Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “weather files”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

Atmospheric and Soil Parameters in Five Urban Sites in Knoxville, Tennessee. 2024

This dataset, which contains ten csv files, reports several meteorological conditions such as temperature, wind speed, solar radiation, and net radiation measured in several urban parks in Knoxville, Tennessee, USA: Cumberland Estates Park (CEP), Socially Equal Energy Efficient Development (SEEED), West View Park (WVP), Victor Ashe Park (VAP), and West Hills Park (WHP). Also, hourly average of soil parameters such soil temperature, moisture, and matric potential measured in the five sites are included in this dataset. Air temperature, wind speed and direction, and solar radiation data were obtained from a METER ATMOS 41 All-in-One Weather Station (Pullman, Washington, USA). Soil moisture and temperature parameters were measured the METER Teros 12 probes embedded to a depth of 5 cm into the soil, while soil matric potential was measured with a METER Teros 21 probe. Incident and emitted radiation (shortwave and longwave) measurements were made using an Apogee (Logan, Utah, USA) net radiometer (Model SN-500-SS). This work is a part of a larger study which investigates the impact of soil moisture and plant evapotranspiration on ambient temperature and relative humidity in several city parks in Knoxville, Tennessee.

54 ENVIRONMENTAL SCIENCES↗

Jet Noise Reduction

The Acoustics Branch is responsible for reducing noise levels for jet and fan components on aircraft engines. To do this, data must be measured and calibrated accurately to ensure validity of test results. This noise reduction is accomplished by modifications to hardware such as jet nozzles, and by the use of other experimental hardware such as fluidic chevrons, elliptic cores, and fluidic shields. To insure validity of data calibration, a variety of software is used. This software adjusts the sound amplitude and frequency to be consistent with data taken on another day. Both the software and the hardware help make noise reduction possible. work properly. These software programs were designed to make corrections for atmosphere, shear, attenuation, electronic, and background noise. All data can be converted to a one-foot lossless condition, using the proper software corrections, making a reading independent of weather and distance. Also, data can be transformed from model scale to full scale for noise predictions of a real flight. Other programs included calculations of Over All Sound Pressure Level (OASPL), Effective Perceived Noise Level (EPNL). OASPL is the integration of sound with respect to frequency, and EPNL is weighted for a human s response to different sound frequencies and integrated with respect to time. With the proper software correction, data taken in the NATR are useful in determining ways to reduce noise. display any difference between two or more data files. Using this program and graphs of the data, the actual and predicted data can be compared. This software was tested on data collected at the Aero Acoustic Propulsion Laboratory (AAPL) using a variety of window types and overlaps. Similarly, short scripts were written to test each individual program in the software suite for verification. Each graph displays both the original points and the adjusted points connected with lines. During this summer, data points were taken during a live experiment at the AAPL to measure Nozzle Acoustic Test Rig (NATR) background noise levels. Six condenser microphones were placed in strategic locations around the dome and the inlet tunnel to measure different noise sources. From the control room the jet was monitored with the help of video cameras and other sensors. The data points were recorded, reduced, and plotted, and will be used to plan future modifications to the NATR. The primary goal to create data reduction test programs and provide verification was completed. As a result of the internship, I learned C/C++, UNIX/LINUX, Excel, and acoustic data processing methods. I also recorded data at the AAPL, then processed and plotted it. These data would be useful to compare against existing data. In addition, I adjusted software to work on the Mac OSX platform. And I used the available training resources.

