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NASA NTRS2011

Strategic Ozone Sounding Networks: Review of Design and Accomplishments

Ozone soundings are used to integrate models, satellite, aircraft and ground-based measurements for better interpretation of ozone variability, including atmospheric losses (predominantly in the stratosphere) and pollution (troposphere). A well-designed network of ozonesonde stations gives information with high vertical and horizontal resolution on a number of dynamical and chemical processes, allowing us to answer questions not possible with aircraft campaigns or current satellite technology. Strategic ozonesonde networks are discussed for high, mid- and low latitude studies. The Match sounding network was designed specifically to follow ozone depletion within the polar vortex; the standard sites are at middle to high northern hemisphere latitudes and typically operate from December through mid-March. Three mid-latitude strategic networks (the IONS series) operated over North America in July-August 2004, March-May and August 2006, and April and June-July-2008. These were designed to address questions about tropospheric ozone budgets and sources, including stratosphere-troposphere transport, and to validate satellite instruments and models. A global network focusing on processes in the equatorial zone, SHADOZ (Southern Hemisphere Additional Ozonesondes), has operated since 1998 in partnership with NOAA, NASA and the Meteorological Services of host countries. Examples of important findings from these networks are described,

Thompson, Anne M.↗

NASA NTRS2018

Radar concepts for the next generation of spaceborne observations of cloud and precipitation processes

Two decades of spaceborne cloud and precipitation radar data provided by the TRMM’s Precipitation Radar (PR) [1], CloudSat’s Cloud Profiling Radar (CPR) [2,3] and GPM’s Dual-frequency Precipitation Radar (DPR) [4] have enabled unprecedented advancements in the global mapping of occurrence and vertical structure of most types of meteorological events. After the immense success of these radars, two new spaceborne atmospheric radars, the EarthCARE Cloud Profiling Radar (CPR) [5], and the Radar in a CubeSat (RainCube) [6] have been developed and will be launched in the upcoming years, and several new radar concepts have been developed and are being considered for a variety of mission concepts. For example, spaceborne precipitation and cloud radars operating at multiple frequencies (e.g., Ku-, Ka- and W-band simultaneously) with a single antenna, and that provide scanning, polarimetric and Doppler capabilities at all frequencies; extremely compact radar architectures that enable accommodation of this category of radars in spacecrafts as small as a 6U CubeSats, as well as Doppler-capable millimeter-wave weather radars for Low Earth Orbit (LEO) or Geostationary Earth Orbit (GEO) satellites, are being defined and developed. These new instrument concepts are intended to fill the current observational gaps in the advancement of weather and climate models, and leverage on the TRMM, GPM and CloudSat experiences.

Sanchez-Barbetty, Mauricio↗

NASA NTRSDate not supplied

Polarimeter + Lidar Derived Aerosol Particle Number Concentration

In this study, we propose a simple method to derive vertically resolved aerosol particle number concentration (Na) using combined polarimetric and lidar remote sensing observations. This method relies on accurate polarimeter retrievals of the fine-mode column-averaged aerosol particle extinction cross section and accurate lidar measurements of vertically resolved aerosol particle extinction coefficient such as those provided by multiwavelength high spectral resolution lidar. We compare the resulting lidar + polarimeter vertically resolved Na product to in situ Na data collected by airborne instruments during the NASA aerosol cloud meteorology interactions over the western Atlantic experiment (ACTIVATE). Based on all 35 joint ACTIVATE flights in 2020, we find a total of 32 collocated in situ and remote sensing profiles that occur on 11 separate days, which contain a total of 322 cloud-free vertically resolved altitude bins of 150 m resolution. We demonstrate that the lidar + polarimeter Na agrees to within 106% for 90% of the 322 vertically resolved points. We also demonstrate similar agreement to within 121% for the polarimeter-derived column-averaged Na. We find that the range-normalized mean absolute deviation (NMAD) for the polarimeter-derived column-averaged Na is 21%, and the NMAD for the lidar + polarimeter-derived vertically resolved Na is 16%. Taken together, these findings suggest that the error in the polarimeter-only column-averaged Na and the lidar + polarimeter vertically resolved Na are of similar magnitude and represent a significant improvement upon current remote sensing estimates of Na.

