ALBERT

Description: We explore the skill of predictions of September Arctic sea ice extent from dynamical models participating in the Sea Ice Outlook (SIO). Forecasts submitted in August, at roughly 2 month lead times, are skillful. However, skill is lower in forecasts submitted to SIO, which began in 2008, than in hindcasts (retrospective forecasts) of the last few decades. The multimodel mean SIO predictions offer slightly higher skill than the single-model SIO predictions, but neither beats a damped persistence forecast at longer than 2 month lead times. The models are largely unsuccessful at predicting each other, indicating a large difference in model physics and/or initial conditions. Motivated by this, we perform an initial condition sensitivity experiment with four SIO models, applying a fixed 1 m perturbation to the initial sea ice thickness. The significant range of the response among the models suggests that different model physics make a significant contribution to forecast uncertainty.

Description: Two systematic calibrations have been compiled for the visible radiances measured by the series of AVHRR instruments flown on the NOAA operational polar weather satellites: one by the International Satellite Cloud Climatology Project (ISCCP), anchored on NASA ER-2 underflights in the 1980s and early 1990s and covering the period 1981-2009, and one by the PATMOS-x project, anchored on comparisons to the MODIS instruments on the Aqua and Terra satellites in the 2000s and covering the period 1979-2010 (this result also includes calibration for the near-IR channels). Both methods have had to extend their anchor calibrations over a long series of instruments using different vicarious approaches, so a comparison provides an opportunity to evaluate how well this extension works by cross-checking the results at the anchor points. The basic result of this comparison is that for the ''afternoon'' series of AVHRRs, the calibrations agree to within their mutual uncertainties. However, this retrospective evaluation also shows that the representation of the time variations can be simplified. The ISCCP procedure had much more difficulty extending the calibration to the ''morning'' series of AVHRRs with the calibrations for NOAA-15 and NOAA-17 exceeding the estimated uncertainties. Given the general agreement, a new calibration for all AVHRR visible radiances (except TIROS-N, NOAA-6, NOAA-19, and MetOp-A) is proposed that is based on the average of the best linear fits to the two time records. The estimated uncertainty of these calibrations is 63% absolute (scaled radiance units).

Description: Capsule: A 21-month deployment to Graciosa Island in the northeastern Atlantic Ocean is providing an unprecedented record of the clouds, aerosols and meteorology in a poorly-sampled remote marine environment The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21 month (April 2009- December 2010) comprehensive dataset documenting clouds, aerosols and precipitation using the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the Northeast Atlantic Ocean, and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulus and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1- 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging. The data from at Graciosa are being compared with short-range forecasts made a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well, but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.

Description: Subtropical marine stratus clouds regulate coastal and global climate, but future trends in these clouds are uncertain. In coastal Southern California (CSCA), interannual variations in summer stratus cloud occurrence are spatially coherent across 24 airfields and dictated by positive relationships with stability above the marine boundary layer (MBL) and MBL height. Trends, however, have been spatially variable since records began in the mid-1900s due to differences in nighttime warming. Among CSCA airfields, differences in nighttime warming, but not daytime warming, are strongly and positively related to fraction of nearby urban cover, consistent with an urban heat island effect. Nighttime warming raises the near-surface dew point depression, which lifts the altitude of condensation and cloud base height, thereby reducing fog frequency. Continued urban warming, rising cloud base heights, and associated effects on energy and water balance would profoundly impact ecological and human systems in highly populated and ecologically diverse CSCA.

Description: The 11 year solar-cycle component of climate variability is assessed in historical simulations of models taken from the Coupled Model Intercomparison Project, phase 5 (CMIP-5). Multiple linear regression is applied to estimate the zonal temperature, wind and annular mode responses to a typical solar cycle, with a focus on both the stratosphere and the stratospheric influence on the surface over the period approximately 1850-2005. The analysis is performed on all CMIP-5 models but focuses on the 13 CMIP-5 models that resolve the stratosphere (high-top models) and compares the simulated solar cycle signature with reanalysis data. The 11 year solar cycle component of climate variability is found to be weaker in terms of magnitude and latitudinal gradient around the stratopause in the models than in the reanalysis. The peak in temperature in the lower equatorial stratosphere (approximately 70 hPa) reported in some studies is found in the models to depend on the length of the analysis period, with the last 30 years yielding the strongest response. A modification of the Polar Jet Oscillation (PJO) in response to the 11 year solar cycle is not robust across all models, but is more apparent in models with high spectral resolution in the short-wave region. The PJO evolution is slower in these models, leading to a stronger response during February, whereas observations indicate it to be weaker. In early winter, the magnitude of the modeled response is more consistent with observations when only data from 1979-2005 are considered. The observed North Pacific high-pressure surface response during the solar maximum is only simulated in some models, for which there are no distinguishing model characteristics. The lagged North Atlantic surface response is reproduced in both high- and low-top models, but is more prevalent in the former. In both cases, the magnitude of the response is generally lower than in observations.

Description: Current understanding of the factors controlling biogenic isoprene emissions and of the fate of isoprene oxidation products in the atmosphere has been evolving rapidly. We use a climate-biosphere-chemistry modeling framework to evaluate the sensitivity of estimates of the tropospheric oxidative capacity to uncertainties in isoprene emissions and photochemistry. Our work focuses on trends across two time horizons: from the Last Glacial Maximum (LGM, 21 000 years BP) to the preindustrial (1770s); and from the preindustrial to the present day (1990s). We find that different oxidants have different sensitivities to the uncertainties tested in this study, with OH being the most sensitive: changes in the global mean OH levels for the LGM-to-preindustrial transition range between -29 and +7, and those for the preindustrial-to-present day transition range between -8 and +17, across our simulations. Our results suggest that the observed glacial-interglacial variability in atmospheric methane concentrations is predominantly driven by changes in methane sources as opposed to changes in OH, the primary methane sink. However, the magnitudes of change are subject to uncertainties in the past isoprene global burdens, as are estimates of the change in the global burden of secondary organic aerosol (SOA) relative to the preindustrial. We show that the linear relationship between tropospheric mean OH and tropospheric mean ozone photolysis rates, water vapor, and total emissions of NOx and reactive carbon first reported in Murray et al. (2014) does not hold across all periods with the new isoprene photochemistry mechanism. Our results demonstrate that inadequacies in our understanding of present-day OH and its controlling factors must be addressed in order to improve model estimates of the oxidative capacity of past and present atmospheres.

Description: The primary product of the Global Aerosol Climatology Project (GACP) is a continuous record of the aerosol optical thickness (AOT) over the oceans. It is based on channel-1 and -2 radiance data from the Advanced Very High Resolution Radiometer (AVHRR) instruments flown on successive National Oceanic and Atmospheric Administration (NOAA) platforms. We extend the previous GACP dataset by four years through the end of 2009 using NOAA-17 and -18 AVHRR radiances recalibrated against MODerate resolution Imaging Spectroradiometer (MODIS) radiance data, thereby making the GACP record almost three decades long. The temporal overlap of over three years of the new NOAA-17 and the previous NOAA-16 record reveals an excellent agreement of the corresponding global monthly mean AOT values, thereby confirming the robustness of the vicarious radiance calibration used in the original GACP product. The temporal overlap of the NOAA-17 and -18 instruments is used to introduce a small additive adjustment to the channel-2 calibration of the latter resulting in a consistent record with increased data density. The Principal Component Analysis (PCA) of the newly extended GACP record shows that most of the volcanic AOT variability can be isolated into one mode responsible for ~12% of the total variance. This conclusion is confirmed by a combined PCA analysis of the GACP, MODIS, andMulti-angle Imaging SpectroRadiometer (MISR) AOTs during the volcano-free period fromFebruary 2000 to December 2009.We show that the modes responsible for the tropospheric AOT variability in the three datasets agree well in terms of correlation and spatial patterns. A previously identified negative AOT trend which started in the late 1980s and continued into the early 2000s is confirmed. Its magnitude and duration indicate that it was caused by changes in tropospheric aerosols. The latest multi-satellite segment of the GACP record shows that this trend tapered off, with no noticeable AOT change after 2002. This result is consistent with the MODIS andMISR AOT records as well as with the recent gradual reversal frombrightening to dimming revealed by surface flux measurements in many aerosol producing regions. Thus the robustness of the GACP record is confirmed, increasing our confidence in the validity of the negative trend. Although the nominal negative GACP AOT trend could partially be an artifact of increasing aerosol absorption, we argue that the time dependence of the GACP record, including the latest flat period, is more consistent with the actual decrease in the tropospheric AOT.

Description: Recent satellite determinations of global distributions of absolute gravity wave (GW) momentum fluxes in the lower stratosphere show maxima over the summer subtropical continents and little evidence of GW momentum fluxes associated with the intertropical convergence zone (ITCZ). This seems to be at odds with parameterizations forGWmomentum fluxes, where the source is a function of latent heating rates, which are largest in the region of the ITCZ in terms of monthly averages. The authors have examined global distributions of atmospheric latent heating, cloud-top-pressure altitudes, and lower-stratosphere absolute GW momentum fluxes and have found that monthly averages of the lower-stratosphere GW momentum fluxes more closely resemble the monthly mean cloud-top altitudes rather than the monthly mean rates of latent heating. These regions of highest cloud-top altitudes occur when rates of latent heating are largest on the time scale of cloud growth. This, plus previously published studies, suggests that convective sources for stratospheric GW momentum fluxes, being a function of the rate of latent heating, will require either a climate model to correctly model this rate of latent heating or some ad hoc adjustments to account for shortcomings in a climate model's land-sea differences in convective latent heating.

Description: Soil dust aerosols created by wind erosion are typically assigned globally uniform physical and chemical properties within Earth system models, despite known regional variations in the mineral content of the parent soil. Mineral composition of the aerosol particles is important to their interaction with climate, including shortwave absorption and radiative forcing, nucleation of cloud droplets and ice crystals, heterogeneous formation of sulfates and nitrates, and atmospheric processing of iron into bioavailable forms that increase the productivity of marine phytoplankton. Here, aerosol mineral composition is derived by extending a method that provides the composition of a wet-sieved soil. The extension accounts for measurements showing significant differences between the mineral fractions of the wetsieved soil and the emitted aerosol concentration. For example, some phyllosilicate aerosols are more prevalent at silt sizes, even though they are nearly absent at these diameters in a soil whose aggregates are dispersed by wet sieving. We calculate the emitted mass of each mineral with respect to size by accounting for the disintegration of soil aggregates during wet sieving. These aggregates are emitted during mobilization and fragmentation of the original undispersed soil that is subject to wind erosion. The emitted aggregates are carried far downwind from their parent soil. The soil mineral fractions used to calculate the aggregates also include larger particles that are suspended only in the vicinity of the source. We calculate the emitted size distribution of these particles using a normalized distribution derived from aerosol measurements. In addition, a method is proposed for mixing minerals with small impurities composed of iron oxides. These mixtures are important for transporting iron far from the dust source, because pure iron oxides are more dense and vulnerable to gravitational removal than most minerals comprising dust aerosols. A limited comparison to measurements from North Africa shows that the model extensions result in better agreement, consistent with a more extensive comparison to global observations as well as measurements of elemental composition downwind of the Sahara, as described in companion articles.

Description: Extreme monsoon rainfall in India has disastrous consequences, including significant socio- economic impacts. However, little is known about the overall trends and climate factors associated with extreme rainfall because rainfall greatly varies across India and because few appropriate methods are available to measure extreme rainfall in the context of such heterogeneity. To provide a comprehensive assessment of extreme monsoon rainfall, we developed a metric using record rainfall data to measure the changes in the likelihood of extreme high and extreme low rainfall over time; this metric is independent of the characteristics of the underlying rainfall distributions. Hence, the metric is ideally suited to aggregate extreme rainfall information across heterogeneous regions covering India. We found that from 1930 to 2013, the likelihood of extreme high and extreme low rainfall increases 2-fold and 4-fold, respectively. These overall trend increases are driven by anomalous increases, particularly in the early 2000s; the likelihood of extreme high and extreme low rainfall increases 5-fold and 18-fold in 2005 and 2002, respectively. These findings imply a broadening of the underlying monsoon rainfall distribution over the past century. We also show that the time patterns of the likelihood of extreme rainfall in recent decades are correlated with the El Nino Southern Oscillation, Indian Ocean Dipole, and surface air temperature in the Northern Hemisphere.

