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Significant Advances in the AIRS Science Team Version-6 Retrieval Algorithm

AIRS/AMSU is the state of the art infrared and microwave atmospheric sounding system flying aboard EOS Aqua. The Goddard DISC has analyzed AIRS/AMSU observations, covering the period September 2002 until the present, using the AIRS Science Team Version-S retrieval algorithm. These products have been used by many researchers to make significant advances in both climate and weather applications. The AIRS Science Team Version-6 Retrieval, which will become operation in mid-20l2, contains many significant theoretical and practical improvements compared to Version-5 which should further enhance the utility of AIRS products for both climate and weather applications. In particular, major changes have been made with regard to the algOrithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the retrieval procedure; 3) compute Outgoing Longwave Radiation; and 4) determine Quality Control. This paper will describe these advances found in the AIRS Version-6 retrieval algorithm and demonstrate the improvement of AIRS Version-6 products compared to those obtained using Version-5,

Susskind, Joel↗

SRT Evaluation of AIRS Version-6.02 and Version-6.02 AIRS Only (6.02 AO) Products

Version-6 contains a number of significant improvements over Version-5. This report compares Version-6 products resulting from the advances listed below to those from Version-5. 1. Improved methodology to determine skin temperature (T(sub s)) and spectral emissivity (Epsilon(sub v)). 2. Use of Neural-net start-up state. 3. Improvements which decrease the spurious negative Version-5 trend in tropospheric temperatures. 4. Improved QC methodology. Version-6 uses separate QC thresholds optimized for Data Assimilation (QC=0) and Climate applications (QC=0,1) respectively. 5. Channel-by-channel clear-column radiances R-hat(sub tau) QC flags. 6. Improved cloud parameter retrieval algorithm. 7. Improved OLR RTA. Our evaluation compared V6.02 and V6.02 AIRS Only (V6.02 AO) Quality Controlled products with those of Version-5.0. In particular we evaluated surface skin temperature T(sub s), surface spectral emissivity Epsilon(sub v), temperature profile T(p), water vapor profile q(p), OLR, OLR(sub CLR), effective cloud fraction alpha-Epsilon, and cloud cleared radiances R-hat(sub tau) . We conducted two types of evaluations. The first compared results on 7 focus days to collocated ECMWF truth. The seven focus days are: September 6, 2002; January 25, 2003; September 29, 2004; August 5, 2005; February 24, 2007; August 10, 2007; and May 30, 2010. In these evaluations, we show results for T(sub s), Epsilon(sub v), T(p), and q(p) in terms of yields, and RMS differences and biases with regard to ECMWF. We also show yield trends as well as bias trends of these quantities relative to ECMWF truth. We also show yields and accuracy of channel by channel QC d values of R-hat(sub tau) for V6.02 and V6.02 AO. Version-5 did not contain channel by channel QC d values of R-hat(sub tau). In the second type of evaluation, we compared V6.03 monthly mean Level-3 products to those of Version-5.0, for four different months: January, April, July, and October; in 3 different years 2003, 2007, and 2011. In particular, we compared V6.03 and V5.0 trends of T(p), q(p), alpha-Epsilon, OLR, and OLR(sub CLR) computed based on results for these 12 time periods

Susskind, Joel↗

Desert Dust Satellite Retrieval Intercomparison

This work provides a comparison of satellite retrievals of Saharan desert dust aerosol optical depth (AOD) during a strong dust event through March 2006. In this event, a large dust plume was transported over desert, vegetated, and ocean surfaces. The aim is to identify and understand the differences between current algorithms, and hence improve future retrieval algorithms. The satellite instruments considered are AATSR, AIRS, MERIS, MISR, MODIS, OMI, POLDER, and SEVIRI. An interesting aspect is that the different algorithms make use of different instrument characteristics to obtain retrievals over bright surfaces. These include multi-angle approaches (MISR, AATSR), polarisation measurements (POLDER), single-view approaches using solar wavelengths (OMI, MODIS), and the thermal infrared spectral region (SEVIRI, AIRS). Differences between instruments, together with the comparison of different retrieval algorithms applied to measurements from the same instrument, provide a unique insight into the performance and characteristics of the various techniques employed. As well as the intercomparison between different satellite products, the AODs have also been compared to co-located AERONET data. Despite the fact that the agreement between satellite and AERONET AODs is reasonably good for all of the datasets, there are significant differences between them when compared to each other, especially over land. These differences are partially due to differences in the algorithms, such as as20 sumptions about aerosol model and surface properties. However, in this comparison of spatially and temporally averaged data, at least as significant as these differences are sampling issues related to the actual footprint of each instrument on the heterogeneous aerosol field, cloud identification and the quality control flags of each dataset.

