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An interpolation method is described for range measurements of high precision and altimetry using repeating intensity-modulated continuous wave (IM-CW) lidar waveforms, where the range is determined by means of a cross-correlation...
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An interpolation method is described for range measurements of high precision and altimetry using repeating intensity-modulated continuous wave (IM-CW) lidar waveforms, where the range is determined by means of a cross-correlation between the digital form of the transmitted signal and the digitized return signal collected by the lidar receiver. This method uses reordering of the array elements in the frequency domain to convert a repeating synthetic pulse signal to single highly interpolated pulse. The computation of this processing is marginally greater than the correlation itself, as it only involves reordering of the correlation in the frequency domain, which makes it possible to implement this in a real time application. It is shown through theoretical arguments and flight-testing that this is a viable method for high-speed interpolated range measurements. Standard deviation is 0.75 m over water with only 350 mw of transmitted power at 2600 m.
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Relationships between modeled and measured meteorological state parameters and cloudy and cloud-free conditions are examined using data taken over the ARM (Atmospheric Radiation Measurement) Southern Great Plains Central Facility ...
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Relationships between modeled and measured meteorological state parameters and cloudy and cloud-free conditions are examined using data taken over the ARM (Atmospheric Radiation Measurement) Southern Great Plains Central Facility between 1 March 2000 and 28 February 2001. Cloud vertical layering was determined from the Active Remotely Sensed Cloud Location product based on the ARM active sensor measurements. Both temperature and relative humidity (RH) observations from balloon-borne Vaisala RS80-15LH radiosonde (SONDE) and the Rapid Update Cycle (RUC) 40-km resolution model are highly correlated, but the SONDE RHs generally exceed those from RUC. Inside cloudy layers, the RH from SONDE is 2–14% higher than the RH from RUC at all pressure levels. Although the layer mean RH within clouds is much greater than the layer mean RH outside clouds or in clear skies, RH thresholds chosen as a function of temperature can more accurately diagnose cloud occurrence for either data set than a fixed RH threshold. For overcast clouds (cloud amount greater than or equal to 90%), it was found that the 50% probability RH threshold for diagnosing a cloud, within a given upper tropospheric layer, is roughly 90% for the SONDE and 80% for RUC data. For partial cloud cover (cloud amount is less than 90%), the SONDE RH thresholds are close to those for RUC at a given probability in upper tropospheric layers. Cloud probability was found to be only minimally dependent on vertical velocity. In the upper troposphere, SONDE ice-supersaturated air occurred in 8 and 35% of the clear and cloudy layers, respectively. The RH was distributed exponentially in the ice supersaturated layers as found in previous studies. The occurrence of high-altitude, ice-supersaturated layers in the RUC data was roughly half of that in the SONDE data. Optimal thresholds were derived as functions of temperature to define the best RH thresholds for accurately determining the mean cloud cover. For warm clouds the typical SONDE threshold exceeds 87%, while the RH thresholds for cold clouds are typically less than 80% and greater than 90% with respect to liquid and ice water, respectively. Preliminary comparisons with satellite data suggest that the relationships between cloudiness and RH and T determined here could be useful for improving the characterization of cloud vertical structure from satellite data by providing information about low-level clouds that were obscured by high-level clouds viewed by the satellite. The results have potential for improving computations of atmospheric heating rate profiles and estimates of aircraft icing conditions. Similar analyses are recommended for later versions of the RUC analyses and forecasts.
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The global (50°N–50°S) distribution of stratospheric column ozone (SCO) is derived using solar backscattered ultraviolet (SBUV) profiles and compared with SCO amounts derived from Stratospheric Aerosol and Gas Experiment (SAGE)...
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The global (50°N–50°S) distribution of stratospheric column ozone (SCO) is derived using solar backscattered ultraviolet (SBUV) profiles and compared with SCO amounts derived from Stratospheric Aerosol and Gas Experiment (SAGE) and ground-based measurements. An evaluation of archived SBUV (version 6) ozone profiles with ozonesonde profiles shows that the low resolution of the SBUV instrument in the troposphere and lower stratosphere leads to a low bias in the SBUV profile in the troposphere and a high bias in the lower stratosphere in regions where anthropogenic tropospheric ozone production influences the climatology. An empirical correction applied to the SBUV profile prior to separating the stratosphere from the troposphere reduces the bias in the lower stratosphere and results in a SCO distribution in good agreement with SCO derived from SAGE ozone profiles. Because the empirical correction is most pronounced at northern middle latitudes, we compare these resultant SCO values with those measured at two northern middle latitude sites (Wallops Island and Hohenpeissenberg) using concurrent measurements from Dobson spectrophotometers and ozonesondes. Our analysis shows that the empirically corrected SCO at these sites captures the seasonal cycle of SCO as well as the seasonal cycle derived from SAGE stratospheric ozone profiles. These results have important implications for the derivation of tropospheric ozone from SBUV ozone profiles in conjunction with Total Ozone Mapping Spectrometer (TOMS) total ozone measurements using the tropospheric ozone residual (TOR) methodology.