Kenny, Patrick↗

Drought index using micrometeorological data from Embrapa weather station at Adolpho Ducke Reserve in Manaus, Brazil

This dataset includes daily resolution time series data including precipitation, minimum and maximum daily air temperature, and air relative humidity downloaded from the Embrapa InfoClima portal (https://www.cnpaf.embrapa.br/infoclima/), with data for the Adolpho Ducke Reserve climatological station in Manaus, Brazil, for the period of January 1, 1980 to December 31, 2016. Using this precipitation record, a Standardized Precipitation Index (SPI) was calculated and added to the dataset, using daily resolution for 180 day intervals and with 20 years for calibration (1980-1999) and adopting a gamma distribution. These data were applied as a proxy for analyzes of precipitation and SPI for the Manaus ZF2 Research station, located approximately 50 Km North of the Adolpho Ducke Reserve. Data are included in a .csv file, and the text file Drought-Indices-Embrapa-Ducke_met_spi_headers.txt provides descriptions of the data file headers.

54 ENVIRONMENTAL SCIENCES↗

What (and How) MERRA-2 Reanalysis Data are Used in Applied Sciences

The Modern Era Retrospective-analysis for Research and Applications, Version 2 (MERRA-2) is the global atmospheric data reanalysis for the satellite era produced by NASA’s Global Modeling and Assimilation Office (GMAO), using the Goddard Earth Observing System Model (GEOS)version 5.12.4. The data are officially distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 data have been widely used by the Earth sciences and application community. Since MERRA-2 data were released in early 2016, the number of registered data users has grown steadily from 1,252 in 2016 to 6477 in 2020. By the end of October 2021, ~16 petabytes (over 360 million files) of data have been distributed to more than 18,900 users. Searching in Google Scholar (https://scholar.google.com/), we have found over 7,000 articles, published between January 2017 and May 2021, involving the use ofMERRA-2 data. The figure shows the numbers for various application areas in which theMERRA-2 data have been used, covering almost all of the application areas defined in NASA Applied Sciences (http://appliedsciences.nasa.gov). The largest number of articles are found in disaster research, with the subcategories ordered in flood, wildfires, hurricanes and cyclones, and other forms of severe weather. In this presentation, we will discuss the preliminary findings from a review of the selected literature that uses MERRA-2 data in applied sciences. The current analytic and interoperable data services at GES DISC are listed, such as the on-the-fly subset and analysis service, NASA Giovanni; THREDDS Data Server(TDS); and Python Jupyter notebooks. In addition, we will introduce two new services for supporting the open sciences: My Dashboard and Related Publications.

data management↗

NASA GEOS Composition Forecast System: GEOS-CF

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution analysis and forecasts for weather, aerosols, and air quality. Since 2019, the NASA Global Earth Observing System (GEOS) model provides global near-real-time historical estimates and daily 5-day forecasts of atmospheric composition to the public at unprecedented horizontal resolution of 0.25 degrees (~25 km) from the surface up to the lower mesosphere. This composition forecast system (“GEOS-CF”) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to deliver detailed analysis of a wide range of air pollutants, including the policy-relevant species such as ozone, carbon monoxide, nitrogen oxides, sulfur dioxide and fine particulate matter (PM2.5). The GEOS-CF is a tool for scientists and the public health community. This presentation will cover 1) an overview of the GEOS-CF modeling framework compared to the GEOS-5 Nature Run with Chemistry (used in the post-processing to make the TEMPO Proxy Data), 2) description of the file used to support the TEMPO retrieval team, and 3) research and development activities as the GEOS-CF system continues to evolve to include multi-constituent data assimilation.

K. Emma Knowland↗

Clouds in ECMWF's 30 KM Resolution Global Atmospheric Forecast Model (TL639)

