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At least 19 records

CONUS-wide Projected Flood Frequency and Uncertainty Estimates, Version 1.0

This dataset presents a large-ensemble of CONUS-wide projected flood frequency and uncertainty estimates across ~2.7 million NHDPlusV2 river reaches over the CONUS. The framework producing this dataset leverages a multi-model, uncertainty-aware modeling framework that allows evaluating shifts in flood frequences at the stream reach level across the CONUS. CONUS-wide ensemble streamflow projections generated from hydrologic simulations driven by downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) outputs are used to derive these flood frequency and uncertainty estimates over the period 1980 - 2099. A spatially consistent regional L-moment algorithm is applied across clusters defined by the US Hydrologic Unit Code Subregions (HUC4s and HUC8s) and NHDPlusV2 stream orders to estimate flood frequencies. The dataset also includes at-site based flood estimates that allow for the comparison between local and regional approach-based estimates, assess projected changes, and characterize their uncertainties. For more reliable estimation of rare flood frequencies such as 500 and 1000-year return periods, super-ensemble based estimates are also included in the dataset. This dataset is derived to support the "Impact-Informed Dam Safety Risk Assessment for Securing Hydropower Assests" project for the US Department of Energy (DOE) Hydropower and Hydrokinetic Office (H2O). For further details, refer to Kao et al. (2022), Ghimire et al. (2023), Ghimire et al. (2025), and Hosking and Wallis (1997).

Ghimire, Ganesh [ORNL] (ORCID:0000000242843941)↗

Status and Plans for Finalization of SRT's Contribution to AIRS Version-7 and Version-7 AO

Version-6.46 temperature profiles, water vapor profiles, and especially total O3, are very much compared to Version-6. With minor tweaking, Version-6.46 is a good candidate for use in Version-7. JPL Version-6.4.6 and Version-6.4.6 AO monthly mean products agree extremely well with each other. Version-6.4.6 AO is accurate enough that there is not necessarily a need to process both Version-7 and Version-7 AO data sets. Single day comparisons show Version-6.46 CrIS/ATMS and Version-6.46 AIRS/AMSU products agree extremely well with each other. We need to demonstrate agreement of Version-6.46 CrIS/ATMS and Version-6.46 AO products on a monthly mean basis for different months and years. CrIS/ATMS and AIRS/AMSU monthly mean comparisons showed excellent agreement using a previous version.

CrIS/ATMS↗

SRT Evaluation of AIRS Version-6.02 and Version-6.02 AIRS Only (6.02 AO) Products

Version-6 contains a number of significant improvements over Version-5. This report compares Version-6 products resulting from the advances listed below to those from Version-5. 1. Improved methodology to determine skin temperature (T(sub s)) and spectral emissivity (Epsilon(sub v)). 2. Use of Neural-net start-up state. 3. Improvements which decrease the spurious negative Version-5 trend in tropospheric temperatures. 4. Improved QC methodology. Version-6 uses separate QC thresholds optimized for Data Assimilation (QC=0) and Climate applications (QC=0,1) respectively. 5. Channel-by-channel clear-column radiances R-hat(sub tau) QC flags. 6. Improved cloud parameter retrieval algorithm. 7. Improved OLR RTA. Our evaluation compared V6.02 and V6.02 AIRS Only (V6.02 AO) Quality Controlled products with those of Version-5.0. In particular we evaluated surface skin temperature T(sub s), surface spectral emissivity Epsilon(sub v), temperature profile T(p), water vapor profile q(p), OLR, OLR(sub CLR), effective cloud fraction alpha-Epsilon, and cloud cleared radiances R-hat(sub tau) . We conducted two types of evaluations. The first compared results on 7 focus days to collocated ECMWF truth. The seven focus days are: September 6, 2002; January 25, 2003; September 29, 2004; August 5, 2005; February 24, 2007; August 10, 2007; and May 30, 2010. In these evaluations, we show results for T(sub s), Epsilon(sub v), T(p), and q(p) in terms of yields, and RMS differences and biases with regard to ECMWF. We also show yield trends as well as bias trends of these quantities relative to ECMWF truth. We also show yields and accuracy of channel by channel QC d values of R-hat(sub tau) for V6.02 and V6.02 AO. Version-5 did not contain channel by channel QC d values of R-hat(sub tau). In the second type of evaluation, we compared V6.03 monthly mean Level-3 products to those of Version-5.0, for four different months: January, April, July, and October; in 3 different years 2003, 2007, and 2011. In particular, we compared V6.03 and V5.0 trends of T(p), q(p), alpha-Epsilon, OLR, and OLR(sub CLR) computed based on results for these 12 time periods

