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Frankenberg, Christian

Publications and source records attributed to Frankenberg, Christian.

36 records · Page 2

The Global Methane Budget 2000-2012

The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (approximately biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modeling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations).For the 2003-2012 decade, global methane emissions are estimated by top-down inversions at 558 TgCH4 yr(exp -1), range 540-568. About 60 of global emissions are anthropogenic (range 50-65%). Since 2010, the bottom-up global emission inventories have been closer to methane emissions in the most carbon-intensive Representative Concentrations Pathway (RCP8.5) and higher than all other RCP scenarios. Bottom-up approaches suggest larger global emissions (736 TgCH4 yr(exp -1), range 596-884) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the top-down budget, it is likely that some of the individual emissions reported by the bottom-up approaches are overestimated, leading to too large global emissions. Latitudinal data from top-down emissions indicate a predominance of tropical emissions (approximately 64% of the global budget, less than 30deg N) as compared to mid (approximately 32%, 30-60deg N) and high northern latitudes (approximately 4%, 60-90deg N). Top-down inversions consistently infer lower emissions in China (approximately 58 TgCH4 yr(exp -1), range 51-72, minus14% ) and higher emissions in Africa (86 TgCH4 yr(exp -1), range 73-108, plus 19% ) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models. The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30-40% on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions. The data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (http://doi.org/10.3334/CDIAC/GLOBAL_ METHANE_BUDGET_2016_V1.1) and the Global Carbon Project.

Saunois, Marielle↗

Capturing Complete Spatial Context in Satellite Observations of Greenhouse Gases

Scientific consensus from a 2015 pre-Decadal Survey workshop highlighted the essential need for a wide-swath (mapping) low earth orbit (LEO) instrument delivering carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) measurements with global coverage. OCO-2 pioneered space-based CO2 remote sensing, but lacks the CH4, CO and mapping capabilities required for an improved understanding of the global carbon cycle. The Carbon Balance Observatory (CARBO) advances key technologies to enable high-performance, cost-effective solutions for a space-based carbon-climate observing system. CARBO is a compact, modular, 15-30° field of view spectrometer that delivers high-precision CO2, CH4, CO and solar induced chlorophyll fluorescence (SIF) data with weekly global coverage from LEO. CARBO employs innovative immersion grating technologies to achieve diffraction-limited performance with OCO-like spatial (2 x 2 sq.km) and spectral (λ/Δλ≈ 20,000) resolution in a package that is >50% smaller, lighter and more cost-effective. CARBO delivers a 25- to 50-fold increase in spatial coverage compared to OCO-2 with no loss of detection sensitivity. Individual CARBO modules weigh < 20 kg, opening diverse new space-based platform opportunities.

Miller, Charles E.↗

Overview of Global Monitoring of Terrestrial Chlorophyll Fluorescence from Space

Despite the critical importance of photosynthesis for the Earth system, understanding how it is influenced by factors such as climate variability, disturbance history, and water or nutrient availability remains a challenge because of the complex interactions and the lack of GPP measurements at various temporal and spatial scales. Space observations of the sun-induced chlorophyll fluorescence (SIF) electromagnetic signal emitted by plants in the 650-850nm spectral range hold the promise of providing a new view of vegetation photosynthesis on a global basis. Global retrievals of SIF from space have recently been achieved from a number of spaceborne spectrometers originally intended for atmospheric research. Despite not having been designed for land applications, such instruments have turned out to provide the necessary spectral and radiometric sensitivity for SIF retrieval from space. The first global measurements of SIF were achieved in 2011 from spectra acquired by the Japanese GOSAT mission launched in 2009. The retrieval takes advantage of the high spectral resolution provided by GOSATs Fourier Transform Spectrometer (FTS) which allows the evaluation of the in-filling of solar Fraunhofer lines by SIF. Unfortunately, GOSAT only provides a sparse spatial sampling with individual soundings separated by several hundred kilometers. Complementary, the Global Ozone Monitoring Experiment-2 (GOME-2) instruments onboard MetOp-A and MetOp-B enable SIF retrievals since 2007 with a continuous and global spatial coverage. GOME-2 measures in the red and near-infrared (NIR) spectral regions with a spectral resolution of 0.5 nm and a pixel size of up to 40x40 km2. Most recently, another global and spatially continuous data set of SIF retrievals at 740 nm spanning the 2003-2012 time frame has been produced from ENVISATSCIAMACHY. This observational scenario has been completed by the first fluorescence data from the NASA-JPL OCO-2 mission (launched in July 2014) and the upcoming Copernicus' Sentinel 5-Precursor to be launched in early 2016. OCO-2 and TROPOMI offer the possibility of monitoring SIF globally with a 100-fold improvement in spatial and temporal resolution with respect to the current measurements from the GOSAT, GOME-2 and SCIAMACHY missions. In this contribution, we will provide an overview of existing global SIF data sets derived from space-based atmospheric spectrometers and will demonstrate the potential of such data to improve our knowledge of vegetation photosynthesis and gross primary production at the synoptic scale. We will show examples of ongoing research exploiting SIF data for an improved monitoring of photosynthetic activity in different ecosystems, including large crop belts worldwide, the Amazon rainforest and boreal evergreen forests.