Global models of the general circulation of the atmosphere resolve a wide range of length scales, and in particular cloud structures extend from planetary scales to the smallest scales resolvable, now down to 30 km in state-of-the-art models. Even the highest resolution models do not resolve small-scale cloud phenomena seen, for example, in Landsat and other high-resolution satellite images of clouds. Unresolved small-scale disturbances often grow into larger ones through non-linear processes that transfer energy upscale. Understanding upscale cascades is of crucial importance in predicting current weather, and in parameterizing cloud-radiative processes that control long term climate. Several movie animations provide examples of the temporal and spatial variation of cloud fields produced in 4-day runs of the forecast model at the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, England, at particular times and locations of simultaneous measurement field campaigns. model resolution is approximately 30 km horizontally (triangular truncation TL639) with 31 vertical levels from surface to stratosphere. Timestep of the model is about 10 minutes, but animation frames are 3 hours apart, at timesteps when the radiation is computed. The animations were prepared from an archive of several 4-day runs at the highest available model resolution, and archived at ECMWF. Cloud, wind and temperature fields in an approximately 1000 km X 1000 km box were retrieved from the archive, then approximately 60 Mb Vis5d files were prepared with the help of Graeme Kelly of ECMWF, and were compressed into MPEG files each less than 3 Mb. We discuss the interaction of clouds and radiation in the model, and compare the variability of cloud liquid as a function of scale to that seen in cloud observations made in intensive field campaigns. Comparison of high-resolution global runs to cloud-resolving models, and to lower resolution climate models is leading to better understanding of the upscale cascade and suggesting new cloud-radiation parameterizations for climate models.

Cahalan, R. F.↗

BOREAS RSS-8 BIOME-BGC SSA Simulation of Annual Water and Carbon Fluxes

The BOREAS RSS-8 team performed research to evaluate the effect of seasonal weather and landcover heterogeneity on boreal forest regional water and carbon fluxes using a process-level ecosystem model, BIOME-BGC, coupled with remote sensing-derived parameter maps of key state variables. This data set contains derived maps of landcover type and crown and stem biomass as model inputs to determine annual evapotranspiration, gross primary production, autotrophic respiration, and net primary productivity within the BOREAS SSA-MSA, at a 30-m spatial resolution. Model runs were conducted over a 3-year period from 1994-1996; images are provided for each of those years. The data are stored in binary image format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

Tool for Forecasting Cool-Season Peak Winds Across Kennedy Space Center and Cape Canaveral Air Force Station

The expected peak wind speed for the day is an important element in the daily morning forecast for ground and space launch operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45th Weather Squadron (45 WS) must issue forecast advisories for KSC/CCAFS when they expect peak gusts for >= 25, >= 35, and >= 50 kt thresholds at any level from the surface to 300 ft. In Phase I of this task, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a cool-season (October - April) tool to help forecast the non-convective peak wind from the surface to 300 ft at KSC/CCAFS. During the warm season, these wind speeds are rarely exceeded except during convective winds or under the influence of tropical cyclones, for which other techniques are already in use. The tool used single and multiple linear regression equations to predict the peak wind from the morning sounding. The forecaster manually entered several observed sounding parameters into a Microsoft Excel graphical user interface (GUI), and then the tool displayed the forecast peak wind speed, average wind speed at the time of the peak wind, the timing of the peak wind and the probability the peak wind will meet or exceed 35, 50 and 60 kt. The 45 WS customers later dropped the requirement for >= 60 kt wind warnings. During Phase II of this task, the AMU expanded the period of record (POR) by six years to increase the number of observations used to create the forecast equations. A large number of possible predictors were evaluated from archived soundings, including inversion depth and strength, low-level wind shear, mixing height, temperature lapse rate and winds from the surface to 3000 ft. Each day in the POR was stratified in a number of ways, such as by low-level wind direction, synoptic weather pattern, precipitation and Bulk Richardson number. The most accurate Phase II equations were then selected for an independent verification. The Phase I and II forecast methods were compared using an independent verification data set. The two methods were compared to climatology, wind warnings and advisories issued by the 45 WS, and North American Mesoscale (NAM) model (MesoNAM) forecast winds. The performance of the Phase I and II methods were similar with respect to mean absolute error. Since the Phase I data were not stratified by precipitation, this method's peak wind forecasts had a large negative bias on days with precipitation and a small positive bias on days with no precipitation. Overall, the climatology methods performed the worst while the MesoNAM performed the best. Since the MesoNAM winds were the most accurate in the comparison, the final version of the tool was based on the MesoNAM winds. The probability the peak wind will meet or exceed the warning thresholds were based on the one standard deviation error bars from the linear regression. For example, the linear regression might forecast the most likely peak speed to be 35 kt and the error bars used to calculate that the probability of >= 25 kt = 76%, the probability of >= 35 kt = 50%, and the probability of >= 50 kt = 19%. The authors have not seen this application of linear regression error bars in any other meteorological applications. Although probability forecast tools should usually be developed with logistic regression, this technique could be easily generalized to any linear regression forecast tool to estimate the probability of exceeding any desired threshold . This could be useful for previously developed linear regression forecast tools or new forecast applications where statistical analysis software to perform logistic regression is not available. The tool was delivered in two formats - a Microsoft Excel GUI and a Tool Command Language/Tool Kit (Tcl/Tk) GUI in the Meteorological Interactive Data Display System (MIDDS). The Microsoft Excel GUI reads a MesoNAM text file containing hourly forecasts from 0 to 84 hours, from one model run (00 or 12 UTC). The GUI then displays e peak wind speed, average wind speed, and the probability the peak wind will meet or exceed the 25-, 35- and 50-kt thresholds. The user can display the Day-1 through Day-3 peak wind forecasts, and separate forecasts are made for precipitation and non-precipitation days. The MIDDS GUI uses data from the NAM and Global Forecast System (GFS), instead of the MesoNAM. It can display Day-1 and Day-2 forecasts using NAM data, and Day-1 through Day-5 forecasts using GFS data. The timing of the peak wind is not displayed, since the independent verification showed that none of the forecast methods performed significantly better than climatology. The forecaster should use the climatological timing of the peak wind (2248 UTC) as a first guess and then adjust it based on the movement of weather features.

