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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Convective Distribution of Tropospheric Ozone and Tracers in the Central American ITCZ Region: Evidence from Observations During TC4

During the Tropical Composition, Clouds and Climate Coupling (TC4) experiment that occurred in July and August of 2007, extensive sampling of active convection in the ITCZ region near Central America was performed from multiple aircraft and satellite sensors. As part of a sampling strategy designed to study cloud processes, the NASA ER-2, WB-57 and DC-8 flew in stacked "racetrack patterns" in convective cells. On July 24, 2007, the ER-2 and DC-8 probed an actively developing storm and the DC-8 was hit by lightning. Case studies of this flight, and of convective outflow on August 5, 2007 reveal a significant anti-correlation between ozone and condensed cloud water content. With little variability in the boundary layer and a vertical gradient, low ozone in the upper troposphere indicates convective transport. Because of the large spatial and temporal variability in surface CO and other pollutants in this region, low ozone is a better convective indicator. Lower tropospheric tracers methyl hydrogen peroxide, total organic bromine and calcium substantiate the ozone results. OMI measurements of mean upper tropospheric ozone near convection show lower ozone in convective outflow. A mass balance estimation of the amount of convective turnover below the tropical tropopause transition layer (TTL) is 50%, with an altitude of maximum convective outflow located between 10 and 11 km, 4 km below the cirrus anvil tops. It appears that convective lofting in this region of the ITCZ is either a two-stage or a rapid mixing process, because undiluted boundary layer air is never sampled in the convective outflow.

Avery, Melody↗
NASA NTRS2002

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 km or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed-shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Lin, Shian-Jiann↗
NASA NTRS2002

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 kin or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed- shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Lin, Shian-Jiann↗
NASA NTRS1993

Coupled ice-ocean variability in the Greenland Sea

A major surface feature of the Greenland Sea during winter is the frequent eastward extension of sea ice south of 75 deg N and an associated embayment to the north. These features are nominally connected with the East Greenland Current, and both the promontory) and the embayment are readily apparent on climatic ice charts. However, there are significant changes in these features on time-scales as short as a few days. Using a combination of satellite microwave images (SSM/I) of ice cover, meteorological data and in situ velocity, temperature and salinity records, we relate the ice distribution and its changes to the developing structure and circulation of the upper ocean during winter 1988-1989. Our measurements illustrate the preconditioning that leads to convective overturn, which in turn brings warmer water to the surface and results in the rapid disappearance of ice. In particular, the surface was cooled to the freezing point by early December and the salinity then increased through ice formation (about 0.016 m/d) and brine rejection. Once the vertical density gradient was sufficiently eroded, a period of high heat flux (greater than 300 W/sq m) in late January provided enough buoyancy loss to convectively mix the upper water column to at least 200 m. We estimate vertical velocities at about 3 cm/s downward during the initial sinking. The deepening of the thermocline raised surface temperatures by over 1 C resulting in nearly 1.5 x 105 km of ice-melt within two days. Average rates of ice retreat are about 2 km/d southwestward, generally consistent with a wind-driven flow. Comparison of hydrographic surveys from before and after the overturning indicate the fresh water was advected out of the area, possibly to the south and east of our moorings.

Roach, A. T.↗
NASA NTRS1997

Role of Boreal Vegetation in Controlling Ecosystem Processes and Feedbacks to Climate

In the field, dark respiration rates are greatest in cores from more northerly locations. This is due in part to greater amounts of dwarf shrub biomass in the more northerly cores, but also to differences in soil organic matter quality. Laboratory incubations of these soils under common conditions show some evidence for greater pools of available carbon in soils from more northerly tundra sites, although the most northerly site does not fit this pattern for reasons which are unclear at this time. While field measurements of cores transplanted among different vegetation types at the same location (Toolik Lake) show relatively small differences in whole ecosystem carbon flux, laboratory incubation of these same soils shows that there are large differences in soil respiration rates under common conditions. This is presumably due to differences in organic matter quality. Microenvironmental site factors (temperature, soil moisture, degree of anaerobiosis, etc.) may be responsible for evening out these differences in the field. These site factors, which differ with slope, aspect, and drainage within a given location along the latitudinal gradient, appear to exert at least as strong a control over carbon fluxes as do macroclimatic factors among sites across the latitudinal gradient. While our field measurements indicate that, in the short term, warming will tend to increase ecosystem losses Of CO2 via respiration more than they will increase plant gross assimilation, the degree to which different topographically-defined plant communities will respond is likely to vary.