Description: We use the new version of NASA Goddard Institute for Space Studies (GISS) climate model, modelE2 with 2 by 2.5 horizontal resolution and 40 vertical layers, with the model top at 0.1 hPa [Schmidt et al., 2014]. We use two different treatments of the atmospheric composition and aerosol indirect effect: (1) TCAD(I) version has fully interactive Tracers of Aerosols and Chemistry in both the troposphere and stratosphere. This model predicts total aerosol number and mass concentrations [Shindell et al., 2013]; (2) TCAM is the aerosol microphysics and chemistry model based on the quadrature methods of moments [Bauer et al., 2008]. Both TCADI and TCAM models include the first indirect effect of aerosols on clouds [Menon et al., 2010]; the TCAD model includes only the direct aerosol effect. We consider the results of the TCAD, TCADI and TCAM models coupled to "Russell ocean model" [Russell et al., 1995], E2-R. We examine the climate response for the "historical period" that include the natural and anthropogenic forcings for 1850 to 2012. The effect of clouds, their feedbacks, as well as the aerosol-cloud interactions are assessed for the transient climate change.

Description: In humid, broadleaf-dominated forests where gap dynamics and partial canopy mortality appears to dominate the disturbance regime at local scales, paleoecological evidence shows alteration at regional-scales associated with climatic change. Yet, little evidence of these broad-scale events exists in extant forests. To evaluate the potential for the occurrence of large-scale disturbance, we used 76 tree-ring collections spanning approx. 840 000 sq km and 5327 tree recruitment dates spanning approx. 1.4 million sq km across the humid eastern United States. Rotated principal component analysis indicated a common growth pattern of a simultaneous reduction in competition in 22 populations across 61 000 km2. Growth-release analysis of these populations reveals an intense and coherent canopy disturbance from 1775 to 1780, peaking in 1776. The resulting time series of canopy disturbance is so poorly described by a Gaussian distribution that it can be described as ''heavy tailed,'' with most of the years from 1775 to 1780 comprising the heavy-tail portion of the distribution. Historical documents provide no evidence that hurricanes or ice storms triggered the 1775-1780 event. Instead, we identify a significant relationship between prior drought and years with elevated rates of disturbance with an intense drought occurring from 1772 to 1775. We further find that years with high rates of canopy disturbance have a propensity to create larger canopy gaps indicating repeated opportunities for rapid change in species composition beyond the landscape scale. Evidence of elevated, regional-scale disturbance reveals how rare events can potentially alter system trajectory: a substantial portion of old-growth forests examined here originated or were substantially altered more than two centuries ago following events lasting just a few years. Our recruitment data, comprised of at least 21 species and several shade-intolerant species, document a pulse of tree recruitment at the subcontinental scale during the late-1600s suggesting that this event was severe enough to open large canopy gaps. These disturbances and their climatic drivers support the hypothesis that punctuated, episodic, climatic events impart a legacy in broadleaf-dominated forests centuries after their occurrence. Given projections of future drought, these results also reveal the potential for abrupt, meso- to large-scale forest change in broadleaf-dominated forests over future decades.

Description: We present an overview of four deep phase-constrained Chandra HETGS X-ray observations of Delta Ori A. Delta Ori A is actually a triple system that includes the nearest massive eclipsing spectroscopic binary, Delta Ori Aa, the only such object that can be observed with little phase-smearing with the Chandra gratings. Since the fainter star, Delta Ori Aa2, has a much lower X-ray luminosity than the brighter primary (Delta Ori Aa1), Delta Ori Aa provides a unique system with which to test the spatial distribution of the X-ray emitting gas around Delta Ori Aa1 via occultation by the photosphere of, and wind cavity around, the X-ray dark secondary. Here we discuss the X-ray spectrum and X-ray line profiles for the combined observation, having an exposure time of nearly 500 ks and covering nearly the entire binary orbit. The companion papers discuss the X-ray variability seen in the Chandra spectra, present new space-based photometry and ground-based radial velocities obtained simultaneously with the X-ray data to better constrain the system parameters, and model the effects of X-rays on the optical and UV spectra. We find that the X-ray emission is dominated by embedded wind shock emission from star Aa1, with little contribution from the tertiary star Ab or the shocked gas produced by the collision of the wind of Aa1 against the surface of Aa2. We find a similar temperature distribution to previous X-ray spectrum analyses. We also show that the line half-widths are about 0.30.5 times the terminal velocity of the wind of star Aa1. We find a strong anti-correlation between line widths and the line excitation energy, which suggests that longer-wavelength, lower-temperature lines form farther out in the wind. Our analysis also indicates that the ratio of the intensities of the strong and weak lines of Fe XVII and Ne X are inconsistent with model predictions, which may be an effect of resonance scattering.

Description: Following its launch in June 2008, high-energy gamma-ray observations by the Fermi Gamma-ray Space Telescope have unveiled over 1000 new sources and opened an important and previously unexplored window on a wide variety of phenomena. These have included the discovery of an population of pulsars pulsing only in gamma rays; the detection of photons up to 10s of GeV from gamma-ray bursts, enhancing our understanding of the astrophysics of these powerful explosions; the detection of hundreds of active galaxies; a measurement of the high energy cosmic-ray electron spectrum which may imply the presence of nearby astrophysical particle accelerators; the determination of the diffuse gamma-ray emission with unprecedented accuracy and the constraints on phenomena such as supersymmetric dark-matter annihilations and exotic relics from the Big Bang. Continuous monitoring of the high-energy gamma-ray sky has uncovered numerous outbursts from active galaxies and the discovery of transient sources in our galaxy. In this talk I will describe the current status of the Fermi observatory and review the science highlights from Fermi.

Description: No abstract available

Description: The NASA Hurricane and Severe Storm Sentinel (HS3) mission is an aircraft field measurements program using NASA's unmanned Global Hawk aircraft system for remote sensing and in situ observations of Atlantic and Caribbean Sea hurricanes. One of the principal microwave instruments is the Hurricane Imaging Radiometer (HIRAD), which measures surface wind speeds and rain rates. For validation of the HIRAD wind speed measurement in hurricanes, there exists a comprehensive set of comparisons with the Stepped Frequency Microwave Radiometer (SFMR) with in situ GPS dropwindsondes [1]. However, for rain rate measurements, there are only indirect correlations with rain imagery from other HS3 remote sensors (e.g., the dual-frequency Ka- & Ku-band doppler radar, HIWRAP), which is only qualitative in nature. However, this paper presents results from an unplanned rain rate measurement validation opportunity that occurred in 2013, when HIRAD flew over an intense tropical squall line that was simultaneously observed by the Tampa NEXRAD meteorological radar (Fig. 1). During this experiment, Global Hawk flying at an altitude of 18 km made 3 passes over the rapidly propagating thunderstorm, while the TAMPA NEXRAD perform volume scans on a 5-minute interval. Using the well-documented NEXRAD Z-R relationship, 2D images of rain rate (mm/hr) were obtained at two altitudes (3 km & 6 km), which serve as surface truth for the HIRAD rain rate retrievals. A preliminary comparison of HIRAD rain rate retrievals (image) for the first pass and the corresponding closest NEXRAD rain image is presented in Fig. 2 & 3. This paper describes the HIRAD instrument, which 1D synthetic-aperture thinned array radiometer (STAR) developed by NASA Marshall Space Flight Center [2]. The rain rate retrieval algorithm, developed by Amarin et al. [3], is based on the maximum likelihood estimation (MLE) technique, which compares the observed Tb's at the HIRAD operating frequencies of 4, 5, 6 and 6.6 GHz with corresponding theoretical Tb values from a forward radiative transfer model (RTM). The optimum solution is the integrated rain rate that minimizes the difference between RTM and observed values. Because the excess Tb from rain comes from the direct upwelling and the indirect reflected downwelling paths through the atmosphere, there are several assumptions made for the 2D rain distribution in the antenna incident plane (crosstrack to flight direction). The opportunity to knowing 2D rain surface truth from NEXRAD at two different altitudes will enable a comprehensive evaluation to be preformed and reported in this paper.

Description: Several young supernova remnants exhibit thin X-ray bright rims of synchrotron radiation at their forward shocks. Thin rims require strong magnetic field amplification beyond simple shock compression if rim widths are only limited by electron energy losses. But, magnetic field damping behind the shock could produce similarly thin rims with less extreme field amplification. Variation of rim width with energy may thus discriminate between competing influences on rim widths. We measured rim widths around Tycho's supernova remnant in 5 energy bands using an archival 750 ks Chandra observation. Rims narrow with increasing energy and are well described by either loss-limited or damped scenarios, so X-ray rim width-energy dependence does not uniquely specify a model. But, radio counterparts to thin rims are not loss-limited and better reflect magnetic field structure. Joint radio and X-ray modeling favors magnetic damping in Tycho's SNR with damping lengths approximately 1-5% of remnant radius and magnetic field strengths approximately 50-400 micron G assuming Bohm diffusion. X-ray rim widths are approximately 1% of remnant radius, somewhat smaller than inferred damping lengths. Electron energy losses are important in all models of X-ray rims, suggesting that the distinction between loss-limited and damped models is blurred in soft X-rays. All loss-limited and damping models require magnetic fields approximately greater than 20 micron G, arming the necessity of magnetic field amplification beyond simple compression.

Description: Small particles forming clouds of interstellar and circumstellar dust, regolith surfaces of many solar system bodies, and cometary atmospheres have a strong and often controlling effect on many ambient physical and chemical processes. Similarly, aerosol and cloud particles exert a strong influence on the regional and global climates of the Earth, other planets of the solar system, and exoplanets. Therefore, detailed and accurate knowledge of physical and chemical characteristics of such particles has the utmost scientific importance.

Description: This report documents analysis results of the Kennedy Space Center updated 50-MHz Doppler Radar Wind Profiler (DRWP) Operational Acceptance Test (OAT). This test was designed to demonstrate that the new DRWP operates in a similar manner to the previous DRWP for use as a situational awareness asset for mission operations at the Eastern Range to identify rapid changes in the wind environment that weather balloons cannot depict. Data examination and two analyses showed that the updated DRWP meets the specifications in the OAT test plan and performs at least as well as the previous DRWP. Data examination verified that the DRWP provides complete profiles every five minutes from 1.8-19.5 km in vertical increments of 150 m. Analysis of 5,426 wind component reports from 49 concurrent DRWP and balloon profiles presented root mean square (RMS) wind component differences around 2.0 m/s. The DRWP's effective vertical resolution (EVR) was found to be 300 m for both the westerly and southerly wind component, which the best EVR possible given the DRWP's vertical sampling interval. A third analysis quantified the sensitivity to rejecting data that do not have adequate signal by assessing the number of first-guess propagations at each altitude. This report documents the data, quality control procedures, methodology, and results of each analysis. It also shows that analysis of the updated DRWP produced results that were at least as good as the previous DRWP with proper rationale. The report recommends acceptance of the updated DRWP for situational awareness usage as per the OAT's intent.