Carboni, E.↗

Statistical Short-Range Guidance for Peak Wind Speed Forecasts at Edwards Air Force Base, CA

The peak winds near the surface are an important forecast element for Space Shuttle landings. As defined in the Shuttle Flight Rules (FRs), there are peak wind thresholds that cannot be exceeded in order to ensure the safety of the shuttle during landing operations. The National Weather Service Spaceflight Meteorology Group (SMG) is responsible for weather forecasts for all shuttle landings. They indicate peak winds are a challenging parameter to forecast. To alleviate the difficulty in making such wind forecasts, the Applied Meteorology Unit (AMTJ) developed a personal computer based graphical user interface (GUI) for displaying peak wind climatology and probabilities of exceeding peak-wind thresholds for the Shuttle Landing Facility (SLF) at Kennedy Space Center. However, the shuttle must land at Edwards Air Force Base (EAFB) in southern California when weather conditions at Kennedy Space Center in Florida are not acceptable, so SMG forecasters requested that a similar tool be developed for EAFB. Marshall Space Flight Center (MSFC) personnel archived and performed quality control of 2-minute average and 10-minute peak wind speeds at each tower adjacent to the main runway at EAFB from 1997- 2004. They calculated wind climatologies and probabilities of average peak wind occurrence based on the average speed. The climatologies were calculated for each tower and month, and were stratified by hour, direction, and direction/hour. For the probabilities of peak wind occurrence, MSFC calculated empirical and modeled probabilities of meeting or exceeding specific 10-minute peak wind speeds using probability density functions. The AMU obtained and reformatted the data into Microsoft Excel PivotTables, which allows users to display different values with point-click-drag techniques. The GUT was then created from the PivotTables using Visual Basic for Applications code. The GUI is run through a macro within Microsoft Excel and allows forecasters to quickly display and interpret peak wind climatology and likelihoods in a fast-paced operational environment. A summary of how the peak wind climatologies and probabilities were created and an overview of the GUT will be presented.

Dreher, Joseph↗

Discovery: Under the Microscope at Kennedy Space Center

The National Aeronautics & Space Administration (NASA) is known for discovery, exploration, and advancement of knowledge. Since the days of Leeuwenhoek, microscopy has been at the forefront of discovery and knowledge. No truer is that statement than today at Kennedy Space Center (KSC), where microscopy plays a major role in contamination identification and is an integral part of failure analysis. Space exploration involves flight hardware undergoing rigorous "visually clean" inspections at every step of processing. The unknown contaminants that are discovered on these inspections can directly impact the mission by decreasing performance of sensors and scientific detectors on spacecraft and satellites, acting as micrometeorites, damaging critical sealing surfaces, and causing hazards to the crew of manned missions. This talk will discuss how microscopy has played a major role in all aspects of space port operations at KSC. Case studies will highlight years of analysis at the Materials Science Division including facility and payload contamination for the Navigation Signal Timing and Ranging Global Positioning Satellites (NA VST AR GPS) missions, quality control monitoring of monomethyl hydrazine fuel procurement for launch vehicle operations, Shuttle Solids Rocket Booster (SRB) foam processing failure analysis, and Space Shuttle Main Engine Cut-off (ECO) flight sensor anomaly analysis. What I hope to share with my fellow microscopists is some of the excitement of microscopy and how its discoveries has led to hardware processing, that has helped enable the successful launch of vehicles and space flight missions here at Kennedy Space Center.