Chapin, F. S., III↗
NASA NTRS2017

Deriving Global OH Abundance and Atmospheric Lifetimes for Long-Lived Gases: A Search for CH3CCl3 Alternatives

An accurate estimate of global hydroxyl radical (OH) abundance is important for projections of air quality, climate, and stratospheric ozone recovery. As the atmospheric mixing ratios of methyl chloroform (CH3CCl3) (MCF), the commonly used OH reference gas, approaches zero, it is important to find alternative approaches to infer atmospheric OH abundance and variability. The lack of global bottom-up emission inventories is the primary obstacle in choosing a MCF alternative. We illustrate that global emissions of long-lived trace gases can be inferred from their observed mixing ratio differences between the Northern Hemisphere (NH) and Southern Hemisphere (SH), given realistic estimates of their NH-SH exchange time, the emission partitioning between the two hemispheres, and the NH versus SH OH abundance ratio. Using the observed long-term trend and emissions derived from the measured hemispheric gradient, the combination of HFC-32 (CH2F2), HFC-134a (CH2FCF3, HFC-152a (CH3CHF2), and HCFC-22 (CHClF2), instead of a single gas, will be useful as a MCF alternative to infer global and hemispheric OH abundance and trace gas lifetimes. The primary assumption on which this multispecies approach relies is that the OH lifetimes can be estimated by scaling the thermal reaction rates of a reference gas at 272 K on global and hemispheric scales. Thus, the derived hemispheric and global OH estimates are forced to reconcile the observed trends and gradient for all four compounds simultaneously. However, currently, observations of these gases from the surface networks do not provide more accurate OH abundance estimate than that from MCF.

Lifetime↗
NASA NTRS2000

Sensing Clouds via Spacecraft Radio Occultation Observations

The presence of clouds dramatically alters the opacity and radiative transfer within Earth's atmosphere at both short and long wavelengths. Knowledge of cloud top and base is needed to estimate the Outgoing Long wave Radiation (OLR) to space and the net radiation at the surface from a given atmospheric profile. Satellite observations are required to provide the global perspective needed for climate. Cloud top pressure can be determined to some accuracy from spaceborne radiance measurements when cloud opacities are sufficiently large and cloud top temperatures are sufficiently low to readily them from the surface. Cloud base is particularly difficult to determine from space. The relatively small sensitivity of long wavelengths must be used to penetrate the clouds while at the same time providing sufficient sensitivity to detect the cloud base. We are studying the indirect sensitivity of radio occultation observations to clouds through their impact on the refractivity structure. The tradewind inversion is an excellent example where a very sharp refractivity structure coincides with the top of the tradewind cumulus and stratus clouds. In general, any cloud with sufficient IR opacity will have large transmissivity gradient at cloud top (base) which will result in large cooling (heating) which will create a thermal inversion at cloud top (base). Both liquid and ice clouds can reach this critical opacity. The thermal inversion and sharp change in specific humidity will cause a sharp change in the refractivity gradient which can be identified in the radio occultation results, particularly the signal amplitude. The occultations yield very accurate information on the height of such features. The heating at cloud base drives convection causing the air to follow a moist adiabat within the Cloud which further helps constrain the interpretation of the observations. The upward expansion of such opaque clouds due to convection may be an important mechanism supplying moisture into the upper troposphere. We will present simulations using high resolution radiosondes from field campaigns representing the expected signatures of such features. We will also present initial results of comparisons between GPS observations and GOES-derived cloud tops to assess the utility of this concept.

Kursinski, E. R.↗
NASA NTRS2016

Radiative Characteristics of Clouds Embedded in Smoke Derived from Airborne Multiangular Measurements

