Search NASA⌕ Search

SEARCH · Search NASA

Results for “COMMUNITY ATMOSPHERE MODEL”

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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Process-Oriented Diagnostics: Principles, Practice, Community Development, and Common Standards

Process-oriented diagnostics (PODs) aim to provide feedback for model developers through model analysis based on physical hypotheses. However, the step from a diagnostic based on relationships among variables, even when hypothesis driven, to specific guidance for revising model formulation or parameterizations can be substantial. The POD may provide more information than a purely performance-based metric, but a gap between POD principles and providing actionable information for specific model revisions can remain. Furthermore, in coordinating diagnostics development, there is a trade-off between freedom for the developer, aiming to capture innovation, and near-term utility to the modeling center. Best practices that allow for the former, while conforming to specifications that aid the latter, are important for community diagnostics development that leads to tangible model improvements. Promising directions to close the gap between principles and practice include the interaction of PODs with perturbed physics experiments and with more quantitative process models as well as the inclusion of personnel from modeling centers in diagnostics development groups for immediate feedback during climate model revisions. Examples are provided, along with best-practice recommendations, based on practical experience from the NOAA Model Diagnostics Task Force (MDTF). Common standards for metrics and diagnostics that have arisen from a collaboration between the MDTF and the Department of Energy’s Coordinated Model Evaluation Capability are advocated as a means of uniting community diagnostics efforts.

58 GEOSCIENCES↗
DOE OSTI2023

Ab initio quantum scattering calculations and a new potential energy surface for the HCl( X 1Σ+)–O2(X3Σg−) system: Collision-induced line shape parameters for O2-perturbed R(0) 0–0 line in H35Cl

The remote sensing of abundance and properties of HCl—the main atmospheric reservoir of Cl atoms that directly participate in ozone depletion—is important for monitoring the partitioning of chlorine between “ozone-depleting” and “reservoir” species. Such remote studies require knowledge of the shapes of molecular resonances of HCl, which are perturbed by collisions with the molecules of the surrounding air. In this work, we report the first fully quantum calculations of collisional perturbations of the shape of a pure rotational line in H35Cl perturbed by an air-relevant molecule [as the first model system we choose the R(0) line in HCl perturbed by O2]. The calculations are performed on our new highly accurate HCl(X1Σ+)–O2(X3Σg−) potential energy surface. In addition to pressure broadening and shift, we also determine their speed dependencies and the complex Dicke parameter. This gives important input to the community discussion on the physical meaning of the complex Dicke parameter and its relevance for atmospheric spectra (previously, the complex Dicke parameter for such systems was mainly determined from phenomenological fits to experimental spectra and the physical meaning of its value in that context is questionable). We also calculate the temperature dependence of the line shape parameters and obtain agreement with the available experimental data. We estimate the total combined uncertainties of our calculations at 2% relative root-mean-square error in the simulated line shape at 296 K. This result constitutes an important step toward computational population of spectroscopic databases with accurate ab initio line shape parameters for molecular systems of terrestrial atmospheric importance.

Chemistry↗
NASA NTRS1987

Aircraft noise synthesis system: Version 4 user instructions

A modified version of the Aircraft Noise Synthesis System with improved directivity and tonal content modeling has been developed. The synthesis system is used to provide test stimuli for studies of community annoyance to aircraft flyover noise. The computer-based system generates realistic, time-varying audio simulations of aircraft flyover noise at a specified observer location on the ground. The synthesis takes into account the time-varying aircraft position relative to the observer; specified reference spectra consisting of broadband, narrowband, and pure tone components; directivity patterns; Doppler shift; atmospheric effects; and ground effects. These parameters can be specified and controlled in such a way as to generate stimuli in which certain noise characteristics such as duration or tonal content are independently varied while the remaining characteristics such as broadband content are held constant. The modified version of the system provides improved modeling of noise directivity patterns and an increased number of pure tone components. User instructions for the modified version of the synthesis system are provided.