Howard, Philip M.↗

An Analysis of Peak Wind Speed Data from Collocated Mechanical and Ultrasonic Anemometers

This study compared peak wind speeds reported by mechanical and ultrasonic anemometers at Cape Canaveral Air Force Station and Kennedy Space Center (CCAFS/KSC) on the east central coast of Florida and Vandenberg Air Force Base (VAFB) on the central coast of California. Launch Weather Officers, forecasters, and Range Safety analysts need to understand the performance of wind sensors at CCAFS/KSC and VAFB for weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The legacy CCAFS/KSC and VAFB weather tower wind instruments are being changed from propeller-and-vane (CCAFS/KSC) and cup-and-vane (VAFB) sensors to ultrasonic sensors under the Range Standardization and Automation (RSA) program. Mechanical and ultrasonic wind measuring techniques are known to cause differences in the statistics of peak wind speed as shown in previous studies. The 45th Weather Squadron (45 WS) and the 30th Weather Squadron (30 WS) requested the Applied Meteorology Unit (AMU) to compare data between the RSA ultrasonic and legacy mechanical sensors to determine if there are significant differences. Note that the instruments were sited outdoors under naturally varying conditions and that this comparison was not designed to verify either technology. Approximately 3 weeks of mechanical and ultrasonic wind data from each range from May and June 2005 were used in this study. The CCAFS/KSC data spanned the full diurnal cycle, while the VAFB data were confined to 1000-1600 local time. The sample of 1-minute data from numerous levels on five different towers on each range totaled more than 500,000 minutes of data (482,979 minutes of data after quality control). The ten towers were instrumented at several levels, ranging from 12 ft to 492 ft above ground level. The ultrasonic sensors were collocated at the same vertical levels as the mechanical sensors and typically within 15 ft horizontally of each another. Data from a total of 53 RSA ultrasonic sensors, collocated with mechanical sensors were compared. The 1- minute average wind speed/direction and the 1-second peak wind speed/direction were compared.

Short, David A.↗

Spatial Correlation and Coherence of Boundary Layer Winds Near Cape Canaveral Florida

The spatial correlation and coherence of winds over separation distances from 8.5 to 31 km based on central Florida data from November 1999 through August 2001 are presented. The winds at altitudes from 500 to 3000 m were measured using a network of five radar wind profilers. The goal was to determine the extent to which the profilers may be considered independent data sources. Quality controlled profiles were produced every 15 minutes for up to sixty gates, each representing 101 m in altitude over the range from 130 m to 6089 m. Five levels, each containing three consecutive gates, were selected for analysis. These levels covered the range from 433 to 3059 m. The results show that the profilers are independent for features having time scales of less than one hour in the winter or two hours in the summer. This does not depend significantly on height. Because the size of the network coincides with the "spectral gap" in the boundary layer, the result also does not depend on the spacing of the profilers within the network.

Merceret, Francis J.↗

The HyMeX Special Observation Period in Central Italy: Precipitation Measurements, Retrieval Techniques and Preliminary Results

The Mediterranean area concentrates the major natural risks related to the water cycle, including heavy precipitation and flash-flooding during the fall season. The capability to predict such high-impact events remains weak because of the contribution of very fine-scale processes and their non-linear interactions with the larger scale processes. These societal and science issues motivate the HyMeX (Hydrological cycle in the Mediterranean Experiment, http://www.hymex.orgl) experimental programme. HyMeX aims at a better quantification and understanding of the water cycle in the Mediterranean with emphasis on intense events. The observation strategy of HyMEX is organized in a long-term (4 years) Enhanced Observation Periods (EOP) and short-term (2 months) Special Observation Periods (SOP). HyMEX has identified 3 main Mediterranean target areas: North-West (NW), Adriatic (A) and South-East (SE). Within each target area several hydrometeorological sites for heavy rainfall and flash flooding have been set up. The hydrometeorological sire in Central Italy (CI) is interested by both western and eastern fronts coming from the Atlantic Ocean and Siberia, respectively. Orographic precipitations play an important role due to the central Apennine range, which reaches nearly 3000 m (Gran Sasso peak). Moreover, convective systems commonly develop in CI during late summer and beginning of autumn, often causing localized hailstorms with cluster organized cells. Western fronts may heavily hit the Tiber basin crossing large urban areas (Rome), whereas eastern fronts can cause flash floods along the Adriatic coastline. Two major basins are involved within Cl region: Tiber basin (1000 km long) and its tributary Aniene and the Aterno-Pescara basin (300 km long). The first HyMeX SOP1.1 was carried out from Sept. till Nov. 2012 in the NW target area The Italian SOP1.1 was coordinated by the Centre of Excellence CETEMPS, University of L'Aquila, a city located in the CI heart. The CI area was covered by a uniquely dense meteorological instrumentation thanks to a synergy between Italian institutions and NASA-GSFC. The following RADARs were operated: a Doppler single-polarization C-band radar located at Mt Midia; the Polar 55C Doppler dual-polarization C-band radar located in Rome; a Doppler C-hand polarimetric radar located at Il Monte (Abnazo); a polarimetric X-band mini-radar in L' Aquila; a polarimetric X-hand portable mini-radar in Rome; a single-polarization X-band mini-radar in Rome. DISDROMETERs were also deployed: 4 Parsivel optical disdrometers in Rome (at Sapienza, CNR-ISAC and CNR-INSEAN); 1 2D-video disdrometer in Rome; 3 Parsivels optical disdrometer respectively in L'Aquila (Abnazo), Avezzano (Abruzzo) and Pescara (Abnazo). Other INSTRUMENTS were available: 1 K-band vertically-pointing micro rain-radar (MRR), 2 Pludix X-band disdrometers, 1 VLF lightning sensor, 1 microwave radiometer at 23-31 GHz in Rome (at Sapienza); the raingauge network with more than 200 stations in Central Italy. Three overpasses in CI were also performed by the Falcon 20 aircraft equipped with the 950Hz cloud radar RASTA Analysis of the SOP1.1 main events in CI will be described by focusing on the raindrop size distribution statistics and its geographical variability. Intercomparison of rainfall estimates from disdrometers, raingauges and radars will be illustrated with the aim to provide a quality-controlled and physically consistent rainfall dataset for meteorological modeling validation and assimilation purposes.