Aerosol number concentration↗

NASA NTRS2022

Polarimeter + Lidar–Derived Aerosol Particle Number Concentration

In this study, we propose a simple method to derive vertically resolved aerosol particle number concentration (Na) using combined polarimetric and lidar remote sensing observations. This method relies on accurate polarimeter retrievals of the fine-mode column-averaged aerosol particle extinction cross section and accurate lidar measurements of vertically resolved aerosol particle extinction coefficient such as those provided by multiwavelength high spectral resolution lidar. We compare the resulting lidar + polarimeter vertically resolved N(a) product to in situ N(a) data collected by airborne instruments during the NASA aerosol cloud meteorology interactions over the western Atlantic experiment (ACTIVATE). Based on all 35 joint ACTIVATE flights in 2020, we find a total of 32 collocated in situ and remote sensing profiles that occur on 11separate days, which contain a total of 322 cloud-free vertically resolved altitude bins of 150 m resolution. We demonstrate that the lidar + polarimeter N(a) agrees to within 106% for 90% of the 322 vertically resolved points. We also demonstrate similar agreement to within 121% for the polarimeter-derived column-averaged N(a). We find that the range-normalized mean absolute deviation (NMAD) for the polarimeter-derived column-averaged Na is 21%, and the NMAD for the lidar + polarimeter-derived vertically resolved Na is 16%. Taken together, these findings suggest that the error in the polarimeter-only column-averaged N(a) and the lidar + polarimeter vertically resolved N(a) are of similar magnitude and represent a significant improvement upon current remote sensing estimates of N(a).

RSP↗

NASA NTRS1997

AMU NEXRAD Exploitation Task

This report documents the results of the Applied Meteorology Unit's NEXRAD Exploitation Task. The objectives of this task are to determine what radar signatures are present prior to and at the time of convection initiation, and to determine radar signatures which will help distinguish whether the ensuing convection will become severe. Radar data from the WSR-88D radar located at NWS Melbourne (WSR-88D/KMLB) were collected between June and September 1995, and 16 convective case studies were analyzed for which the radar was operating during the entire period of interest. All WSR-88D/KMLB products were scrutinized for their utility in detecting convection initiation and severe storm signatures. Through process of elimination, it was found that the 0.5 deg reflectivity product with the lowest reflectivity values displayed is the best product to monitor for convection initiation signatures. Seven meteorological features associated with the initiation of deep convection were identified: the Merritt Island and Indian River convergence zones, interlake convergence, horizontal convective rolls, the sea breeze, storm outflow boundaries, and fires. Their reflectivity values ranged from -5 to 20 dBZ. Of the three severe weather phenomena (winds greater than or equal to 50 kts, tornado, 3/4 inch hail), high wind events due to microbursts were most common in the data set. It was found that the values and trends of composite reflectivity, vertically integrated liquid, and core aspect ratio were key indicators of the potential of a cell to produce a microburst. The data were not analyzed for the other two severe weather phenomena because they rarely occurred during the data collection period. This report also includes suggestions for new WSR-88D products, summaries of ongoing research aimed at creating new products, and explicit recommended procedures for detecting convection initiation and severe storm signatures in the radar data using the currently available technology.

Lambert, Winifred C.↗

NASA NTRS2024

Simulated Feasibility of 3D Lightning Mapping from Space

In addition to the awe it inspires, lightning can illuminate the microphysical processes hidden away within deep convection. The current generation of space-based lightning mapping uses mostly 2D optical imaging to connect overall flash characteristics to their parent storm dynamics, but are missing a dimension’s worth of information. With lightning now classified as an essential climate variable, future spaceborne mappers will need improved capabilities to take advantage of the 3D structure of lightning flashes to support meteorological and climate modeling. We report here on a study of the feasibility of implementing a radio frequency (RF)–based network of satellites for 3D lightning mapping in high resolution from low Earth orbit (LEO). Lightning sources are simulated using existing tools of the Lightning Mapping Array (LMA), modified for orbital detection, and spatially reconstructed using a Levenberg-Marquardt geolocation algorithm to assess sources of uncertainty in these solutions. We analyze the benefits and limitations of this approach compared to existing orbital and ground-based methods. Results of this study show that lightning can be mapped in 3D with a vertical location accuracy better than 2 km using as few as five satellites in LEO capable of measuring the time-of-arrival of impulsive RF signals in the very high frequency (VHF) band. The consequence of this study is that high-resolution, spaceborne 3D mapping of lightning is achievable across most of the globe, having crucial implications for our understanding of not only lightning, but also severe weather development, climate science, and more.