Mccurdy, David A.↗
NASA NTRS2002

A National Program for Analysis of the Climate System

Perhaps the single greatest roadblock to fundamental advances in our understanding of climate variability and climate change is the lack of robust and unbiased long-term global observations of the climate system. Such observations are critical for the identification and diagnosis of climate variations, and provide the constraints necessary for developing and validating climate models. The first generation of reanalysis efforts, by using fixed analysis systems, eliminated the artificial climate signals that occurred in analyses generated at the operational numerical weather prediction centers. These datasets are now widely used by the scientific community in a variety of applications including atmosphere-ocean interactions, seasonal prediction, climate monitoring, the hydrological cycle, and a host of regional and other diagnostic studies. These reanalyses, however, had problems that made them sub-optimal or even unusable for some applications. Perhaps the most serious problem for climate applications was that, while the assimilation system remained fixed, changes in the observing systems did produce spurious changes in the perceived climate. The first generation reanalysis products also exposed problems with physical consistency of the products and the accurate representation of physical processes in the climate system. Examples are bias in the estimates of ocean surface fluxes, and inadequate representation of polar hydrology. In this talk, I will describe some initial plans for a national program on reananlysis. The program is envisioned to be part of an on-going activity to maintain, improve, and reprocess our record of climate observations. I will discuss various issues affecting the quality of reanalyses, with a special focus on those relevant to the ocean.

Schubert, Siegfried↗
NASA NTRS2013

Software Engineering Tools for Scientific Models

Software tools were constructed to address issues the NASA Fortran development community faces, and they were tested on real models currently in use at NASA. These proof-of-concept tools address the High-End Computing Program and the Modeling, Analysis, and Prediction Program. Two examples are the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) atmospheric model in Cell Fortran on the Cell Broadband Engine, and the Goddard Institute for Space Studies (GISS) coupled atmosphere- ocean model called ModelE, written in fixed format Fortran.

Abrams, Marc↗
NASA NTRS2017

Maturation of the Asteroid Threat Assessment Project

As described at IPPW 12 [1], NASA initiated a new research activity focused on Planetary Defense (PD) on October 1, 2014. The overarching function of the Asteroid Threat Assessment Project (ATAP) is to provide capabilities to assess impact damage of any Near-Earth Object (NEO) that could inflict on the Earth. The activity includes four interrelated efforts: Initial Conditions (at the atmospheric entry interface); Entry Modeling (energy deposition in the atmosphere); Hazards (on the surface including winds, over pressures, thermal exposures, craters, tsunami and earthquakes) and Risk (physics-based). This paper outlines progress by ATAP and highlights achievements that are complimentary to activities of interest to the International Planetary Probe community. The ATAPs work is sponsored by NASAs Planetary Defense Coordination Office (PDCO), a part of the agency's Science Mission Directorate [1] Arnold, J. O., et. al., Overview of a New NASA Activity Focused on Planetary Defense, IPPW 12 Cologne Germany, June 15-19. 2015.

Entry and Breakup↗
NASA NTRS2021

Harmonized Emissions Component (HEMCO) 3.0 as a Versatile Emissions Component for Atmospheric Models: Application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS Models

Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to re-grid, combine, overwrite, subset, and scale emissions from different inventories through a configuration file and with no change to the model source code. The configuration file also maps emissions to model species with appropriate units. HEMCO can operate in offline stand-alone mode, but more importantly it provides an online facility for models to compute emissions at runtime. HEMCO complies with the Earth System Modeling Framework (ESMF) for portability across models. We present a new version here, HEMCO 3.0, that features an improved three-layer architecture to facilitate implementation into any atmospheric model and improved capability for calculating emissions at any model resolution including multiscale and unstructured grids. The three-layer architecture of HEMCO 3.0 includes (1) the Data Input Layer that reads the configuration file and accesses the HEMCO library of emission inventories and other environmental data, (2) the HEMCO Core that computes emissions on the user-selected HEMCO grid, and (3) the Model Interface Layer that re-grids (if needed) and serves the data to the atmospheric model and also serves model data to the HEMCO Core for computing emissions dependent on model state (such as from dust or vegetation). The HEMCO Core is common to the implementation in all models, while the Data Input Layer and the Model Interface Layer are adaptable to the model environment. Default versions of the Data Input Layer and Model Interface Layer enable straightforward implementation of HEMCO in any simple model architecture, and options are available to disable features such as re-gridding that may be done by independent couplers in more complex architectures. The HEMCO library of emission inventories and algorithms is continuously enriched through user contributions so that new inventories can be immediately shared across models. HEMCO can also serve as a general data broker for models to process input data not only for emissions but for any gridded environmental datasets. We describe existing implementations of HEMCO 3.0 in (1) the GEOS-Chem “Classic” chemical transport model with shared-memory infrastructure, (2) the high-performance GEOS-Chem (GCHP) model with distributed-memory architecture, (3) the NASA GEOS Earth System Model (GEOS ESM), (4) the Weather Research and Forecasting model with GEOS-Chem (WRF-GC), (5) the Community Earth System Model Version 2 (CESM2), and (6) the NOAA Global Ensemble Forecast System – Aerosols (GEFS-Aerosols), as well as the planned implementation in the NOAA Unified Forecast System (UFS). Implementation of HEMCO in CESM2 contributes to the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA) by providing a common emissions infrastructure to support different simulations of atmospheric chemistry across scales.