Clouds in the presence of absorbing aerosols result in their apparent darkening, observed at the top of atmosphere (TOA), which is associated with the radiative effects of aerosol absorption. Owing to the large radiative effect and potential impacts on regional climate, above-cloud aerosols have recently been characterized in multiple satellite-based studies. While satellite data are particularly useful in showing the radiative impact of above-cloud aerosols at the TOA, recent literature indicates large uncertainties in satellite retrievals of above-cloud aerosol optical depth (AOD) and single scattering albedo (SSA), which are among the most important parameters in the assessment of associated radiative effects. In this study, we analyze radiative characteristics of clouds in the presence of wildfire smoke using airborne data primarily from NASA's Cloud Absorption Radiometer, collected during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites campaign in Canada during the 2008 summer season. We found a strong positive reflectance (R) gradient in the UV-visible (VIS)-near infrared (NIR) spectrum for clouds embedded in dense smoke, as opposed to an (expected) negative gradient for cloud-free smoke and a flat spectrum for smoke-free cloud cover. Several cases of clouds embedded in thick smoke were found, when the aircraft made circular/spiral measurements, which not only allowed the complete characterization of angular distribution of smoke scattering but also provided the vertical distribution of smoke and clouds (within 0.5-5 km). Specifically, the largest darkening by smoke was found in the UV/VIS, with R(sub 0.34 microns) reducing to 0.2 (or 20%), in contrast to 0.8 at NIR wavelengths (e.g., 1.27 microns). The observed darkening is associated with large AODs (0.5-3.0) and moderately low SSA (0.85-0.93 at 0.53 microns), resulting in a significantly large instantaneous aerosol forcing efficiency of 254 +/- 47 W/sq m/τ. Our observations of smoke-cloud radiative interactions were found to be physically consistent with theoretical plane-parallel 1-D and Monte Carlo 3-D radiative transfer calculations, capturing the observed gradient across UV-VIS-NIR. Results from this study offer insights into aerosol-cloud radiative interactions and may help in better constraining satellite retrieval algorithms.

absorbing aerosols↗
NASA NTRS2020

The Evolution of Lidar Networks: A US Perspective

Atmospheric aerosols and clouds play an important role in climate by directly scattering and absorbing sunlight. Aerosol-cloud interactions modify the particle properties causing indirect effects, alter aerosol deposition and rainfall, and contribute substantially to the uncertainties in predicting climate effects. Aerosols also affect air quality and both constituents modulate boundary layer dynamics to a certain extent, in turn impacting aerosol transport and aerosol-cloud interactions. The spatiotemporal distribution of aerosol and cloud layers is thus important, and lidar remains the primary instrument for determining the vertical distribution of aerosols and thin clouds. Lidar still provides important information for opaque cloud layers by determining base heights. Combined lidar and radar data provide a comprehensive coverage of aerosol and cloud vertical distributions, and thus locations where and when they interact. Lidar data provide a means of constraining column aerosol loading observations (e.g. AOD) to vertical extents. In addition, lidar has proven effective at determining a proxy for boundary layer height by examining aerosol gradients and/or cloud base heights in lidar profiles. Polarized lidars provide additional information on particle shape, allowing estimates of cloud phase and separation of dust or smoke from sulfate and sea salt aerosols. Given the importance of lidar observations and a critical maturation in technology and retrieval techniques, several organizations began to build operational lidar networks around 2000. The European Aerosol Research Lidar Network (EARLINET) was started as a research focused network of advanced lidars across Europe. The Asian Dust Lidar Network (ADNET) was also developed as a regional network providing lidar profiles of dust and pollution across Eastern Asia. In the US, the NASA Micro Pulse Lidar Network (MPLNET) was created to provide global lidar profiling at key sites in the NASA Aerosol Robotic Network (AERONET). The Network for the Detection of Atmospheric Composition Change (NDACC) pre-dates these networks and many sites have lidar, but it is not strictly a lidar network and at the time focused less on the lower troposphere. Finally, there were already existing ceilometer networks operated by various meteorological agencies, but in particular here in the US the profile data has not been available. The ceilometer networks were used to provide only clouds base heights and estimates of PBL height. Thus, the distinguishing feature between lidar and ceilometer networks was historically the ability to actually provide profile information (in addition to differences in wavelength, and advanced retrievals such as the raman technique). As time progressed, each lidar network matured and developed more operational capabilities and data sets, coupled with viable data centers providing DAAC services and access to near-real-time (NRT) data. In 2008 under WMO guidance, the Global Atmospheric Watch (GAW) Aerosol Lidar Observation Network (GALION) was formed as a global network made up of the existing lidar networks. The goal was to share information, best practices, and develop frameworks and techniques for quality data. GALION grew to include several other regional lidar networks and this has led to a vast increase in quality lidar sites worldwide.