Description: Climate change is a significant risk for agricultural production. Even under optimistic scenarios for climate mitigation action, present-day agricultural areas are likely to face significant increases in temperatures in the coming decades, in addition to changes in precipitation, cloud cover, and the frequency and duration of extreme heat, drought, and flood events (IPCC, 2013). These factors will affect the agricultural system at the global scale by impacting cultivation regimes, prices, trade, and food security (Nelson et al., 2014a). Global-scale evaluation of crop productivity is a major challenge for climate impact and adaptation assessment. Rigorous global assessments that are able to inform planning and policy will benefit from consistent use of models, input data, and assumptions across regions and time that use mutually agreed protocols designed by the modeling community. To ensure this consistency, large-scale assessments are typically performed on uniform spatial grids, with spatial resolution of typically 10 to 50 km, over specified time-periods. Many distinct crop models and model types have been applied on the global scale to assess productivity and climate impacts, often with very different results (Rosenzweig et al., 2014). These models are based to a large extent on field-scale crop process or ecosystems models and they typically require resolved data on weather, environmental, and farm management conditions that are lacking in many regions (Bondeau et al., 2007; Drewniak et al., 2013; Elliott et al., 2014b; Gueneau et al., 2012; Jones et al., 2003; Liu et al., 2007; Muller and Robertson, 2014; Van den Hoof et al., 2011;Waha et al., 2012; Xiong et al., 2014). Due to data limitations, the requirements of consistency, and the computational and practical limitations of running models on a large scale, a variety of simplifying assumptions must generally be made regarding prevailing management strategies on the grid scale in both the baseline and future periods. Implementation differences in these and other modeling choices contribute to significant variation among global-scale crop model assessments in addition to differences in crop model implementations that also cause large differences in site-specific crop modeling (Asseng et al., 2013; Bassu et al., 2014).

Description: An array of rotating sunshades based on emerging solar sail technology will be deployed in a novel Earth orbit to provide near-continuous partial shading of the Earth, reducing the heat input to the atmosphere by blocking a small percentage of the incoming sunlight, and mitigating local weather effects of anticipated climate change over the next century. The technology will provide local cooling relief during extreme heat events (and heating relief during extreme cold events) thereby saving human lives, agriculture, livestock, water and energy needs. A synthesis of the solar sail design, the sails' operational modes, and the selected orbit combine to provide local weather modification.

Description: No abstract available

Description: The Goddard microphysics scheme was recently improved by adding a 4th ice class (frozen dropshail). This new 4ICE scheme was implemented and tested in the Goddard Cumulus Ensemble model (GCE) for an intense continental squall line and a moderate,less-organized continental case. Simulated peak radar reflectivity profiles were improved both in intensity and shape for both cases as were the overall reflectivity probability distributions versus observations. In this study, the new Goddard 4ICE scheme is implemented into the regional-scale NASA Unified - Weather Research and Forecasting model (NU-WRF) and tested on an intense mesoscale convective system that occurred during the Midlatitude Continental Convective Clouds Experiment (MC3E). The NU42WRF simulated radar reflectivities, rainfall intensities, and vertical and horizontal structure using the new 4ICE scheme agree as well as or significantly better with observations than when using previous versions of the Goddard 3ICE (graupel or hail) schemes. In the 4ICE scheme, the bin microphysics-based rain evaporation correction produces more erect convective cores, while modification of the unrealistic collection of ice by dry hail produces narrow and intense cores, allowing more slow-falling snow to be transported rearward. Together with a revised snow size mapping, the 4ICE scheme produces a more horizontally stratified trailing stratiform region with a broad, more coherent light rain area. In addition, the NU-WRF 4ICE simulated radar reflectivity distributions are consistent with and generally superior to those using the GCE due to the less restrictive open lateral boundaries

Description: South India is characterized by a wide variety of landscapes, soils and climatic zones. It is comprised of tropical, semi-arid, humid-moist, and high-altitude environments, which support a diversity of agricultural systems. Our study focused on the state of Tamil Nadu, which is characterized by a generally tropical climate, and receive rainfall during both the southwest monsoon season (SWM, June to September) and the northeast monsoon (NEM, September to December). Agriculture continues to be an important sector in the state economy, as more than 56 of the people depend on agriculture and allied sectors for their livelihood. Analysis of land-use patterns in Tamil Nadu reveals that in the past decade there has been a reduction in net sown area and current fallow, while the share of cultivable wastelands has increased. The area under cereals, pulses, and oilseeds had marginally declined, although area under commercial crops like turmeric, sugar-cane, banana, fruits, and vegetables has shown an increasing trend. The production performance of major crops like cereals, pulses, and oilseeds has not shown any significant increase. Demand and supply gap of important crops in Tamil Nadu for the year 2010 indicates that the state is lagging far behind in the production of various crops.

Description: ARC3.2 presents a broad synthesis of the latest scientific research on climate change and cities. Mitigation and adaptation climate actions of 100 cities are documented throughout the 16 chapters, as well as online through the ARC3.2 Case Study Docking Station. Pathways to Urban Transformation, Major Findings, and Key Messages are highlighted here in the ARC3.2 Summary for City Leaders. These sections lay out what cities need to do achieve their potential as leaders of climate change solutions. UCCRN Regional Hubs in Europe, Latin America, Africa, Australia and Asia will share ARC3.2 findings with local city leaders and researchers. The ARC3.2 Summary for City Leaders synthesizes Major Findings and Key Messages on urban climate science, disasters and risks, urban planning and design, mitigation and adaptation, equity and environmental justice, economics and finance, the private sector, urban ecosystems, urban coastal zones, public health, housing and informal settlements, energy, water, transportation, solid waste, and governance. These were based on climate trends and future projections for 100 cities around the world.

Description: What's in this Report? What's New? This fifth Program Annual Technology Report (PATR) summarizes the Programs technology development activities for fiscal year (FY) 2015. The PATR serves four purposes.1. Summarize the technology gaps identified by the astrophysics community;2. Present the results of this years technology gap prioritization by the PCOS Technology Management Board (TMB);3. Report on newly funded PCOS Strategic Astrophysics Technology (SAT) projects; and4. Detail progress, current status, and activities planned for the coming year for all technologies supported by PCOS Supporting Research and Technology (SRT) funding in FY 2015. .

Description: Global warming on decadal and centennial timescales is mediated and ameliorated by the oceansequestering heat and carbon into its interior. Transient climate change is a function of the efficiency by whichanthropogenic heat and carbon are transported away from the surface into the ocean interior (Hansen et al. 1985).Gregory and Mitchell (1997) and Raper et al. (2002) were the first to identify the importance of the ocean heat uptakeefficiency in transient climate change. Observational estimates (Schwartz 2012) and inferences from coupledatmosphere-ocean general circulation models (AOGCMs; Gregory and Forster 2008; Marotzke et al. 2015), suggest thatocean heat uptake efficiency on decadal timescales lies in the range 0.5-1.5 W/sq m/K and is thus comparable to theclimate feedback parameter (Murphy et al. 2009). Moreover, the ocean not only plays a key role in setting the timing ofwarming but also its regional patterns (Marshall et al. 2014), which is crucial to our understanding of regional climate,carbon and heat uptake, and sea-level change. This short communication is based on a presentation given by A.Romanou at a recent workshop, Oceans Carbon and Heat Uptake: Uncertainties and Metrics, co-hosted by US CLIVARand OCB. As briefly reviewed below, we have incomplete but growing knowledge of how ocean models used in climatechange projections sequester heat and carbon into the interior. To understand and thence reduce errors and biases inthe ocean component of coupled models, as well as elucidate the key mechanisms at work, in the final section we outlinea proposed model intercomparison project named FAFMIP. In FAFMIP, coupled integrations would be carried out withprescribed overrides of wind stress and freshwater and heat fluxes acting at the sea surface.

Description: The spatial pattern across the continental United States of the interannual variance of warm season water-dependent evapotranspiration, a pattern of relevance to land-atmosphere feedback, cannot be measured directly. Alternative and indirect approaches to estimating the pattern, however, do exist, and given the uncertainty of each, we use several such approaches here. We first quantify the water dependent evapotranspiration variance pattern inherent in two derived evapotranspiration datasets available from the literature. We then search for the pattern in proxy geophysical variables (air temperature, stream flow, and NDVI) known to have strong ties to evapotranspiration. The variances inherent in all of the different (and mostly independent) data sources show some differences but are generally strongly consistent they all show a large variance signal down the center of the U.S., with lower variances toward the east and (for the most part) toward the west. The robustness of the pattern across the datasets suggests that it indeed represents the pattern operating in nature. Using Budykos hydroclimatic framework, we show that the pattern can largely be explained by the relative strength of water and energy controls on evapotranspiration across the continent.

Description: ROVER is the Citizen Science arm of the NASA Clouds and the Earth's Radiant Energy System (CERES) Students' Cloud Observations On-Line (S'COOL) Project. Since 2007, participants around the world have been making and reporting ground truth observations of clouds to assist in the validation of the NASA CERES satellite instrument. NASA scientists are very interested in learning how clouds affect our atmosphere, weather, and climate (relating to climate change). It is the clouds, in part, that affect the overall temperature and energy balance of the Earth. The more we know about clouds, the more we will know about our Earth as a system and citizen scientists are an important piece of that puzzle! As a ROVER cloud observer, all participants follow simple online tutorials to collect data on cloud type, height, cover and related conditions. Observations are sent to NASA to be matched to similar information obtained from satellites and sent back to participants for comparison and analysis. The supporting ROVER website houses a searchable database archiving all participant reports and matching satellite data. By involving Citizen Scientists in cloud observations and reporting we can gain a valuable set of data that would have been previously unavailable to science teams due to funding, manpower, and resource limitations or would have taken an unreasonable amount of time to collect. Reports from a wide range of Citizen Scientist locations are helpful to assess the satellite data under different conditions. With nothing more than their eyes and an internet connection participants provide a different perspective and analysis of clouds, adding to a more complete picture of what's happening in the atmosphere in which we live.

Description: 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.

Description: As temperatures increase, the onset and severity of droughts is likely to become more intense. Improved tools for understanding, monitoring and predicting droughts will be a key component of 21st century climate adaption. The best drought monitoring systems will bring together accurate precipitation estimates with skillful climate and weather forecasts. Such systems combine the predictive power inherent in the current land surface state with the predictive power inherent in low frequency ocean-atmosphere dynamics. To this end, researchers at the Climate Hazards Group (CHG), in collaboration with partners at the USGS and NASA, have developed i) a long (1981-present) quasi-global (50degS-50degN, 180degW-180degE) high resolution (0.05deg) homogenous precipitation data set designed specifically for drought monitoring, ii) tools for understanding and predicting East African boreal spring droughts, and iii) an integrated land surface modeling (LSM) system that combines rainfall observations and predictions to provide effective drought early warning. This talk briefly describes these three components. Component 1: CHIRPS The Climate Hazards group InfraRed Precipitation with Stations (CHIRPS), blends station data with geostationary satellite observations to provide global near real time daily, pentadal and monthly precipitation estimates. We describe the CHIRPS algorithm and compare CHIRPS and other estimates to validation data. The CHIRPS is shown to have high correlation, low systematic errors (bias) and low mean absolute errors. Component 2: Hybrid statistical-dynamic forecast strategies East African droughts have increased in frequency, but become more predictable as Indo- Pacific SST gradients and Walker circulation disruptions intensify. We describe hybrid statistical-dynamic forecast strategies that are far superior to the raw output of coupled forecast models. These forecasts can be translated into probabilities that can be used to generate bootstrapped ensembles describing future climate conditions. Component 3: Assimilation using LSMs CHIRPS rainfall observations (component 1) and bootstrapped forecast ensembles (component 2) can be combined using LSMs to predict soil moisture deficits. We evaluate the skill such a system in East Africa, and demonstrate results for 2013.

Description: Remote sensing observations show that space weathering processes affect all airless bodies in the Solar System to some degree. Sample analyses and lab experiments provide insights into the chemical, spectroscopic and mineralogic effects of space weathering and aid in the interpretation of remote- sensing data. For example, analyses of particles returned from the S-type asteroid Itokawa by the Hayabusa mission revealed that space-weathering on that body was dominated by interactions with the solar wind acting on LL ordinary chondrite-like materials [1, 2]. Understanding and predicting how the surface regoliths of primitive carbonaceous asteroids respond to space weathering processes is important for future sample return missions (Hayabusa 2 and OSIRIS-REx) that are targeting objects of this type. Here, we report the results of our preliminary ion irradiation experiments on a hydrated carbonaceous chondrite with emphasis on microstructural and infrared spectral changes.

Description: Small bodies record the chemical, physical, and dynamical processes that gave birth to and shaped the solar system. The great variety of small bodies reflects the diversity of both their genesis and their histories. The DARe mission conducts a critical test of how small body populations reflect a history of planetary migration and planetesimal scattering. This understanding is crucial for planning future NASA missions and placing current and past missions into context.

