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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Terra-Populus v0.1: A Python Library for LandScan High-Definition Population Analysis and Modeling

The terra-populus library is designed for use by the LandScan HD technical team, offering a streamlined set of tools for generating and updating LandScan HD datasets from foundational building-level data, referred to as 'molecules,' provided by the building-level attribution team. This document serves as the primary technical documentation for terra-populus. Version 0.1 of the library includes the core modeling components necessary for LandScan HD production. It enables the generation of the LandScan HD Baseline dataset as well as corresponding confidence measures for the occupancy rates used. Parameters have been included for incorporating damaged building indicators and changes in population, to faciliate the creation of rapid updates for LandScan HD. Future iterations of terra-populus will introduce tools for creating a confidence index, and quantifying and propagating uncertainty, facilitating the creation of probabilistic LandScan HD outputs. This report provides an overview of the tools available in the library and the corresponding code implementations. One of the key advancements implemented in terra-populus is a redefinition of the atomic modeling unit for LandScan HD. Traditionally, the LandScan HD vector analytical framework has generated population estimates at the building sub-component (molecule) level. However, terra-populus adopts a building-level modeling approach. This shift is an operational decision aimed at aligning LandScan HD outputs with confidence measures, which are computed and validated at the building level (confidence measures are not included in this version of terra-populus, aside from those associated with the occupancy rates). Additional advancements to the LandScan HD modeling, as implemented by terra-populus, include a minimum population value parameter and an auto assignment of building floor counts. The population minimum value was implemented to prevent buildings and subsequent LandScan HD pixels that contained small values that may not rasterize in production. An 'auto' value has been included as a method for dealing with buildings lacking floor count information, where it is the average floor count of all other buildings with a residential building use type tag. The logic behind this is to remain consistent with the current logic employed for dealing with building use type null instances, where a null use type is defaulted to residential since it is the most common building type. The auto logic is intended to apply the most common building floor count of the most common type of buildings. The tools provided in terra-populus represent a significant step forward in improving the efficiency, reproducibility, and transparency of the LandScan HD modeling process. As the library evolves, it will continue to serve as a foundational resource for high-resolution population modeling.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2019

The Terra Vega Active Light Source: A First Step in a New Approach to Perform Nighttime Absolute Radiometric Calibrations and Early Results Calibrating the VIIRS DNB

A fully automated, National Institute of Standards and Technology (NIST)-traceable artificial light source called Terra Vega has been developed to radiometrically calibrate the Visible Infrared Imaging Radiometer (VIIRS) Day Night Band (DNB) working in high gain stage (HGS) mode. The Terra Vega active point source is a calibrated integrating sphere that is only a fraction in size of a VIIRS DNB pixel. As such, it can be considered analogous to a ground-based photometric reference star. Vicarious calibrations that employ active point sources are different than those that make use of traditional extended sources and can be applyed to quantify the brightness of artificial light sources. The active source is successfully fielded, and early results indicate that it can be used to augment and validate the radiometric calibration of the VIIRS DNB HGS sensor on both the Suomi National Polar-orbiting Partnership (NPP) and NOAA-20 satellites. The VIIRS DNB HGS sensor can benefit from this technology as on-board calibration is challenging and hinges on transferring low gain stage (LGS) calibration using a solar diffuser to the medium gain stage (MGS) and HGS via regions of overlap. Current vicarious calibration methods that use a lunar-illuminated extended source estimate the HGS radiometric accuracy to within 8-15%. By comparison, early results and analysis showed that Terra Vega is stable to about 1%. Under clear dark night conditions, predicted top-of-atmosphere radiance from Terra Vega ranged between 1–11% of VIIRS measured values. Terra Vega’s excellent stability opens up new opportunities to validate and develop nighttime imaging applications based on point sources.

Ryan, Robert↗
DOE OSTI2021

Albedo Measurement of the Terra Pave White Albedo Product: Cooperative Research and Development Final Report

The Terra Pave team is creating an eco-friendly, cost-effective road coating that controls dust and dirt on high-traffic roads near solar field installations to reduce the dirt cover on panels, which lowers energy output. The Terra Pave White Albedo product also has the capability to increase the amount of solar radiation reflected from the ground to the backside of bifacial PV modules, thereby increasing the amount of electricity generated. This work will quantify the amount of solar radiation reflected from the Terra Pave White albedo product by measuring its albedo, which is the ratio of the reflected radiation to the incoming radiation. Albedo is measured with two horizontal pyranometers with one ground-facing and the other sky-facing.