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A simulated 30-year climate data record of net cloud radiative effect (defined as the difference between clear- and all-sky net top-of-atmosphere radiative flux) based on the first 5 years of Clouds and the Earth's Radiant Energy ...
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A simulated 30-year climate data record of net cloud radiative effect (defined as the difference between clear- and all-sky net top-of-atmosphere radiative flux) based on the first 5 years of Clouds and the Earth's Radiant Energy System (CERES) Terra measurements is created in order to investigate how gaps in the record affect our ability to constrain cloud radiative feedback. To ensure a trend estimate with an uncertainty small enough to constrain cloud radiative feedback to 25% of anthropogenic forcing in the next few decades, the absolute calibration change across the gap must be <0.3% in the shortwave (SW) region and <0.1% in the longwave (LW) region for a 1-year gap occurring in the middle of the record. Given that current calibration accuracy of CERES is 2% in the SW and 1% in the LW (at the 95% significance level), a gap of any length anywhere in the record will significantly increase the time required in order to detect a trend above natural variability because data collected prior to and after the gap cannot be combined accurately enough to ensure trend detection at the required level. To avoid gaps, at least 6 months of global or 1 year of tropical overlapping measurements between successive instruments are needed, based on overlapping CERES Terra and Aqua data.
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We derive aerosol extinction profiles from airborne and space-based lidar backscatter signals by constraining the retrieval with column aerosol optical thickness (AOT), with no need to rely on assumptions about aerosol type or lid...
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We derive aerosol extinction profiles from airborne and space-based lidar backscatter signals by constraining the retrieval with column aerosol optical thickness (AOT), with no need to rely on assumptions about aerosol type or lidar ratio. The backscatter data were acquired by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the Cloud-Aerosol Lidar and Infrared Pathfmder Satellite Observation (CALIPSO) satellite. The HSRL also simultaneously measures aerosol extinction coefficients independently using the high spectral resolution lidar technique, thereby providing an ideal data set for evaluating the retrieval. We retrieve aerosol extinction profiles from both HSRL and CALIOP attenuated backscatter data constrained with HSRL, Moderate-Resolution Imaging Spectroradiometer (MODIS), and Multiangle Imaging Spectroradiometer column AOT. The resulting profiles are compared with the aerosol extinction measured by HSRL. Retrievals are limited to cases where the column aerosol thickness is greater than 0.2 over land and 0.15 over water. In the case of large AOT, the results using the Aqua MODIS constraint over water are poorer than Aqua MODIS over land or Terra MODIS. The poorer results relate to an apparent bias in Aqua MODIS AOT over water observed in August 2007. This apparent bias is still under investigation. Finally, aerosol extinction coefficients are derived from CALIPSO backscatter data using AOT from Aqua MODIS for 28 profiles over land and 9 over water. They agree with coincident measurements by the airborne HSRL to within ±0.016 km~(-1) ± 20% for at least two-thirds of land points and within ±0.028 km~(-1) ± 20% for at least two-thirds of ocean points.
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The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data processing scheme only retrieves extinction profiles in those portions of the return signal where cloud or aerosol layers have been identified by the CALIOP layer ...
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The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data processing scheme only retrieves extinction profiles in those portions of the return signal where cloud or aerosol layers have been identified by the CALIOP layer detection scheme. In this study we use 2 years of CALIOP and Moderate Resolution Imaging Spectroradiometer (MODIS) data to quantify the aerosol optical depth of undetected weakly backscattering layers. Aerosol extinction and column-averaged lidar ratio is retrieved from CALIOP level 1B (version 4) profile using MODIS aerosol optical depth (AOD) as a constraint over oceans from March 2013 to February 2015. To quantify the undetected layer AOD (ULA), an unconstrained retrieval is applied globally using a lidar ratio of 28.75 sr estimated from constrained retrievals during the daytime over the ocean. We find a global mean ULA of 0.031±0.052. There is no significant difference in ULA between land and ocean. However, the fraction of undetected aerosol layers rises considerably during daytime, when the large amount of solar background noise lowers the signal-to-noise ratio. For this reason, there is a difference in ULA between day (0.036±0.066) and night (0.025±0.021). ULA is larger in the northern hemisphere and relatively larger at high latitudes. Large ULA for the polar regions is strongly related to the cases where the CALIOP level 2 product reports zero AOD. This study provides an estimate of the complement of AOD that is not detected by lidar and bounds the CALIOP AOD uncertainty to provide corrections for science studies that employ the CALIOP level 2 AOD.
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Biological aerosols represent a diverse subset of particulate matter that is emitted directly to the atmosphere in the form of (but not limited to) bacteria, fungal spores, pollens, viruses, and plant debris. These particles can h...