vegetation agriculture satellite↗

Consistent Evaluation of ACOS-GOSAT, BESD-SCIAMACHY, CarbonTracker, and MACC Through Comparisons to TCCON

Consistent validation of satellite CO2 estimates is a prerequisite for using multiple satellite CO2 measurements for joint flux inversion, and for establishing an accurate long-term atmospheric CO2 data record. Harmonizing satellite CO2 measurements is particularly important since the differences in instruments, observing geometries, sampling strategies, etc. imbue different measurement characteristics in the various satellite CO2 data products. We focus on validating model and satellite observation attributes that impact flux estimates and CO2 assimilation, including accurate error estimates, correlated and random errors, overall biases, biases by season and latitude, the impact of coincidence criteria, validation of seasonal cycle phase and amplitude, yearly growth, and daily variability. We evaluate dry-air mole fraction (X(sub CO2)) for Greenhouse gases Observing SATellite (GOSAT) (Atmospheric CO2 Observations from Space, ACOS b3.5) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) (Bremen Optimal Estimation DOAS, BESD v2.00.08) as well as the CarbonTracker (CT2013b) simulated CO2 mole fraction fields and the Monitoring Atmospheric Composition and Climate (MACC) CO2 inversion system (v13.1) and compare these to Total Carbon Column Observing Network (TCCON) observations (GGG2012/2014). We find standard deviations of 0.9, 0.9, 1.7, and 2.1 parts per million vs. TCCON for CT2013b, MACC, GOSAT, and SCIAMACHY, respectively, with the single observation errors 1.9 and 0.9 times the predicted errors for GOSAT and SCIAMACHY, respectively. We quantify how satellite error drops with data averaging by interpreting according to (error(sup 2) equals a(sup 2) plus b(sup 2) divided by n (with n being the number of observations averaged, a the systematic (correlated) errors, and b the random (uncorrelated) errors). a and b are estimated by satellites, coincidence criteria, and hemisphere. Biases at individual stations have year-to-year variability of 0.3 parts per million, with biases larger than the TCCON predicted bias uncertainty of 0.4 parts per million at many stations. We find that GOSAT and CT2013b under-predict the seasonal cycle amplitude in the Northern Hemisphere (NH) between 46 and 53 degrees North latitude, MACC over-predicts between 26 and 37 degrees North latitude, and CT2013b under-predicts the seasonal cycle amplitude in the Southern Hemisphere (SH). The seasonal cycle phase indicates whether a data set or model lags another data set in time. We find that the GOSAT measurements improve the seasonal cycle phase substantially over the prior while SCIAMACHY measurements improve the phase significantly for just two of seven sites. The models reproduce the measured seasonal cycle phase well except for at Lauder_125HR (CT2013b) and Darwin (MACC). We compare the variability within 1 day between TCCON and models in June-July-August; there is correlation between 0.2 and 0.8 in the NH, with models showing 10-50 percent the variability of TCCON at different stations and CT2013b showing more variability than MACC. This paper highlights findings that provide inputs to estimate flux errors in model assimilations, and places where models and satellites need further investigation, e.g., the SH for models and 45-67 degrees North latitude for GOSAT and CT2013b.

