Search NASA⌕ Search

SEARCH · Search NASA

Results for “global uncertainty analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

FLUXNET-CH4 Synthesis Activity: Objectives, Observations, and Future Directions

This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH4) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH4 flux measurements globally, initial results comparing CH4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH4 fluxes across sites ranged from −0.2 ± 0.02 g C m(exp -2) yr(exp -1) for an upland forest site to 114.9 ± 13.4 g C m(exp -2) yr(exp -1) for an estuarine freshwater marsh, with fluxes exceeding 40 g C m(exp -2) yr(exp -1) at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH4 flux across wetland sites globally. Water table position was positively correlated with annual CH4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH4 estimates due to gap-filling and random errors were on average ±1.6 g C m(exp -2) yr(exp -1) at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH4 flux database, the controls on ecosystem CH4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH4 emissions.

Knox, Sara H.↗

Construction of Polarimetric Radar-Based Reference Rain Maps for the Iowa Flood Studies Campaign

The Global Precipitation Measurement (GPM) Mission Iowa Flood Studies (IFloodS) campaign was conducted in central and northeastern Iowa during the months of April-June, 2013. Specific science objectives for IFloodS included quantification of uncertainties in satellite and ground-based estimates of precipitation, 4-D characterization of precipitation physical processes and associated parameters (e.g., size distributions, water contents, types, structure etc.), assessment of the impact of precipitation estimation uncertainty and physical processes on hydrologic predictive skill, and refinement of field observations and data analysis approaches as they pertain to future GPM integrated hydrologic validation and related field studies. In addition to field campaign archival of raw and processed satellite data (including precipitation products), key ground-based platforms such as the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars, University of Iowa X-band dual-polarimetric radars, a large network of paired rain gauge platforms, and a large network of 2D Video and Parsivel disdrometers were deployed. In something of a canonical approach, the radar (NPOL in particular), gauge and disdrometer observational assets were deployed to create a consistent high-quality distributed (time and space sampling) radar-based ground "reference" rainfall dataset, with known uncertainties, that could be used for assessing the satellite-based precipitation products at a range of space/time scales. Subsequently, the impact of uncertainties in the satellite products could be evaluated relative to the ground-benchmark in coupled weather, land-surface and distributed hydrologic modeling frameworks as related to flood prediction. Relative to establishing the ground-based "benchmark", numerous avenues were pursued in the making and verification of IFloodS "reference" dual-polarimetric radar-based rain maps, and this study documents the process and results as they pertain specifically to efforts using the NPOL radar dataset. The initial portions of the "process" involved dual-polarimetric quality control procedures which employed standard phase and correlation-based approaches to removal of clutter and non-meteorological echo. Calculation of a scale-adaptive KDP was accomplished using the method of Wang and Chandrasekar (2009; J. Atmos. Oceanic Tech.). A dual-polarimetric blockage algorithm based on Lang et al. (2009; J. Atmos. Oceanic Tech.) was then implemented to correct radar reflectivity and differential reflectivity at low elevation angles. Next, hydrometeor identification algorithms were run to identify liquid and ice hydrometeors. After the quality control and data preparation steps were completed several different dual-polarimetric rain estimation algorithms were employed to estimate rainfall rates using rainfall scans collected approximately every two to three minutes throughout the campaign. These algorithms included a polarimetrically-tuned Z-R algorithm that adjusts for drop oscillations (via Bringi et al., 2004, J. Atmos. Oceanic Tech.), and several different hybrid polarimetric variable approaches, including one that made use of parameters tuned to IFloodS 2D Video Disdrometer measurements. Finally, a hybrid scan algorithm was designed to merge the rain rate estimates from multiple low level elevation angle scans (where blockages could not be appropriately corrected) in order to create individual low-level rain maps. Individual rain maps at each time step were subsequently accumulated over multiple time scales for comparison to gauge network data. The comparison results and overall error character depended strongly on rain event type, polarimetric estimator applied, and range from the radar. We will present the outcome of these comparisons and their impact on constructing composited "reference" rainfall maps at select time and space scales.