14 SOLAR ENERGY↗
DOE OSTI2016

TERRA: Building New Communities for Advanced Biofuels

ARPA-E’s Transportation Energy Resources from Renewable Agriculture (TERRA) program is bringing together top experts from different disciplines – agriculture, robotics and data analytics – to rethink the production of advanced biofuel crops. ARPA-E Program Director Dr. Joe Cornelius discusses the TERRA program and explains how ARPA-E’s model enables multidisciplinary collaboration among diverse communities. The video focuses on two TERRA projects—Donald Danforth Center and Purdue University—that are developing and integrating cutting-edge remote sensing platforms, complex data analytics tools and plant breeding technologies to tackle the challenge of sustainably increasing biofuel stocks.

09 BIOMASS FUELS↗
DOE OSTI2019

Evaluation of the Impact of Horizontal Grid Spacing in Terra Incognita on Coupled Mesoscale–Microscale Simulations Using the WRF Framework

Coupled mesoscale-microscale simulations are required to provide time-varying weather-dependent inflow and forcing for large-eddy simulations under general flow conditions. Such coupling necessarily spans a wide range of spatial scales (i.e., ~10 m to ~10 km). In this paper, we use simulations that involve multiple nested domains with horizontal grid spacings in the terra incognita (i.e., ≲km) that may affect simulated conditions in both the outer and inner domains. We examine the impact on simulated wind speed and turbulence associated with forcing provided by a terrain with grid spacing in the terra incognita. We perform a suite of simulations that use combinations of varying horizontal grid spacings and turbulence parameterization/modeling using the Weather Research and Forecasting (WRF) Model using a combination of planetary boundary layer (PBL) and large-eddy simulation subgrid-scale (LES-SGS) models. The results are analyzed in terms of spectral energy, turbulence kinetic energy, and proper orthogonal decomposition (POD) energy. The results show that the output from the microscale domain depends on the type of turbulence model (e.g., PBL or LES-SGS model) used for a given horizontal grid spacing but is independent of the horizontal grid spacing and turbulence modeling of the parent domain. Simulation using a single domain produced less POD energy in the first few modes compared to a coupled simulation (one-way nesting) for similar horizontal grid spacing, which highlights that coupled simulations are required to accurately pass the mesoscale features into the microscale domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Global Surface Net-Radiation at 5 km from MODIS Terra

Reliable and fine resolution estimates of surface net-radiation are required for estimating latent and sensible heat fluxes between the land surface and the atmosphere. However, currently, fine resolution estimates of net-radiation are not available and consequently it is challenging to develop multi-year estimates of evapotranspiration at scales that can capture land surface heterogeneity and are relevant for policy and decision-making. We developed and evaluated a global net-radiation product at 5 km and 8-day resolution by combining mutually consistent atmosphere and land data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra. Comparison with net-radiation measurements from 154 globally distributed sites (414 site-years) from the FLUXNET and Surface Radiation budget network (SURFRAD) showed that the net-radiation product agreed well with measurements across seasons and climate types in the extratropics (Wilmott's index ranged from 0.74 for boreal to 0.63 for Mediterranean sites). Mean absolute deviation between the MODIS and measured net-radiation ranged from 38.0 ± 1.8 W.m -2 in boreal to 72.0 ± 4.1 W.m -2 in the tropical climates. The mean bias was small and constituted only 11%, 0.7%, 8.4%, 4.2%, 13.3%, and 5.4% of the mean absolute error in daytime net-radiation in boreal, Mediterranean, temperate-continental, temperate, semi-arid, and tropical climate, respectively. To assess the accuracy of the broader spatiotemporal patterns, we upscaled error-quantified MODIS net-radiation and compared it with the net-radiation estimates from the coarse spatial (1° x 1°) but high temporal resolution gridded net-radiation product from the Clouds and Earth's Radiant Energy System (CERES). Our estimates agreed closely with the net-radiation estimates from the CERES. Difference between the two was less than 10W.m -2 in 94% of the total land area. MODIS net-radiation product will be a valuable resource for the science community studying turbulent fluxes and energy budget at the Earth's surface.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Performance of Laser-Based Electronic Devices for Structural Analysis of Amazonian Terra-Firme Forests