Barrett, Joe H., III↗

Data Assimilation Cycling for Weather Analysis

This software package runs the atmospheric model MM5 in data assimilation cycling mode to produce an optimized weather analysis, including the ability to insert or adjust a hurricane vortex. The program runs MM5 through a cycle of short forecasts every three hours where the vortex is adjusted to match the observed hurricane location and storm intensity. This technique adjusts the surrounding environment so that the proper steering current and environmental shear are achieved. MM5cycle uses a Cressman analysis to blend observation into model fields to get a more accurate weather analysis. Quality control of observations is also done in every cycle to remove bad data that may contaminate the analysis. This technique can assimilate and propagate data in time from intermittent and infrequent observations while maintaining the atmospheric field in a dynamically balanced state. The software consists of a C-shell script (MM5cycle.driver) and three FORTRAN programs (splitMM5files.F, comRegrid.F, and insert_vortex.F), and are contained in the pre-processor component of MM5 called "Regridder." The model is first initialized with data from a global model such as the Global Forecast System (GFS), which also provides lateral boundary conditions. These data are separated into single-time files using splitMM5.F. The hurricane vortex is then bogussed in the correct location and with the correct wind field using insert_vortex.F. The modified initial and boundary conditions are then recombined into the model fields using comRegrid.F. The model then makes a three-hour forecast. The three-hour forecast data from MM5 now become the analysis for the next short forecast run, where the vortex will again be adjusted. The process repeats itself until the desired time of analysis is achieved. This code can also assimilate observations if desired.

Tran, Nam↗

Recovering Nimbus Era Observations at the NASA GES DISC

Between 1964 and 1978, NASA launched a series of seven Nimbus meteorological satellites which provided Earth observations for 30 years. These satellites, carrying a total of 33 instruments to observe the Earth at visible, infrared, ultraviolet, and microwave wavelengths, revolutionized weather forecasting, provided early observations of ocean color and atmospheric ozone, and prototyped location-based search and rescue capabilities. The Nimbus series paved the way for a number of currently operational systems such as the EOS (Earth Observation System) Terra, Aqua, and Aura platforms. The original data archive includes both magnetic tapes and film media. These media are well past their expected end of life, placing at risk valuable data that are critical to extending the history of Earth observations back in time. GES DISC (Goddard Earth Sciences Data and Information Services Center) has been incorporating these data into a modern online archive by recovering the digital data files from the tapes, and scanning images of the data from film strips. The digital data products were written on obsolete hardware systems in outdated file formats, and in the absence of metadata standards at that time, were often written in proprietary file structures. Through a tedious and laborious process, oft-corrupted data are recovered, and incomplete metadata and documentation are reconstructed.