Radar↗

Spectral Range Within Global aCDOM(440) Algorithms for Oceanic, Coastal, and Inland Waters with Application to Airborne Measurements

The optically active component of dissolved organic material in aquatic ecosystems, or colored dissolved organic matter (CDOM), is represented by the coefficient of absorption due to the dissolved aquatic constituents at 440 nm, aCDOM(440). Remote sensing of aCDOM(440) enables characterization of ecosystem processes and aids in retrieval of chlorophyll a, a proxy for phytoplankton biomass. Spectrally adjacent band-ratio domains, e.g., blue to green, have previously been applied for remote sensing of aCDOM(440) in coastal and oceanic waters with similar results compared to more complex semi-analytical algorithms. Estimation of aCDOM(440) from ratios of the most spectrally separated ocean color wavebands (end members), e.g., ultraviolet (UV) to near-infrared (NIR), termed end-member analysis (EMA), has previously been shown to increase the accuracy of global aCDOM(440) retrievals from in-water observations of diffuse attenuation and to enable a unified algorithmic perspective without requiring regional adjustment of internal bio-optical parameters. EMA of above-water observations is evaluated herein, with a focus on coastal and inland waters in which increasing optical complexity and likelihood of bottom reflectance challenge the oceanic algorithms developed for deep and optically simple (case-1) waters. Analysis herein of three independent, in situ, bio-optical datasets indicates significant correlation between aCDOM(440) and end-member band ratios (next-generation 320 and 780 nm or legacy 412 and 670 nm ratios) with a coefficient of determination, R2, of 0.87 (log-scale) or higher based on a dataset spanning the dynamic range of global, conservative water bodies. For applicable wavelengths, EMA algorithms are shown to agree with case-1 relationships and to produce consistent log-scale uncertainties across more than three orders of magnitude in aCDOM(440) values (0.001–2.305 m􀀀1). EMA using UV and NIR wavelengths (320 and 780 nm) is applied to low-altitude airborne observations and satisfies 25% uncertainty based on unbiased percent differences (UPDs) within each of three dissimilar match-up sites ranging in aCDOM(440) from 0.02–0.57 m􀀀1. Results demonstrate that EMA is a useful and robust approach for the remote sensing of aCDOM(440) in coastal and inland waters, which are generally shallower, contain more optically complex environments, and span a greater range in aCDOM(440) than oceanic waters.

CDOM↗

Using High Frequency Passive Microwave, A-train, and TRMM Data to Evaluate Hydrometer Structure in the NASA GEOS-5 Data Assimilation System

Validating water vapor and prognostic condensate in global models remains a challenging research task. Model parameterizations are still subject to a large number of tunable parameters; furthermore, accurate and representative in situ observations are very sparse, and satellite observations historically have significant quantitative uncertainties. Progress on improving cloud / hydrometeor fields in models stands to benefit greatly from the growing inventory ofA-Train data sets. ill the present study we are using a variety of complementary satellite retrievals of hydrometeors to examine condensate produced by the emerging NASA Modem Era Retrospective Analysis for Research and Applications, MERRA, and its associated atmospheric general circulation model GEOS5. Cloud and precipitation are generated by both grid-scale prognostic equations and by the Relaxed Arakawa-Schubert (RAS) diagnostic convective parameterization. The high frequency channels (89 to 183.3 GHz) from AMSU-B and MRS on NOAA polar orbiting satellites are being used to evaluate the climatology and variability of precipitating ice from tropical convective anvils. Vertical hydrometeor structure from the Tropical Rainfall Measuring Mission (TRMM) and CloudSat radars are used to develop statistics on vertical hydrometeor structure in order to better interpret the extensive high frequency passive microwave climatology. Cloud liquid and ice water path data retrieved from the Moderate Resolution Imaging Spectroradiometer, MODIS, are used to investigate relationships between upper level cloudiness and tropical deep convective anvils. Together these data are used to evaluate cloud / ice water path, gross aspects of vertical hydrometeor structure, and the relationship between cloud extent and surface precipitation that the MERRA reanalysis must capture.