Haipeng Lin↗
NASA NTRS2022

LGM Paleoclimate Constraints Inform Cloud Parameterizations and Equilibrium Climate Sensitivity in CESM2

The Community Earth System Model version 2 (CESM2) simulates a high equilibrium climate sensitivity (ECS > 5°C) and a Last Glacial Maximum (LGM) that is substantially colder than proxy temperatures. In this study, we examine the role of cloud parameterizations in simulating the LGM cooling in CESM2. Through substituting different versions of cloud schemes in the atmosphere model, we attribute the excessive LGM cooling to the new CESM2 schemes of cloud microphysics and ice nucleation. Further exploration suggests that removing an inappropriate limiter on cloud ice number (NoNimax) and decreasing the time-step size (substepping) in cloud microphysics largely eliminate the excessive LGM cooling. NoNimax produces a more physically consistent treatment of mixed-phase clouds, which leads to an increase in cloud ice content and a weaker shortwave cloud feedback over mid-to-high latitudes and the Southern Hemisphere subtropics. Microphysical substepping further weakens the shortwave cloud feedback. Based on NoNimax and microphysical substepping, we have developed a paleoclimate-calibrated CESM2 (PaleoCalibr), which simulates well the observed twentieth century warming and spatial characteristics of key cloud and climate variables. PaleoCalibr has a lower ECS (∼4°C) and a 20% weaker aerosol-cloud interaction than CESM2. PaleoCalibr represents a physically more consistent treatment of cloud microphysics than CESM2 and is a valuable tool in climate change studies, especially when a large climate forcing is involved. Our study highlights the unique value of paleoclimate constraints in informing the cloud parameterizations and ultimately the future climate projection.

equilibrium climate sensitivity↗
DOE OSTI2023

A convection-permitting dynamically downscaled dataset over the Midwestern United States

Climate change is expected to have far-reaching effects at both the global and regional scale, but local effects are difficult to determine from coarse-resolution climate studies. Dynamical downscaling can provide insight into future climate projections on local scales. Here, we present a new dynamically downscaled dataset for Indiana and the surrounding regions. Output from the Community Earth System Model (CESM) version 1 is downscaled using the Weather Research and Forecasting model (WRF). Simulations are run with a 24-hr reinitialization strategy and a 12-hr spin-up window. WRF output is bias corrected to the National Centers for Environmental Protection/National Center for Atmospheric Research 40-year Reanalysis project (NCEP) using a modified quantile mapping method. Bias-corrected 2-m air temperature and accumulated precipitation are the initial focus, with additional variables planned for future releases. Regional climate change signals agree well with larger global studies, and local fine-scaled features are visible in the resulting dataset, such as urban heat islands, frontal passages, and orographic temperature gradients. This high-resolution climate dataset could be used for down-stream applications focused on impacts across the domain, such as urban planning, energy usage, water resources, agriculture and public health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

The Mechanisms of Natural Variability and its Interaction with Anthropogenic Climate Change Final Report

The project had two main components. The first concerns estimating the climate sensitivity in the presence of forcing uncertainty and natural variability. Climate sensitivity is the increase in the average surface temperature for a given increase in greenhouse gases, for example a doubling of carbon dioxide. We have provided new, probabilistic estimates of climate sensitivity using a simple climate model an the observed warming in the 20th century, in conjunction with ideas in data assimilation and parameter estimation developed in the engineering community. The estimates combine the uncertainty in the anthropogenic aerosols with the uncertainty arising because of natural variability. The second component concerns how the atmospheric circulation itself might change with anthropogenic global warming. We have shown that GCMs robustly predict an increase in the length scale of eddies, and we have also explored the dynamical mechanisms whereby there might be a shift in the latitude of the jet stream associated with anthropogenic warming. Such shifts in the jet might cause large changes in regional climate, potentially larger than the globally-averaged signal itself. We have also shown that the tropopause robustly increases in height with global warming, and that the Hadley Cell expands, and that the expansion of the Hadley Cell is correlated with the polewards movement of the mid-latitude jet.