data recovery↗

Data Albums: An Event Driven Search, Aggregation and Curation Tool for Earth Science

One of the largest continuing challenges in any Earth science investigation is the discovery and access of useful science content from the increasingly large volumes of Earth science data and related information available. Approaches used in Earth science research such as case study analysis and climatology studies involve gathering discovering and gathering diverse data sets and information to support the research goals. Research based on case studies involves a detailed description of specific weather events using data from different sources, to characterize physical processes in play for a specific event. Climatology-based research tends to focus on the representativeness of a given event, by studying the characteristics and distribution of a large number of events. This allows researchers to generalize characteristics such as spatio-temporal distribution, intensity, annual cycle, duration, etc. To gather relevant data and information for case studies and climatology analysis is both tedious and time consuming. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. Those who know exactly the datasets of interest can obtain the specific files they need using these systems. However, in cases where researchers are interested in studying a significant event, they have to manually assemble a variety of datasets relevant to it by searching the different distributed data systems. In these cases, a search process needs to be organized around the event rather than observing instruments. In addition, the existing data systems assume users have sufficient knowledge regarding the domain vocabulary to be able to effectively utilize their catalogs. These systems do not support new or interdisciplinary researchers who may be unfamiliar with the domain terminology. This paper presents a specialized search, aggregation and curation tool for Earth science to address these existing challenges. The search tool automatically creates curated "Data Albums", aggregated collections of information related to a specific science topic or event, containing links to relevant data files (granules) from different instruments; tools and services for visualization and analysis; and information about the event contained in news reports, images or videos to supplement research analysis. Curation in the tool is driven via an ontology based relevancy ranking algorithm to filter out non-relevant information and data.

Ramachandran, Rahul↗

Gupta-et-al_2024_EarthsFuture

Results from Gupta et al. submitted to Earth's Future. All code to reproduce the experiment and make the figures can be found here: https://github.com/rg727/Gupta-etal_2024_EarthsFuture The data provided in this repository are (1) Weather Regime Data , (2) Hydroclimate Data, and (3) CALFEWS output. In (1), there are Markov chains of daily weather regimes generated over the 600-year paleo-period. In (2), there are three sets of data: Historical daily CDEC data for 12 input locations into CALFEWS, 600-year long daily paleo data (streamflow and snow) for each input location, and (3) 600-year long daily climate-change data (4 degree temperature increase + 7% precipitation scaling applied to (2)) which serves as the "climate change scenario" in the study. Please reference the GitHub repository on how to use these data to reproduce the results. The CALFEWS output for the Paleo and Climate Change scenarios is stored in (3). More information can be found in the Gupta-et-al_2024_EarthsFuture-README file.

Gupta, Rohini↗

Software Development for SonicSonde Instrumentation Suite

The SonicSonde is an innovative weather instrumentation suite for boundary layer sampling. Software development included creating a graphical user interface (GUI) to receive, process, archive, and display data in real-time. Targeted at the Windows operating system but with multi-platform extensibility in mind, the GUI was developed using Qt 5.14 in C++. A key design consideration was to allow for tailored displays and analysis while also permitting additional sensors to be added to the platform. As such, the application relies heavily on flexible interfaces and multithreading processing for capturing, modelling, and plotting data. The object-oriented nature of Qt made it ideal for this purpose. The application supports input through live serial streams and static .csv or .dat files, custom meteorological graphs, and user-dictated panel views and output intervals. Additionally, the GUI displays real-time information about the state of the instrument. The versatility of the SonicSonde will allow meteorologists and researchers to perform or better support a variety of aeronautic and atmospheric missions.