CubeSpark↗

NASA NTRSDate not supplied

WMO Assessment 2022: Chapter 3 Summary

Efforts for the 2022 Scientific Assessment on Ozone Depletion published by the World Meteorological Organization are well underway. Chapter 3, titled “Update on Global Ozone: Past, Present, and Future”, presents our current understanding of global ozone outside of the polar regions and this talk summarizes some of the highlights and changes from the previous Assessment in 2018. Since the last Assessment, the longer observational records show a small, significant increase in near-global total column ozone. A small significant increase in total column ozone is also seen in the mid-latitudes of both hemispheres, but not yet the tropics. Different processes operating at different altitudes complicate the interpretation of the overall total column trend. However, a significant increase in upper stratospheric ozone noted in the previous Assessment continues, driven by declines in ozone depleting substances and increases in greenhouse gases. Model simulations support our understanding of these trends. Over the coming century, we expect an increase in global stratospheric ozone as the concentrations of ozone depleting substances decline. The future evolution for different latitudes and vertical levels depends on the future concentrations of greenhouse gases and precursors of tropospheric ozone., These other influences may lead to total ozone column levels that remain below 1980 values even after ozone depleting substance concentrations have recovered to pre-1980 levels.

Birgit Hassler↗

NASA NTRS1994

Comparison of buoy-mounted 74-kHz acoustic Doppler current profilers with vector-measuring current meters

In December 1991, the National Data Buoy Center (NDBC) deployed two meteorological buoys in the Southern California Bight on a transect between San Diego and San Clemente Island. Each buoy consisted of a 10-m discus hull instrumented to measure a suite of meteorological parameters, and, for the first time in the NDBC buoy program, acoustic Doppler current profilers (ADCPs) were included to gather hourly current profiles beneath the two buoys. Moorings instrumented with seven vector-measuring current meters (VMCMs) were deployed adjacent to the NDBC buoys for several months and provided current observations for comparison with the ADCP measurements. When wave-induced buoy motion is not overly large, the observations of horizontal current made by the ADCP and the VMCM are highly correlated. Time series of differences between ADCP and VMCM measurements are characterized by a mean difference (bias error) of about 0.01 m/s and standard deviation of about 0.035 m/s for 1-h observations. Estimates of current spectra from ADCP and VMCM records suggest that the ADCP system can be characterized by a white noise level of 2 x 10(exp -3) sq m/sq s/cph. However, when the in situ environment is such that large surface waves are present (including breaking waves and whitecaps), erroneous current values are usually reported by the ADCP. Mean values of vertical velocities reported by the ADCP appear to be much larger than what could be physically expected and are therefore deemed unreliable.

Winant, Clinton↗

NASA NTRS2023

Overview and Statistical Analysis of Boundary Layer Clouds and Precipitation Over the Western North Atlantic Ocean

Due to their fast evolution and large natural variability in macro- and microphysical properties, the accurate representation of boundary layer clouds in current climate models remains a challenge. One of the regions with large intermodel spread in the Coupled Model Intercomparison Project Phase 6 ensemble is the western North Atlantic Ocean. Here, statistically representative in situ measurements can help to develop and constrain the parameterization of clouds in global models. To this end, we performed comprehensive measurements of boundary layer clouds, aerosol, trace gases, and radiation in the western North Atlantic Ocean during the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) mission. In total, 174 research flights with 574 flight hours for cloud and precipitation measurements were performed with the HU-25 Falcon during three winter (February–March 2020, January–April 2021, and November 2021–March 2022) and three summer seasons (August–September 2020, May–June 2021, and May–June 2022). Here we present a statistical evaluation of 16 140 individual cloud events probed by the fast cloud droplet probe and the two-dimensional stereo cloud probe during 155 research flights in a representative and repetitive flight strategy allowing for robust statistical data analyses. We show that the vertical profiles of distributions of the liquid water content and the cloud droplet effective diameter (ED) increase with altitude in the marine boundary layer. Due to higher updraft speeds, higher cloud droplet number concentrations (N liquid ) were measured in winter compared to summer despite lower cloud condensation nucleus abundance. Flight cloud cover derived from statistical analysis of in situ data is reduced in summer and shows large variability. This seasonal contrast in cloud coverage is consistent with a dominance of a synoptic pattern in winter that favors conditions for the formation of stratiform clouds at the western edge of cyclones (post-cyclonic). In contrast, a dominant summer anticyclone is concomitant with the occurrence of shallow cumulus clouds and lower cloud coverage. The evaluation of boundary layer clouds and precipitation in the N liquid ED phase space sheds light on liquid, mixed-phase, and ice cloud properties and helps to categorize the cloud data. Ice and liquid precipitation, often masked in cloud statistics by a high abundance of liquid clouds, is often observed throughout the cloud. The ACTIVATE in situ cloud measurements provide a wealth of cloud information useful for assessing airborne and satellite remote-sensing products, for global climate and weather model evaluations, and for dedicated process studies that address precipitation and aerosol–cloud interactions.