Tropical vegetation biomass represents a key component of the carbon stored in global forest ecosystems. Estimates of aboveground biomass commonly rely on measurements of tree size (diameter and height) and then indirectly relate, via allometric relationships and wood density, to biomass sampled from a relatively small number of harvested and weighed trees. Recently, however, novel in situ remote sensing techniques have been proposed, which may provide nondestructive alternative approaches to derive biomass estimates. Nonetheless, we still lack knowledge of the measurement uncertainties, as both the calibration and validation of estimates using different techniques and instruments requires consistent assessment of the underlying errors. To that end, we investigate different approaches estimating the tropical aboveground biomass in situ. We quantify the total and systematic errors among measurements obtained from terrestrial light detection and ranging (LiDAR), hypsometer-based trigonometry, and traditional forest inventory. We show that laser-based estimates of aboveground biomass are in good agreement (<10% measurement uncertainty) with traditional measurements. However, relative uncertainties vary among the allometric equations based on the vegetation parameters used for parameterization. We report the error metrics for measurements of tree diameter and tree height and discuss the consequences for estimated biomass. Despite methodological differences detected in this study, we conclude that laser-based electronic devices could complement conventional measurement techniques, thereby potentially improving estimates of tropical vegetation biomass.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Probing Terra Incognita of Ni–P Catalysts: Operando Explorations during Hydrogen Evolution Reaction

We have developed two Ni phosphide preparation methods allowing operando XAS surface-sensitive studies of well-defined bulk systems. For Ni K-edge XAS, a Ni 2 P phase-pure powder was sintered into a high-density pellet and polished for grazing incidence XAS. Ni sites were mildly affected by the acidic electrolyte prior to the HER, while the applied cathodic potential caused the reduction of Ni surface states beyond the states of as-prepared Ni 2 P. The computed fully H-covered Ni 2 P [0001] model describes the difference in the operando Ni K-edge GIXAS spectrum well. Upon turning the applied bias off, the Ni sites became immediately oxidized, forming NiO on the surface. Thus, the active phase during the HER is covalent Ni 0 close to that in the intermetallic phosphides, and Ni 2+ oxides formed after, and not during, the HER. For P K-edge XAS, Ni foam was phosphorized to form a thin Ni 3 P layer while preserving its high surface area. Upon immersion in the acidic electrolyte, the P sites underwent removal of P 5+ phosphates and formed new P coordination, possibly due to the adsorption of protons from the electrolyte. These new P surface states were not affected by turning the cathodic current on and off as soon as the sample was immersed in the acidic electrolyte. However, the removal of the sample from the electrochemical cell and drying in air resulted in substantial depletion and oxidation of surface P. Echoing the observed Ni site chemistry during HER, XAS and XPS suggest that the in situ active P sites are different from the oxidized P states observed under ex situ conditions.

Kong, Seongyoung [Iowa State Univ., Ames, IA (Unit↗
DOE OSTI2018

L-TERRA [SWR-15-34]

Lidar (light detection and ranging) instruments are often used in wind energy studies in place of meteorological towers, as they can collect measurements at higher heights than met towers and are more easily moved to different parts of a site. While lidars can accurately measure mean wind speeds, they frequently measure different values of turbulence intensity (TI) than would be measured by a cup anemometer on a tower. Discrepancies in TI values are caused by several factors, including instrument noise and volume averaging. The inability of lidars to accurately measure turbulence is a significant barrier to replacing met towers with lidars in the future. There is currently no accepted standard process for quantifying and removing these errors in lidar TI measurements. The Software is an error reduction algorithm for lidar-measured turbulence. The algorithm is trained using co-located lidar and meteorological tower data. Lidar-measured parameters, such as wind speed, shear, and TI, will be used to predict the difference between the lidar- and tower-measured TI. The algorithm will be disseminated as a set of computer code that can be used by lidar users and manufacturers to correct lidar TI data in real time or in post-processing.