Robertson, Franklin↗

The Central Role of Air Quality Observations in NASA's GEOS Composition Forecasting Model

The NASA GEOS composition forecast model (GEOS-CF) provides global, high-resolution (25 km) air quality forecasts in near-real time. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). The resolution of the forecasts is the highest compared to current, publicly-available global composition forecasts.Air quality observations are an indispensable tool to evaluate the model's ability to capture the strong temporal and spatial gradients of air pollutants across the globe. We show how comparisons against near-real time observations available through OpenAQ (www.openaq.org) demonstrate the model's overall success in reproducing surface concentrations of ozone, nitrogen dioxide, and PM2.5. This analysis also helps identifying current limitations of the model, for example over South America. The model-observation mismatches are most likely caused by uncertainties in the emissions data. Using the example of Rio de Janeiro, we show how the model skill can be improved by using local, high-resolution emission inventories in combination with air quality data.

Keller, Christoph A.↗

Evaporation from the Southern Ocean Estimated on the Basis of AIRS Satellite Data

Evaporation plays an important role in the global water and energy cycles and, hence, in climate change. Evaporation over the Southern Ocean, where the Antarctic sea ice coverage has a large annual cycle, is poorly quantified. In this study, daily evaporation is estimated for the Southern Ocean with a sea‐ice‐specific algorithm, using surface temperature and air humidity from National Aeronautics and Space Administration's Atmospheric Infrared Sounder (AIRS), and wind speeds from Modern‐Era Retrospective Analysis for Research and Applications, Version 2 (MERRA‐2), reanalysis during 2003–2016. An uncertainty of 34% was found in the evaporation product. The results indicate that annual evaporation has considerable interannual and regional variability, but with a decreasing trend during the study period over most of the Southern Ocean. There are, however, areas where evaporation has increased, specifically in the Ross Sea in winter and summer, with smaller positive trends in spring and fall. Overall, the changes in the difference between the surface specific humidity and the air specific humidity, and to a much lesser extent in the wind speed, are the main drivers for the changes in evaporation throughout the year. During spring and fall months, changes to the sea ice cover, which alter the surface specific humidity, are the main drivers for the change, but in summer and winter the main driver is the air‐specific humidity. Air masses originating from the Antarctic continent (south) are associated with cold and dry conditions, which increase evaporation, whereas air masses from lower latitudes in the Southern Ocean (north) are associated with warm and moist conditions, decreasing evaporation. Comparisons with other reanalysis evaporation products produce similar trends, although annual averages differ.

Boisvert, Linette↗

OVOC (Oxygenated Volatile Organic Chemicals) in the Global Atmosphere: Atmospheric Budgets, Oceanic Concentrations, and Uncertainties

Airborne measurements of oxygenated volatile organic chemicals (OVOC), OH free radicals, and tracers of pollution were performed over the Pacific during Winter/Spring of 2001. Large concentrations of OVOC are present in the global troposphere and are expected to play an important role in atmospheric chemistry. Their total abundance (SIGMAOVOC) was nearly twice that of non-methane hydrocarbons (SIGMAC2-C8 NMHC). Throughout the troposphere, the OH reactivity of OVOC is comparable to that of methane and far exceeds that of NHMC. A comparison of these data with western Pacific observations collected some seven years earlier (Feb.-March, 1994) did not reveal significant differences. Analysis of the relative enhancement of selected OVOC with respect to CH3Cl and CO in twelve plumes originating from fires and sampled in the free troposphere (3-11 km) is used to assess their primary and secondary emissions from biomass combustion. The composition of these plumes also indicates a large shift of reactive nitrogen into the PAN reservoir thereby limiting ozone formation. These data are combined with other observations and interpreted with the help of a global 3-D model to assess OVOC global sources and sinks. We further interpret atmospheric observations with the help of an air-sea exchange model io show that oceans can be both net so~rces and sinks. An extremely large oceanic reservoir of OVOC, that exceeds the atmospheric reservoir by more than an order of magnitude, can be inferred to be present. We conclude that OVOC sources are extremely large (150-500 TgC y-1) but remain poorly quantified. In many cases, measured concentrations are uncertain and incompatible with our present knowledge of atmospheric chemistry. Results based on observations from several field studies and critical gaps will be discussed.

