https://www.esa-fire-cci.org/, last access: 10 November 2018) and their repositories (pixel at
full resolution: https://doi.org/cpk7, and grid: https://doi.org/gcx9gf).
Earth System Science Data - Tập 10 Số 4 - Trang 2015-2031
Altimetry, gravimetry, GPS and viscoelastic modeling data for the joint inversion for glacial isostatic adjustment in Antarctica (ESA STSE Project REGINA) Abstract. The poorly known correction for the ongoing deformation of the solid Earth caused by glacial isostatic adjustment (GIA) is a major uncertainty in determining the mass balance of the Antarctic ice sheet from measurements of satellite gravimetry and to a lesser extent satellite altimetry. In the past decade, much progress has been made in consistently modeling ice sheet and solid Earth interactions; however, forward-modeling solutions of GIA in Antarctica remain uncertain due to the sparsity of constraints on the ice sheet evolution, as well as the Earth's rheological properties. An alternative approach towards estimating GIA is the joint inversion of multiple satellite data – namely, satellite gravimetry, satellite altimetry and GPS, which reflect, with different sensitivities, trends in recent glacial changes and GIA. Crucial to the success of this approach is the accuracy of the space-geodetic data sets. Here, we present reprocessed rates of surface-ice elevation change (Envisat/Ice, Cloud,and land Elevation Satellite, ICESat; 2003–2009), gravity field change (Gravity Recovery and Climate Experiment, GRACE; 2003–2009) and bedrock uplift (GPS; 1995–2013). The data analysis is complemented by the forward modeling of viscoelastic response functions to disc load forcing, allowing us to relate GIA-induced surface displacements with gravity changes for different rheological parameters of the solid Earth. The data and modeling results presented here are available in the PANGAEA database (https://doi.org/10.1594/PANGAEA.875745). The data sets are the input streams for the joint inversion estimate of present-day ice-mass change and GIA, focusing on Antarctica. However, the methods, code and data provided in this paper can be used to solve other problems, such as volume balances of the Antarctic ice sheet, or can be applied to other geographical regions in the case of the viscoelastic response functions. This paper presents the first of two contributions summarizing the work carried out within a European Space Agency funded study: Regional glacial isostatic adjustment and CryoSat elevation rate corrections in Antarctica (REGINA).
Earth System Science Data - Tập 10 Số 1 - Trang 493-523
Global Carbon Budget 2015 Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen–carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005–2014), EFF was 9.0 ± 0.5 GtC yr−1, ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 4.4 ± 0.1 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 3.0 ± 0.8 GtC yr−1. For the year 2014 alone, EFF grew to 9.8 ± 0.5 GtC yr−1, 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yr−1 that took place during 2005–2014. Also, for 2014, ELUC was 1.1 ± 0.5 GtC yr−1, GATM was 3.9 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and SLAND was 4.1 ± 0.9 GtC yr−1. GATM was lower in 2014 compared to the past decade (2005–2014), reflecting a larger SLAND for that year. The global atmospheric CO2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in EFF will be near or slightly below zero, with a projection of −0.6 [range of −1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of EFF and assumed constant ELUC for 2015, cumulative emissions of CO2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO2) for 1870–2015, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2015).