Description: The theory of particle acceleration via diffusive shock acceleration (DSA) has been studied in depth by Gosling et al. (1981), van Nes et al. (1984), Mason (2000), Desai et al. (2003), Zank et al. (2006), among many others. Recently, Parker and Zank (2012, 2014) and Parker et al. (2014) using the Advanced Composition Explorer (ACE) shock database at 1 AU explored two questions: does the upstream distribution alone have enough particles to account for the accelerated downstream distribution and can the slope of the downstream accelerated spectrum be explained using DSA? As was shown in this research, diffusive shock acceleration can account for a large population of the shocks. However, Parker and Zank (2012, 2014) and Parker et al. (2014) used a subset of the larger ACE database. Recently, work has successfully been completed that allows for the entire ACE database to be considered in a larger statistical analysis. We explain DSA as it applies to single and multiple shocks and the shock criteria used in this statistical analysis. We calculate the expected injection energy via diffusive shock acceleration given upstream parameters defined from the ACE Solar Wind Electron, Proton, and Alpha Monitor (SWEPAM) data to construct the theoretical upstream distribution. We show the comparison of shock strength derived from diffusive shock acceleration theory to observations in the 50 keV to 5 MeV range from an instrument on ACE. Parameters such as shock velocity, shock obliquity, particle number, and time between shocks are considered. This study is further divided into single and multiple shock categories, with an additional emphasis on forward-forward multiple shock pairs. Finally with regard to forwardforward shock pairs, results comparing injection energies of the first shock, second shock, and second shock with previous energetic population will be given.

Description: As temperatures increase, the onset and severity of droughts is likely to become more intense. Improved tools for understanding, monitoring and predicting droughts will be a key component of 21st century climate adaption. The best drought monitoring systems will bring together accurate precipitation estimates with skillful climate and weather forecasts. Such systems combine the predictive power inherent in the current land surface state with the predictive power inherent in low frequency ocean-atmosphere dynamics. To this end, researchers at the Climate Hazards Group (CHG), in collaboration with partners at the USGS and NASA, have developed i) a long (1981-present) quasi-global (50degS-50degN, 180degW-180degE) high resolution (0.05deg) homogenous precipitation data set designed specifically for drought monitoring, ii) tools for understanding and predicting East African boreal spring droughts, and iii) an integrated land surface modeling (LSM) system that combines rainfall observations and predictions to provide effective drought early warning. This talk briefly describes these three components. Component 1: CHIRPS The Climate Hazards group InfraRed Precipitation with Stations (CHIRPS), blends station data with geostationary satellite observations to provide global near real time daily, pentadal and monthly precipitation estimates. We describe the CHIRPS algorithm and compare CHIRPS and other estimates to validation data. The CHIRPS is shown to have high correlation, low systematic errors (bias) and low mean absolute errors. Component 2: Hybrid statistical-dynamic forecast strategies East African droughts have increased in frequency, but become more predictable as Indo- Pacific SST gradients and Walker circulation disruptions intensify. We describe hybrid statistical-dynamic forecast strategies that are far superior to the raw output of coupled forecast models. These forecasts can be translated into probabilities that can be used to generate bootstrapped ensembles describing future climate conditions. Component 3: Assimilation using LSMs CHIRPS rainfall observations (component 1) and bootstrapped forecast ensembles (component 2) can be combined using LSMs to predict soil moisture deficits. We evaluate the skill such a system in East Africa, and demonstrate results for 2013.

Description: The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. As recently as in 2011 part of this region underwent one of the worst famine events in its history. Timely and skillful drought forecasts at seasonal scale for this region can inform better water and agro-pastoral management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts. However seasonal drought prediction in this region faces several challenges. Lack of skillful seasonal rainfall forecasts; the focus of this presentation, is one of those major challenges. In the past few decades, major strides have been taken towards improvement of seasonal scale dynamical climate forecasts. The National Centers for Environmental Prediction's (NCEP) National Multi-model Ensemble (NMME) is one such state-of-the-art dynamical climate forecast system. The NMME incorporates climate forecasts from 6+ fully coupled dynamical models resulting in 100+ ensemble member forecasts. Recent studies have indicated that in general NMME offers improvement over forecasts from any single model. However thus far the skill of NMME for forecasting rainfall in a vulnerable region like the East Africa has been unexplored. In this presentation we report findings of a comprehensive analysis that examines the strength and weakness of NMME in forecasting rainfall at seasonal scale in East Africa for all three of the prominent seasons for the region. (i.e. March-April-May, July-August-September and October-November- December). Simultaneously we also describe hybrid approaches; that combine statistical approaches with NMME forecasts; to improve rainfall forecast skill in the region when raw NMME forecasts lack in skill.

Description: The detection of clouds in satellite imagery has a number of important applications in weather and climate studies. The presence of clouds can alter the energy budget of the Earthatmosphere system through scattering and absorption of shortwave radiation and the absorption and reemission of infrared radiation at longer wavelengths. The scattering and absorption characteristics of clouds vary with the microphysical properties of clouds, hence the cloud type. Thus, detecting the presence of clouds over a region in satellite imagery is important in order to derive atmospheric or surface parameters that give insight into weather and climate processes. For many applications however, clouds are a contaminant whose presence interferes with retrieving atmosphere or surface information. In these cases, is important to isolate cloudfree pixels, used to retrieve atmospheric thermodynamic information or surface geophysical parameters, from cloudy ones. This abstract describes an application of a twochannel bispectral composite threshold (BCT) approach applied to VIIRS imagery. The simplified BCT approach uses only the 10.76 and 3.75 micrometer spectral channels from VIIRS in two spectral tests; a straightforward infrared threshold test with the longwave channel and a shortwave - longwave channel difference test. The key to the success of this approach as demonstrated in past applications to GOES and MODIS data is the generation of temporally and spatially dependent thresholds used in the tests from a previous number of days at similar observations to the current data. The paper and subsequent presentation will present an overview of the approach and intercomparison results with other satellites, methods, and against verification data.

Description: At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Pythonbased software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize preexisting Python modules as well as to be objectoriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25year history into a common data structure suitable for userdefined analyses. It features rapid, simplified (i.e., one line of code) production of quicklook imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publicationready figures. Deconvolution of the polarizationvarying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward realtime AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during MayJune 2014. The second software package is the Marshall MultiRadar/MultiSensor (MRMS) Mosaic Python Toolkit, or MMMPy for short. MMMPy was designed to read, analyze, and display threedimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMMPy can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMMPy can easily stitch multiple tiles together to provide a larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMMPy can also write to the native MRMS binary format, and subsectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMMPy also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMMPy, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Pythonbased analysis routines with the U.S. Department of Energy's PyART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFCbased implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convectivescale analysis, situational awareness, and forensic meteorology. PyTDA exploits PyART's radar data ingest routines and data model to rapidly produce aviationrelevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the PyART framework will be highlighted. Pythonbased analysis within the PyART framework is also being done for new research related to intercomparison of groundbased radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds.

Description: The Global Precipitation Measurement (GPM) is an international mission to provide next-generation observations of rain and snow worldwide. The GPM built on Tropical Rainfall Measuring Mission (TRMM) legacy, while the core observatory will extend the observations to higher latitudes. The GPM observations can help advance our understanding of precipitation microphysics and storm structures. Launched on February 27th, 2014, the GPM core observatory is carrying advanced instruments that can be used to quantify when, where, and how much it rains or snows around the world. Therefore, the use of GPM data in numerical modeling work is a new area and will have a broad impact in both research and operational communities. The goal of this research is to examine the methodology of assimilation of the GPM retrieved products. The data assimilation system used in this study is the community Gridpoint Statistical Interpolation (GSI) system for the Weather Research and Forecasting (WRF) model developed by the Development Testbed Center (DTC). The community GSI system runs in independently environment, yet works functionally equivalent to operational centers. With collaboration with the NASA Short-term Prediction Research and Transition (SPoRT) Center, this research explores regional assimilation of the GPM products with case studies. Our presentation will highlight our recent effort on the assimilation of the GPM product 2AGPROFGMI, the retrieved Microwave Imager (GMI) rainfall rate data for initializing a real convective storm. WRF model simulations and storm scale data assimilation experiments will be examined, emphasizing both model initialization and short-term forecast of precipitation fields and processes. In addition, discussion will be provided on the development of enhanced assimilation procedures in the GSI system with respect to other GPM products. Further details of the methodology of data assimilation, preliminary result and test on the impact of GPM data and the influence on precipitation forecast will be presented at the conference.

Description: The NASA/Shortterm Prediction, Research, and Transition (SPoRT) Program works closely with NOAA/NWS weather forecasters to transition unique satellite data and capabilities into operations in order to assist with nowcasting and shortterm forecasting issues. Several multispectral composite imagery (i.e. RGB) products were introduced to users in the early 2000s to support hydrometeorology and aviation challenges as well as incident support. These activities lead to SPoRT collaboration with the GOESR Proving Ground efforts where instruments such as MODIS (Aqua, Terra) and SNPP/VIIRS imagers began to be used as nearrealtime proxies to future capabilities of the Advanced Baseline Imager (ABI). One of the composite imagery products introduced to users was the Nighttime Microphysics RGB, originally developed by EUMETSAT. SPoRT worked to transition this imagery to NWS users, provide regionspecific training, and assess the impact of the imagery to aviation forecast needs. This presentation discusses the method used to interact with users to address specific aviation forecast challenges, including training activities undertaken to prepare for a product assessment. Users who assessed the multispectral imagery ranged from southern U.S. inland and coastal NWS weather forecast offices (WFOs), to those in the Rocky Mountain Front Range region and West Coast, as well as highlatitude forecasters of Alaska. These userbased assessments were documented and shared with the satellite community to support product developers and the broad users of new generation satellite data.

Description: Hurricane Arthur (2014) was an early season hurricane that had its roots in a convective complex in the Southern Plains of the U.S. As the complex moved into northern Texas, a Mesoscale Convective Vortex (MCV) formed and drifted towards the east of the southern U.S. for a few days before emerging over the southwest Atlantic near South Carolina. The MCV drifted south and slowly acquired tropical characteristics, eventually becoming a Category 2 hurricane that would affect much of eastern North Carolina prior to the 4th of July holiday weekend. Arthur continued up the coast, brushing portions of southeast New England and merged with an upper-level low, completing a full tropical to extratropical-transition in the process, producing damaging wind gusts in portions of the Canadian Maritimes. As part of the GOES-R and JPSS Satellite Proving Grounds, multiple proxy and operational products were available to analyze and forecast this complex evolution. The Storm Prediction Center had products available to monitor the initial severe thunderstorm aspect, while the National Hurricane Center and Ocean Prediction Center were able to monitor the tropical and extratropical transition of Arthur using various convective and red, green, blue (RGB) products that have been introduced in recent years. This paper will discuss Arthur's evolution through the eyes of the various Satellite Proving Ground demonstrations.

Description: Rapid increases in total lightning (also termed "lightning jumps") have been observed for many decades. Lightning jumps have been well correlated to severe and hazardous weather occurrence. The main focus of lightning jump work has been on the development of lightning algorithms to be used in realtime assessment of storm intensity. However, in these studies it is typically assumed that the updraft "increases" without direct measurements of the vertical motion, or specification of which updraft characteristic actually increases (e.g., average speed, maximum speed, or convective updraft volume). Therefore, an endtoend physical and dynamical basis for coupling rapid increases in total flash rate to increases in updraft speed and volume must be understood in order to ultimately relate lightning occurrence to severe storm metrics. Herein, we use polarimetric, multiDoppler, and lightning mapping array measurements to provide physical context as to why rapid increases in total lightning are closely tied to severe and hazardous weather.

Description: The Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) has been collecting observations of total lightning in the global tropics and subtropics (roughly 38 deg S - 38 deg N) since December 1997. A similar instrument, the Optical Transient Detector, operated from 1995-2000 on another low earth orbit satellite that also saw high latitudes. Lightning data from these instruments have been used to create gridded climatologies and time series of lightning flash rate. These include a 0.5 deg resolution global annual climatology, and lower resolution products describing the annual cycle and the diurnal cycle. These products are updated annually. Results from the update through 2013 will be shown at the conference. The gridded products are publicly available for download. Descriptions of how each product can be used will be discussed, including strengths, weaknesses, and caveats about the smoothing and sampling used in various products.