ACOS-GOSAT↗

Validation of GOSAT Data Products; Interim Report on the GOSAT/TANSO Project

The Orbiting Carbon Observatory-2 (OCO-2) Team has continued working closely with the Greenhouse Gases Observing Satellite (GOSAT) team to (i) conduct vicarious calibration experiments in Railroad Valley, NV, U.S.A., (ii) retrieve estimates of X CO2 from OCO-2 and GOSAT TANSO-FTS data, and (iii) validate these products using internationally recognized standards. The OCO-/GOSAT relationship was reinforced in March 2015 with the signing a new Memorandum of Understanding between NASA and the GOSAT and GOSAT-2 partners. Over the past year, while the GOSAT team has been finalizing the V201 product, the OCO-2 team has focused primarily on the delivery of the OCO-2 product, providing new opportunities for cross calibration of the OCO-2 and GOSAT instruments and cross validation of their products. These efforts are just now producing results. Members of the OCO-2 team have also continued the analysis of the GOSAT V161.161 data and the ACOS B3.5 products. Those efforts have produced 2 new refereed publications and several others in review. The OCO-2 now preparing to reprocess the entire GOSAT TANSO-FTS data record using the GOSAT V201 product and OCO-2 B7 algorithm to produce a 7-year, multi-satellite climate data record for X(sub CO2).

Wennberg, Paul↗

Global and Time-Resolved Monitoring of Crop Photosynthesis with Chlorophyll Fluorescence

Photosynthesis is the process by which plants harvest sunlight to produce sugars from carbon dioxide and water. It is the primary source of energy for all life on Earth; hence it is important to understand how this process responds to climate change and human impact. However, model-based estimates of gross primary production (GPP, output from photosynthesis) are highly uncertain, in particular over heavily managed agricultural areas. Recent advances in spectroscopy enable the space-based monitoring of sun-induced chlorophyll fluorescence (SIF) from terrestrial plants. Here we demonstrate that spaceborne SIF retrievals provide a direct measure of the GPP of cropland and grassland ecosystems. Such a strong link with crop photosynthesis is not evident for traditional remotely sensed vegetation indices, nor for more complex carbon cycle models. We use SIF observations to provide a global perspective on agricultural productivity. Our SIF-based crop GPP estimates are 50-75% higher than results from state-of-the-art carbon cycle models over, for example, the US Corn Belt and the Indo-Gangetic Plain, implying that current models severely underestimate the role of management. Our results indicate that SIF data can help us improve our global models for more accurate projections of agricultural productivity and climate impact on crop yields. Extension of our approach to other ecosystems, along with increased observational capabilities for SIF in the near future, holds the prospect of reducing uncertainties in the modeling of the current and future carbon cycle.

fluorescence↗

Prospects for Chlorophyll Fluorescence Remote Sensing from the Orbiting Carbon Observatory-2

The Orbiting Carbon Observatory-2 (OCO-2), scheduled to launch in July 2014, is a NASA mission designed to measure atmospheric CO2. Its main purpose is to allow inversions of net flux estimates of CO2 on regional to continental scales using the total column CO2 retrieved using high-resolution spectra in the 0.76, 1.6, and 2.0 nm ranges. Recently, it was shown that solar-induced chlorophyll fluorescence (SIF), a proxy for gross primary production (GPP, carbon uptake through photosynthesis), can be accurately retrieved from space using high spectral resolution radiances in the 750 nm range from the Japanese GOSAT and European GOME-2 instruments. Here, we use real OCO-2 thermal vacuum test data as well as a full repeat cycle (16 days) of simulated OCO-2 spectra under realistic conditions to evaluate the potential of OCO-2 for retrievals of chlorophyll fluorescence and also its dependence on clouds and aerosols. We find that the single-measurement precision is 0.3-0.5 Wm(exp -2)sr(exp -1) nm(exp -1) (15-25% of typical peak values), better than current measurements from space but still difficult to interpret on a single-sounding basis. The most significant advancement will come from smaller ground-pixel sizes and increased measurement frequency, with a 100-fold increase compared to GOSAT (and about 8 times higher than GOME-2). This will largely decrease the need for coarse spatial and temporal averaging in data analysis and pave the way to accurate local studies.We also find that the lack of full global mapping from the OCO-2 only incurs small representativeness errors on regional averages. Eventually, the combination of net ecosystem exchange (NEE) derived from CO2 source/sink inversions and SIF as proxy for GPP from the same satellite will provide a more process-based understanding of the global carbon cycle.