Gatlin, Patrick↗

An Evidence Base for Human Spaceflight Risks in Wikipedia

NASA's Human Research Program (HRP) is focused on understanding and mitigating thirty two risks to crew health and performance in exploration missions beyond low Earth orbit. The HRP has developed an evidence report for each of the risks. Most evidence reports are a brief review article describing the evidence related to a specified risk, written at a level appropriate for the scientifically educated, non‐specialist reader. Each evidence report captured the current state of knowledge from both research and operations. Two limitations of the evidence reports have become apparent: 1) they are updated infrequently and 2) they do not take full advantage of the expertise available in other space agencies and in related fields of terrestrial research. Therefore, the HRP is experimenting with the use of Wikipedia articles as a repository for evidence. Wikipedia's accessibility to the international space flight community and researchers in related terrestrial fields creates the opportunity to generate a more timely and comprehensive evidence base. Initial Wikipedia articles were populated for seven risks using a subset of the information in the HRP‐approved evidence reports: Fatigue and Sleep Loss, Treating An Ill or Injured Crew Member, Radiation Carcinogenesis, Visual Impairment and Intracranial Pressure, Renal Stone Formation, Team Cohesion, and Intervertebral Disc Damage. Since the initial articles were created, there have been additions to these Wikipedia articles, including content from sources outside the HRP, and editorial changes to the pages. We will report on the nature of the contributions made after the initial articles were created, the comprehensiveness of the resulting Wikipedia articles, and the effort required to maintain quality control of the content. The Wikipedia approach will also be compared to wiki efforts that exert more traditional editorial control of content prior to posting.

Kundrot, Craig↗

Integrating a Microwave Radiometer into Radar Hardware for Simultaneous Data Collection Between the Instruments