Description: Hyperspectral infrared sounder radiance data are assimilated into operational modeling systems however the process is computationally expensive and only approximately 1% of available data are assimilated due to data thinning as well as the fact that radiances are restricted to cloud-free fields of view. In contrast, the number of hyperspectral infrared profiles assimilated is much higher since the retrieved profiles can be assimilated in some partly cloudy scenes due to profile coupling other data, such as microwave or neural networks, as first guesses to the retrieval process. As the operational data assimilation community attempts to assimilate cloud-affected radiances, it is possible that the use of retrieved profiles might offer an alternative methodology that is less complex and more computationally efficient to solve this problem. The NASA Short-term Prediction Research and Transition (SPoRT) Center has assimilated hyperspectral infrared retrieved profiles into Weather Research and Forecasting Model (WRF) simulations using the Gridpoint Statistical Interpolation (GSI) System. Early research at SPoRT demonstrated improved initial conditions when assimilating Atmospheric Infrared Sounder (AIRS) thermodynamic profiles into WRF (using WRF-Var and assigning more appropriate error weighting to the profiles) to improve regional analysis and heavy precipitation forecasts. Successful early work has led to more recent research utilizing WRF and GSI for applications including the assimilation of AIRS profiles to improve WRF forecasts of atmospheric rivers and assimilation of AIRS, Cross-track Infrared and Microwave Sounding Suite (CrIMSS), and Infrared Atmospheric Sounding Interferometer (IASI) profiles to improve model representation of tropopause folds and associated non-convective wind events. Although more hyperspectral infrared retrieved profiles can be assimilated into model forecasts, one disadvantage is the retrieved profiles have traditionally been assigned the same error values as the rawinsonde observations when assimilated with GSI. Typically, satellitederived profile errors are larger and more difficult to quantify than traditional rawinsonde observations (especially in the boundary layer), so it is important to appropriately assign observation errors within GSI to eliminate potential spurious innovations and analysis increments that can sometimes arise when using retrieved profiles. The goal of this study is to describe modifications to the GSI source code to more appropriately assimilate hyperspectral infrared retrieved profiles and outline preliminary results that show the differences between a model simulation that assimilated the profiles as rawinsonde observations and one that assimilated the profiles in a module with the appropriate error values.

Description: Dust and pollution emissions from Asia are often transported across the Pacific Ocean to over the western United States. Therefore, it is essential to fully understand the impact of these aerosols on clouds and precipitation forming over the eastern Pacific and western United States, especially during atmospheric river events that account for up to half of California's annual precipitation and can lead to widespread flooding. In order for numerical modeling simulations to accurately represent the present and future regional climate of the western United States, we must account for the aerosol-cloud-precipitation interactions associated with Asian dust and pollution aerosols. Therefore, we have constructed a detailed study utilizing multi-sensor satellite observations, NOAA-led field campaign measurements, and targeted numerical modeling studies where Asian aerosols interacted with cloud and precipitation processes over the western United States. In particular, we utilize aerosol optical depth retrievals from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS), NOAA Geostationary Operational Environmental Satellite (GOES-11), and Japan Meteorological Agency (JMA) Multi-functional Transport Satellite (MTSAT) to effectively detect and monitor the trans-Pacific transport of Asian dust and pollution. The aerosol optical depth (AOD) retrievals are used in assimilating the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in order to provide the model with an accurate representation of the aerosol spatial distribution across the Pacific. We conduct WRF-Chem model simulations of several cold-season atmospheric river events that interacted with Asian aerosols and brought significant precipitation over California during February-March 2011 when the NOAA CalWater field campaign was ongoing. The CalWater field campaign consisted of aircraft and surface measurements of aerosol and precipitation processes that help extensively validate our WRF-Chem model simulations. After validating the capability of the WRF-Chem in realistically simulating the aerosol-cloud precipitation interactions, we conduct sensitivity studies where the AOD is doubled to diagnose whether an increasing concentration of Asian aerosols over the western United States will lead to further impacts on the cloud and precipitation processes over California. We also perform sensitivity studies where the aerosols will be partitioned into dust-only and pollution-only in order to separate the impacts of the differing Asian aerosol species. The results of our WRF-Chem model simulations aim to show that the trans-Pacific transport of Asian aerosols influence the precipitation associated with atmospheric river events that can ultimately impact the regional climate of the western United States. 1 University

Description: Extreme events by their nature fall outside the bounds of routine experience. With imperfect or ambiguous measuring systems, it is appropriate to question whether an unusual measurement represents an extreme event or is the result of instrument errors or other sources of noise. About three weeks after the Tropical Rainfall Measuring Mission (TRMM) satellite began collecting data in Dec 1997, a thunderstorm was observed over northern Argentina with 85 GHz brightness temperatures below 50 K and 37 GHz brightness temperatures below 70 K (Zipser et al. 2006). These values are well below what had previously been observed from satellite sensors with lower resolution. The 37 GHz brightness temperatures are also well below those measured by TRMM for any other storm in the subsequent 16 years. Without corroborating evidence, it would be natural to suspect a problem with the instrument, or perhaps an irregularity with the platform during the first weeks of the satellite mission. Automated quality control flags or other procedures in retrieval algorithms could treat these measurements as errors, because they fall outside the expected bounds. But the TRMM satellite also carries a radar and a lightning sensor, both confirming the presence of an intense thunderstorm. The radar recorded 40+ dBZ reflectivity up to about 19 km altitude. More than 200 lightning flashes per minute were recorded. That same storm's 19 GHz brightness temperatures below 150 K would normally be interpreted as the result of a low-emissivity water surface (e.g., a lake, or flood waters) if not for the simultaneous measurements of such intense convection. This paper will examine records from TRMM and related satellite sensors including SSMI, AMSR-E, and the new GMI to find the strongest signatures resulting from thunderstorms, and distinguishing those from sources of noise. The lowest brightness temperatures resulting from thunderstorms as seen by TRMM have been in Argentina in November and December. For SSMI sensors carried on five DMSP satellites examined so far, the lowest thunderstorm-related brightness temperatures have been from Argentina in November - December and from Minnesota in June-July. The Minnesota cases were associated with spotter reports of large hail, significant severe wind, and tornadoes. Those locations have the record-holders for each satellite. The lowest AMSR-E 36.5 GHz brightness temperatures associated with deep convection have been in Argentina; the lowest 89.0 GHz brightness temperatures were from Typhoon Bolaven in the Philippine Sea. This paper will show examples of cases with the lowest brightness temperatures, and map the locations of these and other storms with brightness temperatures nearly as low. The study is largely motivated by the new GMI sensor on the Global Precipitation Mission core satellite, launched in February 2014, with its high resolution expected to reveal unprecedented low brightness temperatures when extreme events are encountered.

Description: Several mission concepts are being studied to directly image planets around nearby stars. It is commonly thought that directly imaging a potentially habitable exoplanet around a Sun-like star requires space telescopes with apertures of at least 1m. A notable exception to this is Alpha Centauri (A and B), which is an extreme outlier among FGKM stars in terms of apparent habitable zone size: the habitable zones are approximately 3x wider in apparent size than around any other FGKM star. This enables a approximately 30-45cm visible light space telescope equipped with a modern high performance coronagraph or star shade to resolve the habitable zone at high contrast and directly image any potentially habitable planet that may exist in the system. The raw contrast requirements for such an instrument can be relaxed to 1e-8 if the mission spends 2 years collecting tens of thousands of images on the same target, enabling a factor of 500-1000 speckle suppression in post processing using a new technique called Orbital Difference Imaging (ODI). The raw light leak from both stars is controllable with a special wave front control algorithm known as Multi-Star Wave front Control (MSWC), which independently suppresses diffraction and aberrations from both stars using independent modes on the deformable mirror. This paper will present an analysis of the challenges involved with direct imaging of Alpha Centauri with a small telescope and how the above technologies are used together to solve them. We also show an example of a small coronagraphic mission concepts to take advantage of this opportunity called "ACESat: Alpha Centauri Exoplanet Satellite" submitted to NASA's small Explorer (SMEX) program in December of 2014.

Description: Many environments in space contain very low temperature mixed molecular ices that are exposed to ionizing radiation in the form of cosmic rays and high-energy photons. While traditional chemistry would not be expected to occur at the temperatures typical of these ices (T 〈 50 K), ionizing radiation can break bonds in the original molecules in the ices to form highly reactive ions and radicals. These ions and radicals are subsequently free to react despite the low temperatures of the original ices. Laboratory experiments, many of them carried out at the Astrochemistry Laboratory at NASA-Ames, show that the irradiation of ices made of even simple molecules like H2O, CO, CO2, CH4, NH3, etc. can result in the robust formation of large numbers of far more complex organic compounds. Many of these new products are of direct interest to astrobiology. For example, the irradiation of mixed molecular ices has been shown to produce amino acids, amphiphiles, quinones, sugars, heterocyclic compounds, and nucleobases, all molecular building blocks used by terrestrial life. Insofar as the presence of these materials plays a role in the origin of life on planets, this has profound implications for the potential abundance of life in the universe since these experiments simulate universal conditions that are expected to be found wherever new stars and planets form.

Description: Using infrared satellite data, previous work has shown a consistent diurnal cycle in the pattern of cold cloud tops around mature tropical cyclones. In particular, an increase in the coverage by cold cloud tops often occurs in the inner core of the storm around the time of sunset and subsequently propagates outward to several hundred kilometers over the course of the following day. This consistent cycle may have important implications for structure and intensity changes of tropical cyclones and the forecasting of such changes. Because infrared satellite measurements are primarily sensitive to cloud top, the goal of this study is to use passive and active microwave measurements from the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR), respectively, to examine and better understand the tropical cyclone diurnal cycle throughout a larger depth of the storm's clouds. The National Hurricane Center's best track dataset was used to extract all PR and TMI pixels within 1000 km of each tropical cyclone that occurred in the Atlantic basin between 1998-2011. Then the data was composited according to radius (100-km bins from 0-1000 km) and local standard time (LST; 3-hr bins). Specifically, PR composites involved finding the percentage of pixels with reflectivity greater than or equal to 20 dBZ at various heights (i.e., 2-14 km in increments of 2 km) as a function of radius and time. The 37- and 85- GHz TMI channels are especially sensitive to scattering by precipitation-sized ice in the mid to upper portions of clouds. Hence, the percentage of 37- and 85-GHz polarization corrected temperatures less than various thresholds were calculated using data from all storms as a function of radius and time. For 37 GHz, thresholds of 260 K, 265 K, 270 K, and 275 K were used, and for 85 GHz, thresholds of 200-270 K in increments of 10 K were utilized. Note that convection forced by the interactions of a tropical cyclone with land (e.g., due to frictional convergence) may disrupt the natural convective cycle of a cyclone. Hence, only data pertaining to storms whose centers were greater than 300 km from land were included in the composites. Early results suggest the presence of a diurnal cycle in the PR composites of all Atlantic basin tropical cyclones from a height of 2-12 km from approximately 0-400 km radius, but the cycle is most apparent above 6 km. At a height of 8 km, there is a peak (minimum) in the percentage of PR pixels greater than or equal to 20 dBZ near 0 (21) LST in the inner core with some indication that this signal propagates outward with time. In contrast, the 37- and 85-GHz composites show little indication of a diurnal cycle at any radii, regardless of the threshold used. Ongoing work with this project will involve sub-setting the composites according to storm intensity to see if the diurnal cycle varies with storm strength. Moderate to strong vertical wind shear often leads to asymmetries in tropical cyclone convection and may disrupt the cyclone's natural diurnal cycle. Therefore, wind shear thresholds will be applied to the composites to determine if the diurnal cycle becomes more apparent in a low shear environment. Finally, other work to be completed will involve developing composites for other tropical cyclone basins, including the East Pacific, Northwest Pacific, South Pacific, and Indian Ocean.