Singh, Hanwant B.↗

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↗

Online Assessment of Satellite-Derived Global Precipitation Products

Precipitation is difficult to measure and predict. Each year droughts and floods cause severe property damages and human casualties around the world. Accurate measurement and forecast are important for mitigation and preparedness efforts. Significant progress has been made over the past decade in satellite precipitation product development. In particular, products' spatial and temporal resolutions as well as timely availability have been improved by blended techniques. Their resulting products are widely used in various research and applications. However biases and uncertainties are common among precipitation products and an obstacle exists in quickly gaining knowledge of product quality, biases and behavior at a local or regional scale, namely user defined areas or points of interest. Current online inter-comparison and validation services have not addressed this issue adequately. To address this issue, we have developed a prototype to inter-compare satellite derived daily products in the TRMM Online Visualization and Analysis System (TOVAS). Despite its limited functionality and datasets, users can use this tool to generate customized plots within the United States for 2005. In addition, users can download customized data for further analysis, e.g. comparing their gauge data. To meet increasing demands, we plan to increase the temporal coverage and expanded the spatial coverage from the United States to the globe. More products have been added as well. In this poster, we present two new tools: Inter-comparison of 3B42RT and 3B42 Inter-comparison of V6 and V7 TRMM L-3 monthly products The future plans include integrating IPWG (International Precipitation Working Group) Validation Algorithms/statistics, allowing users to generate customized plots and data. In addition, we will expand the current daily products to monthly and their climatology products. Whenever the TRMM science team changes their product version number, users would like to know the differences by inter-comparing both versions of TRMM products in their areas of interest. Making this service available to users will help them to better understand associated changes. We plan to implement this inter-comparison in TRMM standard monthly products with the IPWG algorithms. The plans outlined above will complement and accelerate the existing and ongoing validation activities in the community as well as enhance data services for TRMM and the future Global Precipitation Mission (GPM).

Liu, Zhong↗

Sensitivity of the Assimilated Ozone in the UTLS to Model and Data Selection Changes

This presentation will discuss the sensitivity of assimilated ozone fields in the upper troposphere and lower stratosphere (UTLS) to a number of factors, focusing mainly on aspects of data selection and the prediction model. This is important, because assimilation represents an attempt to construct our best estimates of the true ozone field; however, inaccuracies in the UTLS ozone distribution translate into an uncertainty in factors such as the calculated radiative forcing of climate or the inferred stratosphere-troposphere exchange (STE) of ozone. The 3D ozone data assimilation system, from NASA's Global Modeling and Assimilation Office (GMAO), combines observations of total ozone column and stratospheric profiles with predictions from an off-line, parameterized chemistry and transport model (pCTM) to produce six-hourly, global analyses. The first experiments discussed assimilate ozone retrievals from the Earth-Probe Total Ozone Mapping Spectrometer (EPTOMS) and stratospheric profiles from the Solar Backscatter UltraViolet/2 (SBUV/2) instrument. The SBUV/2 ozone data have a coarse vertical resolution, with increased uncertainty below the ozone maximum, and TOMS provides only total ozone columns. Thus, the assimilated ozone profiles in the UTLS region are only weakly constrained by the incoming SBUV and TOMS data. Consequently, the assimilated ozone distribution should be sensitive to changes in inputs to the statistical analysis scheme. Sensitivity studies have been conducted to examine the responses to TOMS and SBUV/2 data selection, modifications of the forecast and observation error covariance models, and the model formulation (turning off chemistry or using different wind analyses in the pCTM). The second set of experiments includes an additional data type: ozone retrieved from infrared limb-emission by MIPAS on Envisat. These data offer not only improved vertical resolution in the stratosphere, but also give measurements in the polar night. Comparisons of the assimilated ozone fields from both sets of experiments with independent observations, primarily ozone sondes, are used to determine the impact of each of these changes. It is shown that many of the changes have a significant impact on the UTLS ozone estimates. Implications for interpretation of STE and radiative forcing of climate are discussed.