meterology↗

RHOD Site - NOAA PSL Wind Retrievals WINDoe / Derived Data

This dataset contains daily NetCDF files with horizontal wind profiles retrieved with the WINDoe retrieval (Gebauer and Bell 2024) at Rhode Island (RHOD). WINDoe retrievals datasets are also available at Nantucket Island (NANT, nant.windoe.z01.c1) and Block Island (BLOC, bloc.windoe.z01.c1). WINDoe is an optimal estimation algorithm to retrieve wind profiles combining multiple instruments. The code is available in this github repository (https://github.com/OAR-atmospheric-observations/WINDoe/tree/main) and the retrieval is described by Gebauer and Bell (2024). WINDoe allows combining the individual datasets and outputs into one profile taking into account the information and uncertainties of each dataset. The use of WINDoe minimizes data gaps and maximizes data availability, compared to using wind profiles from only one of the instruments. The regular height grid eases comparisons to numerical weather prediction models. Code modifications have been made that include reading in WFIP3 specific instruments, averaging Doppler lidar radial velocities at various azimuth angles to avoid overfitting, and allowing the user to define a height grid by the user in the vipfile. The instruments used as input to the retrieval are a radar wind profiler (low- and high resolution mode) providing data in and above the boundary layer, a scanning Doppler lidar usually providing data throughout the boundary layer, a profiling lidar providing data from 50 to 200 m at BLOC and NANT, and from 10 to 280 m at Rhode Island, and a surface tower (4 m at NANT and RHOD and 10 m at BLOC). From the scanning lidars, we used radial velocity measurements at 60 deg elevation angle at six different azimuth angles with a resolution of approximately 30 m along the line of sight and the lowest range gate at approximately 70 m. The wind profiles are retrieved with WINDoe up to 3.74 km with 10 m vertical resolution. The profiles are retrieved every 15 min at BLOC and NANT and every 60 min at RHOD.

17 WIND ENERGY↗

BLOC Site - NOAA PSL Wind Retrievals WINDoe / Derived Data

This dataset contains daily netcdf files with horizontal wind profiles retrieved with the WINDoe retrieval (Gebauer and Bell 2024) at Block Island (BLOC). WINDoe retrievals datasets are also available at Nantucket Island (NANT, nant.windoe.z01.c1) and Rhode Island (RHOD, rhod.windoe.z01.c1). WINDoe is an optimal estimation algorithm to retrieve wind profiles combining multiple instruments. The code is available in this github repository (https://github.com/OAR-atmospheric-observations/WINDoe/tree/main), and the retrieval is described by Gebauer and Bell (2024). WINDoe allows combining the individual datasets and outputs into one profile taking into account the information and uncertainties of each dataset. The use of WINDoe minimizes data gaps and maximizes data availability, compared to using wind profiles from only one of the instruments. The regular height grid eases comparisons to numerical weather prediction models. Code modifications have been made that include reading in WFIP3 specific instruments, averaging Doppler lidar radial velocities at various azimuth angles to avoid overfitting, and allowing the user to define a height grid by the user in the vipfile. The instruments used as input to the retrieval are a radar wind profiler (low- and high resolution mode) providing data in and above the boundary layer, a scanning Doppler lidar usually providing data throughout the boundary layer, a profiling lidar providing data from 50 to 200 m at BLOC and NANT, and from 10 to 280 m at Rhode Island, and a surface tower (4 m at NANT and RHOD and 10 m at BLOC). From the scanning lidars, we used radial velocity measurements at 60 deg elevation angle at six different azimuth angles with a resolution of approximately 30 m along the line of sight and the lowest range gate at approximately 70 m. The wind profiles are retrieved with WINDoe up to 3.74 km with 10 m vertical resolution. The profiles are retrieved every 15 min at BLOC and NANT and every 60 min at RHOD.