The conventional method for integrating a radiometer into radar hardware is to share the RF front end between the instruments, and to have separate IF receivers that take data at separate times. Alternatively, the radar and radiometer could share the antenna through the use of a diplexer, but have completely independent receivers. This novel method shares the radar's RF electronics and digital receiver with the radiometer, while allowing for simultaneous operation of the radar and radiometer. Radars and radiometers, while often having near-identical RF receivers, generally have substantially different IF and baseband receivers. Operation of the two instruments simultaneously is difficult, since airborne radars will pulse at a rate of hundreds of microseconds. Radiometer integration time is typically 10s or 100s of milliseconds. The bandwidth of radar may be 1 to 25 MHz, while a radiometer will have an RF bandwidth of up to a GHz. As such, the conventional method of integrating radar and radiometer hardware is to share the highfrequency RF receiver, but to have separate IF subsystems and digitizers. To avoid corruption of the radiometer data, the radar is turned off during the radiometer dwell time. This method utilizes a modern radar digital receiver to allow simultaneous operation of a radiometer and radar with a shared RF front end and digital receiver. The radiometer signal is coupled out after the first down-conversion stage. From there, the radar transmit frequencies are heavily filtered, and the bands outside the transmit filter are amplified and passed to a detector diode. This diode produces a DC output proportional to the input power. For a conventional radiometer, this level would be digitized. By taking this DC output and mixing it with a system oscillator at 10 MHz, the signal can instead be digitized by a second channel on the radar digital receiver (which typically do not accept DC inputs), and can be down-converted to a DC level again digitally. This unintuitive step allows the digital receiver to sample both the radiometer and radar data at a rapid, synchronized data rate (greater than 1 MHz bandwidth). Once both signals are sampled by the same digital receiver, high-speed quality control can be performed on the radiometer data to allow it to take data simultaneously with the radar. The radiometer data can be blanked during radar transmit, or when the radar return is of a power level high enough to corrupt the radiometer data. Additionally, the receiver protection switches in the RF front end can double as radiometer calibration sources, the short (four-microsecond level) switching periods integrated over many seconds to estimate the radiometer offset. The major benefit of this innovation is that there is minimal impact on the radar performance due to the integration of the radiometer, and the radiometer performance is similarly minimally affected by the radar. As the radar and radiometer are able to operate simultaneously, there is no extended period of integration time loss for the radiometer (maximizing sensitivity), and the radar is able to maintain its full number of pulses (increasing sensitivity and decreasing measurement uncertainty).

McLinden, Matthew↗

A Preliminary Analysis of Precipitation Properties and Processes during NASA GPM IFloodS

The Iowa Flood Studies (IFloodS) is a NASA Global Precipitation Measurement (GPM) ground measurement campaign, which took place in eastern Iowa from May 1 to June 15, 2013. The goals of the field campaign were to collect detailed measurements of surface precipitation using ground instruments and advanced weather radars while simultaneously collecting data from satellites passing overhead. Data collected by the radars and other ground instruments, such as disdrometers and rain gauges, will be used to characterize precipitation properties throughout the vertical column, including the precipitation type (e.g., rain, graupel, hail, aggregates, ice crystals), precipitation amounts (e.g., rain rate), and the size and shape of raindrops. The impact of physical processes, such as aggregation, melting, breakup and coalescence on the measured liquid and ice precipitation properties will be investigated. These ground observations will ultimately be used to improve rainfall estimates from satellites and in particular the algorithms that interpret raw data for the upcoming GPM mission's Core Observatory satellite, which launches in 2014. The various precipitation data collected will eventually be used as input to flood forecasting models in an effort to improve capabilities and test the utility and limitations of satellite precipitation data for flood forecasting. In this preliminary study, the focus will be on analysis of NASA NPOL (S‐band, polarimetric) radar (e.g., radar reflectivity, differential reflectivity, differential phase, correlation coefficient) and NASA 2D Video Disdrometers (2DVDs) measurements. Quality control and processing of the radar and disdrometer data sets will be outlined. In analyzing preliminary cases, particular emphasis will be placed on 1) documenting the evolution of the rain drop size distribution (DSD) as a function of column melting processes and 2) assessing the impact of range on ground‐based polarimetric radar estimates of DSD properties.

Carey, Lawrence↗

Use of MODIS Cloud Top Pressure to Improve Assimilation Yields of AIRS Radiances in GSI

Improvements to global and regional numerical weather prediction have been demonstrated through assimilation of data from NASA's Atmospheric Infrared Sounder (AIRS). Current operational data assimilation systems use AIRS radiances, but impact on regional forecasts has been much smaller than for global forecasts. Previously, it has been shown that cloud top designation associated with quality control procedures within the Gridpoint Statistical Interpolation (GSI) system used operationally by a number of Joint Center for Satellite Data Assimilation (JCSDA) partners may not provide the best representation of cloud top pressure (CTP). Because this designated CTP determines which channels are cloud-free and, thus, available for assimilation, ensuring the most accurate representation of this value is imperative to obtaining the greatest impact from satellite radiances. This paper examines the assimilation of hyperspectral sounder data used in operational numerical weather prediction by comparing analysis increments and numerical forecasts generated using operational techniques with a research technique that swaps CTP from the Moderate-resolution Imaging Spectroradiometer (MODIS) for the value of CTP calculated from the radiances within GSI.