Earth System Science Data - Tập 7 Số 2 - Trang 349-396
EDGAR v4.3.2 Global Atlas of the three major greenhouse gas emissions for the period 1970–2012 Abstract. The Emissions Database for Global Atmospheric Research (EDGAR) compiles
anthropogenic emissions data for greenhouse gases (GHGs), and for multiple air
pollutants, based on international statistics and emission factors. EDGAR data
provide quantitative support for atmospheric modelling and for mitigation
scenario and impact assessment analyses as well as for policy evaluation. The
new version (v4.3.2) of the EDGAR emission inventory provides global
estimates, broken down to IPCC-relevant source-sector levels, from 1970 (the
year of the European Union's first Air Quality Directive) to 2012 (the end
year of the first commitment period of the Kyoto Protocol, KP). Strengths of
EDGAR v4.3.2 include global geo-coverage (226 countries), continuity in time,
and comprehensiveness in activities. Emissions of multiple chemical
compounds, GHGs as well as air pollutants, from relevant sources (fossil fuel
activities but also, for example, fermentation processes in agricultural
activities) are compiled following a bottom-up (BU), transparent and IPCC-compliant methodology. This paper describes
EDGAR v4.3.2 developments with respect to three major long-lived GHGs (CO2,
CH4, and N2O) derived from a wide range of human activities
apart from the land-use, land-use change and forestry (LULUCF) sector and
apart from savannah burning; a companion paper quantifies and discusses
emissions of air pollutants. Detailed information is included for each of the
IPCC-relevant source sectors, leading to global totals for 2010 (in the
middle of the first KP commitment period) (with a 95 % confidence
interval in parentheses): 33.6(±5.9) Pg CO2 yr−1, 0.34(±0.16) Pg CH4 yr−1, and 7.2(±3.7) Tg N2O yr−1. We provide uncertainty factors in emissions
data for the different GHGs and for three different groups of countries: OECD
countries of 1990, countries with economies in transition in 1990, and the
remaining countries in development (the UNFCCC non-Annex I parties). We
document trends for the major emitting countries together with the European
Union in more detail, demonstrating that effects of fuel markets and
financial instability have had greater impacts on GHG trends than effects of
income or population. These data (https://doi.org/10.5281/zenodo.2658138,
Janssens-Maenhout et al., 2019) are visualised with annual and monthly global emissions grid maps
of 0.1∘×0.1∘ for each source sector.
Earth System Science Data - Tập 11 Số 3 - Trang 959-1002
A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): an application of the Community Emissions Data System (CEDS) Abstract. Global anthropogenic emission inventories remain vital
for understanding the sources of atmospheric pollution and the associated impacts on the environment, human health, and society.
Rapid changes in today's society require that these inventories provide
contemporary estimates of multiple atmospheric pollutants with both source
sector and fuel type information to understand and effectively mitigate
future impacts. To fill this need, we have updated the open-source Community
Emissions Data System (CEDS) (Hoesly et al., 2019) to
develop a new global emission inventory, CEDSGBD-MAPS. This inventory
includes emissions of seven key atmospheric pollutants (NOx; CO;
SO2; NH3; non-methane volatile organic compounds, NMVOCs; black carbon, BC; organic carbon, OC) over the time period from 1970–2017
and reports annual country-total emissions as a function of 11 anthropogenic
sectors (agriculture; energy generation; industrial processes;
on-road and non-road transportation; separate residential, commercial, and other
sectors (RCO); waste; solvent use; and international shipping) and four fuel
categories (total coal, solid biofuel, the sum of liquid-fuel and
natural-gas combustion, and remaining process-level emissions). The
CEDSGBD-MAPS inventory additionally includes monthly global gridded
(0.5∘ × 0.5∘) emission fluxes for each compound, sector, and fuel type to facilitate their
use in earth system models. CEDSGBD-MAPS utilizes updated activity
data, updates to the core CEDS default scaling procedure, and modifications
to the final procedures for emissions gridding and aggregation. Relative to the previous CEDS inventory (Hoesly et
al., 2018), these updates extend the emission estimates from 2014 to 2017
and improve the overall agreement between CEDS and two widely used global
bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the
most contemporary global emission estimates to date for these key
atmospheric pollutants and is the first to provide global estimates for
these species as a function of multiple fuel types and source
sectors. Dominant sources of global NOx and SO2 emissions in 2017
include the combustion of oil, gas, and coal in the energy and industry
sectors as well as on-road transportation and international shipping for
NOx. Dominant sources of global CO emissions in 2017 include on-road
transportation and residential biofuel combustion. Dominant global sources
of carbonaceous aerosol in 2017 include residential biofuel combustion,
on-road transportation (BC only), and emissions from the waste
sector. Global emissions of NOx, SO2, CO, BC, and OC all peak in
2012 or earlier, with more recent emission reductions driven by large
changes in emissions from China, North America, and Europe. In contrast,
global emissions of NH3 and NMVOCs continuously increase between 1970
and 2017, with agriculture as a major source of global NH3
emissions and solvent use, energy, residential, and the on-road transport
sectors as major sources of global NMVOCs. Due to similar development
methods and underlying datasets, the CEDSGBD-MAPS emissions are
expected to have consistent sources of uncertainty as other bottom-up
inventories. The CEDSGBD-MAPS source
code is publicly available online through GitHub:
https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS (last access: 1 December 2020). The
CEDSGBD-MAPS emission inventory dataset (both annual country-total and
monthly global gridded files) is publicly available under https://doi.org/10.5281/zenodo.3754964
(McDuffie et al., 2020c).