Newman, Jennifer↗
DOE OSTI2017

An error reduction algorithm to improve lidar turbulence estimates for wind energy

Abstract. Remote-sensing devices such as lidars are currently being investigated as alternatives to cup anemometers on meteorological towers for the measurement of wind speed and direction. Although lidars can measure mean wind speeds at heights spanning an entire turbine rotor disk and can be easily moved from one location to another, they measure different values of turbulence than an instrument on a tower. Current methods for improving lidar turbulence estimates include the use of analytical turbulence models and expensive scanning lidars. While these methods provide accurate results in a research setting, they cannot be easily applied to smaller, vertically profiling lidars in locations where high-resolution sonic anemometer data are not available. Thus, there is clearly a need for a turbulence error reduction model that is simpler and more easily applicable to lidars that are used in the wind energy industry. In this work, a new turbulence error reduction algorithm for lidars is described. The Lidar Turbulence Error Reduction Algorithm, L-TERRA, can be applied using only data from a stand-alone vertically profiling lidar and requires minimal training with meteorological tower data. The basis of L-TERRA is a series of physics-based corrections that are applied to the lidar data to mitigate errors from instrument noise, volume averaging, and variance contamination. These corrections are applied in conjunction with a trained machine-learning model to improve turbulence estimates from a vertically profiling WINDCUBE v2 lidar. The lessons learned from creating the L-TERRA model for a WINDCUBE v2 lidar can also be applied to other lidar devices. L-TERRA was tested on data from two sites in the Southern Plains region of the United States. The physics-based corrections in L-TERRA brought regression line slopes much closer to 1 at both sites and significantly reduced the sensitivity of lidar turbulence errors to atmospheric stability. The accuracy of machine-learning methods in L-TERRA was highly dependent on the input variables and training dataset used, suggesting that machine learning may not be the best technique for reducing lidar turbulence intensity (TI) error. Future work will include the use of a lidar simulator to better understand how different factors affect lidar turbulence error and to determine how these errors can be reduced using information from a stand-alone lidar.

17 WIND ENERGY↗
DOE OSTI2016

Improving Lidar Turbulence Estimates for Wind Energy

Remote sensing devices (e.g., lidars) are quickly becoming a cost-effective and reliable alternative to meteorological towers for wind energy applications. Although lidars can measure mean wind speeds accurately, these devices measure different values of turbulence intensity (TI) than an instrument on a tower. In response to these issues, a lidar TI error reduction model was recently developed for commercially available lidars. The TI error model first applies physics-based corrections to the lidar measurements, then uses machine-learning techniques to further reduce errors in lidar TI estimates. The model was tested at two sites in the Southern Plains where vertically profiling lidars were collocated with meteorological towers. This presentation primarily focuses on the physics-based corrections, which include corrections for instrument noise, volume averaging, and variance contamination. As different factors affect TI under different stability conditions, the combination of physical corrections applied in L-TERRA changes depending on the atmospheric stability during each 10-minute time period. This stability-dependent version of L-TERRA performed well at both sites, reducing TI error and bringing lidar TI estimates closer to estimates from instruments on towers. However, there is still scatter evident in the lidar TI estimates, indicating that there are physics that are not being captured in the current version of L-TERRA. Two options are discussed for modeling the remainder of the TI error physics in L-TERRA: machine learning and lidar simulations. Lidar simulations appear to be a better approach, as they can help improve understanding of atmospheric effects on TI error and do not require a large training data set.

17 WIND ENERGY↗
DOE OSTI2021

Core Analysis E-Reports Produced for the Southwest Regional Partnership on Carbon Sequestration for Wells 13-10A, 13-14, and 32-8 of the Farnsworth Unit, Texas

