On the use of IR lidar and K(sub a)-band radar for observing cirrus clouds

Advances in lidar and radar technology have potential for providing new and better information on climate significant parameters of cirrus. Consequently, the NOAA Wave Propagation Lab. is commencing CLARET (Cloud Lidar And Radar Exploratory Test) to evaluate the promise of these new capabilities. Parameters under study include cloud particle size distribution, height of cloud bases, tops, and multiple layers, and cloud dynamics revealed through measurement of vertical motions. The first phase of CLARET is planned for Sept. 1989. The CO2 coherent Doppler lidar and the sensitive K sub a band radar hold promise for providing valuable information on cirrus that is beyond the grasp of current visible lidars

Combining Active and Passive Airborne Remote Sensing to Quantify NO2 and Ox Production near Bakersfield, CA

Aims: The objective of this study is to demonstrate the integrated use of passive and active remote sensing instruments to quantify the rate of NOx emissions, and investigate the Ox production rates from an urban area.Place and Duration of Study: A research flight on June 15, 2010 was conducted over Bakersfield, CA and nearby areas with oil and natural gas production. Methodology: Three remote sensing instruments, namely the University of Colorado AMAX-DOAS, NOAA TOPAZ lidar, and NCAS Doppler lidar were deployed aboard the NOAA Twin Otter during summer 2010. Production rates of nitrogen dioxide (NO2) and Ox&lsquo;(background corrected O3 + NO2) were quantified using the horizontal flux divergence approach by flying closed loops near Bakersfield, CA. By making concurrent measurements of the trace gases as well as the wind fields, we have reduced the uncertainty due to wind field in production rates.Results: We find that the entire region is a source for both NO2 and Ox&rsquo;. NO2 production is highest over the city (1.35 kg hr-1 km-2 NO2), and about 30 times lower at background sites (0.04 kg hr-1 km-2 NO2). NOx emissions as represented in the CARB 2010 emission inventory agreewell with our measurements over Bakersfield city (within 30%). However, emissions upwind of the city are significantly underestimated. The Ox&rsquo; production is less variable, found ubiquitous, and accounts for 7.4 kg hr-1 km-2 Ox&rsquo; at background sites. Interestingly, the maximum of 17.1 kg hr-1 km-2 Ox&rsquo;production was observed upwind of the city. A plausible explanation for the efficient Ox&rsquo; production upwind of Bakersfield, CA are favorable volatile organic compound (VOC) to NOx ratios for Ox&rsquo; production, that are affected by emissions from large oil and natural gas operations in that area. Conclusion: The NO2 and O3 source fluxes vary significantly, and allow us to separate and map NOx emissions and Ox production rates in the Central Valley. The data is probed over spatial scales that link closely with those predicted by atmospheric models, and provide innovative means to test and improve atmospheric models that are used to manage air resources. Emissions from oil and natural gas operations are a source for O3 air pollution, and deserve further study to better characterize effects on public health.</p

The Indianapolis Flux Experiment (INFLUX): A test-bed for developing urban greenhouse gas emission measurements

The objective of the Indianapolis Flux Experiment (INFLUX) is to develop, evaluate and improve methods for measuring greenhouse gas (GHG) emissions from cities. INFLUX’s scientific objectives are to quantify CO2 and CH4 emission rates at 1 km2 resolution with a 10% or better accuracy and precision, to determine whole-city emissions with similar skill, and to achieve high (weekly or finer) temporal resolution at both spatial resolutions. The experiment employs atmospheric GHG measurements from both towers and aircraft, atmospheric transport observations and models, and activity-based inventory products to quantify urban GHG emissions. Multiple, independent methods for estimating urban emissions are a central facet of our experimental design. INFLUX was initiated in 2010 and measurements and analyses are ongoing. To date we have quantified urban atmospheric GHG enhancements using aircraft and towers with measurements collected over multiple years, and have estimated whole-city CO2 and CH4 emissions using aircraft and tower GHG measurements, and inventory methods. Significant differences exist across methods; these differences have not yet been resolved; research to reduce uncertainties and reconcile these differences is underway. Sectorally- and spatially-resolved flux estimates, and detection of changes of fluxes over time, are also active research topics. Major challenges include developing methods for distinguishing anthropogenic from biogenic CO2 fluxes, improving our ability to interpret atmospheric GHG measurements close to urban GHG sources and across a broader range of atmospheric stability conditions, and quantifying uncertainties in inventory data products. INFLUX data and tools are intended to serve as an open resource and test bed for future investigations. Well-documented, public archival of data and methods is under development in support of this objective

Assessing the optimized precision of the aircraft mass balance method for measurement of urban greenhouse gas emission rates through averaging