58 GEOSCIENCES↗
DOE OSTI2024

Bias Correcting NOAA's High-Resolution Rapid Refresh (HRRR) Wind Resource Data for Grid Integration Applications [Slides]

Many weather years of high-quality wind data are widely accepted in the grid integration community to be important for studying wind energy technical potential, energy system operations, and grid resilience. NREL makes high-quality wind and solar resource data available. NREL's Grid-Atmosphere workshop (March 2024) identified NREL National Solar Radiation Database as widely used in grid integration modeling, but there is less agreement on commonly used wind datasets. One important factor identified by ESIG's 2023 report 'Weather Dataset Needs for Planning and Analyzing Modern Power Systems' for gold standard wind data is regular updates. To address the need for regular updates, NREL's team can now process all currently available and regularly updated High-Resolution Rapid Refresh (HRRR) outputs. HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). One barrier to NREL using HRRR is systematic bias and consistency with NREL's existing wind datasets (e.g. WIND Toolkit, 'WTK') across weather years. To address this barrier, we show that the HRRR can be interpolated and bias-corrected to be consistent with NRE's existing datasets. We call the new dataset BC-HRRR (bias-corrected HRRR). As with historical datasets like the WTK, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling). BC-HRRR's (2015-present) consistency with WTK (2007-2013) allows NREL to extend internal grid integration tooling with 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. The rest of this slide deck documents the BC-HRRR processing methods, validation, and its implications for intended use.

17 WIND ENERGY↗
NASA NTRS2002

Towards a Multisensor Approach to Improve on Current TRMM Retrievals of Clouds and Precipitation

The Tropical Rainfall Measuring Mission (TRMM) was designed to measure tropical rainfall and its variation from a low inclination orbiting satellite. The TRMM payload was carefully chosen to overcome a number of limitations of past satellite observing systems. This payload is predicated on the combination of active and passive observations from the TRMM Precipitation Radar (PR) and TRMM Microwave Imager (TMI) and Visible and Infrared Scanner (VIRS). Our research over the past three years has been devoted to the challenge of developing the most effective way of combining complementary information from these sensors to provide the most consistent estimate of precipitation. We have approached this problem from three directions. The first was to carry out preliminary analysis of passive microwave and infrared data from the TMI and VIRS instruments to understand the character of clear and cloudy skies in the basis defined by polarization and brightness temperature differences. Using this information as a foundation, the properties of two retrieval algorithms were analyzed, one for retrieving ice clouds from VIRS that was developed in parallel with this project and the other for rainfall from the TMI. Finally, the knowledge gleaned from each of these studies, coupled with ancillary data from NWP models and a broadband radiative transfer model, was used to create and algorithm for synthesizing the principal components of the Earth's energy budget from the basic building blocks of the atmosphere, gases, clouds, and precipitation. Principal results from each of these areas of research and their role in the TRMM and climate communities are summarized.

Stephens, Graeme L.↗
NASA NTRS2011

Incorporating JULES into NASA's Land Information System (LIS) and Investigations of Land-Atmosphere Coupling

NASA's Land Information System (LIS; lis.gsfc.nasa.gov) is a flexible land surface modeling and data assimilation framework developed over the past decade with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. LIS features a high performance and flexible design, and operates on an ensemble of land surface models for extension over user-specified regional or global domains. The extensible interfaces of LIS allow the incorporation of new domains, land surface models (LSMs), land surface parameters, meteorological inputs, data assimilation and optimization algorithms. In addition, LIS has also been demonstrated for parameter estimation and uncertainty estimation, and has been coupled to the Weather Research and Forecasting (WRF) mesoscale model. A visiting fellowship is currently underway to implement JULES into LIS and to undertake some fundamental science on the feedbacks between the land surface and the atmosphere. An overview of the LIS system, features, and sample results will be presented in an effort to engage the community in the potential advantages of LIS-JULES for a range of applications. Ongoing efforts to develop a framework for diagnosing land-atmosphere coupling will also be presented using the suite of LSM and PBL schemes available in LIS and WRF along with observations from the U. S .. Southern Great Plains. This methodology provides a potential pathway to study factors controlling local land-atmosphere coupling (LoCo) using the LIS-WRF system, which will serve as a testbed for future experiments to evaluate coupling diagnostics within the community.