Aerosol↗

NASA NTRS2004

Role of Meteorology in Flights of a Solar-Powered Airplane

In the summer of 2001, the Helios prototype solar-powered uninhabited aerial vehicle (UAV) [a lightweight, remotely piloted airplane] was deployed to the Pacific Missile Range Facility (PMRF), at Kauai, Hawaii, in an attempt to fly to altitudes above 100,000 ft (30.48 km). The goal of flying a UAV to such high altitudes has been designated a level-I milestone of the NASA Environmental Research Aircraft and Sensor Technology (ERAST) program. In support of this goal, meteorologists from NASA Dryden Flight Research Center were sent to PMRF, as part of the flight crew, to provide current and forecast weather information to the pilots, mission directors, and planners. Information of this kind is needed to optimize flight conditions for peak aircraft performance and to enable avoidance of weather conditions that could adversely affect safety. In general, the primary weather data of concern for ground and flight operations are wind speeds (see Figure 1). Because of its long wing span [247 ft (.75 m)] and low weight [1,500 to 1,600 lb (about 680 to 726 kg)], the Helios airplane is sensitive to wind speeds exceeding 7 kn (3.6 m/s) at the surface. Also, clouds are of concern because they can block sunlight needed to energize an array of solar photovoltaic cells that provide power to the airplane. Vertical wind shear is very closely monitored in order to prevent damage or loss of control due to turbulence.

Donohue, Casey↗

NASA NTRS1991

The role of global cloud climatologies in validating numerical models

Reliable estimates of the components of the surface radiation budget are important in studies of ocean-atmosphere interaction, land-atmosphere interaction, ocean circulation and in the validation of radiation schemes used in climate models. The methods currently under consideration must necessarily make certain assumptions regarding both the presence of clouds and their vertical extent. Because of the uncertainties in assumed cloudiness, all these methods involve perhaps unacceptable uncertainties. Here, a theoretical framework that avoids the explicit computation of cloud fraction and the location of cloud base in estimating the surface longwave radiation is presented. Estimates of the global surface downward fluxes and the oceanic surface net upward fluxes were made for four months (April, July, October and January) in 1985 to 1986. These estimates are based on a relationship between cloud radiative forcing at the top of the atmosphere and the surface obtained from a general circulation model. The radiation code is the version used in the UCLA/GLA general circulation model (GCM). The longwave cloud radiative forcing at the top of the atmosphere as obtained from Earth Radiation Budget Experiment (ERBE) measurements is used to compute the forcing at the surface by means of the GCM-derived relationship. This, along with clear-sky fluxes from the computations, yield maps of the downward longwave fluxes and net upward longwave fluxes at the surface. The calculated results are discussed and analyzed. The results are consistent with current meteorological knowledge and explainable on the basis of previous theoretical and observational works; therefore, it can be concluded that this method is applicable as one of the ways to obtain the surface longwave radiation fields from currently available satellite data.

HARSHVARDHAN↗

NASA NTRS2015

Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

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

Lang, Timothy J.↗

NASA NTRS2008

Sensitivity of Photolysis Frequencies and Key Tropospheric Oxidants in a Global Model to Cloud Vertical Distributions and Optical Properties

