ALBERT

Description: Emission Inventory (EI) is a fundamental tool to monitor global compliance of greenhouse gases (GHGs) emissions reduction actions. Inventory guidelines provide a best practice to help EI compilers to make comparable national emission estimates, in spite of the differences in data availability across countries and regions. There are a variety of sources of errors and uncertainties, however, that originate beyond what the inventory guidelines define. For example, spatially-explicit EIs, which are a key product for atmospheric modeling applications, are often developed for research purposes, and there are no specific guidelines to disaggregate emission estimates from country scale. On top of that, EIs are fundamentally prone to systematic biases due to the simple calculation methodology and thus an objective evaluation (e.g. atmospheric top-down estimates) is needed to assure the accuracy of the estimates. ODIAC is a global high-resolution (1x1 km) fossil fuel carbon dioxide (CO2) gridded EI that is now often used in atmospheric CO2 modeling. ODIAC is based on disaggregation of national emission estimates made by CDIAC, which is the well accepted standard in the community. The ODIAC emission data product is updated on an annual basis using best available statistical data. Subnational spatial emission patterns are estimated using power plant profiles and satellite-observations of nighttime lights. In addition to the conventional CDIAC gridded data product, ODIAC carries international bunker emissions (shipping and aviation), which allows flux inversion modelers to accurately impose the global total fossil fuel emissions and their horizontal and vertical distribution. We have extensively evaluated ODIAC emissions using fine-grained EIs as well as a high-resolution atmospheric model simulation across different scales (national, subnational/regional, and urban policy relevant) with a focus on the uncertainties associated with the emission disaggregation. We have examined the use of NASA's Black Marble Suomi-NPP/VIIRS nightlight data.

Description: No abstract available

Description: Color Vision Deficiency (CVD) is a decreased ability to discern between particular colors. 8% of men and 0.4% of women have some form of CVD. An informal poll of AGU and AMS twitter followers yielded 10% of 70 respondents self identifying as having CVD. When presenting data on a two-dimensional plane it is common to use colors to represent values, the mapping between values and colors is known as a colormap. Colormap choice is personal and is influenced by: (1) Ability to highlight scientifically interesting data. (2) Institutional choices (supervisor insists on a certain colormap). (3) Domain dominance of a particular colormap (common in the radar community). Colormap choice should be influenced by: (1) Ability to highlight scientifically interesting data. (2) Perceptual uniformity (thus not creating artificial structure). (3) Approachability by those with visual impairments (CVD). (4) Ideally, but not always achievable, reproducibility in greyscale.

Description: The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5C and 2.0C above pre-industrial conditions. The protocols for the 1.5C/2.0C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some bread basket regions, at both 1.5C and 2.0C. Declines are especially evident in simulations that do not take into account direct CO2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5C and 2.0C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate. This article is part of the theme issue The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5C above pre-industrial levels.

Description: In fulfillment of requirements of the Maryland Commission on Climate Change Act of 2015, this report provides updated projections of the amount of sea-level rise relative to Maryland coastal lands that is expected into the next century. These projections represent the consensus of an Expert Group drawn from the Mid-Atlantic region. The framework for these projections is explicitly tied to the projections of global sea-level rise included in the Intergovernmental Panel on Climate Change Fifth Assessment (2014) and incorporates regional factors such as subsidence, distance from melting glaciers and polar ice sheets, and ocean currents. The probability distribution of estimates of relative sea-level rise from the baseline year of 2000 are provided over time and, after 2050, for three different greenhouse gas emissions pathways: Growing Emissions (RCP8.5), Stabilized Emissions (RCP4.5), and meeting the Paris Agreement (RCP2.6). This framework has been recently used in developing relative sea-level rise projections for California, Oregon, Washington, New Jersey, and Delaware as well as several metropolitan areas. The Likely range (66% probability) of the relative rise of mean sea level expected in Maryland between 2000 and 2050 is 0.8 to 1.6 feet, with about a one-in-twenty chance it could exceed 2.0 feet and about a one-in-one hundred chance it could exceed 2.3 feet. Later this century, rates of sea-level rise increasingly depend on the future pathway of global emissions of greenhouse gases during the next sixty years. If emissions continue to grow well into the second half of the 21st century, the Likely range of sea-level rise experienced in Maryland is 2.0 to 4.2 feet over this century, two to four times the sea-level rise experienced during the 20th century. Moreover, there is a one-in-twenty chance that it could exceed 5.2 feet. If, on the other hand, global society were able to bring net greenhouse gas emissions to zero in time to meet the goals of the Paris Climate Agreement and reduce emissions sufficient to limit the increase in global mean temperature to less than 2Celsius over pre-industrial levels, the Likely range for 2100 is 1.2 to 3.0 feet, with a one-in-twenty chance that it would exceed 3.7 feet. The difference in sea-level rise between these contrasting scenarios would diverge even more during the next century, with the failure to reduce emissions in the near term resulting in much greater sea-level rise 100 years from now. Moreover, recent research suggests that, without imminent and substantial reductions in greenhouse gas emissions, the loss of polar ice sheets-and thus the rate of sea-level rise-may be more rapid than assumed in these projections, particularly under the Growing Emissions scenario. These probabilistic sea-level rise projections can and should be used in planning and regulation, infrastructure siting and design, estimation of changes in tidal range and storm surge, developing inundation mapping tools, and adaptation strategies for high-tide flooding and saltwater intrusion.