Santanello, Joseph↗
NASA NTRS2012

The Extreme Ultraviolet (EUV) Instrument for the MAVEN Mission

The Mars Atmosphere and Volatile Evolution Mission (MAVEN) will explore the variability in the planet's upper atmosphere and ionosphere that is dominated by interactions with the sun, specifically the high-energy photons in the soft X-ray and extreme ultraviolet wavelengths as well as interactions with the solar wind. Scientists will use MAVEN data to determine the current loss rate of volatile compounds from the Mars atmosphere, then extrapolate back in time in order to give historical estimations of state of the Mars atmosphere and climate, its ability to sustain liquid water, and the potential for the Martian habitability. The EUV instrument is critical in measuring the Space Weather driver of this atmospheric variability. It will directly observe a three EUV wavelength ranges and their variability due to solar flares (time scales of seconds to hours) as well as active region evolution (months), which will then act as proxies for a model to determine the entire 0.1-200 nm solar spectrum at all times during the MAVEN mission. These EUV measurements and models results will compliment the other instruments that will provide direct in-situ as well as remote sensing observations of the Martian atmospheric response to this solar driver. This presentation will be an introduction of this instrument and its science measurements and goals to the larger community, as well as a status report on its progress.

Chamberlin, Phillip C.↗
NASA NTRS2017

Stratospheric Intrusion-Influenced Ozone Air Quality Exceedences Investigated in MERRA-2

Ozone near the surface is harmful to human health and is a result of the photochemical reaction with both man-made and natural precursor pollutant sources. Therefore, in order to reduce near surface ozone concentrations, communities must reduce anthropogenic pollution sources. However, the injection of stratospheric ozone into the troposphere, known as a stratospheric intrusion, can also lead to concentrations of ground-level ozone exceeding air quality standards. Stratospheric intrusions are dynamical atmospheric features, however, these intrusions have been misrepresented in models and reanalyses until recently, as the features of a stratospheric intrusion are best identified in horizontal resolutions of approximately 50 km or smaller. NASA's Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) reanalysis is a publicly-available high-resolution dataset (~50 km) with assimilated ozone that characterizes stratospheric ozone on the same spatiotemporal resolution as the meteorology. We show that stratospheric intrusions that impact surface air quality are well represented in the MERRA-2 reanalysis. This is demonstrated through a case study analysis of stratospheric intrusion events which were identified by the United States Environmental Protection Agency (EPA) to impact surface ozone air quality in spring 2012 in Colorado. The stratospheric intrusions are identified in MERRA-2 by the folding of the dynamical tropopause under the jet stream and subsequent isentropic descent of dry, O3-rich stratospheric air towards the surface where ozone air quality exceedences were observed. The MERRA-2 reanalysis can support air quality agencies for more rapid identification of the impact of stratospheric air on ground-level ozone.