17 WIND ENERGY↗

NANT Site - NOAA PSL Wind Retrievals WINDoe / Derived Data

This dataset contains daily NetCDF files with horizontal wind profiles retrieved with the WINDoe retrieval (Gebauer and Bell 2024) at Nantucket Island (NANT). WINDoe retrievals datasets are also available at Block Island (BLOC, bloc.windoe.z01.c1) and Rhode Island (RHOD, rhod.windoe.z01.c1). WINDoe is an optimal estimation algorithm to retrieve wind profiles combining multiple instruments. The code is available in this github repository (https://github.com/OAR-atmospheric-observations/WINDoe/tree/main), and the retrieval is described by Gebauer and Bell (2024). WINDoe allows combining the individual datasets and outputs into one profile taking into account the information and uncertainties of each dataset. The use of WINDoe minimizes data gaps and maximizes data availability, compared to using wind profiles from only one of the instruments. The regular height grid eases comparisons to numerical weather prediction models. Code modifications have been made that include reading in WFIP3 specific instruments, averaging Doppler lidar radial velocities at various azimuth angles to avoid overfitting, and allowing the user to define a height grid by the user in the vipfile. The instruments used as input to the retrieval are a radar wind profiler (low- and high resolution mode) providing data in and above the boundary layer, a scanning Doppler lidar usually providing data throughout the boundary layer, a profiling lidar providing data from 50 to 200 m at BLOC and NANT, and from 10 to 280 m at Rhode Island, and a surface tower (4 m at NANT and RHOD and 10 m at BLOC). From the scanning lidars, we used radial velocity measurements at 60 deg elevation angle at six different azimuth angles with a resolution of approximately 30 m along the line of sight and the lowest range gate at approximately 70 m. The wind profiles are retrieved with WINDoe up to 3.74 km with 10 m vertical resolution. The profiles are retrieved every 15 min at BLOC and NANT and every 60 min at RHOD.

17 WIND ENERGY↗

Raw seedling and sapling census data collected from June 2015 - April 2019 within a tropical wet forest in Puerto Rico

This data package contains data used to evaluate the effects of experimental warming (4˚C above ambient), drought, and hurricane disturbance on species richness, diversity, and composition of understory plant communities across ontogeny at the Tropical Responses to Altered Climate Experiment (TRACE) in Luquillo, Puerto Rico. The raw data in this package include a file for the species composition matrix of woody seedlings (>10 cm and <20 cm height; TRACE_composition_seedling.csv) and saplings (>20 cm height; TRACE_composition_sapling.csv) within the six TRACE plots, collected during six census dates from June 2015 to April 2019. Also included is also a file with the species names associated with the species codes found in the composition files (TRACE_species_codes.csv), and a data dictionary file describing the columns in the composition files (data_dictionary_composition_files.csv). All data files are in csv format, with the exception of the metadata which is in xml format.

54 ENVIRONMENTAL SCIENCES↗

BOREAS TE-19 Ecosystem Carbon Balance Model

The BOREAS TE-19 team developed a model called the Spruce and Moss Model (SPAM) designed to simulate the daily carbon balance of a black spruce/moss boreal forest ecosystem. It is driven by daily weather conditions, and consists of four components: (1) soil climate, (2) tree photosynthesis and respiration, (3) moss photosynthesis and respiration, and (4) litter decomposition and associated heterotrophic respiration. The model simulates tree gross and net photosynthesis, wood respiration, live root respiration, moss gross and net photosynthesis, and heterotrophic respiration (decomposition of root litter, young needle and moss litter, and humus). These values can be combined to generate predictions of total site net ecosystem exchange of carbon (NEE), total soil dark respiration (live roots + heterotrophs + live moss), spruce and moss net productivity, and net carbon accumulation in the soil. To date, simulations have been of the BOREAS NSA-OBS and SSA-OBS tower sites, from 1968-95 (except 1990-93). The files include source code and sample input and output files in ASCII format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).

Hall, Forrest G.↗