Pawson, Steven↗

Implications of CO Bias for Ozone and Methane Lifetime in a CCM

A low bias in carbon monoxide compared to observations at high latitudes is a common feature of chemistry climate models. CO bias can both indicate and contribute to a bias in modeled OH and methane lifetime. This study examines possible causes of CO bias in the ACCMIP simulation of the GEOSCCM, and considers how attributing the CO bias to uncertainty in CO emissions versus biases in other constituents impacts the relationship between CO bias and methane lifetime. We use a simplified model of CO tagged by source with specified OH to quantify the sensitivity of the CO bias to changes in CO emissions or OH concentration, comparing the modeled CO to surface and MOPITT observations. The simplified model shows that decreasing OH in the northern hemisphere removes most of the global mean and inter-hemispheric bias in surface CO. We then use results from this analysis to explore how adjusting CO sources in the CCM impacts the concentrations of ozone, OH and methane. The CCM simulation also exhibits biases in ozone and water vapor compared to observations. We use a parameterized CO-OH-CH4 model that takes ozone and water vapor as inputs to the parameterization to examine whether correcting water and ozone biases can alter OH enough to remove the CO bias. Through this analysis, we aim to better quantify the relationship between CO bias and model biases in ozone concentrations and methane lifetime.

carbon monoxide↗

Seismic Study of the Dynamics of the Solar Subsurface from SoHO Observations

In collaboration with Dr. Baudin, we have developed and refined the new observational methodology for local helioseismology known as time-distance analysis. Global helioseismology study the solar oscillations as a superposition of resonant modes, whose properties (mode frequencies) reflect the global structure of the sun (sound speed stratification, rotation rate, etc). In contrast, local helioseismology look at the solar oscillations as wave packets whose propagation will be affected by perturbations of the media sampled. These local perturbations (sound speed or velocity flows) will modify the propagation time, that in turn can be used as a diagnostic tool for a given region. From a data reduction perspective, the processing of solar dopplergrams that result in time-distance maps, i.e. propagation times as a function of distance between bounces at the surface, is radically different from the methodology used for global mode analysis. We have, in a first step, further develop the programs needed to carry out such analysis. We have then applied them to NMI data set, and explore the trade-off between various averaging and filtering approaches - steps required to improve the signal-to-noise ratio of correlation maps - and the resulting stability and precision of the fitted propagation times. While excessive averaging (whether over space, propagation distance, or time) will reduce the diagnostic potential of the method, insufficient averaging lead to unstable fits, or uncertainties so large as to hide the information we seek. In a second phase, we have developed the analysis methodology required to infer local properties from perturbation in time propagation. Namely, we have developed time-distance inversion techniques, with an emphasis on inferences of velocity flows from time anomalies. Note also that during the period covered by this grant, all the investigators on this proposal (i.e., Drs. Baudin, Eff-Darwich, Korzennik, and Noyes) took part in the organization of the SOHO 6 /GONG 99 Workshop: Structure and Dynamics of the Interior of the Sun and Sunlike Stars, held on June 1-4 1999 at the Boston Park Plaza Hotel in Boston, Massachusetts, USA. it was very well attended by more than 160 participants from 26 countries from all over the world. The proceedings were published in two volumes as ESA SP-418, with Sessions I-III in Volume 1, and Sessions IV-VI in Volume 2 (1,000 pages in total). The complete contents are also included in digital form on a CD-ROM included with Volume 1. This CD-ROM also contains additional multi-media material that complements some of the contributions.

Korzennik, Sylvain G.↗

TRMM: Status of Precipitation Estimates and Science Highlights

As a part of NASA's Earth System Enterprise, the Tropical Rainfall Measuring Mission (TRMM) seeks to understand the mechanisms through which changes in tropical rainfall influence global circulation. Over the past 3 years, TRMM has contributed significantly towards reducing uncertainty in satellite estimates of rainfall in the Tropics, where almost 67% of the Earth's rain falls. TRMM has provided knowledge related to the climatology, seasonality, and variation of tropical rainfall; the mesoscale structure of rain-producing systems; and the physics of precipitation. An overview of these results will be presented. Additionally, a summary of research highlights will be presented focusing on application of TRMM data to topics such as hurricane monitoring, climate analysis, forecasting, microphysics, environmental impacts, and El Nino/La Nina. Examples and plans for operational use of TRMM data in tropical cyclone monitoring and other applications will also be given.