Knowland, K. Emma↗
DOE OSTI2018

2018 Atmospheric Radiation Measurement (ARM) Annual Report

In fiscal year 2018 (FY2018), the Atmospheric Radiation Measurement (ARM) user facility carried out important measurement missions around the globe and worked to better couple ARM measurements with the needs of the science community through the evaluation of priorities and the continued development of new capabilities, including efforts to better link data and models. While many of these efforts have been ongoing, their importance was supported by recommendations from the 2017 ARM Triennial Review. In February 2018, we submitted the final plans to the U.S. Department of Energy (DOE) that ARM will commit to accomplish over the next two years to address the Triennial Review recommendations. We then began implementing activities to: improve and track communications effectiveness at conferences and through the User Executive Committee implement additional metrics to track ARM’s scientific impact, including on model improvement engage users beyond the traditional DOE Office of Biological and Environmental Research (BER)/Atmospheric System Research (ASR) communities increase the timely production and delivery of ARM Mobile Facility value-added products (VAPs) and create a mechanism to better set expectations for VAP delivery to users improve Data Discovery, ARM’s portal for accessing more than 25 years’ worth of data, for users define a clear process for biennially reviewing instrumentation, data products, and other activities with the goal of determining where resources should be applied update the radar plan and create a plan for optimizing aerosol data collection implement operational plans for the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project and establish a plan for selecting the next science target for LASSO. We have made great progress in all of these areas, much of which is shared in this report, including plans for setting priorities for aerosol measurements and data product development. In FY2018, ARM also brought many plans to fruition that were outlined in its 2014 Decadal Vision strategy, such as the implementation of the LASSO project that integrates observations and models and the continued advancement in the use of unmanned aerial systems (UAS).

MARCUS, POPEYE, Oliktok Point, Eastern North Atlan↗
DOE OSTI2019

Plant Root Exudates Increase Methane Emissions through Direct and Indirect Pathways

The largest natural source of CH4 to the atmosphere is wetlands, which produce 20% to 50% of total global emissions. Vascular plants play a key role regulating wetland CH4 emissions through multiple mechanisms. They often contain aerenchymatous tissues which act as a diffusive pathway for CH4 to travel from the anoxic soil to the atmosphere and for O2 to diffuse into the soil and enable methanotrophy. Plants also exude carbon from their roots which stimulates microbial activity and fuels methanogenesis. This study investigated these mechanisms in a laboratory experiment utilizing rootboxes containing either Carex aquatilis plants, silicone tubes that simulated aerenchymatous gas transfer, or only soil as a control. CH4 emissions were far greater from planted boxes than from control boxes or simulated plants, indicating that the physical transport pathway of aerenchyma was of little importance when not paired with other effects of plant biology. Plants were exposed to 13CO2 at two time-points and subsequent enrichment of root tissue, rhizosphere soil, and emitted CH4 was used in an isotope mixing model to determine the proportion of plant-derived versus soil-derived carbon supporting methanogenesis. Results showed that carbon exuded by plants was converted to CH4 but that plants also increased emission of soil-derived carbon relative to the other experimental treatments. This result signifies that plants and root exudates altered the soil chemical environment and microbial community such that microbial utilization of soil carbon was increased (e.g. microbial priming) and/or oxidation of soil-derived CH4 was decreased (e.g., by microbial competition for oxygen).

methane, wetlands, microbial priming, root exudate↗
DOE OSTI2025

Influence of Lake Ice Biases in Reanalysis Data on Downscaled Climate Simulations over the Great Lakes Region

This data package contains observation-based and model-simulated datasets (all provided in NetCDF format) for evaluating how wintertime lake-ice representation affects regional weather and climate over the Laurentian Great Lakes (freshwater lake ecosystem) during the high–ice-cover winter of 2009. The observational component includes: (1) Stage IV gridded precipitation at 4 km, hourly resolution for January–February 2009 over the Great Lakes region (radar–gauge multisensor precipitation analyses); (2) Great Lakes Surface Environmental Analysis (GLSEA) satellite-derived lake-ice coverage at 1.3 km, daily resolution for the 2009 winter months, providing ice coverage over Lakes Superior, Michigan, Huron, Erie, and Ontario; and (3) in situ measurements at the Standard Rock site on Lake Superior from the Great Lakes Evaporation Network (GLEN) at hourly resolution, including near-surface atmospheric variables and sensible and latent heat fluxes (air–lake exchange) at a fixed point location. The modeling component provides corresponding fields from two simulations, both archived at 4 km, hourly resolution: a standalone Weather Research Forecasting model (WRF) run driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5), and a two-way coupled model using WRF and the Finite Volume Community Ocean Model (WRF-FVCOM, a 3-D hydrodynamic lake model). These outputs include variables relevant to air–lake interaction and lake-effect processes (e.g., near-surface temperature, humidity, wind, precipitation, and surface turbulent fluxes), enabling direct comparison with the observational datasets. Users can analyze and visualize these NetCDF files with common tools such as Python (e.g., xarray, netCDF4, numpy, pandas), NCO/CDO, Panoply, or ncview; NetCDF variables can also be converted to other formats (e.g., CSV, GeoTIFF) using these utilities.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