Description: Cyclogenesis is a key forecast challenge at operational forecasting centers such as WPC and OPC, so these centers have a particular interest in unique products that can identify key storm features. In some cases, explosively developing extratropical cyclones can produce hurricane force, non-convective winds along the East Coast and north Atlantic as well as the Pacific Ocean, with the potential to cause significant damage to life and property. Therefore, anticipating cyclogenesis for these types of storms is crucial for furthering the NOAA goal of a "Weather Ready Nation". Over the last few years, multispectral imagery (i.e. RGB) products have gained popularity among forecasters. The GOES-R satellite champion at WPC/OPC has regularly evaluated the Air Mass RGB products from GOES Sounder, MODIS, and SEVIRI to aid in forecasting cyclogenesis as part of ongoing collaborations with SPoRT within the framework of the GOES-R Proving Ground. WPC/OPC has used these products to identify regions of stratospheric air associated with tropopause folds that can lead to cyclogenesis and hurricane force winds. RGB products combine multiple channels or channel differences into multi-color imagery in which different colors represent a particular cloud or air mass type. Initial interaction and feedback from forecasters evaluating the legacy Air Mass RGBs revealed some uncertainty regarding what physical processes the qualitative RGB products represent and color interpretation. To enhance forecaster confidence and interpretation of the Air Mass RGB, NASA SPoRT has transitioned a total column ozone product from AIRS retrievals to the WPC/OPC. The use of legacy AIRS demonstrates future JPSS capabilities possible with CrIS or OMPS. Since stratospheric air can be identified by anomalous potential vorticity and warm, dry, ozone-rich air, hyperspectral infrared sounder ozone products can be used in conjunction with the Air Mass RGB for identifying the role of stratospheric air in explosive cyclogenesis and hurricane force wind events. Currently, forecasters at WPC/OPC are evaluating the Air Mass RGB imagery in conjunction with the AIRS total column ozone to aid forecasting cyclogenesis and high wind forecasts. One of the limitations of the total ozone product is that it is difficult for forecasters to determine whether elevated ozone concentrations are related to stratospheric air or climatologically high values of ozone in certain regions. To address this limitation, SPoRT created an AIRS ozone anomaly product which calculates the percent of normal ozone based on a global stratospheric ozone mean climatology. With the knowledge that ozone values 125 percent of normal and greater typically represent stratospheric air; the anomaly product can be used with the total column ozone product to confirm regions of stratospheric air on the Air Mass RGB. This presentation describes the generation of these products along with forecaster feedback concerning the use of the AIRS ozone products in conjunction with the Air Mass RGB product for the unique forecast challenges WPC/OPC face. Additionally examples of CrIS ozone and anomaly products will be shown to further demonstrate the utility and capability of JPSS in forecasting unique events.

Description: Mesoscale weather conditions can have an adverse effect on space launch, landing, ground processing, and weather advisories, watches, and warnings at the Eastern Range (ER) in Florida and Wallops Flight Facility (WFF) in Virginia. During summer, land-sea interactions across Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) lead to sea breeze front formation, which can spawn deep convection that can hinder operations and endanger personnel and resources. Many other weak locally-driven low-level boundaries and their interactions with the sea breeze front and each other can also initiate deep convection in the KSC/CCAFS area. These convective processes often last 60 minutes or less and pose a significant challenge to the local forecasters. Surface winds during the transition seasons (spring and fall) pose the most difficulties for the forecasters at WFF. They also encounter problems forecasting convective activity and temperature during those seasons. Therefore, accurate mesoscale model forecasts are needed to better forecast a variety of unique weather phenomena. Global and national scale models cannot properly resolve important local-scale weather features at each location due to their horizontal resolutions being much too coarse. Therefore, a properly tuned local data assimilation (DA) and forecast model at a high resolution is needed to provide improved capability. To accomplish this, a number of sensitivity tests were performed using the Weather Research and Forecasting (WRF) model in order to determine the best DA/model configuration for operational use at each of the space launch ranges to best predict winds, precipitation, and temperature. A set of Perl scripts to run the Gridpoint Statistical Interpolation (GSI)/WRF in real-time were provided by NASA's Short-term Prediction Research and Transition Center (SPoRT). The GSI can analyze many types of observational data including satellite, radar, and conventional data. The GSI/WRF scripts use a cycled GSI system similar to the operational North American Mesoscale (NAM) model. The scripts run a 12-hour pre-cycle in which data are assimilated from 12 hours prior up to the model initialization time. A number of different model configurations were tested for both the ER and WFF by varying the horizontal resolution on which the data assimilation was done. Three different grid configurations were run for the ER and two configurations were run for WFF for archive cases from 27 Aug 2013 through 10 Nov 2013. To quantify model performance, standard model output will be compared to the Meteorological Assimilation Data Ingest System (MADIS) data. The MADIS observation data will be compared to the WRF forecasts using the Model Evaluation Tools (MET) verification package. In addition, the National Centers for Environmental Prediction's Stage IV precipitation data will be used to validate the WRF precipitation forecasts. The author will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for each space launch range.

Description: (AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the followon sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has also been developed. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. It employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derives the probability of snowfall. Cloud properties are retrieved using an inversion method with an iteration algorithm and a twostream radiative transfer model. A method adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. The SFR products are being used mainly in two communities: hydrology and weather forecast. Global blended precipitation products traditionally do not include snowfall derived from satellites because such products were not available operationally in the past. The ATMS and AMSU/MHS SFR now provide the winter precipitation information for these blended precipitation products. Weather forecasters mainly rely on radar and station observations for snowfall forecast. The SFR products can fill in gaps where no conventional snowfall data are available to forecasters. The products can also be used to confirm radar and gauge snowfall data and increase forecasters' confidence in their prediction.

Description: The use of cloud computing resources continues to grow within the public and private sector components of the weather enterprise as users become more familiar with cloudcomputing concepts, and competition among service providers continues to reduce costs and other barriers to entry. Cloud resources can also provide capabilities similar to highperformance computing environments, supporting multinode systems required for near realtime, regional weather predictions. Referred to as "Infrastructure as a Service", or IaaS, the use of cloud-based computing hardware in an ondemand payment system allows for rapid deployment of a modeling system in environments lacking access to a large, supercomputing infrastructure. Use of IaaS capabilities to support regional weather prediction may be of particular interest to developing countries that have not yet established large supercomputing resources, but would otherwise benefit from a regional weather forecasting capability. Recently, collaborators from NASA Marshall Space Flight Center and Ames Research Center have developed a scripted, ondemand capability for launching the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS), which includes precompiled binaries of the latest version of the Weather Research and Forecasting (WRF) model. The WRFEMS provides scripting for downloading appropriate initial and boundary conditions from global models, along with higherresolution vegetation, land surface, and sea surface temperature data sets provided by the NASA Shortterm Prediction Research and Transition (SPoRT) Center. This presentation will provide an overview of the modeling system capabilities and benchmarks performed on the Amazon Elastic Compute Cloud (EC2) environment. In addition, the presentation will discuss future opportunities to deploy the system in support of weather prediction in developing countries supported by NASA's SERVIR Project, which provides capacity building activities in environmental monitoring and prediction across a growing number of regional hubs throughout the world. Capacitybuilding applications that extend numerical weather prediction to developing countries are intended to provide near realtime applications to benefit public health, safety, and economic interests, but may have a greater impact during disaster events by providing a source for local predictions of weatherrelated hazards, or impacts that local weather events may have during the recovery phase.

Description: In 2012, the Experimental Products Development Team (EPDT) was formed within NASA's Short-term Prediction Research and Transition (SPoRT) Center to create training for development of plugins to extend the National Weather Service (NWS) Advanced Weather Interactive Processing System (AWIPS) version 2. The broader atmospheric science community had a need for AWIPS II development training being created at SPoRT and EPDT was expanded to include other groups who were looking for training. Since the expansion of the group occurred, EPDT has provided AWIPS II development training to over thirty participants spanning a wide variety of groups such as NWS Systems Engineering Center, NWS Meteorological Development Laboratory, and several NOAA Cooperative Institutes. Participants within EPDT solidify their learning experience through handson learning and by participating in a "code-sprint" in which they troubleshoot existing and develop plugins. The handson learning workshop is instructor lead with participants completing exercises within the AWIPS II Development Environment. During the code sprints EPDT groups work on projects important to the community and have worked on various plugins such as an RGB image recipe creation tool, and an mPing (crowd sourced precipitation type reporting system) ingest and display. EPDT has developed a welldefined training regime which prepares participants to fully develop plugins for the extendible AWIPS II architecture from ingest to the display of new data. SPoRT has hosted 2 learning workshops and 1 code sprint over the last two years, and continues to build and shape the EPDT group based on feedback from previous workshops. The presentation will provide an overview of EPDT current and future activities, and best practices developed within EPDT.

Description: Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous in many astrophysical environments, and are likely present in interstellar clouds and protostellar disks [1]. In dense molecular clouds,PAHs and other gas-phase species are expected tocondense onto grains to form mixed molecular ice mantles dominated by small molecules like H2O, CH3OH, NH3, CO, and CO2 [2]. These icy mantleslikely undergo energetic processing from ionizing radiation in the form of cosmic rays and high-energy photons.

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Description: Regularized formulations of orbital motion apply a series of techniques to improve the numerical integration of the orbit. Despite their advantages and potential applications little attention has been paid to the propagation of the partial derivatives of the corresponding set of elements or coordinates, required in many orbit-determination scenarios and optimization problems. This paper fills this gap by presenting the general procedure for integrating the state-transition matrix of the system together with the nominal trajectory using regularized formulations and different sets of elements. The main difficulty comes from introducing an independent variable different from time, because the solution needs to be synchronized. The correction of the time delay is treated from a generic perspective not focused on any particular formulation. The synchronization using time-elements is also discussed. Numerical examples include strongly-perturbed orbits in the Pluto system, motivated by the recent flyby of the New Horizons spacecraft, together with a geocentric flyby of the NEAR spacecraft.

Description: Information about the physical characteristics of Near Earth Asteroids (NEAs) is needed to model behavior during atmospheric entry, to assess the risk of an impact, and to model possible mitigation techniques. The intrinsic properties of interest to entry and mitigation modelers, however, rarely are directly measureable. Instead we measure other properties and infer the intrinsic physical properties, so determining the complete set of characteristics of interest is far from straightforward. In addition, for the majority of NEAs, only the basic measurements exist so often properties must be inferred from statistics of the population of more completely characterized objects. We will provide an assessment of the current state of knowledge about the physical characteristics of importance to asteroid threat assessment. In addition, an ongoing effort to collate NEA characteristics into a readily accessible database for use by the planetary defense community will be discussed.

Description: ISMIP6 (Ice Sheet Model Intercomparison Project for CMIP6) targets the Cryosphere in a Changing Climate and the Future Sea Level Grand Challenges of the WCRP (World Climate Research Program). Primary goal is to provide future sea level contribution from the Greenland and Antarctic ice sheets, along with associated uncertainty. Secondary goal is to investigate feedback due to dynamic ice sheet models. Experiment design uses and augment the existing CMIP6 (Coupled Model Intercomparison Project Phase 6) DECK (Diagnosis, Evaluation, and Characterization of Klima) experiments. Additonal MIP (Model Intercomparison Project)- specific experiments will be designed for ISM (Ice Sheet Model). Effort builds on the Ice2sea, SeaRISE (Sea-level Response to Ice Sheet Evolution) and COMBINE (Comprehensive Modelling of the Earth System for Better Climate Prediction and Projection) efforts.

Description: The probability for an extreme five-day September rainfall event over northeast Colorado, as was observed in early September 2013, has likely decreased due to climate change.