The submission is three electronic reports (e-reports) produced by Terra Tek, a former Schlumberger company, for and under the oversight of the Southwest Regional Partnership on Carbon Sequestration (SWP). The SWP designed and implemented a coring and core analysis program in conjunction with the previous field operator Chaparral Energy, L.L.C. The main SWP contacts who oversaw the coring and core analysis program, including geologic core descriptions and sample selection for testing by the Terra Tek, are listed below in the Authors section. The three reports are for Wells 13-10A, 13-14, and 32-8 of the Farnsworth Unit, TX, a site of the SWP's CO2 storage and enhanced oil recovery project. The e-reports include many data types that are not listed in full detail here, but may include: geomechanical, geochemical, and petrophysical measurements; white light and UV core photos; spectral gamma logs on the core; and Heterogeneous Rock Analysis logs. Fracture core review reports are included for Wells 13-14 and 32-8. The three e-reports each have many subfolders with the various types of data in spreadsheets, pdfs, image files, or other formats. The main e-reports for each well are listed by the well name. The sub-folder “E-Report” for each well has a Report.html file, which, when opened, will have hyperlinks to the various data sets and information. The files in the zipped folder will need to be extracted for the Report.html files to work properly. These authors thank Joseph Hall, a geologist formerly of Chaparral Energy, L.L.C., for assistance in designing the coring program, his geologic expertise of the Farnsworth Unit, and his assistance with characterizing the core. Christopher Gillespie, of Terra Tek at the time, managed the myriad geomechanical, geochemical, and petrophysical measurements provided by Terra Tek for this project. The core from which the samples were collected for this project are housed at the Subsurface Data and Core Libraries of the New Mexico Bureau of Geology and Mineral Resources, Socorro, New Mexico, USA. Funding for this project is provided by the U.S. Department of Energy's (DOE) National Energy Technology Laboratory (NETL) through the Southwest Regional Partnership on Carbon Sequestration (SWP) under Award No. DE-FC26-05NT42591. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. These e-reports describe objective technical results and analysis. Any subjective views or opinions that might be expressed in the reports do not necessarily represent the views of the US Department of Energy or the United States Government.

Caprock↗
DOE OSTI2024

Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research

Introduction The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped. Methods To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Results Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. Discussion We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Genetics & Heredity↗
DOE OSTI2021

Radioactive Thoron 220 Rn Exhalation From Unfired Mud Building Material Into Room Air of Earthen Dwellings

Thoron ( 220 Rn), an isotope of radon with a strong α-decay energy, and its short-lived metallic progeny can pose an elevated lung cancer hazard in room air when unfired-soil derived building materials are used in earthen dwellings. Changes in moisture content and density influencing the thoron exhalation rate from earthen materials into room air were studied in the laboratory with terra rossa from a village on the Ðòng Van Karst Plateau Geopark, Viêt Nam, where ethnic minorities construct traditional dwellings with unfired terra rossa walls and floors. Our results show that the thoron exhalation rate from mud surfaces depends on (i) the content of radioactive parental nuclides in mineral components; (ii) the moisture content of mud where ~5–10 weight % water maximizes the 220 Rn exhalation rate; and (iii) the density of dry mud as primarily controlled by internal macroscopic voids, fractures, and porosity. Additional time-series of 220 Rn exhalation data from an interior mud wall of a terra rossa-built house under different seasonal and weather conditions show that the temperature is influencing thoron exhalation via the water vapor pressure deficit (VPD) in air and the associated amount of atmospheric moisture adsorbed onto indoor mud surfaces. Our data suggest that occupants of “mud house” earthen dwellings in northern Viêt Nam are exposed to an increased thoron geohazard during cooler weather, low VPD, and high relative humidity in air. Detailed studies are needed to evaluate the thoron geohazard for inhabitants of mud-built dwellings in other climates and geological terrains.

58 GEOSCIENCES↗
DOE OSTI2016

A radiation closure study of Arctic stratus cloud microphysical properties using the collocated satellite-surface data and Fu-Liou radiative transfer model

Retrievals of cloud microphysical properties based on passive satellite imagery are especially difficult over snow-covered surfaces because of the bright and cold surface. To help quantify their uncertainties, single-layered overcast liquid-phase Arctic stratus cloud microphysical properties retrieved by using the Clouds and the Earth's Radiant Energy System Edition 2 and Edition 4 (CERES Ed2 and Ed4) algorithms are compared with ground-based retrievals at the Atmospheric Radiation Measurement North Slope of Alaska (ARM NSA) site at Barrow, AK, during the period from March 2000 to December 2006. A total of 206 and 140 snow-free cases (Rsfc ≤ 0.3), and 108 and 106 snow cases (R sfc > 0.3), respectively, were selected from Terra and Aqua satellite passes over the ARM NSA site. The CERES Ed4 and Ed2 optical depth (τ) and liquid water path (LWP) retrievals from both Terra and Aqua are almost identical and have excellent agreement with ARM retrievals under snow-free and snow conditions. In order to reach a radiation closure study for both the surface and top of atmosphere (TOA) radiation budgets, the ARM precision spectral pyranometer-measured surface albedos were adjusted (63.6% and 80% of the ARM surface albedos for snow-free and snow cases, respectively) to account for the water and land components of the domain of 30 km × 30 km. Most of the radiative transfer model calculated SW↓ sfc and SW↑ TOA fluxes by using ARM and CERES cloud retrievals and the domain mean albedos as input agree with the ARM and CERES flux observations within 10 W m -2 for both snow-free and snow conditions. Sensitivity studies show that the ARM LWP and r e retrievals are less dependent on solar zenith angle (SZA), but all retrieved optical depths increase with SZA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Cloud optical and microphysical properties derived from ground-based and satellite sensors over a site in the Yangtze Delta region: CLOUD PROPERTIES IN EASTERN CHINA