As a follow-up study to our recent assessment of the radiative effects of clouds on tropospheric chemistry, this paper presents an analysis of the sensitivity of such effects to cloud vertical distributions and optical properties in a global 3-D chemical transport model (GEOS4-Chem CTM). GEOS-Chem was driven with a series of meteorological archives (GEOS1-STRAT, GEOS-3 and GEOS-4) generated by the NASA Goddard Earth Observing System data assimilation system, which have significantly different cloud optical depths (CODs) and vertical distributions. Clouds in GEOS1-STRAT and GEOS-3 have more similar vertical distributions while those in GEOS-4 are optically much thinner in the tropical upper troposphere. We find that the radiative impact of clouds on global photolysis frequencies and hydroxyl radical (OH) is more sensitive to the vertical distribution of clouds than to the magnitude of column CODs. Model simulations with each of the three cloud distributions all show that the change in the global burden of O3 due to clouds is less than 5%. Model perturbation experiments with GEOS-3, where the magnitude of 3-D CODs are progressively varied by -100% to 100%, predict only modest changes (<5%) in global mean OH concentrations. J(O1D), J(NO2) and OH concentrations show the strongest sensitivity for small CODs and become insensitive at large CODs due to saturation effects. Caution should be exercised not to use in photochemical models a value for cloud single scattering albedo lower than about 0.999 in order to be consistent with the current knowledge of cloud absorption at the UV wavelength. Our results have important implications for model intercomparisons and climate feedback on tropospheric photochemistry.

Liu, Hongyu↗

NASA NTRS2012

The Distribution of Snow Black Carbon observed in the Arctic and Compared to the GISS-PUCCINI Model

In this study, we evaluate the ability of the latest NASA GISS composition-climate model, GISS-E2- PUCCINI, to simulate the spatial distribution of snow BC (sBC) in the Arctic relative to present-day observations. Radiative forcing due to BC deposition onto Arctic snow and sea ice is also estimated. Two sets of model simulations are analyzed, where meteorology is linearly relaxed towards National Centers for Environmental Prediction (NCEP) and towards NASA Modern Era Reanalysis for Research and Applications (MERRA) reanalyses. Results indicate that the modeled concentrations of sBC are comparable with presentday observations in and around the Arctic Ocean, except for apparent underestimation at a few sites in the Russian Arctic. That said, the model has some biases in its simulated spatial distribution of BC deposition to the Arctic. The simulations from the two model runs are roughly equal, indicating that discrepancies between model and observations come from other sources. Underestimation of biomass burning emissions in Northern Eurasia may be the main cause of the low biases in the Russian Arctic. Comparisons of modeled aerosol BC (aBC) with long-term surface observations at Barrow, Alert, Zeppelin and Nord stations show significant underestimation in winter and spring concentrations in the Arctic (most significant in Alaska), although the simulated seasonality of aBC has been greatly improved relative to earlier model versions. This is consistent with simulated biases in vertical profiles of aBC, with underestimation in the lower and middle troposphere but overestimation in the upper troposphere and lower stratosphere, suggesting that the wet removal processes in the current model may be too weak or that vertical transport is too rapid, although the simulated BC lifetime seems reasonable. The combination of observations and modeling provides a comprehensive distribution of sBC over the Arctic. On the basis of this distribution, we estimate the decrease in snow and sea ice albedo and the resulting radiative forcing. We suggest that the albedo reduction due to BC deposition presents significant space-time variations, with highest mean reductions of 1.25% in the Russian Arctic, which are much larger than those in other Arctic regions (0.39% to 0.64 %). The averaged value over the Arctic north of 66degN is 0.4-0.6% during spring, leading to regional surface radiative forcings of 0.7, 1.1 and 1.0Wm(exp−2) in spring 2007, 2008 and 2009, respectively.

Dou, T.↗

NASA NTRS2008

Simulation of Ground Winds Time Series for the NASA Crew Launch Vehicle (CLV)

Simulation of wind time series based on power spectrum density (PSD) and spectral coherence models for ground wind turbulence is described. The wind models, originally developed for the Shuttle program, are based on wind measurements at the NASA 150-m meteorological tower at Cape Canaveral, FL. The current application is for the design and/or protection of the CLV from wind effects during on-pad exposure during periods from as long as days prior to launch, to seconds or minutes just prior to launch and seconds after launch. The evaluation of vehicle response to wind will influence the design and operation of constraint systems for support of the on-pad vehicle. Longitudinal and lateral wind component time series are simulated at critical vehicle locations. The PSD model for wind turbulence is a function of mean wind speed, elevation and temporal frequency. Integration of the PSD equation over a selected frequency range yields the variance of the time series to be simulated. The square root of the PSD defines a low-pass filter that is applied to adjust the components of the Fast Fourier Transform (FFT) of Gaussian white noise. The first simulated time series near the top of the launch vehicle is the inverse transform of the adjusted FFT. Simulation of the wind component time series at the nearest adjacent location (and all other succeeding next nearest locations) is based on a model for the coherence between winds at two locations as a function of frequency and separation distance, where the adjacent locations are separated vertically and/or horizontally. The coherence function is used to calculate a coherence weighted FFT of the wind at the next nearest location, given the FFT of the simulated time series at the previous location and the essentially incoherent FFT of the wind at the selected location derived a priori from the PSD model. The simulated time series at each adjacent location is the inverse Fourier transform of the coherence weighted FFT. For a selected design case, the equations, the process and the simulated time series at multiple vehicle stations are presented.