Welton, Ellsworth J.↗
NASA NTRS1994

Characteristics of stratosphere-troposphere exchange in a general circulation model

In this study we examine mass exchange, water vapor exchange, and the behavior of idealized tracers and parcels to diagnose Stratosphere-Troposphere Exchange (STE) in the National Center for Atmospheric Research (NCAR) General Circulation Model (GCM), the Community Climate Model (CCM2). The CCM2 correctly represents the seasonality of mass exchange across 100 hPa, but values are uniformly too strong. Water vapor, however, indicates that tropical STE is not well represented in the CCM2; even though mean tropopause temperatures are colder than observed, the lower stratosphere is too moist. Most net mass flux occurs at water vapor mixing ratios of about 4-5 parts per million by volume (ppmv), about 1 ppmv too moist. Vertical resolution has little impact on the nature of tropical STE. In midlatitudes, CCM2 more successfully represents STE, which occurs in developing baroclinic waves and stationary anticyclones. Exchange from troposphere to stratosphere does occur but only influences the lowest few kilometers of the extratropical stratosphere, even for tracers with large vertical gradients.

Mote, Philip W.↗
NASA NTRS2020

Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high‐resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED‐2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED‐2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems.

Marcos Longo↗
NASA NTRS2021

Data Assimilation of Terrestrial Water Storage Observations to Estimate Precipitation Fluxes: A Synthetic Experiment

The Gravity Recovery and Climate Experiment (GRACE) mission and its Follow-On (GRACE-FO) mission provide unprecedented observations of terrestrial water storage (TWS) dynamics at basin to continental scales. Established GRACE data assimilation techniques directly adjust the simulated water storage components to improve the estimation of groundwater, streamflow, and snow water equivalent. Such techniques artificially add/subtract water to/from prognostic variables, thus upsetting the simulated water balance. To overcome this limitation, we propose and test an alternative assimilation scheme in which precipitation fluxes are adjusted to achieve the desired changes in simulated TWS. Using a synthetic data assimilation experiment, we show that the scheme improves performance skill in precipitation estimates in general, but that it is more robust for snowfall than for rainfall, and it fails in certain regions with strong horizontal gradients in precipitation. The results demonstrate that assimilation of TWS observations can help correct (adjust) the model’s precipitation forcing and, in turn, enhance model estimates of TWS, snow mass, soil moisture, runoff, and evaporation. A key limitation of the approach is the assumption that all errors in TWS originate from errors in precipitation. Nevertheless, the proposed approach produces more consistent improvements in simulated runoff than the established GRACE data assimilation techniques.

Data Assimilation↗
NASA NTRS2024

Effects of Water on the Density and Elevation of Tesserae on Venus

While the current conditions on Venus are inhospitable, with surface temperatures of ~ 470 °C, pressures of 92 bars, and a CO 2 dominated atmosphere, early Venus may have had a more temperate climate with water on the surface. Water is not only crucial to understanding the habitability potential of Venus, but also has major implications for the tectonic regime and thermal evolution of a planet. Tesserae are believed to be the oldest exposed features on the surface of Venus and may have formed during a period with higher water content. Some of this water might have been preserved as hydrous minerals in the Venusian subsurface. The presence of these minerals has an effect on the density profiles and isostatic behaviour of the tesserae and therefore requires a more detailed investigation. Here we will present results of phase equilibria and isostasy modelling on a range of Tesserae-analogue rock compositions with varying water content and along a range of potential thermal gradients. We compare our results to anhydrous models performed previously under similar thermal regime to constrain the conditions (rock composition, thermal gradient, and water content) needed for tesserae stability.

A R Baker↗
NASA NTRS2017

Development of Multi-Sensor Global Cloud and Radiance Composites for Earth Radiation Budget Monitoring from DSCOVR

The Deep Space Climate Observatory (DSCOVR) enables analysis of the daytime Earth radiation budget via the onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). Radiance observations and cloud property retrievals from low earth orbit and geostationary satellite imagers have to be co-located with EPIC pixels to provide scene identification in order to select anisotropic directional models needed to calculate shortwave and longwave fluxes. A new algorithm is proposed for optimal merging of selected radiances and cloud properties derived from multiple satellite imagers to obtain seamless global hourly composites at 5-kilometer resolution. An aggregated rating is employed to incorporate several factors and to select the best observation at the time nearest to the EPIC measurement. Spatial accuracy is improved using inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling. The composite data are subsequently remapped into EPIC-view domain by convolving composite pixels with the EPIC point spread function (PSF) defined with a half-pixel accuracy. PSF-weighted average radiances and cloud properties are computed separately for each cloud phase. The algorithm has demonstrated contiguous global coverage for any requested time of day with a temporal lag of under 2 hours in over 95 percent of the globe.