Susskind, Joel↗

Changes in the TRMM Version-5 and Version-6 Precipitation Radar Products Due to Orbit Boost

The performance of the version-5 and version-6 Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) products before and after the satellite orbit boost is assessed through a series of comparisons with Weather Surveillance Radar (WSR)-88D ground-based radar in Melbourne, Florida. Analysis of the comparisons of radar reflectivity near the storm top from the ground radar and both versions of the PR indicates that the PR bias relative to the WSR radar at Melbourne is on the order of 1dB for both pre- and post-boost periods, indicating that the PR products maintain accurate calibration after the orbit boost. Comparisons with the WSR-88D near-surface reflectivity factors indicate that both versions of the PR products accurately correct for attenuation in stratiform rain. However, in convective rain, both versions exhibit negative biases in the near-surface radar reflectivity with version-6 products having larger negative biases than version-5. Rain rate comparisons between the ground and space radars show similar characteristics

Liao, Liang↗

The Salinity Retrieval Algorithms for the NASA Aquarius Version 5 and SMAP Version 3 Releases

The Aquarius end-of-mission (Version 5) salinity data set was released in December 2017. This article gives a comprehensive overview of the main steps of the Level 2 salinity retrieval algorithm. In particular, we will discuss the corrections for wind induced surface roughness, atmospheric oxygen absorption, reflected galactic radiation and side-lobe intrusion from land surfaces. Most of these corrections have undergone major updates from previous versions, which has helped mitigating temporal and zonal biases. Our article also discusses the ocean target calibration for Aquarius Version 5. We show how formal error estimates for the Aquarius retrievals can be obtained by perturbing the input to the algorithm. The performance of the Aquarius Version 5 salinity retrievals is evaluated against salinity measurements from the ARGO network and the HYCOM model. When stratified as function of sea surface temperature or sea surface wind speed, the difference between Aquarius Version 5 and ARGO is within +/-0.1 psu. The estimated global RMS uncertainty for monthly 100 km averages is 0.128 psu for the Aquarius Version 5 retrievals. Finally, we show how the Aquarius Version 5 salinity retrieval algorithm is adapted to retrieve salinity from the Soil-Moisture Active Passion (SMAP) mission.

retrieval algorithm↗

The Salinity Retrieval Algorithms for the NASA Aquarius Version 5 and SMAP Version 3 Releases

The Aquarius end-of-mission (Version 5) salinity data set was released in December 2017. This article gives a comprehensive overview of the main steps of the Level 2 salinity retrieval algorithm. In particular, we will discuss the corrections for wind induced surface roughness, atmospheric oxygen absorption, reflected galactic radiation and side-lobe intrusion from land surfaces. Most of these corrections have undergone major updates from previous versions, which has helped mitigating temporal and zonal biases. Our article also discusses the ocean target calibration for Aquarius Version 5. We show how formal error estimates for the Aquarius retrievals can be obtained by perturbing the input to the algorithm. The performance of the Aquarius Version 5 salinity retrievals is evaluated against salinity measurements from the ARGO network and the HYCOM model. When stratified as function of sea surface temperature or sea surface wind speed, the difference between Aquarius Version 5 and ARGO is within +-0.1 psu. The estimated global RMS uncertainty for monthly 100 km averages is 0.128 psu for the Aquarius Version 5 retrievals. Finally, we show how the Aquarius Version 5 salinity retrieval algorithm is adapted to retrieve salinity from the Soil-Moisture Active Passion (SMAP) mission.

calibration↗

Users' instructions for the NASA/MSFC cloud-rise preprocessor program, version 6, and the NASA/MSFC multilayer diffusion program, version 6: Research version for Univac 1108 system

The cloud-rise preprocessor and multilayer diffusion computer programs were used by NASA in predicting concentrations and dosages downwind from normal and abnormal launches of rocket vehicles. These programs incorporated: (1) the latest data for the heat content and chemistry of rocket exhaust clouds; (2) provision for the automated calculation of surface water pH due to deposition of HCl from precipitation scavenging; (3) provision for automated calculation of concentration and dosage parameters at any level within the vertical grounds for which meteorological inputs have been specified; and (4) provision for execution of multiple cases of meteorological data. Procedures used to automatically calculate wind direction shear in a layer were updated.