To effectively address climate change, aggressive mitigation policies need to be implemented to reduce greenhouse gas emissions. Anthropogenic carbon emissions are mostly generated from urban environments, where human activities are spatially concentrated. Improvements in uncertainty determinations and precision of measurement techniques are critical to permit accurate and precise tracking of emissions changes relative to the reduction targets. As part of the INFLUX project, we quantified carbon dioxide (CO2), carbon monoxide (CO) and methane (CH4) emission rates for the city of Indianapolis by averaging results from nine aircraft-based mass balance experiments performed in November-December 2014. Our goal was to assess the achievable precision of the aircraft-based mass balance method through averaging, assuming constant CO2, CH4 and CO emissions during a three-week field campaign in late fall. The averaging method leads to an emission rate of 14,600 mol/s for CO2, assumed to be largely fossil-derived for this period of the year, and 108 mol/s for CO. The relative standard error of the mean is 17% and 16%, for CO2 and CO, respectively, at the 95% confidence level (CL), i.e. a more than 2-fold improvement from the previous estimate of ~40% for single-flight measurements for Indianapolis. For CH4, the averaged emission rate is 67 mol/s, while the standard error of the mean at 95% CL is large, i.e. ±60%. Given the results for CO2 and CO for the same flight data, we conclude that this much larger scatter in the observed CH4 emission rate is most likely due to variability of CH4 emissions, suggesting that the assumption of constant daily emissions is not correct for CH4 sources. This work shows that repeated measurements using aircraft-based mass balance methods can yield sufficient precision of the mean to inform emissions reduction efforts by detecting changes over time in urban emissions

Predicting Spatial Patterns of Plant Recruitment Using Animal-Displacement Kernels

For plants dispersed by frugivores, spatial patterns of recruitment are primarily influenced by the spatial arrangement and characteristics of parent plants, the digestive characteristics, feeding behaviour and movement patterns of animal dispersers, and the structure of the habitat matrix. We used an individual-based, spatially-explicit framework to characterize seed dispersal and seedling fate in an endangered, insular plant-disperser system: the endemic shrub Daphne rodriguezii and its exclusive disperser, the endemic lizard Podarcis lilfordi. Plant recruitment kernels were chiefly determined by the disperser's patterns of space utilization (i.e. the lizard's displacement kernels), the position of the various plant individuals in relation to them, and habitat structure (vegetation cover vs. bare soil). In contrast to our expectations, seed gut-passage rate and its effects on germination, and lizard speed-of-movement, habitat choice and activity rhythm were of minor importance. Predicted plant recruitment kernels were strongly anisotropic and fine-grained, preventing their description using one-dimensional, frequency-distance curves. We found a general trade-off between recruitment probability and dispersal distance; however, optimal recruitment sites were not necessarily associated to sites of maximal adult-plant density. Conservation efforts aimed at enhancing the regeneration of endangered plant-disperser systems may gain in efficacy by manipulating the spatial distribution of dispersers (e.g. through the creation of refuges and feeding sites) to create areas favourable to plant recruitment

Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL.

Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype

Does soil pyrogenic carbon determine plant functional traits in Amazon Basin forests?

Amazon forests are fire-sensitive ecosystems and consequently fires affect forest structure and composition. For instance, the legacy of past fire regimes may persist through some species and traits that are found due to past fires. In this study, we tested for relationships between functional traits that are classically presented as the main components of plant ecological strategies and environmental filters related to climate and historical fires among permanent mature forest plots across the range of local and regional environmental gradients that occur in Amazonia. We used percentage surface soil pyrogenic carbon (PyC), a recalcitrant form of carbon that can persist for millennia in soils, as a novel indicator of historical fire in old-growth forests. Five out of the nine functional traits evaluated across all 378 species were correlated with some environmental variables. Although there is more PyC in Amazonian soils than previously reported, the percentage soil PyC indicated no detectable legacy effect of past fires on contemporary functional composition. More species with dry diaspores were found in drier and hotter environments. We also found higher wood density in trees from higher temperature sites. If Amazon forest past burnings were local and without distinguishable attributes of a widespread fire regime, then impacts on biodiversity would have been small and heterogeneous. Alternatively, sufficient time may have passed since the last fire to allow for species replacement. Regardless, as we failed to detect any impact of past fire on present forest functional composition, if our plots are representative then it suggests that mature Amazon forests lack a compositional legacy of past fire

Multiscale analyses of moisture transport by the central plains lowlevel jet during IHOP

During the International H2O Project (IHOP) in the Southern U.S. Central Plains in May and June 2002, aircraft missions on June 3 and June 9 2002 made detailed lidar and dropsonde observations of intense phases of the low-level jet (LLJ) . Combined with standard and enhanced operational observations (primarily radiosondes and profilers) and other ground-based research observations, data from these missions represent an unprecedented opportunity to describe moisture transport in the LLJ at scales ranging from the synoptic scales resolved by the radiosonde network to sub-mesoscale features in the moisture and wind fields observed by airborne lidar instruments

The Athena-OAWL Doppler Wind Lidar Mission

With the objective of providing tropospheric wind profile data over the mid-latitude oceans and tropics for data-starved weather forecast models, the Earth Venture Instrument (EV-I) Mission concept “Atmospheric Transport, Hurricanes, and Extratropical Numerical weAther prediction with the Optical Autocovariance Wind Lidar” (ATHENA-OAWL) was proposed in November 2013. The mission concept is described here along with a brief history of the OAWL system development and current development of an ATHENA-OAWL airborne demonstrator under NASA’s Venture Technology development