Khlopenkov, Konstantin↗
NASA NTRS1992

Effects of weather on the retrieval of sea ice concentration and ice type from passive microwave data

Effects of wind, water vapor, and cloud liquid water on ice concentration and ice type calculated from passive microwave data are assessed through radiative transfer calculations and observations. These weather effects can cause overestimates in ice concentration and more substantial underestimates in multi-year ice percentage by decreasing polarization and by decreasing the gradient between frequencies. The effect of surface temperature and air temperature on the magnitudes of weather-related errors is small for ice concentration and substantial for multiyear ice percentage. The existing weather filter in the NASA Team Algorithm addresses only weather effects over open ocean; the additional use of local open-ocean tie points and an alternative weather correction for the marginal ice zone can further reduce errors due to weather. Ice concentrations calculated using 37 versus 18 GHz data show little difference in total ice covered area, but greater differences in intermediate concentration classes. Given the magnitude of weather-related errors in ice classification from passive microwave data, corrections for weather effects may be necessary to detect small trends in ice covered area and ice type for climate studies.

Maslanik, J. A.↗
NASA NTRS2005

Remote sensing of sea ice thickness by a combined spatial and frequency domain interferometer : formulations, instrument design & development

The thickness of Arctic sea ice plays a critical role in Earth's climate and ocean circulation. An accurate measurement of this parameter on synoptic scales at regular intervals would enable characterization of this important component for the understanding of ocean circulation and the global heat balance. Presented in this paper is a low frequency VHF interferometer technique and associated radar instrument design to measure sea ice thickness based on the use of backscatter correlation functions. The sea ice medium is represented as a multi-layered medium consisting of snow, seaice and sea water, with the interfaces between layers characterized as rough surfaces. This technique utilizes the correlation of two radar waves of different frequencies and incident and observation angles, scattered from the sea ice medium. The correlation functions relate information about the sea ice thickness. Inversion techniques such as the genetic algorithm, gradient descent, and least square methods, are used to derive sea ice thickness from the phase information related by the correlation functions.

remote sensing↗
NASA NTRS1998

Towards quantifying mesoscale flows in the troposphere using Raman lidar and Sondes

Water vapor plays an important role in the energetics of the boundary layer processes which in turn play a key role in regulating regional and global climate. It plays a primary role in Earth's hydrological cycle, in radiation balance as a direct absorber of infrared radiation, and in atmospheric circulation as a latent heat energy source, as well as in determining cloud development and atmospheric stability. Water vapor concentration, expressed as a mass mixing ratio (g kg(exp -l)), is conserved in all meteorological processes except condensation and evaporation. This property makes it an ideal choice for studying many of the atmosphere's dynamic features. Raman scattering measurements from lidar also allow retrieval of water vapor mixing ratio profiles at high temporal and vertical resolution. Raman lidars sense water vapor to altitudes not achievable with towers and surface systems, sample the atmosphere at much higher temporal resolution than radiosondes or satellites, and do not require strong vertical gradients or turbulent fluctuations in temperature that is required by acoustic sounders and radars. Analysis of highly-resolved water vapor profiles are used here to characterize two important mesoscale flows: thunderstorm outflows and a cold front passage. The data were obtained at the Atmospheric Radiation Measurement Site (CART) by the groundbased Department of Energy/Sandia National Laboratories lidar (CART Raman lidar or CARL) and Goddard Space Flight Center Scanning Raman Lidar (SRL). A detailed discussion of the SRL and CARL performance during the IOPs is given by others in this meeting.

Demoz, B.↗
NASA NTRS1985

Remote sensing of wetland parameters related to carbon cycling

Measurement of the rates of important biogeochemical fluxes on regional or global scales is vital to understanding the geochemical and climatic consequences of natural biospheric processes and of human intervention in those processes. Remote data gathering and interpretation techniques were used to examine important cycling processes taking place in wetlands over large geographic expanses. Large area estimation of vegetative biomass and productivity depends upon accurate, consistent measurements of canopy spectral reflectance and upon wide applicability of algorithms relating reflectance to biometric parameters. Results of the use of airborne multispectral scanner data to map above-ground biomass in a Delaware salt marsh are shown. The mapping uses an effective algorithm linking biomass to measured spectral reflectance and a means to correct the scanner data for large variations in the angle of observation of the canopy. The consistency of radiometric biomass algorithms for marsh grass when they are applied over large latitudinal and tidal range gradients were also examined. Results of a 1 year study of methane emissions from tidal wetlands along a salinity gradient show marked effects of temperature, season, and pore-water chemistry in mediating flux to the atmosphere.

Bartlett, David S.↗