Adelfang, Stanley I.↗

NASA NTRS1996

Parallelization and Visual Analysis of Multidimensional Fields: Application to Ozone Production, Destruction, and Transport in Three Dimensions

The three-dimensional, spectral transport model used in the current project was first successfully integrated over climatological time scales by Dr. Guang Ping Lou for the simulation of atmospheric N2O using the United Kingdom Meteorological Office (UKMO) 4-dimensional, assimilated wind and temperature data set. A non-parallel, FORTRAN version of this integration using a fairly simple N2O chemistry package containing only photo-chemical reactions was used to verify our initial parallel model results. The integrations reproduced the gross features of the observed stratospheric climatological N2O distributions but also simulated the structure of the stratospheric Antarctic vortex and its evolution. Subsequently, Dr. Thomas Kindler, who produced much of the parallel version of our model, enlarged the N2O model chemistry package to include N2O reactions involving O(D-1) and also introduced assimilated wind data from NASA as well as UKMO. Initially, transport calculations without chemistry were run using Carbon-14 as a non-reactive tracer gas with the result that large differences in the transport properties of the two assimilated wind data sets were apparent from the resultant Carbon-14 distributions. Subsequent calculations for N2O, including its chemistry, with the two input winds data sets with verification from UARS satellite observations have refined the transport differences between the two such that the model's steering capabilities could be used to infer the correct climatological vertical velocity fields required to support the N2O observations. During this process, it was also discovered that both the NASA and the UKMO data contained spurious values in some of the higher frequency wave components, leading to incorrect local transport calculations and ultimately affecting the large scale properties of the model's N2O distributions, particularly at tropical latitudes. Subsequent model runs with wind data that had been filtered to remove some of the high frequency components produced much more realistic N2O distributions. During the past few months, the UKMO wind data base for a complete two-year period was processed into spectral form for model use. This new version of the input transport data base now includes complete temperature fields as well as the necessary wind data. This was done to facilitate advanced chemical calculations in the parallel model which often depend upon temperature. Additional UKMO data is being added as it becomes available.

Schwan, Karsten↗

NASA NTRS2007

Evaluating the Capacity of Global CO2 Flux and Atmospheric Transport Models to Incorporate New Satellite Observations

As we enter the new era of satellite remote sensing for CO2 and other carbon cyclerelated quantities, advanced modeling and analysis capabilities are required to fully capitalize on the new observations. Model estimates of CO2 surface flux and atmospheric transport are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, and ultimately for future projections of carbon-climate interactions. For application to current, planned, and future remotely sensed CO2 data, it is desirable that these models are accurate and unbiased at time scales from less than daily to multi-annual and at spatial scales from several kilometers or finer to global. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 1998 through 2006. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at lxi degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-2), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to in situ observations at sites in Northern mid latitudes and the continental tropics. The influence of key process representations is inferred. We find that the model can resolve much of the hourly to synoptic variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The seasonal cycle and its interannual variations generally respond adequately, but discrepancies in the tropics suggest the need for a refinement of the soil moisture dependence of the respiration flux in CASA. Examples and inferences for interpretation of satellite data will be discussed. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in the terrestrial CO2 sink and revolutionize our understanding of the key processes controlling atmospheric CO2 and its evolution with time.

Kawa, S. R.↗

NASA NTRS2011

A Ground Validation Network for the Global Precipitation Measurement Mission

A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA's Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to "matchup" the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was −1.88 dBZ. The PR-GR bias was found to increase with the amount of PR attenuation correction applied, with the PR-GR bias reaching −3.07 dBZ in cases where the attenuation correction applied is greater than 6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%-40%.

Schwaller, Mathew R.↗