ALBERT

Description: Substantial uncertainties still exist in the scientific understanding of the possible interactions between urban and natural (biogenic) emissions in the production and transformation of atmospheric aerosol and the resulting impact on climate change. The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Carbonaceous Aerosol and Radiative Effects Study (CARES) carried out in June 2010 in Central Valley, California, was a comprehensive effort designed to improve this understanding. The primary objective of the field study was to investigate the evolution of secondary organic and black carbon aerosols and their climate-related properties in the Sacramento urban plume as it was routinely transported into the forested Sierra Nevada foothills area. Urban aerosols and trace gases experienced significant physical and chemical transformations as they mixed with the reactive biogenic hydrocarbons emitted from the forest. Two heavily-instrumented ground sites – one within the Sacramento urban area and another about 40 km to the northeast in the foothills area – were set up to characterize the evolution of meteorological variables, trace gases, aerosol precursors, aerosol size, composition, and climate-related properties in freshly polluted and "aged" urban air. On selected days, the DOE G-1 aircraft was deployed to make similar measurements upwind and across the evolving Sacramento plume in the morning and again in the afternoon. The NASA B-200 aircraft, carrying remote sensing instruments, was also deployed to characterize the vertical and horizontal distribution of aerosols and aerosol optical properties within and around the plume. This overview provides: (a) the scientific background and motivation for the study, (b) the operational and logistical information pertinent to the execution of the study, (c) an overview of key observations and initial findings from the aircraft and ground-based sampling platforms, and (d) a roadmap of planned data analyses and focused modeling efforts that will facilitate the integration of new knowledge into improved representations of key aerosol processes and properties in climate models.

Description: We present Bedmap2, a new suite of gridded products describing surface elevation, ice-thickness and the seafloor and subglacial bed elevation of the Antarctic south of 60° S. We derived these products using data from a variety of sources, including many substantial surveys completed since the original Bedmap compilation (Bedmap1) in 2001. In particular, the Bedmap2 ice thickness grid is made from 25 million measurements, over two orders of magnitude more than were used in Bedmap1. In most parts of Antarctica the subglacial landscape is visible in much greater detail than was previously available and the improved coverage of data has in many areas revealed the full scale of mountain ranges, valleys, basins and troughs, only fragments of which were previously indicated in local surveys. The derived statistics for Bedmap2 show that the volume of ice contained in the Antarctic ice sheet (27 million km3) and its potential contribution to sea-level rise (58 m) are similar to those of Bedmap1, but the mean thickness of the ice sheet is 4.6 % greater, the mean depth of the bed beneath the grounded ice sheet is 72 m lower and the area of ice sheet grounded on bed below sea level is increased by 10 %. The Bedmap2 compilation highlights several areas beneath the ice sheet where the bed elevation is substantially lower than the deepest bed indicated by Bedmap1. These products, along with grids of data coverage and uncertainty, provide new opportunities for detailed modelling of the past and future evolution of the Antarctic ice sheets.

Description: Substantial uncertainties still exist in the scientific understanding of the possible interactions between urban and natural (biogenic) emissions in the production and transformation of atmospheric aerosol and the resulting impact on climate change. The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Carbonaceous Aerosol and Radiative Effects Study (CARES) carried out in June 2010 in Central Valley, California, was a comprehensive effort designed to improve this understanding. The primary objective of the field study was to investigate the evolution of secondary organic and black carbon aerosols and their climate-related properties in the Sacramento urban plume as it was routinely transported into the forested Sierra Nevada foothills area. Urban aerosols and trace gases experienced significant physical and chemical transformations as they mixed with the reactive biogenic hydrocarbons emitted from the forest. Two heavily-instrumented ground sites – one within the Sacramento urban area and another about 40 km to the northeast in the foothills area – were set up to characterize the evolution of meteorological variables, trace gases, aerosol precursors, aerosol size, composition, and climate-related properties in freshly polluted and "aged" urban air. On selected days, the DOE G-1 aircraft was deployed to make similar measurements upwind and across the evolving Sacramento plume in the morning and again in the afternoon. The NASA B-200 aircraft, carrying remote sensing instruments, was also deployed to characterize the vertical and horizontal distribution of aerosols and aerosol optical properties within and around the plume. This overview provides: (a) the scientific background and motivation for the study, (b) the operational and logistical information pertinent to the execution of the study, (c) an overview of key observations and initial results from the aircraft and ground-based sampling platforms, and (d) a roadmap of planned data analyses and focused modeling efforts that will facilitate the integration of new knowledge into improved representations of key aerosol processes in climate models.