vegetation agriculture satellite↗

Methane from the Tropospheric Emission Spectrometer (TES)

TES V5 CH4 captures latitudinal gradients, regional variability and interannual variation in the free troposphere. V5 joint retrievals offer improved sensitivity to lower troposphere. Time series extends from 2004 to present. V5 reprocessing in progress. Upper tropospheric bias. Mitigated by N2O correction. Appears largely spatially uniform, so can be corrected. How to relate free-tropospheric values to surface emissions.

methane gas (CH4)↗

Geostationary Carbon Process Mapper (GCPM)

Geostationary Carbon Process Mapper (GCPM) is an earth science mission to measure key atmospheric trace gases related to climate change and human activity.Understanding of sources and sinks of CO2 is currently limited by frequency of observations and uncertainty in vertical transport. GCPM improves this situation by making simultaneous high resolution measurements of CO2, CH4, CF, and CO in near-IR, many times per day. GCPM is able to investigate processes with time scales of minutes to hours. CO2, CH4, CF, Co selected because their combination provides information needed to disentangle natural and anthropogenic sources/sinks. Quasi-continuous monitoring effectively eliminates atmospheric transport uncertainties from source/sink inversion modeling. will have one instrument (GeoFTS), hosted on a commercial communications satellite, planned for two years operation. GCPM will affordably advance the understanding of observed cycle variability improving future climate projections.

Carbon Process↗

The Geostationary Fourier Transform Spectrometer

The Geostationary Fourier Transform Spectrometer (GeoFTS) is an imaging spectrometer designed for an earth science mission to measure key atmospheric trace gases and process tracers related to climate change and human activity. The GeoFTS instrument is a half meter cube size instrument designed to operate in geostationary orbit as a secondary "hosted" payload on a commercial geostationary satellite mission. The advantage of GEO is the ability to continuously stare at a region of the earth, enabling frequent sampling to capture the diurnal variability of biogenic fluxes and anthropogenic emissions from city to continental scales. The science goal is to obtain a process-based understanding of the carbon cycle from simultaneous high spatial resolution measurements of carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), and chlorophyll fluorescence (CF) many times per day in the near infrared spectral region to capture their spatial and temporal variations on diurnal, synoptic, seasonal and interannual time scales. The GeoFTS instrument is based on a Michelson interferometer design with a number of advanced features incorporated. Two of the most important advanced features are the focal plane arrays and the optical path difference mechanism. A breadboard GeoFTS instrument has demonstrated functionality for simultaneous measurements in the visible and IR in the laboratory and subsequently in the field at the California Laboratory for Atmospheric Remote Sensing (CLARS) observatory on Mt. Wilson overlooking the Los Angeles basin. A GeoFTS engineering model instrument is being developed which will make simultaneous visible and IR measurements under space flight like environmental conditions (thermal-vacuum at 180 K). This will demonstrate critical instrument capabilities such as optical alignment stability, interferometer modulation efficiency, and high throughput FPA signal processing. This will reduce flight instrument development risk and show that the GeoFTS design is mature and flight ready.

Carbon exchanges↗

An Examination of the Spatial Distribution of Carbon Dioxide and Systematic Errors

The industrial period and modern age is characterized by combustion of coal, oil, and natural gas for primary energy and transportation leading to rising levels of atmospheric of CO2. This increase, which is being carefully measured, has ramifications throughout the biological world. Through remote sensing, it is possible to measure how many molecules of CO2 lie in a defined column of air. However, other gases and particles are present in the atmosphere, such as aerosols and water, which make such measurements more complicated1. Understanding the detailed geometry and path length of the observation is vital to computing the concentration of CO2. Comparing these satellite readings with ground-truth data (TCCON) the systematic errors arising from these sources can be assessed. Once the error is understood, it can be scaled for in the retrieval algorithms to create a set of data, which is closer to the TCCON measurements1. Using this process, the algorithms are being developed to reduce bias, within.1% worldwide of the true value. At this stage, the accuracy is within 1%, but through correcting small errors contained in the algorithms, such as accounting for the scattering of sunlight, the desired accuracy can be achieved.

Carbon Dioxide (CO2)↗