Earth System Science Data - Tập 12 Số 4 - Trang 3413-3442
The Open-source Data Inventory for Anthropogenic CO&lt;sub&gt;2&lt;/sub&gt;, version 2016 (ODIAC2016): a global monthly fossil fuel CO&lt;sub&gt;2&lt;/sub&gt; gridded emissions data product for tracer transport simulations and surface flux inversions Abstract. The Open-source Data Inventory for Anthropogenic CO2 (ODIAC) is a global high-spatial-resolution gridded emissions data product that distributes carbon dioxide (CO2) emissions from fossil fuel combustion. The emissions spatial distributions are estimated at a 1 × 1 km spatial resolution over land using power plant profiles (emissions intensity and geographical location) and satellite-observed nighttime lights. This paper describes the year 2016 version of the ODIAC emissions data product (ODIAC2016) and presents analyses that help guide data users, especially for atmospheric CO2 tracer transport simulations and flux inversion analysis. Since the original publication in 2011, we have made modifications to our emissions modeling framework in order to deliver a comprehensive global gridded emissions data product. Major changes from the 2011 publication are (1) the use of emissions estimates made by the Carbon Dioxide Information Analysis Center (CDIAC) at the Oak Ridge National Laboratory (ORNL) by fuel type (solid, liquid, gas, cement manufacturing, gas flaring, and international aviation and marine bunkers); (2) the use of multiple spatial emissions proxies by fuel type such as (a) nighttime light data specific to gas flaring and (b) ship/aircraft fleet tracks; and (3) the inclusion of emissions temporal variations. Using global fuel consumption data, we extrapolated the CDIAC emissions estimates for the recent years and produced the ODIAC2016 emissions data product that covers 2000–2015. Our emissions data can be viewed as an extended version of CDIAC gridded emissions data product, which should allow data users to impose global fossil fuel emissions in a more comprehensive manner than the original CDIAC product. Our new emissions modeling framework allows us to produce future versions of the ODIAC emissions data product with a timely update. Such capability has become more significant given the CDIAC/ORNL's shutdown. The ODIAC data product could play an important role in supporting carbon cycle science, especially modeling studies with space-based CO2 data collected in near real time by ongoing carbon observing missions such as the Japanese Greenhouse gases Observing SATellite (GOSAT), NASA's Orbiting Carbon Observatory-2 (OCO-2), and upcoming future missions. The ODIAC emissions data product including the latest version of the ODIAC emissions data (ODIAC2017, 2000–2016) is distributed from http://db.cger.nies.go.jp/dataset/ODIAC/ with a DOI (https://doi.org/10.17595/20170411.001).