Bjorklund, J. R.↗

PDQ Users Manual. Manual Version 2, for PDQ Code Version 1.20

PDQ is a tool for the management of the input and execution of batch jobs for simulation codes that use a text based input system. It accomplishes this goal by operating at two levels. First, it takes input file templates (commonly known at LANL as input deck templates) and creates multiple instantiations by performing substitutions of data from table files into symbols (variables) found in the template. Second, it provides commands to submit the created files to the SLURM batch system for execution. These two activities taken together produce a whole that is greater than the sum of its parts and provides an elegant way of executing studies across multiple similar simulations while minimizing the risk of typographical errors in the input files. PDQ was originally developed as a job management system called XVS by Jeff McAninch while he was at LANL. Besides the capabilities described here, XVS had many other features specific for interactions with particular simulation codes. After Jeff’s departure, maintenance of XVS was taken over by Rendell Carver; he added some new features as well as kept it functioning as the batch system at LANL was changed from LSF to MOAB to SLURM. In 2017, Rob Pelak decided to develop a different version that removed the additional features (many of which were rendered obsolete with the retirement of the simulation code or batch system that they supported) and produced a cleaner “bare bones” version of XVS. A few other behaviors of XVS that Rob found irksome were altered. Rob gave the resulting code a new name: PDQ. In 2022 Danielle McDermott developed a version that runs under Python 3.X. As suggested by Rob, she used the python2to3 utility to identify most changes. Given that PDQ continues to operate with Python version 2.7 we have advanced the version number to 1.20.

97 MATHEMATICS AND COMPUTING↗

Comparison of TRMM 2A25 Products Version 6 and Version 7 with NOAA/NSSL Ground Radar-Based National Mosaic QPE

Characterization of the error associated to satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving spaceborne passive and active microwave measurements for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. We focus here on the error structure of Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The problem was addressed in a previous paper by comparison of 2A25 version 6 (V6) product with reference values derived from NOAA/NSSL's ground radar-based National Mosaic and QPE system (NMQ/Q2). The primary contribution of this study is to compare the new 2A25 version 7 (V7) products that were recently released as a replacement of V6. This new version is considered superior over land areas. Several aspects of the two versions are compared and quantified including rainfall rate distributions, systematic biases, and random errors. All analyses indicate V7 is an improvement over V6.

Kirstetter, Pierre-Emmanuel↗

The AERONET Version 3 Aerosol Retrieval Algorithm, Associated Uncertainties and Comparisons to Version 2