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Biological aerosols represent a diverse subset of particulate matter that is emitted directly to the atmosphere in the form of (but not limited to) bacteria, fungal spores, pollens, viruses, and plant debris. These particles can have local air quality implications, but potentially play a larger climate role by acting as efficient ice nucleating particles (INPs) and cloud condensation nuclei. We have deployed a Wideband Integrated Bioaerosol Sensor on the NASA DC-8 aircraft to (1) quantify boundary layer (BL) variability of fluorescent biological aerosol particle (FBAP) concentrations in the Southeast United States (SEUS), (2) link this variability explicitly to land cover heterogeneity in the region, and (3) examine the vertical profile of bioaerosols in the context of convective vertical redistribution. Flight-averaged FBAP concentrations ranged between 0.1 and 0.43 scm~(-3) (cm~(-3) at standard temperature and pressure) with relatively homogeneous concentrations throughout the region; croplands showed the highest concentrations in the BL (0.37 scm~(-3)), and lowest concentrations were associated with evergreen forests (0.24 scm~(-3)). Observed FBAP concentrations are in generally good agreement with model parameterized emission rates for bacteria, and discrepancies are likely the result of fungal spore contributions. Shallow convection in the region is shown to be a relatively efficient lofting mechanism as the vertical transport efficiency of FBAP is at least equal to black carbon aerosol, suggesting that ground-level FBAP survives transport into the free troposphere to be available for INP activation. Comparison of the fraction of coarse-mode particles that were biological (f_(FBAP)) suggested that the SEUS (f_(FBAP) = 8.5%) was a much stronger source of bioaerosols than long-range transport during a Saharan Air Layer (SAL) dust event (f_(FBAP) = 0.17%) or summertime marine emissions in the Gulf of Mexico (f_(FBAP) = 0.73%).
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THE CLARREO VISION FROM THE NATIONAL RESEARCH COUNCIL DECADAL SURVEY. A critical issue for climate change observations is that their absolute accuracy is insufficient to confidently observe decadal climate change signals (NRC 2007...
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THE CLARREO VISION FROM THE NATIONAL RESEARCH COUNCIL DECADAL SURVEY. A critical issue for climate change observations is that their absolute accuracy is insufficient to confidently observe decadal climate change signals (NRC 2007; Trenberth et al. 2013; Trenberth and Fasullo 2010; Ohring et al. 2005; Ohring 2007). Observing decadal climate change is critical to assessing the accuracy of climate model projections (Solomon et al. 2007; Masson and Knutti 2011; Stott and Kettleborough 2002) as well as to attributing climate change to various sources (Solomon et al. 2007). Sound policymaking requires high confidence in climate predictions verified against decadal change observations with rigorously known accuracy.
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NASA's development of new concepts for the Crew Exploration Vehicle Orion presents many similar challenges to those worked in the 1960s during the Apollo programme. However, with improved modelling capabilities, new challenges ari...
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NASA's development of new concepts for the Crew Exploration Vehicle Orion presents many similar challenges to those worked in the 1960s during the Apollo programme. However, with improved modelling capabilities, new challenges arise. For example, the use of the commercial code LS-DYNA, although widely used and accepted in the technical community, often involves high-dimensional, time-consuming and computationally intensive simulations. Because of the computational cost, these tools are often used to evaluate specific conditions and are rarely used for statistical analysis. This paper discusses an approach to capture what is learned from a limited number of LS-DYNA simulations to develop models that allow users to conduct interpolation of solutions at a fraction of the computational time. In this approach, response surface models are used to predict the system time responses to a water landing as a function of capsule speed, direction, attitude, water speed and water direction. Furthermore, these models can also be used to ascertain the adequacy of the design in terms of probability measures. This paper presents a description of the LS-DYNA model, a brief summary of the response surface techniques, the analysis of variance approach used in the sensitivity studies, equations used to estimate impact parameters, results showing conditions that might cause injuries and concluding remarks.
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In this theoretical study, modulation techniques are developed to support the Active Sensing of CO_2 Emissions over Nights, Days, and Seasons (ASCENDS) mission. A continuous wave (CW) lidar system using sine waves modulated by max...
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In this theoretical study, modulation techniques are developed to support the Active Sensing of CO_2 Emissions over Nights, Days, and Seasons (ASCENDS) mission. A continuous wave (CW) lidar system using sine waves modulated by maximum length (ML) pseudo-noise (PN) codes is described for making simultaneous online/offline differential absorption measurements. Amplitude and phase-shift keying (PSK) modulated intensity modulation (IM) carriers, in addition to a hybrid-pulse technique are investigated, which exhibit optimal autocorrelation properties. A method is presented to bandwidth limit the ML sequence based on a filter implemented in terms of Jacobi theta functions, which does not significantly degrade the resolution or introduce sidelobes as a means of reducing aliasing and IM carrier bandwidth.
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