Shepherd, J. Marshall↗

Assessment of Satellite Radiometry in the Visible Domain

Marine reflectance and chlorophyll-a concentration are listed among the Essential Climate Variables by the Global Climate Observing System. To contribute to climate research, the satellite ocean color data records resulting from successive missions need to be consistent and well characterized in terms of uncertainties. This chapter reviews various approaches that can be used for the assessment of satellite ocean color data. Good practices for validating satellite products with in situ data and the current status of validation results are illustrated. Model-based approaches and inter-comparison techniques can also contribute to characterize some components of the uncertainty budget, while time series analysis can detect issues with the instrument radiometric characterization and calibration. Satellite data from different missions should also provide a consistent picture in scales of variability, including seasonal and interannual signals. Eventually, the various assessment approaches should be combined to create a fully characterized climate data record from satellite ocean color.

ocean color↗

Use of three-cornered hat error estimates in MERRA-2 to guide an improved reanalysis-Part 1

The three-cornered hat (3CH) method estimates the uncertainties of three different co-located model or observational data sets (Anthes and Rieckh, 2018; Sjoberg et al., 2021). Rieckh et al. (2021) used the 3CH method to compare the random error statistics of different global forecast and reanalysis models, as well as radio occultation (RO) and radiosonde observations. That study showed that the MERRA-2 reanalysis, while having smaller errors in the stratosphere than its predecessor MERRA, had larger errors in the troposphere than many of the other data sets analyzed. The MERRA-2 errors were particularly large in the tropics. In a collaborative effort between UCAR’s COSMIC (Constellation Observing System for Meteorology, Ionosphere and Meteorology) program and NASA’s Global Modeling and Assimilation Office (GMAO), we carried out further 3CH error diagnostics to help isolate the causes of these larger errors and help guide the development of an improved reanalysis. This presentation summarizes random error statistics associated with MERRA-2, ECMWF’s ERA5 reanalysis, and COSMIC-2 (C2) RO observations. We compute 3CH error variance estimates of refractivity, as well as temperature and specific humidity using UCAR’s COSMIC Data Analysis and Archive Center (CDAAC) improved 1D-variational (1D-Var) retrieval (wetPf2) over 15 latitude bands from 45S to 45N. The 1D-Var retrievals of specific humidity and temperature for C2 use NCEP’s Global Forecast System (GFS) as the background. Anthes et al. (2021) showed that it gives accurate estimates of temperature and specific humidity in the tropics and subtropics, even in the challenging environment of intense Hurricane Dorian (2019). This presentation confirms the previous results that MERRA-2 has significantly larger errors in the tropics and subtropics than either C2 or ERA5. Its errors are larger between 30S and 30N compared to 30-45 N-S latitudes, and are also larger over land compared to oceans. Most of the MERRA-2 refractivity errors come from specific humidity, except over land below 3 km where temperature errors are large. These results suggest that moist convection and atmospheric boundary layer physics in MERRA-2 may be responsible for a significant part of the higher uncertainties. These results are being used to guide GMAO in developing an improved next-generation reanalysis, as shown in a companion presentation submitted to this conference (El Akkraoui et al., 2021), which extends this study and describes improvements to MERRA-2 leading to the next GMAO reanalysis.

Jeremiah Sjoberg↗

Modeling Uncertainty in Large Natural Resource Allocation Problems

The productivity of the world's natural resources is critically dependent on a variety of highly uncertain factors, which obscure individual investors and governments that seek to make long-term, sometimes irreversible investments in their exploration and utilization. These dynamic considerations are poorly represented in disaggregated resource models, as incorporating uncertainty into large-dimensional problems presents a challenging computational task. This study introduces a novel numerical method to solve large-scale dynamic stochastic natural resource allocation problems that cannot be addressed by conventional methods. The method is illustrated with an application focusing on the allocation of global land resource use under stochastic crop yields due to adverse climate impacts and limits on further technological progress. For the same model parameters, the range of land conversion is considerably smaller for the dynamic stochastic model as compared to deterministic scenario analysis. The scenario analysis can thus significantly overstate the magnitude of expected land conversion under uncertain crop yields.