Description: The Wide-Field Infrared Survey Explorer (WISE) has uncovered a striking cluster of young stellar object (YSO) candidates associated with the L1509 dark cloud in Auriga. The WISE observations, at 3.4, 4.6, 12, and 22 microns, show a number of objects with colors consistent with YSOs, and their spectral energy distributions suggest the presence of circumstellar dust emission, including numerous Class I, flat spectrum, and Class II objects. In general, the YSOs in L1509 are much more tightly clustered than YSOs in other dark clouds in the Taurus-Auriga star forming region, with Class I and flat spectrum objects confined to the densest aggregates, and Class II objects more sparsely distributed. We estimate a most probable distance of 485-700 pc, and possibly as far as the previously estimated distance of 2 kpc.

Description: The spectra of analysis and forecast error are examined using the observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASAGMAO). A global numerical weather prediction model, the Global Earth Observing System version 5 (GEOS-5) with Gridpoint Statistical Interpolation (GSI) data assimilation, is cycled for two months with once-daily forecasts to 336 hours to generate a control case. Verification of forecast errors using the Nature Run as truth is compared with verification of forecast errors using self-analysis; significant underestimation of forecast errors is seen using self-analysis verification for up to 48 hours. Likewise, self analysis verification significantly overestimates the error growth rates of the early forecast, as well as mischaracterizing the spatial scales at which the strongest growth occurs. The Nature Run-verified error variances exhibit a complicated progression of growth, particularly for low wave number errors. In a second experiment, cycling of the model and data assimilation over the same period is repeated, but using synthetic observations with different explicitly added observation errors having the same error variances as the control experiment, thus creating a different realization of the control. The forecast errors of the two experiments become more correlated during the early forecast period, with correlations increasing for up to 72 hours before beginning to decrease.

Description: Precipitation in the central U.S. decreases by about 25% during the seasonal transition from June to July, and this precipitation decrease has been observed to have intensified since 1979. Such an intensification could enhance future spring drought occurrences such as was the case in the 2012 "flash drought" in the Midwestern U.S., where conditions evolved quickly from being abnormally dry to exceptionally dry within a mere month from June to July. In this study, various atmospheric and land reanalysis datasets were analyzed to examine the trend calculated from 1979 to 2012 in the June-to-July seasonal transition. It was found that the change in precipitation deficit was accompanied by increased downward shortwave radiation flux and tropospheric subsidence, enhanced evaporative fraction, as well as an elevated planetary boundary layer height. The change in the tropospheric circulation encompassed an anomalous ridge over the western U.S. and a trough on either side; this wave-form circulation pattern is known to induce dry conditions in the central U.S. Possibly, the trends in the June-to-July seasonal shifts in precipitation, drought severity and tropospheric circulation intensified the 2012 "flash drought" in timing and extent. The knowledge of the trends allows one to anticipate the evolution of spring onset of drought into the summer.

Description: High-frequency TMI and AMSR-E radiances, which are sensitive to precipitation over land, are assimilated into the Goddard Weather Research and Forecasting Model- Ensemble Data Assimilation System (WRF-EDAS) for a few heavy rain events over the continental US. Independent observations from surface rainfall, satellite IR brightness temperatures, as well as ground-radar reflectivity profiles are used to evaluate the impact of assimilating rain-sensitive radiances on cloud and precipitation within WRF-EDAS. The evaluations go beyond comparisons of forecast skills and domain-mean statistics, and focus on studying the cloud and precipitation features in the jointed rainradiance and rain-cloud space, with particular attentions on vertical distributions of height-dependent cloud types and collective effect of cloud hydrometers. Such a methodology is very helpful to understand limitations and sources of errors in rainaffected radiance assimilations. It is found that the assimilation of rain-sensitive radiances can reduce the mismatch between model analyses and observations by reasonably enhancing/reducing convective intensity over areas where the observation indicates precipitation, and suppressing convection over areas where the model forecast indicates rain but the observation does not. It is also noted that instead of generating sufficient low-level warmrain clouds as in observations, the model analysis tends to produce many spurious upperlevel clouds containing small amount of ice water content. This discrepancy is associated with insufficient information in ice-water-sensitive radiances to address the vertical distribution of clouds with small amount of ice water content. Such a problem will likely be mitigated when multi-channel multi-frequency radiances/reflectivity are assimilated over land along with sufficiently accurate surface emissivity information to better constrain the vertical distribution of cloud hydrometers.

Description: The Wilkinson Microwave Anisotropy Probe (WMAP) mapped the distribution of temperature and polarization over the entire sky in five microwave frequency bands. These full-sky maps were used to obtain measurements of temperature and polarization anisotropy of the cosmic microwave background with the unprecedented accuracy and precision. The analysis of two-point correlation functions of temperature and polarization data gives determinations of the fundamental cosmological parameters such as the age and composition of the universe, as well as the key parameters describing the physics of inflation, which is further constrained by three-point correlation functions. WMAP observations alone reduced the flat cold dark matter (Lambda Cold Dark Matter) cosmological model (six) parameter volume by a factor of 〉 68, 000 compared with pre-WMAP measurements. The WMAP observations (sometimes in combination with other astrophysical probes) convincingly show the existence of non-baryonic dark matter, the cosmic neutrino background, flatness of spatial geometry of the universe, a deviation from a scale-invariant spectrum of initial scalar fluctuations, and that the current universe is undergoing an accelerated expansion. The WMAP observations provide the strongest ever support for inflation; namely, the structures we see in the universe originate from quantum fluctuations generated during inflation.

Description: Numerous cloud microphysical schemes designed for cloud and mesoscale models are currently in use, ranging from simple bulk to multi-moment, multi-class to explicit bin schemes. This study details the benefits of adding a 4th ice class (hail) to an already improved 3-class ice bulk microphysics scheme developed for the Goddard Cumulus Ensemble model based on Rutledge and Hobbs (1983,1984). Besides the addition and modification of several hail processes from Lin et al. (1983), further modifications were made to the 3-ice processes, including allowing greater ice super saturation and mitigating spurious evaporationsublimation in the saturation adjustment scheme, allowing graupelhail to become snow via vapor growth and hail to become graupel via riming, and the inclusion of a rain evaporation correction and vapor diffusivity factor. The improved 3-ice snowgraupel size-mapping schemes were adjusted to be more stable at higher mixing rations and to increase the aggregation effect for snow. A snow density mapping was also added. The new scheme was applied to an intense continental squall line and a weaker, loosely-organized continental case using three different hail intercepts. Peak simulated reflectivities agree well with radar for both the intense and weaker case and were better than earlier 3-ice versions when using a moderate and large intercept for hail, respectively. Simulated reflectivity distributions versus height were also improved versus radar in both cases compared to earlier 3-ice versions. The bin-based rain evaporation correction affected the squall line case more but did not change the overall agreement in reflectivity distributions.

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Description: NASA's Orbiting Carbon Observatory-2 satellite will make the first space-based measurements of carbon dioxide in Earth's atmosphere. In support of the mission, Goddard Space Flight Center will fly air missions from Wallops Flight Facility to gather finer-grained data in areas of interest. Goddard started working with Blacksburg, Virginia-based Aeroprobe Corporation through the SBIR program in 2008 to develop sensors for such flights, and the company has since commercialized the resulting product.

Description: Presented is comparison between CERES SFC EBAF data and the CMIP5 climate models in the Arctic.

Description: The Arctic is one of the most climatically sensitive regions of the Earth. Climate models robustly project the Arctic to warm 2-3 times faster than the global mean surface temperature, termed polar warming amplification (PWA), but also display the widest range of surface temperature projections in this region. The response of the Arctic to increased CO2 modulates the response in tropical and extra-tropical regions through teleconnections in the atmospheric circulation. An increased frequency of extreme precipitation events in the northern mid-latitudes, for example, has been linked to the change in the background equator-to-pole temperature gradient implied by PWA. Understanding the Arctic climate system is therefore important for predicting global climate change. The ice albedo feedback is the primary mechanism driving PWA, however cloud and dynamical feedbacks significantly contribute. These feedback mechanisms, however, do not operate independently. How do clouds respond to variations in sea ice? This critical question is addressed by combining sea ice, cloud, and radiation observations from satellites, including CERES, CloudSAT, CALIPSO, MODIS, and microwave radiometers, to investigate sea ice-cloud interactions at the interannual timescale in the Arctic. Cloud characteristics are strongly tied to the atmospheric dynamic and thermodynamic state. Therefore, the sensitivity of Arctic cloud characteristics, vertical distribution and optical properties, to sea ice anomalies is computed within atmospheric dynamic and thermodynamic regimes. Results indicate that the cloud response to changes in sea ice concentration differs significantly between atmospheric state regimes. This suggests that (1) the atmospheric dynamic and thermodynamic characteristics and (2) the characteristics of the marginal ice zone are important for determining the seasonal forcing by cloud on sea ice variability.

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Description: This presentation uses publicly available CERES and radiosonde data to investigate the sensitivity of thetropical convective diurnal cycle to atmosphere state. Averaging surface observations into regimes of convective intensitydefined by satellite shows great promise for physical understandingof convection. Convective processes in the Amazon are highly variable seasonallyand locally. Buoyancy/CIN more important JJA Mesoscale/synoptic features easier to separate Length/depth of buoyancy layer very important in DJF (EL). Moisture more important DJF, esp. UTH Humidity of lower atmosphere significantly impacts LTS, LCL and abilityfor parcels to reach LFC. Lower level jet strength/direction important Convective initiation correlated with LTS, LR, LTH, EL Duration/Phase better correlated with humidity variables Surface Flux amplitude well correlated with convection

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Description: This work evaluates the multilayer cloud (MCF) algorithm based on CO2-slicing techniques against CALISPO-CloudSat (CLCS) measurement. This evaluation showed that the MCF underestimates the presence of multilayered clouds compared with CLCS and are retrained to cloud emissivities below 0.8 and cloud optical septs no larger than 0.3.

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Description: We explore the connections between various coordinate systems associated with observersmoving inwardly along radial geodesics in the Schwarzschild geometry. Painleve-Gullstrand (PG) time is adapted to freely falling observers dropped from rest from infinity; Lake-Martel-Poisson (LMP) time coordinates are adapted to observers who start at infinity with non-zero initial inward velocity; Gautreau-Hoffmann time coordinates are adapted to observers dropped from rest from a finite distance from the black hole horizon.We construct from these an LMP family and a proper-time family of time coordinates, the intersection of which is PG time. We demonstrate that these coordinate families are distinct, but related, one-parameter generalizations of PG time, and show linkage to Lematre coordinates as well.

Description: NASA's Clouds and the Earth's Radiant Energy System (CERES) project integrates CERES, Moderate Resolution Imaging Spectroradiometer (MODIS), and geostationary satellite observations to provide top-of-atmosphere (TOA) irradiances derived from broadband radiance observations by CERES instruments. It also uses snow cover and sea ice extent retrieved from microwave instruments as well as thermodynamic variables from reanalysis. In addition, these variables are used for surface and atmospheric irradiance computations. The CERES project provides TOA, surface, and atmospheric irradiances in various spatial and temporal resolutions. These data sets are for climate research and evaluation of climate models. Long-term observations are required to understand how the Earth system responds to radiative forcing. A simple model is used to estimate the time to detect trends in TOA reflected shortwave and emitted longwave irradiances.

Description: We explore the emission properties of a dissipative pulsar magnetosphere model introduced by Kalapotharakos et al. comparing its high-energy light curves and spectra, due to curvature radiation, with data collected by the Fermi LAT. The magnetosphere structure is assumed to be near the force-free solution. The accelerating electric field, inside the light cylinder (LC), is assumed to be negligible, while outside the LC it rescales with a finite conductivity (sigma). In our approach we calculate the corresponding high-energy emission by integrating the trajectories of test particles that originate from the stellar surface, taking into account both the accelerating electric field components and the radiation reaction forces. First, we explore the parameter space assuming different value sets for the stellar magnetic field, stellar period, and conductivity. We show that the general properties of the model are in a good agreement with observed emission characteristics of young gamma-ray pulsars, including features of the phase-resolved spectra. Second, we find model parameters that fit each pulsar belonging to a group of eight bright pulsars that have a published phase-resolved spectrum. The sigma values that best describe each of the pulsars in this group show an increase with the spin-down rate (E ) and a decrease with the pulsar age, expected if pair cascades are providing the magnetospheric conductivity. Finally, we explore the limits of our analysis and suggest future directions for improving such models.