The Aerosol Robotic Network (AERONET) Version 3 (V3) aerosol retrieval algorithm is described, which is based on the Version 2 (V2) algorithm with numerous updates. Comparisons of V3 aerosol retrievals to those of V2 are presented, along with a new approach to estimate uncertainties in many of the retrieved aerosol parameters. Changes in the V3 aerosol retrieval algorithm include (1) a new polarized radiative transfer code (RTC), which replaced the scalar RTC of V2, (2) detailed characterization of gas absorption by adding NO2 and H2O to specify total gas absorption in the atmospheric column, specification of vertical profiles of all the atmospheric species, (3) new bidirectional reflectance distribution function (BRDF) parameters for land sites adopted from the MODIS BRDF/Albedo product, (4) a new version of the extraterrestrial solar flux spectrum, and (5) a new temperature correction procedure of both direct Sun and sky radiance measurements. The potential effect of each change in V3 on single scattering albedo (SSA) retrievals was analyzed. The operational almucantar retrievals of V2 versus V3 were compared for four AERONET sites: GSFC, Mezaira, Mongu, and Kanpur. Analysis showed very good agreement in retrieved parameters of the size distributions. Comparisons of SSA retrievals for dust aerosols (Mezaira) showed a good agreement in 440 nm SSA, while for longer wavelengths V3 SSAs are systematically higher than those of V2, with the largest mean difference at 675 nm due to cumulative effects of both extraterrestrial solar flux and BRDF changes. For non-dust aerosols, the largest SSA deviation is at 675 nm due to differences in extraterrestrial solar flux spectrums used in each version. Further, the SSA 675 nm mean differences are very different for weakly (GSFC) and strongly (Mongu) absorbing aerosols, which is explained by the lower sensitivity to a bias in aerosol scattering optical depth by less absorbing aerosols. A new hybrid (HYB) sky radiance measurement scan is introduced and discussed. The HYB combines features of scans in two different planes to maximize the range of scattering angles and achieve scan symmetry, thereby allowing for cloud screening and spatial averaging, which is an advantage over the principal plane scan that lacks robust symmetry. We show that due to an extended range of scattering angles, HYB SSA retrievals for dust aerosols exhibit smaller variability with solar zenith angles (SZAs) than those of almucantar (ALM), which allows extension of HYB SSA retrievals to SZAs less than 50∘ to as small as 25∘. The comparison of SSA retrievals from closely time-matched HYB and ALM scans in the 50 to 75∘ SZA range showed good agreement with the differences below ∼0.005. We also present an approach to estimate retrieval uncertainties which utilizes the variability in retrieved parameters generated by perturbing both measurements and auxiliary input parameters as a proxy for retrieval uncertainty. The perturbations in measurements and auxiliary inputs are assumed as estimated biases in aerosol optical depth (AOD), radiometric calibration of sky radiances combined with solar spectral irradiance, and surface reflectance. For each set of Level 2 Sun/sky radiometer observations, 27 inputs corresponding to 27 combinations of biases were produced and separately inverted to generate the following statistics of the inversion results: average, standard deviation, minimum and maximum values. From these statistics, standard deviation (labeled U27) is used as a proxy for estimated uncertainty, and a lookup table (LUT) approach was implemented to reduce the computational time. The U27 climatological LUT was generated from the entire AERONET almucantar (1993–2018) and hybrid (2014–2018) scan databases by binning U27s in AOD (440 nm), Angström exponent (AE, 440–870 nm), and SSA (440, 675, 870, 1020 nm). Using this LUT approach, the uncertainty estimates U27 for each individual V3 Level 2 retrieval can be obtained by interpolation using the corresponding measured and inverted combination of AOD, AE, and SSA.

Aliaksandr Siniuk↗

Aircraft noise prediction program propeller analysis system IBM-PC version user's manual version 2.0

The IBM-PC version of the Aircraft Noise Prediction Program (ANOPP) Propeller Analysis System (PAS) is a set of computational programs for predicting the aerodynamics, performance, and noise of propellers. The ANOPP-PAS is a subset of a larger version of ANOPP which can be executed on CDC or VAX computers. This manual provides a description of the IBM-PC version of the ANOPP-PAS and its prediction capabilities, and instructions on how to use the system on an IBM-XT or IBM-AT personal computer. Sections within the manual document installation, system design, ANOPP-PAS usage, data entry preprocessors, and ANOPP-PAS functional modules and procedures. Appendices to the manual include a glossary of ANOPP terms and information on error diagnostics and recovery techniques.

Nolan, Sandra K.↗

Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site‐Level Observations in the Central Midwestern United States

Abstract With projected expansion of biofuel production at a global scale, there is a pressing need to develop adequate representation of bioenergy crops in land surface models to help effectively quantify the biogeophysical and biogeochemical effects of its associated land use changes. This study implements two new perennial bioenergy crops, Miscanthus and switchgrass, into the Community Land Model Version 5 based on site‐level observations from the midwestern United States by modifying parameters associated with photosynthesis, phenology, allocation, decomposition, and carbon cost of nitrogen uptake and integrating concomitantly land management practices. Sensitivity analyses indicate that carbon and energy fluxes of the perennial crops are most sensitive to photosynthesis and phenology parameters. Validation of simulated fluxes against site‐level measurements demonstrates that the model is capable of capturing the overall patterns of energy and carbon fluxes, as well as physiological transitions from leaf emergence to senescence. Compared to annual crops, perennial crops feature longer growing season, greater leaf areas, and higher productivity, leading to increased transpiration, lower annual runoff, and larger carbon uptake. The model simulations suggest that with higher CO 2 assimilation rates and lower demands for nutrients and water, high‐yielding perennial crops are promising alternatives of bioenergy feedstocks compared to traditional annual crops not only for mitigating climate change but also for environmental conservation purposes by reducing fertilizer application and therefore alleviating surface‐ and ground‐water contaminations. Although the local‐scale simulations shed light on potential benefits of using perennial grasses as bioenergy feedstocks, quantifying consequences of their plantations at larger scales warrants additional investigation.