Zavodsky, Bradley↗

Assessment of Error in Aerosol Optical Depth Measured by AERONET Due to Aerosol Forward Scattering

We present an analysis of the effect of aerosol forward scattering on the accuracy of aerosol optical depth (AOD) measured by CIMEL Sun photometers. The effect is quantified in terms of AOD and solar zenith angle using radiative transfer modeling. The analysis is based on aerosol size distributions derived from multi-year climatologies of AERONET aerosol retrievals. The study shows that the modeled error is lower than AOD calibration uncertainty (0.01) for the vast majority of AERONET level 2 observations, ~99.53%. Only ~0.47% of the AERONET database corresponding mostly to dust aerosol with high AOD and low solar elevations has larger biases. We also show that observations with extreme reductions in direct solar irradiance do not contribute to level 2 AOD due to low Sun photometer digital counts below a quality control cutoff threshold.

AERONET↗

Use of MODIS Cloud Top Pressure to Improve Assimilation Yields of AIRS Radiances in GSI

Radiances from hyperspectral sounders such as the Atmospheric Infrared Sounder (AIRS) are routinely assimilated both globally and regionally in operational numerical weather prediction (NWP) systems using the Gridpoint Statistical Interpolation (GSI) data assimilation system. However, only thinned, cloud-free radiances from a 281-channel subset are used, so the overall percentage of these observations that are assimilated is somewhere on the order of 5%. Cloud checks are performed within GSI to determine which channels peak above cloud top; inaccuracies may lead to less assimilated radiances or introduction of biases from cloud-contaminated radiances.Relatively large footprint from AIRS may not optimally represent small-scale cloud features that might be better resolved by higher-resolution imagers like the Moderate Resolution Imaging Spectroradiometer (MODIS). Objective of this project is to "swap" the MODIS-derived cloud top pressure (CTP) for that designated by the AIRS-only quality control within GSI to test the hypothesis that better representation of cloud features will result in higher assimilated radiance yields and improved forecasts.

Zavodsky, Bradley↗

Radiative Forcing in the ACCMIP Historical and Future Climate Simulations

A primary goal of the Atmospheric Chemistry and Climate Model IntercomparisonProject (ACCMIP) was to characterize the short-lived drivers of preindustrial to 2100climate change in the current generation of climate models. Here we evaluate historicaland 5 future radiative forcing in the 10 ACCMIP models that included aerosols, 8 of whichalso participated in the Coupled Model Intercomparison Project phase 5 (CMIP5).The models generally reproduce present-day climatological total aerosol opticaldepth (AOD) relatively well. components to this total, however, and most appear to underestimate AOD over East10 Asia. The models generally capture 1980-2000 AOD trends fairly well, though theyunderpredict AOD increases over the YellowEastern Sea. They appear to strongly underestimate absorbing AOD, especially in East Asia, South and Southeast Asia, SouthAmerica and Southern Hemisphere Africa.We examined both the conventional direct radiative forcing at the tropopause (RF) and the forcing including rapid adjustments (adjusted forcing AF, including direct andindirect effects). The models calculated all aerosol all-sky 1850 to 2000 global meanannual average RF ranges from 0.06 to 0.49 W m(sup -2), with a mean of 0.26 W m(sup -2) and a median of 0.27 W m(sup -2. Adjusting for missing aerosol components in some modelsbrings the range to 0.12 to 0.62W m(sup -2), with a mean of 0.39W m(sup -2). Screen20ing the models based on their ability to capture spatial patterns and magnitudes ofAOD and AOD trends yields a quality-controlled mean of 0.42W m(sup -2) and range of0.33 to 0.50 W m(sup -2) (accounting for missing components). The CMIP5 subset of ACCMIPmodels spans 0.06 to 0.49W m(sup -2), suggesting some CMIP5 simulations likelyhave too little aerosol RF. A substantial, but not well quantified, contribution to histori25cal aerosol RF may come from climate feedbacks (35 to 58). The mean aerosol AF during this period is 1.12W m(sup -2) (median value 1.16W m(sup -2), range 0.72 to1.44W m(sup -2), indicating that adjustments to aerosols, which include cloud, water vaporand temperature, lead to stronger forcing than the aerosol direct RF.