Description: Observations of a comprehensive suite of inorganic and organic trace gases, including non-methane hydrocarbons (NMHCs), halogenated organics and oxygenated volatile organic compounds (OVOCs), obtained from the NASA DC-8 over Canada during the ARCTAS aircraft campaign in July 2008 illustrate that convection is important for redistributing both long- and short-lived species throughout the troposphere. Convective outflow events were identified by the elevated mixing ratios of organic species in the upper troposphere relative to background conditions. Several dramatic events were observed in which isoprene and its oxidation products were detected at hundreds of pptv at altitudes higher than 8 km. Two events are studied in detail using detailed experimental data and the NASA Langley Research Center (LaRC) box model. One event had no lightning NOx (NO + NO2) associated with it and the other had substantial lightning NOx (LNOx 〉 1 ppbv). When convective storms transport isoprene from the boundary layer to the upper troposphere and no LNOx is present, OH is reduced due to scavenging by isoprene, which serves to slow the chemistry, resulting in longer lifetimes for species that react with OH. Ozone and PAN production is minimal in this case. In the case where isoprene is convected and LNOx is present, there is a large effect on the expected ensuing chemistry: isoprene exerts a dominant impact on HOx and nitrogen-containing species; the relative contribution from other species to HOx, such as peroxides, is insignificant. The isoprene reacts quickly, resulting in primary and secondary products, including formaldehyde and methyl glyoxal. The model predicts enhanced production of alkyl nitrates (ANs) and peroxyacyl nitrate compounds (PANs). PANs persist because of the cold temperatures of the upper troposphere resulting in a large change in the NOx mixing ratios which, in turn, has a large impact on the HOx chemistry. Ozone production is substantial during the first few hours following the convection to the UT, resulting in a net gain of approximately 10 ppbv compared to the modeled scenario in which LNOx is present but no isoprene is present aloft.

Description: Land models, which have been developed by the modeling community in the past two decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure and evaluate performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land models. The framework includes (1) targeted aspects of model performance to be evaluated; (2) a set of benchmarks as defined references to test model performance; (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies; and (4) model improvement. Component 4 may or may not be involved in a benchmark analysis but is an ultimate goal of general modeling research. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and the land-surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics across timescales in response to both weather and climate change. Benchmarks that are used to evaluate models generally consist of direct observations, data-model products, and data-derived patterns and relationships. Metrics of measuring mismatches between models and benchmarks may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data-model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance for future improvement. Iterations between model evaluation and improvement via benchmarking shall demonstrate progress of land modeling and help establish confidence in land models for their predictions of future states of ecosystems and climate.

Description: A well documented, publicly available, global data set of surface ocean carbon dioxide (CO2) parameters has been called for by international groups for nearly two decades. The Surface Ocean CO2 Atlas (SOCAT) project was initiated by the international marine carbon science community in 2007 with the aim of providing a comprehensive, publicly available, regularly updated, global data set of marine surface CO2, which had been subject to quality control (QC). Many additional CO2 data, not yet made public via the Carbon Dioxide Information Analysis Center (CDIAC), were retrieved from data originators, public websites and other data centres. All data were put in a uniform format following a strict protocol. Quality control was carried out according to clearly defined criteria. Regional specialists performed the quality control, using state-of-the-art web-based tools, specially developed for accomplishing this global team effort. SOCAT version 1.5 was made public in September 2011 and holds 6.3 million quality controlled surface CO2 data points from the global oceans and coastal seas, spanning four decades (1968–2007). Three types of data products are available: individual cruise files, a merged complete data set and gridded products. With the rapid expansion of marine CO2 data collection and the importance of quantifying net global oceanic CO2 uptake and its changes, sustained data synthesis and data access are priorities.

Description: Peatlands are a major terrestrial carbon store and a persistent natural carbon sink during the Holocene, but there is considerable uncertainty over the fate of peatland carbon in a changing climate. It is generally assumed that higher temperatures will increase peat decay, causing a positive feedback to climate warming and contributing to the global positive carbon cycle feedback. Here we use a new extensive database of peat profiles across northern high latitudes to examine spatial and temporal patterns of carbon accumulation over the past millennium. Opposite to expectations, our results indicate a small negative carbon cycle feedback from past changes in the long-term accumulation rates of northern peatlands. Total carbon accumulated over the last 1000 yr is linearly related to contemporary growing season length and photosynthetically active radiation, suggesting that variability in net primary productivity is more important than decomposition in determining long-term carbon accumulation. Furthermore, northern peatland carbon sequestration rate declines over the climate transition from the Medieval Climate Anomaly (MCA) to the Little Ice Age (LIA), probably because of lower LIA temperatures combined with increased cloudiness suppressing net primary productivity. Other factors including changing moisture status, peatland distribution, fire, nitrogen deposition, permafrost thaw and methane emissions will also influence future peatland carbon cycle feedbacks, but our data suggest that the carbon sequestration rate could increase over many areas of northern peatlands.