Cai, Yongyang↗

An Inversion Analysis of Recent Variability in Natural CO2 Fluxes Using GOSAT and In Situ Observations

About one-half of the global CO2 emissions from fossil fuel combustion and deforestation accumulates in the atmosphere, where it contributes to global warming. The rest is taken up by vegetation and the ocean. The precise contribution of the two sinks, and their location and year-to-year variability are, however, not well understood. We use two different approaches, batch Bayesian synthesis inversion and variational data assimilation, to deduce the global spatiotemporal distributions of CO2 fluxes during 2009-2010. One of our objectives is to assess different sources of uncertainties in inferred fluxes, including uncertainties in prior flux estimates and observations, and differences in inversion techniques. For prior constraints, we utilize fluxes and uncertainties from the CASA-GFED model of the terrestrial biosphere and biomass burning driven by satellite observations and interannually varying meteorology. We also use measurement-based ocean flux estimates and two sets of fixed fossil CO2 emissions. Here, our inversions incorporate column CO2 measurements from the GOSAT satellite (ACOS retrieval, filtered and bias-corrected) and in situ observations (individual flask and afternoon-average continuous observations) to estimate fluxes in 108 regions over 8-day intervals for the batch inversion and at 3 x 3.75 weekly for the variational system. Relationships between fluxes and atmospheric concentrations are derived consistently for the two inversion systems using the PCTM atmospheric transport model driven by meteorology from the MERRA reanalysis. We compare the posterior fluxes and uncertainties derived using different data sets and the two inversion approaches, and evaluate the posterior atmospheric concentrations against independent data including aircraft measurements. The optimized fluxes generally resemble those from other studies. For example, the results indicate that the terrestrial biosphere is a net CO2 sink, and a GOSAT-only inversion suggests a shift in the global sink from the tropics south to the north relative to the prior and to an in-situ-only inversion. We also find a smaller terrestrial sink in higher-latitude northern regions in boreal summer of 2010 relative to 2009.

Carbon dioxide↗

Estimates of Ice Sheet Mass Balance from Satellite Altimetry: Past and Future

A major uncertainty in predicting sea level rise is the sensitivity of ice sheet mass balance to climate change, as well as the uncertainty in present mass balance. Since the annual water exchange is about 8 mm of global sea level equivalent, the 20% uncertainty in current mass balance corresponds to 1.6 mm/yr in sea level change. Furthermore, estimates of the sensitivity of the mass balance to temperature change range from perhaps as much as - 10% to + 10% per K. A principal purpose of obtaining ice sheet elevation changes from satellite altimetry has been estimation of the current ice sheet mass balance. Limited information on ice sheet elevation change and their implications about mass balance have been reported by several investigators from radar altimetry (Seasat, Geosat, ERS-1&2). Analysis of ERS-1&2 data over Greenland for 7 years from 1992 to 1999 shows mixed patterns of ice elevation increases and decreases that are significant in terms of regional-scale mass balances. Observed seasonal and interannual variations in ice surface elevation are larger than previously expected because of seasonal and interannUal variations in precipitation, melting, and firn compaction. In the accumulation zone, the variations in firn compaction are modeled as a function of temperature leaving variations in precipitation and the mass balance trend. Significant interannual variations in elevation in some locations, in particular the difference in trends from 1992 to 1995 compared to 1995 to 1999, can be explained by changes in precipitation over Greenland. Over the 7 years, trends in elevation are mostly positive at higher elevations and negative at lower elevations. In addition, trends for the winter seasons (from a trend analysis through the average winter elevations) are more positive than the corresponding trends for the summer. At lower elevations, the 7-year trends in some locations are strongly negative for summer and near zero or slightly positive for winter. These observations also demonstrate the potential for relating the variability in mass balance to changes in precipitation, temperature, and melting. Beginning in January 2002, NASA's ICESat laser altimeter mission will provide significantly better elevation accuracy and spatial coverage to 86E latitude and to the margins of the ice sheets.

Zwally, H. Jay↗