Climate Models↗

Correction Technique for Raman Water Vapor Lidar Signal-Dependent Bias and Suitability for Water Wapor Trend Monitoring in the Upper Troposphere

The MOHAVE-2009 campaign brought together diverse instrumentation for measuring atmospheric water vapor. We report on the participation of the ALVICE (Atmospheric Laboratory for Validation, Interagency Collaboration and Education) mobile laboratory in the MOHAVE-2009 campaign. In appendices we also report on the performance of the corrected Vaisala RS92 radiosonde measurements during the campaign, on a new radiosonde based calibration algorithm that reduces the influence of atmospheric variability on the derived calibration constant, and on other results of the ALVICE deployment. The MOHAVE-2009 campaign permitted the Raman lidar systems participating to discover and address measurement biases in the upper troposphere and lower stratosphere. The ALVICE lidar system was found to possess a wet bias which was attributed to fluorescence of insect material that was deposited on the telescope early in the mission. Other sources of wet biases are discussed and data from other Raman lidar systems are investigated, revealing that wet biases in upper tropospheric (UT) and lower stratospheric (LS) water vapor measurements appear to be quite common in Raman lidar systems. Lower stratospheric climatology of water vapor is investigated both as a means to check for the existence of these wet biases in Raman lidar data and as a source of correction for the bias. A correction technique is derived and applied to the ALVICE lidar water vapor profiles. Good agreement is found between corrected ALVICE lidar measurments and those of RS92, frost point hygrometer and total column water. The correction is offered as a general method to both quality control Raman water vapor lidar data and to correct those data that have signal-dependent bias. The influence of the correction is shown to be small at regions in the upper troposphere where recent work indicates detection of trends in atmospheric water vapor may be most robust. The correction shown here holds promise for permitting useful upper tropospheric water vapor profiles to be consistently measured by Raman lidar within NDACC (Network for the Detection of Atmospheric Composition Change) and elsewhere, despite the prevalence of instrumental and atmospheric effects that can contaminate the very low signal to noise measurements in the UT.

MOHAVE-2009↗

Evaluation of RTM370 Polyimide Composites by Resin Film Infusion (RFI)

RTM370 imide oligomer based on 2,3,3',4'-biphenyl dianhydride (a-BPDA), 3,4'-oxydianiline (3,4'-ODA) and terminated with the 4-phenylethynylphthalic (PEPA) endcap has been shown to exhibit a low melt viscosity (10-30 poise) at 280 C with a pot-life of 1-2 h and a high cured glass-transition temperature (Tg) of 370 C. RTM370 resin has been successfully infused into fiberglass-stitched T650-35 carbon-fabric preforms (ranged from 3- to 6-mm thick) by resin film infusion (RFI). The resulting composite panels were inspected by ultrasonic C-scan and by photomicrographs before and after post-curing as a quality control. Mechanical tests such as unnotched compression (UNC), open-hole compression (OHC), and short-beam shear strength (SBS) at ambient and elevated temperatures were performed before and after isothermal aging at 288 C for 1000 h to assess high-temperature performance. Thermal cycling of RTM370 stitched composites was also conducted from -54 C to 288 C for up to 1600 cycles to evaluate the microcrack resistance of RTM370 polyimide composites fabricated by RFI.

Polyimide↗

Intercomparison of Desert Dust Optical Depth from Satellite Measurements

This work provides a comparison of satellite retrievals of Saharan desert dust aerosol optical depth (AOD) during a strong dust event through March 2006. In this event, a large dust plume was transported over desert, vegetated, and ocean surfaces. The aim is to identify the differences between current datasets. The satellite instruments considered are AATSR, AIRS, MERIS, MISR, MODIS, OMI, POLDER, and SEVIRI. An interesting aspect is that the different algorithms make use of different instrument characteristics to obtain retrievals over bright surfaces. These include multi-angle approaches (MISR, AATSR), polarisation measurements (POLDER), single-view approaches using solar wavelengths (OMI, MODIS), and the thermal infrared spectral region (SEVIRI, AIRS). Differences between instruments, together with the comparison of different retrieval algorithms applied to measurements from the same instrument, provide a unique insight into the performance and characteristics of the various techniques employed. As well as the intercomparison between different satellite products, the AODs have also been compared to co-located AERONET data. Despite the fact that the agreement between satellite and AERONET AODs is reasonably good for all of the datasets, there are significant differences between them when compared to each other, especially over land. These differences are partially due to differences in the algorithms, such as assumptions about aerosol model and surface properties. However, in this comparison of spatially and temporally averaged data, it is important to note that differences in sampling, related to the actual footprint of each instrument on the heterogeneous aerosol field, cloud identification and the quality control flags of each dataset can be an important issue.

desert dust↗