Description: NASAs Mars Climate Modeling Center at Ames Research Center is currently undergoing an exciting period of growth in personnel, modeling capabilities, and science productivity. We are transitioning from our legacy Arakawa C-grid finite-difference dynamical core to the NOAA/GFDL cubed-sphere finite-volume dynamical core for simulating the climate of Mars in a global framework. This highly parallelized core is scalable and flexible, which allows for significant improvements in the horizontal and vertical resolutions of our simulations. We have implemented the Ames water ice cloud microphysics package described in Haberle et al. (2018) into this new dynamical core. We will present high-resolution simulations of the dust and water cycles that show that sub-degree horizontal resolution improves the agreement between the vertical distribution of dust and water ice and observations. In particular, both water ice clouds and dust are transported to higher altitudes due to stronger topographic circulations at high resolution. Preliminary results suggest that high-resolution global modeling is needed to properly capture critical features of the dust and water cycles, and thus the current Mars climate.

Description: Rain-on-snow (ROS) events have been the focus of numerous studies in the past five years. Their characteristics(frequency, extent, and duration) represent a new and relevant climate indicator. However, monitoring ROS occurrences remotely using satellite observations is deemed challenging. The ROS events can be sporadic, of very different intensities, and the outcome of the rain water uncertain (either it freezes in the snow cover or runs off). Using passive and active microwave remote sensing observations, our study proposes new approaches to monitor the occurrence of ROS events.Specifically, we utilize observations from Advanced Microwave Scanning Radiometer 2 (AMSR2), and Global Precipitation Measurements (GPM) Microwave Imager (GMI), and GPM Dual-frequency Precipitation Radar (DPR). We compare our ROS detection against weather stations and recently published algorithms using a different set of microwave frequencies.

Description: NASA is investigating the utility of a strategically-constructed constellation of infrared sounders on board small satellites to be able to ultimately provide spaceborne measurements of wind. The method proposed by instrument teams is to fly multiple instruments in complementary orbits so that atmospheric motion vector measurements can be made. As part of the investigation of this measurement approach, the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center performed a set of Observing System Simulation Experiments (OSSEs) to demonstrate the value of the wind measurements as well as the corresponding infrared radiance observations that will come from the constellation. This work was an extension of the GMAO OSSE infrastructure and is in the context of the MISTIC Winds concept. It is noted, though, that this provided insight to the overall measurement strategy. This talk addresses the simulation of the atmospheric motion vectors retrieved via the constellation, the simulation and validation of the radiance observations measured via the constellation, the specification of observations errors for both winds and radiances, and the extension of the data assimilation system to utilize these additional observations on top of a full global observation system. Finally, the results from a set of OSSE experiments is presented.

Description: The Silurian Diana Mills pluton is a metamorphosed mafic-ultramafic body in the Piedmont Province of Virginia. Major rock types in the pluton include metadiorite and chloriteamphibole rock, with lesser amounts of hornblendite. However, the most visually striking rocks, found at 4 locations, consist of tanweathering nodules in a dark green matrix. The purpose of this study was to investigate the origin of these nodular rocks. All rocks show evidence of greenschistfacies metamorphism, but relict igneous textures are preserved locally. Apart from the nodules, Caamphibole is ubiquitous in all rock types. Nodules are dominated by serpentine or talc (+magnetite +/- chromite), and many show a thin (less than or equal to 5 mm) radially oriented shell of serpentine against adjacent matrix. The nodules are ultramafic (Mg# approx. 80-90, up to7,563 ppm Cr, up to 2,038 ppm Ni), and their normative mineralogy is dominated by olivine and orthopyroxene. Thus, they represent metamorphosed harzburgites and pyroxenites. Matrix minerals are dominantly amphibole + chlorite, along with variable amounts of talc + magnetite. Some matrix samples are chloriterich, probably reflecting metasomatic reaction with nodules (i.e., they are smallscale ''blackwalls''). Matrix samples are also ultramafic (high Mg#, Cr, and Ni). The matrix of the nodulebearing outcrops is essentially the same as other chloriteamphibole rocks elsewhere in the pluton. We consider these rocks to represent emplacement of an original hornblende peridotite crystal mush (a mixture of crystals and hydrous melt), which locally carried harzburgitic nodules. The nodules most likely represent the earliestformed cumulates from the Diana Mills parent magma.

Description: We assess the impact of satellite sea surface salinity (SSS) observations on dynamical ENSO forecasts. Assimilation of SSS improves the mixed layer depth (MLD) and modulates the Kelvin waves associated with ENSO. In column 2, the initialization differences between experiments that assimilate SSS minus those withholding SSS assimilation are presented. Column 3 shows examples of forecasts generated for the different phases of ENSO. From March to June 2015, the availability of two overlapping satellite SSS instruments, Aquarius and SMAP, allows a unique opportunity to compare and contrast coupled forecasts generated with the benefit of these two satellite SSS observation types. The far right column compares assimilation of Aquarius, SMAP and combined Aquaries and SMAP on forecasts for the 2015 El Nino.