Description: Results from simulations performed for the Atmospheric Chemistry and Climate Modeling Intercomparison Project (ACCMIP) are analysed to examine how OH and methane lifetime may change from present-day to the future, under different climate and emissions scenarios. Present-day (2000) mean tropospheric chemical lifetime derived from the ACCMIP multi-model mean is 9.8 ± 1.6 yr, lower than a recent observationally-based estimate, but with a similar range to previous multi-model estimates. Future model projections are based on the four Representative Concentration Pathways (RCPs), and the results also exhibit a~large range. Decreases in global methane lifetime of 4.5 ± 9.1% are simulated for the scenario with lowest radiative forcing by 2100 (RCP 2.6), while increases of 8.5 ± 10.4% are simulated for the scenario with highest radiative forcing (RCP 8.5). In this scenario, the key driver of the evolution of OH and methane lifetime is methane itself, since its concentration more than doubles by 2100, and it consumes much of the OH that exists in the troposphere. Stratospheric ozone recovery, which drives tropospheric OH decreases through photolysis modifications, also plays a~partial role. In the other scenarios, where methane changes are less drastic, the interplay between various competing drivers leads to smaller and more diverse OH and methane lifetime responses, which are difficult to attribute. For all scenarios, regional OH changes are even more variable, with the most robust feature being the large decreases over the remote oceans in RCP 8.5. Through a~regression analysis, we suggest that differences in emissions of non-methane volatile organic compounds and in the simulation of photolysis rates may be the main factors causing the differences in simulated present-day OH and methane lifetime. Diversity in predicted changes between present-day and future was found to be associated more strongly with differences in modelled climate changes, specifically global temperature and humidity. Finally, through perturbation experiments we calculated an OH feedback factor (F) of 1.29 from present-day conditions (1.65 from 2100 RCP 8.5 conditions) and a~climate feedback on methane lifetime of 0.33 ± 0.13 yr K−1, on average.

Description: Here, we report preliminary estimates of the column averaged carbon dioxide (CO2) dry air mole fraction, XCO2, retrieved from spectra recorded over land by the Greenhouse gases Observing Satellite, GOSAT (nicknamed "Ibuki"), using retrieval methods originally developed for the NASA Orbiting Carbon Observatory (OCO) mission. After screening for clouds and other known error sources, these retrievals reproduce much of the expected structure in the global XCO2 field, including its variation with latitude and season. However, low yields of retrieved XCO2 over persistently cloudy areas and ice covered surfaces at high latitudes limit the coverage of some geographic regions, even on seasonal time scales. Comparisons of early GOSAT XCO2 retrievals with XCO2 estimates from the Total Carbon Column Observing Network (TCCON) revealed a global, −2% (7–8 parts per million, ppm, with respect to dry air) XCO2 bias and 2 to 3 times more variance in the GOSAT retrievals. About half of the global XCO2 bias is associated with a systematic, 1% overestimate in the retrieved air mass, first identified as a global +10 hPa bias in the retrieved surface pressure. This error has been attributed to errors in the O2 A-band absorption cross sections. Much of the remaining bias and spurious variance in the GOSAT XCO2 retrievals has been traced to uncertainties in the instrument's calibration, oversimplified methods for generating O2 and CO2 absorption cross sections, and other subtle errors in the implementation of the retrieval algorithm. Many of these deficiencies have been addressed in the most recent version (Build 2.9) of the retrieval algorithm, which produces negligible bias in XCO2 on global scales as well as a ~30% reduction in variance. Comparisons with TCCON measurements indicate that regional scale biases remain, but these could be reduced by applying empirical corrections like those described by Wunch et al. (2011b). We recommend that such corrections be applied before these data are used in source sink inversion studies to minimize spurious fluxes associated with known biases. These and other lessons learned from the analysis of GOSAT data are expected to accelerate the delivery of high quality data products from the Orbiting Carbon Observatory-2 (OCO-2), once that satellite is successfully launched and inserted into orbit.

Description: Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1) targeted aspects of model performance to be evaluated, (2) a set of benchmarks as defined references to test model performance, (3) metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4) model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1) a priori thresholds of acceptable model performance and (2) a scoring system to combine data–model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties of land models to improve their prediction performance skills.