Earth System Science Data - Tập 10 Số 1 - Trang 87-107
An extended time series (2000–2018) of global NPP-VIIRS-like nighttime light data from a cross-sensor calibration Abstract. The nighttime light (NTL) satellite data have been widely
used to investigate the urbanization process. The Defense Meteorological
Satellite Program Operational Linescan System (DMSP-OLS) stable nighttime
light data and Suomi National Polar-orbiting Partnership Visible Infrared
Imaging Radiometer Suite (NPP-VIIRS) nighttime light data are two widely
used NTL datasets. However, the difference in their spatial resolutions and
sensor design requires a cross-sensor calibration of these two datasets for
analyzing a long-term urbanization process. Different from the traditional
cross-sensor calibration of NTL data by converting NPP-VIIRS to
DMSP-OLS-like NTL data, this study built an extended time series (2000–2018)
of NPP-VIIRS-like NTL data through a new cross-sensor calibration from
DMSP-OLS NTL data (2000–2012) and a composition of monthly NPP-VIIRS NTL
data (2013–2018). The proposed cross-sensor calibration is unique due to the
image enhancement by using a vegetation index and an auto-encoder model.
Compared with the annual composited NPP-VIIRS NTL data in 2012, our product
of extended NPP-VIIRS-like NTL data shows a good consistency at the pixel
and city levels with R2 of 0.87 and 0.95, respectively. We also found
that our product has great accuracy by comparing it with DMSP-OLS radiance-calibrated NTL (RNTL) data in 2000, 2004, 2006, and 2010. Generally, our
extended NPP-VIIRS-like NTL data (2000–2018) have an excellent spatial
pattern and temporal consistency which are similar to the composited
NPP-VIIRS NTL data. In addition, the resulting product could be easily
updated and provide a useful proxy to monitor the dynamics of demographic
and socioeconomic activities for a longer time period compared to existing
products. The extended time series (2000–2018) of nighttime light data is
freely accessible at https://doi.org/10.7910/DVN/YGIVCD (Chen et
al., 2020).
Earth System Science Data - Tập 13 Số 3 - Trang 889-906
The Stratospheric Water and Ozone Satellite Homogenized (SWOOSH) database: a long-term database for climate studies Abstract. In this paper, we describe the construction of the Stratospheric Water and Ozone Satellite Homogenized (SWOOSH) database, which includes vertically resolved ozone and water vapor data from a subset of the limb profiling satellite instruments operating since the 1980s. The primary SWOOSH products are zonal-mean monthly-mean time series of water vapor and ozone mixing ratio on pressure levels (12 levels per decade from 316 to 1 hPa). The SWOOSH pressure level products are provided on several independent zonal-mean grids (2.5, 5, and 10°), and additional products include two coarse 3-D griddings (30° long × 10° lat, 20° × 5°) as well as a zonal-mean isentropic product. SWOOSH includes both individual satellite source data as well as a merged data product. A key aspect of the merged product is that the source records are homogenized to account for inter-satellite biases and to minimize artificial jumps in the record. We describe the SWOOSH homogenization process, which involves adjusting the satellite data records to a “reference” satellite using coincident observations during time periods of instrument overlap. The reference satellite is chosen based on the best agreement with independent balloon-based sounding measurements, with the goal of producing a long-term data record that is both homogeneous (i.e., with minimal artificial jumps in time) and accurate (i.e., unbiased). This paper details the choice of reference measurements, homogenization, and gridding process involved in the construction of the combined SWOOSH product and also presents the ancillary information stored in SWOOSH that can be used in future studies of water vapor and ozone variability. Furthermore, a discussion of uncertainties in the combined SWOOSH record is presented, and examples of the SWOOSH record are provided to illustrate its use for studies of ozone and water vapor variability on interannual to decadal timescales. The version 2.5 SWOOSH data are publicly available at doi:10.7289/V5TD9VBX.