Comprehensive surface - based retrievals of cloud optical and microphysical properties were made at Taihu, a highly polluted site in central Yangtze Delta region, during a research campaign from May 2008 to December 2009. C loud optical depth (COD) , effective radius (R e ) and liquid water path (LWP) were retrieved from measurements made with a suite of ground - based and space - borne instruments, including an Analytical Spectral Devices (ASD) spectroradiometer , a Multi - Filter Rotating Shadowband R adiometer (MFRSR) , a Multichannel Microwave Radiometer Profiler (MWRP), and the Moderate Resolution Imaging Spectroradiometer ( MODIS) on Terra and Aqua satellites . Retrievals from zenith radiance measurements capture better the temporal variation of cloud properties than do retrievals from hemispherical fluxes . Annual mean LWP, COD and R e are 115.8 ± 90.8 g/m 2 , 28.5 ± 19.2, and 6.9 ± 4.2 μ m . Over 90% of LWP is less than 250 g/m 2 . Most of COD (>90%) fall s between 5 and 60 and ~ 80% of R e is less than 10 μ m . Maximum ( minimum ) values of LWP and R e occur in summer ( winter ); COD is highest in winter and spring. R aining and non - raining clouds have significant difference s in LWP, COD and R e . R ainfall frequency i s best correlated with LWP, followed by COD and R e . Cloud properties retrieved from multiple ground - based instruments are also compared with those from satellite retrievals. On average, relative to surface retrievals, mean differences of satellite retrievals in cloud LWP, COD and R e were - 33.6 g/m 2 ( - 26.4%), - 5.8 ( - 31.4%), and 2.9 μ m (29.3% ) for 11 MODIS - Terra overpasses , and - 43.3 g/m 2 ( - 2 2.3 %), - 3.0 ( - 10.0 %) and - 1.3 μ m ( - 12.0 %) for 8 MODIS - Aqua 40 overpasses, respectively. These discrep ancies indicate that MODIS cloud products still suffer 41 from large uncertainties in this region

Liu, Jianjun↗
DOE OSTI2016

Mesoscale to microscale wind farm flow modeling and evaluation

The increasing size of wind turbines, with rotors already spanning more than 150 m diameter and hub heights above 100 m, requires proper modeling of the atmospheric boundary layer (ABL) from the surface to the free atmosphere. Furthermore, large wind farm arrays create their own boundary layer structure with unique physics. This poses significant challenges to traditional wind engineering models that rely on surface-layer theories and engineering wind farm models to simulate the flow in and around wind farms. However, adopting an ABL approach offers the opportunity to better integrate wind farm design tools and meteorological models. The challenge is how to build the bridge between atmospheric and wind engineering model communities and how to establish a comprehensive evaluation process that identifies relevant physical phenomena for wind energy applications with modeling and experimental requirements. A framework for model verification, validation, and uncertainty quantification is established to guide this process by a systematic evaluation of the modeling system at increasing levels of complexity. In terms of atmospheric physics, ‘building the bridge’ means developing models for the so-called ‘terra incognita,’ a term used to designate the turbulent scales that transition from mesoscale to microscale. This range of scales within atmospheric research deals with the transition from parameterized to resolved turbulence and the improvement of surface boundary-layer parameterizations. The coupling of meteorological and wind engineering flow models and the definition of a formal model evaluation methodology, is a strong area of research for the next generation of wind conditions assessment and wind farm and wind turbine design tools. Some fundamental challenges are identified in order to direct future research in this area.

17 WIND ENERGY↗