Description: Halogens in the troposphere are increasingly recognized as playing an important role for atmospheric chemistry, and possibly climate. Bromine and iodine react catalytically to destroy ozone (O3), oxidize mercury, and modify oxidative capacity that is relevant for the lifetime of greenhouse gases. Most of the tropospheric O3 and methane (CH4) loss occurs at tropical latitudes. Here we report simultaneous measurements of vertical profiles of bromine oxide (BrO) and iodine oxide (IO) in the tropical and subtropical free troposphere (10degN to 40degS), and show that these halogens are responsible for 34% of the column-integrated loss of tropospheric O3. The observed BrO concentrations increase strongly with altitude (approx.3.4 pptv at 13.5 km), and are 2-4 times higher than predicted in the tropical free troposphere. BrO resembles model predictions more closely in stratospheric air. The largest model low bias is observed in the lower tropical transition layer (TTL) over the tropical eastern Pacific Ocean, and may reflect a missing inorganic bromine source supplying an additional 2.5-6.4 pptv total inorganic bromine (Bry), or model overestimated Bry wet scavenging. Our results highlight the importance of heterogeneous chemistry on ice clouds, and imply an additional Bry source from the debromination of sea salt residue in the lower TTL. The observed levels of bromine oxidize mercury up to 3.5 times faster than models predict, possibly increasing mercury deposition to the ocean. The halogen-catalyzed loss of tropospheric O3 needs to be considered when estimating past and future ozone radiative effects.

Description: The formation scenario of a gapped disk, i.e., transitional disk, and its asymmetry is still under debate. Proposed scenarios such as disk-planet interaction, photoevaporation, grain growth, anticyclonic vortex, eccentricity, and their combinations would result in different radial distributions of the gas and the small (sub-micron size) and large (millimeter size) dust grains as well as asymmetric structures in a disk. Optical/near-infrared (NIR) imaging observations and (sub-)millimeter interferometry can trace small and large dust grains, respectively; therefore multi-wavelength observations could help elucidate the origin of complicated structures of a disk. Here we report Submillimeter Array observations of the dust continuum at 1.3 mm and CO-12 J = 2 yields 1 line emission of the pre-transitional protoplanetary disk around the solar-mass star PDS 70. PDS 70, a weak-lined T Tauri star, exhibits a gap in the scattered light from its disk with a radius of approx. 65 AU at NIR wavelengths. However, we found a larger gap in the disk with a radius of approx. 80 AU at 1.3 mm. Emission from all three disk components (the gas and the small and large dust grains) in images exhibits a deficit in brightness in the central region of the disk, in particular, the dust disk in small and large dust grains has asymmetric brightness. The contrast ratio of the flux density in the dust continuum between the peak position to the opposite side of the disk reaches 1.4. We suggest the asymmetries and different gap radii of the disk around PDS 70 are potentially formed by several (unseen) accreting planets inducing dust filtration.

Description: We present new high-resolution (approximately 0.09) H-band imaging observations of the circumstellar disk around the T Tauri star SU Aur. Our observations with Subaru-HiCIAO have revealed the presence of scattered light as close as 0.15 (approximately 20 AU) to the star. Within our image, we identify bright emission associated with a disk with a minimum radius of approximately 90 AU, an inclination of approximately 35 deg from the plane of the sky, and an approximate PA of 15 deg for the major axis. We find a brightness asymmetry between the northern and southern sides of the disk due to a non-axisymmetric disk structure. We also identify a pair of asymmetric tail structures extending east and west from the disk. The western tail extends at least 2. 5 (350 AU) from the star, and is probably associated with a reflection nebula previously observed at optical and near-IR wavelengths. The eastern tail extends at least 1 (140 AU) at the present signal-to-noise. These tails are likely due to an encounter with an unseen brown dwarf, but our results do not exclude the explanation that these tails are outflow cavities or jets.

Description: During inactive phases of Madden-Julian Oscillation (MJO), there are plenty of deep but small convective systems and far fewer deep and large ones. During active phases of MJO, a manifestation of an increase in the occurrence of large and deep cloud clusters results from an amplification of large-scale motions by stronger convective heating. This study is designed to quantitatively examine the roles of small and large cloud clusters during the MJO life cycle. We analyze the cloud object data from Aqua CERES (Clouds and the Earth's Radiant Energy System) observations between July 2006 and June 2010 for tropical deep convective (DC) and cirrostratus (CS) cloud object types according to the real-time multivariate MJO index, which assigns the tropics to one of the eight MJO phases each day. The cloud object is a contiguous region of the earth with a single dominant cloud-system type. The criteria for defining these cloud types are overcast footprints and cloud top pressures less than 400 hPa, but DC has higher cloud optical depths (=10) than those of CS (〈10). The size distributions, defined as the footprint numbers as a function of cloud object diameters, for particular MJO phases depart greatly from the combined (8-phase) distribution at large cloud-object diameters due to the reduced/increased numbers of cloud objects related to changes in the large-scale environments. The medium diameter corresponding to the combined distribution is determined and used to partition all cloud objects into "small" and "large" groups of a particular phase. The two groups corresponding to the combined distribution have nearly equal numbers of footprints. The medium diameters are 502 km for DC and 310 km for cirrostratus. The range of the variation between two extreme phases (typically, the most active and depressed phases) for the small group is 6-11% in terms of the numbers of cloud objects and the total footprint numbers. The corresponding range for the large group is 19-44%. In terms of the probability density functions of radiative and cloud physical properties, there are virtually no differences between the MJO phases for the small group, but there are significant differences for the large groups for both DC and CS types. These results suggest that the intreseasonal variation signals reside at the large cloud clusters while the small cloud clusters represent the background noises resulting from various types of the tropical waves with different wavenumbers and propagation speeds/directions.

Description: Time-series analysis has often been a useful tool in atmospheric science for deriving long-term trends in various atmospherically important parameters (e.g., temperature or the concentration of trace gas species). In particular, time-series analysis has been repeatedly applied to satellite datasets in order to derive the long-term trends in stratospheric ozone, which is a critical atmospheric constituent. However, many of the potential pitfalls relating to the non-uniform sampling of the datasets were often ignored and the results presented by the scientific community have been unknowingly biased. A newly developed and more robust application of this technique is applied to the Stratospheric Aerosol and Gas Experiment (SAGE) II version 7.0 ozone dataset and the previous biases and newly derived trends are presented.

Description: We present new Hubble Space Telescope Cosmic Origins Spectrograph far-ultraviolet (far-UV) spectroscopy and Keck Echellete optical spectroscopy of 11 ultraluminous infrared galaxies (ULIRGs), a rare population of local galaxies experiencing massive gas inflows, extreme starbursts, and prominent outflows. We detect Ly(alpha) emission from eight ULIRGs and the companion to IRAS09583+4714. In contrast to the P Cygni profiles often seen in galaxy spectra, the Ly(alpha) profiles exhibit prominent, blueshifted emission out to Doppler shifts exceeding 1000 km/s in three H II-dominated and two AGN-dominated ULIRGs. To better understand the role of resonance scattering in shaping the Ly(alpha) line profiles, we directly compare them to non-resonant emission lines in optical spectra. We find that the line wings are already present in the intrinsic nebular spectra, and scattering merely enhances the wings relative to the line core. The Ly(alpha) attenuation (as measured in the COS aperture) ranges from that of the far-UV continuum to over 100 times more. A simple radiative transfer model suggests the Ly(alpha) photons escape through cavities which have low column densities of neutral hydrogen and become optically thin to the Lyman continuum in the most advanced mergers. We show that the properties of the highly blueshifted line wings on the Ly(alpha) and optical emission-line profiles are consistent with emission from clumps of gas condensing out of a fast, hot wind. The luminosity of the Ly(alpha) emission increases nonlinearly with the ULIRG bolometric luminosity and represents about 0.1-1% of the radiative cooling from the hot winds in the H II-dominated ULIRGs.

Description: Infrared (IR) excesses around K-type red giants (RGs) have previously been discovered using Infrared Astronomy Satellite (IRAS) data, and past studies have suggested a link between RGs with overabundant lithium and IR excesses, implying the ejection of circumstellar shells or disks. We revisit the question of IR excesses around RGs using higher spatial resolution IR data, primarily from the Wide-field Infrared Survey Explorer. Our goal was to elucidate the link between three unusual RG properties: fast rotation, enriched lithium, and IR excess. Our sample of RGs includes those with previous IR detections, a sample with well-defined rotation and lithium abundance measurements with no previous IR measurements, and a large sample of RGs asserted to be lithium-rich in the literature; we have 316 targets thought to be K giants, about 40% of which we take to be Li-rich. In 24 cases with previous detections of IR excess at low spatial resolution, we believe that source confusion is playing a role, in that either (a) the source that is bright in the optical is not responsible for the IR flux, or (b) there is more than one source responsible for the IR flux as measured in IRAS. We looked for IR excesses in the remaining sources, identifying 28 that have significant IR excesses by approximately 20 micrometers (with possible excesses for 2 additional sources). There appears to be an intriguing correlation in that the largest IR excesses are all in Li-rich K giants, though very few lithium-rich K giants have IR excesses (large or small). These largest IR excesses also tend to be found in the fastest rotators. There is no correlation of IR excess with the carbon isotopic ratio, 12C/13C. IR excesses by 20 micrometers, though relatively rare, are at least twice as common among our sample of lithium-rich K giants. If dust shell production is a common by-product of Li enrichment mechanisms, these observations suggest that the IR excess stage is very short-lived, which is supported by theoretical calculations. Conversely, the lithium-enrichment mechanism may only occasionally produce dust, and an additional parameter (e.g., rotation) may control whether or not a shell is ejected.

Description: We use a Monte Carlo code to calculate the geodesic orbits of test particles around Kerr black holes, generating a distribution function of both bound and unbound populations of dark matter (DM) particles. From this distribution function, we calculate annihilation rates and observable gamma-ray spectra for a few simple DM models. The features of these spectra are sensitive to the black hole spin, observer inclination, and detailed properties of the DM annihilation cross-section and density profile. Confirming earlier analytic work, we find that for rapidly spinning black holes, the collisional Penrose process can reach efficiencies exceeding 600%, leading to a high-energy tail in the annihilation spectrum. The high particle density and large proper volume of the region immediately surrounding the horizon ensures that the observed flux from these extreme events is non-negligible.

Description: Globally, freshwater shortage is one of the most dangerous risks for society. Changing hydro-climatic and socioeconomic conditions have aggravated water scarcity over the past decades. A wide range of studies show that water scarcity will intensify in the future, as a result of both increased consumptive water use and, in some regions, climate change. Although it is well-known that El Nio- Southern Oscillation (ENSO) affects patterns of precipitation and drought at global and regional scales, little attention has yet been paid to the impacts of climate variability on water scarcity conditions, despite its importance for adaptation planning. Therefore, we present the first global-scale sensitivity assessment of water scarcity to ENSO, the most dominant signal of climate variability. We show that over the time period 1961-2010, both water availability and water scarcity conditions are significantly correlated with ENSO-driven climate variability over a large proportion of the global land area (〉 28.1 %); an area inhabited by more than 31.4% of the global population. We also found, however, that climate variability alone is often not enough to trigger the actual incidence of water scarcity events. The sensitivity of a region to water scarcity events, expressed in terms of land area or population exposed, is determined by both hydro-climatic and socioeconomic conditions. Currently, the population actually impacted by water scarcity events consists of 39.6% (CTA: consumption-to-availability ratio) and 41.1% (WCI: water crowding index) of the global population, whilst only 11.4% (CTA) and 15.9% (WCI) of the global population is at the same time living in areas sensitive to ENSO-driven climate variability. These results are contrasted, however, by differences in growth rates found under changing socioeconomic conditions, which are relatively high in regions exposed to water scarcity events. Given the correlations found between ENSO and water availability and scarcity conditions, and the relative developments of water scarcity impacts under changing socioeconomic conditions, we suggest that there is potential for ENSO-based adaptation and risk reduction that could be facilitated by more research on this emerging topic.

Description: No abstract available