Earth System Science Data - Tập 8 Số 2 - Trang 461-490
Global Carbon Budget 2018 Abstract. Accurate assessment of anthropogenic carbon dioxide
(CO2) emissions and their redistribution among the atmosphere,
ocean, and terrestrial biosphere – the “global carbon budget” – is
important to better understand the global carbon cycle, support the
development of climate policies, and project future climate change. Here we
describe data sets and methodology to quantify the five major components of
the global carbon budget and their uncertainties. Fossil CO2
emissions (EFF) are based on energy statistics and cement
production data, while emissions from land use and land-use change (ELUC),
mainly deforestation, are based on land use and land-use change data and
bookkeeping models. Atmospheric CO2 concentration is measured
directly and its growth rate (GATM) is computed from the annual
changes in concentration. The ocean CO2 sink (SOCEAN)
and terrestrial CO2 sink (SLAND) are estimated with
global process models constrained by observations. The resulting carbon
budget imbalance (BIM), the difference between the estimated
total emissions and the estimated changes in the atmosphere, ocean, and
terrestrial biosphere, is a measure of imperfect data and understanding of
the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2008–2017), EFF was
9.4±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.7±0.02 GtC yr−1,
SOCEAN 2.4±0.5 GtC yr−1, and SLAND 3.2±0.8 GtC yr−1, with a budget imbalance BIM of
0.5 GtC yr−1 indicating overestimated emissions and/or underestimated
sinks. For the year 2017 alone, the growth in EFF was about 1.6 %
and emissions increased to 9.9±0.5 GtC yr−1. Also for 2017,
ELUC was 1.4±0.7 GtC yr−1, GATM was 4.6±0.2 GtC yr−1, SOCEAN was 2.5±0.5 GtC yr−1, and SLAND was 3.8±0.8 GtC yr−1,
with a BIM of 0.3 GtC. The global atmospheric
CO2 concentration reached 405.0±0.1 ppm averaged over 2017.
For 2018, preliminary data for the first 6–9 months indicate a renewed
growth in EFF of +2.7 % (range of 1.8 % to 3.7 %) based
on national emission projections for China, the US, the EU, and India and
projections of gross domestic product corrected for recent changes in the
carbon intensity of the economy for the rest of the world. The analysis
presented here shows that the mean and trend in the five components of the
global carbon budget are consistently estimated over the period of 1959–2017,
but discrepancies of up to 1 GtC yr−1 persist for the representation
of semi-decadal variability in CO2 fluxes. A detailed comparison
among individual estimates and the introduction of a broad range of
observations show (1) no consensus in the mean and trend in land-use change
emissions, (2) a persistent low agreement among the different methods on
the magnitude of the land CO2 flux in the northern extra-tropics,
and (3) an apparent underestimation of the CO2 variability by ocean
models, originating outside the tropics. This living data update documents
changes in the methods and data sets used in this new global carbon budget
and the progress in understanding the global carbon cycle compared with
previous publications of this data set (Le Quéré et al., 2018, 2016,
2015a, b, 2014, 2013). All results presented here can be downloaded from
https://doi.org/10.18160/GCP-2018.
Earth System Science Data - Tập 10 Số 4 - Trang 2141-2194
Global CO&lt;sub&gt;2&lt;/sub&gt; emissions from cement production, 1928–2017 Abstract. Global production of cement has grown very rapidly in recent years, and after
fossil fuels and land-use change, it is the third-largest source of
anthropogenic emissions of carbon dioxide. The availability of the required
data for estimating emissions from global cement production is poor, and it
has been recognised that some global estimates are significantly inflated.
Here we assemble a large variety of available datasets, prioritising official
data and emission factors, including estimates submitted to the UNFCCC plus
new estimates for China and India, to present a new analysis of global
process emissions from cement production. We show that global process
emissions in 2017 were 1.48±0.20 Gt CO2, equivalent to about
4 % of emissions from fossil fuels. Cumulative emissions from 1928 to
2017 were 36.9±2.3 Gt CO2, 70 % of which have occurred
since 1990. Emissions in 2016 were 28 % lower than those recently
reported by the Global Carbon Project. The data associated with this article
can be found at https://doi.org/10.5281/zenodo.831454.
Earth System Science Data - Tập 10 Số 4 - Trang 2213-2239
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