Cheng, Yanyan↗

Validation of the Community Land Model Version 5 over the Contiguous United States (CONUS) using in situ and remote sensing data sets

The Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM Version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over the Contiguous United States (CONUS) at scales which land surface changes and hydrometeorological and hydroclimatological applications are more locally relevant is yet to be assessed. In this study, we conducted three simulations at 0.125? during 1979-2018 over the CONUS using different configurations of CLM, namely CLM5-biogeochemistry (CLM5BGC), CLM4.5BGC, and CLM5-satellite phenology (CLM5SP). We validated and compared their simulations against multiple remote-sensed and in-situ datasets. Overall, the parametric and structural updates (e.g., carbon cost for nitrogen uptake, variable soil thickness, dry surface layer) in CLM5 improve its ability in capturing terrestrial biogeochemical dynamics. The low evapotranspiration in CLM5BGC is associated with biases in simulating vegetation phenological characteristics rather than soil water limitations. The mismatch between CLM5BGC-simulated peak leaf area index and reference data can be attributed to CLM5BGC's inability in simulating phenology of trees and grasses. The differences between CLM-simulated irrigation and reference estimates can be attributed to differences between processes represented in models and in reality, and uncertainties in input and validation datasets. Evaluation against observations at small catchments suggest that hydrologic parameters needed to be calibrated to improve simulations of runoff, especially subsurface runoff. Additional efforts are needed to incorporate spatially-distributed plant phenology and physiology parameters and regional-specific agricultural management practices (e.g., planting, harvest).

Cheng, Yanyan↗

Climate, Variability, and Climate Sensitivity of “Middle Atmosphere” Chemistry Configurations of the Community Earth System Model Version 2, Whole Atmosphere Community Climate Model Version 6 (CESM2(WACCM6))

Abstract Simulating whole atmosphere dynamics, chemistry, and physics is computationally expensive. It can require high vertical resolution throughout the middle and upper atmosphere, as well as a comprehensive chemistry and aerosol scheme coupled to radiation physics. An unintentional outcome of the development of one of the most sophisticated and hence computationally expensive model configurations is that it often excludes a broad community of users with limited computational resources. Here, we analyze two configurations of the Community Earth System Model Version 2, Whole Atmosphere Community Climate Model Version 6 (CESM2(WACCM6)) with simplified “middle atmosphere” chemistry at nominal 1 and 2° horizontal resolutions. Using observations, a reanalysis, and direct model comparisons, we find that these configurations generally reproduce the climate, variability, and climate sensitivity of the 1° nominal horizontal resolution configuration with comprehensive chemistry. While the background stratospheric aerosol optical depth is elevated in the middle atmosphere configurations as compared to the comprehensive chemistry configuration, it is comparable among all configurations during volcanic eruptions. For any purposes other than those needing an accurate representation of tropospheric organic chemistry and secondary organic aerosols, these simplified chemistry configurations deliver reliable simulations of the whole atmosphere that require 35% and 86% fewer computational resources at nominal 1 and 2° horizontal resolution, respectively.

54 ENVIRONMENTAL SCIENCES↗

Causes of Reduced Climate Sensitivity in E3SM From Version 1 to Version 2

The effective climate sensitivity in the Department of Energy's Energy Exascale Earth System Model (E3SM) has decreased from 5.3 K in version 1 to 4.0 K in version 2. This reduction is mainly due to a weaker positive cloud feedback that leads to a stronger negative radiative feedback. Present-day atmosphere-only experiments with uniform 4 K sea surface temperature warming are used to separate the contributions of individual model modifications to the reduced cloud feedback. We find that the reduced cloud feedback is mostly driven by changes over the tropical marine low cloud regime, mainly related to a new trigger function for the deep convection scheme and modifications in the cloud microphysics scheme. The new trigger function helps weaken the low cloud reduction by increasing the cloud water detrainment at low levels from deep convection under warming. Changes to the formula of autoconversion rate from liquid to rain and an introduced minimum cloud droplet number concentration threshold in cloud microphysical calculations help sustain clouds against dissipation by suppressing precipitation generation with warming. In the midlatitudes, the increased Wegener-Bergeron-Findeisen (WBF) efficiency strongly reduces present-day liquid water and leads to a stronger negative cloud optical depth feedback. The reduced trade cumulus cloud feedback in v2 is closer to estimates from recent observational and large-eddy modeling studies but might not be due to the right physical reasons. The reduced mid-latitude cloud feedback may be more plausible because more realistic present-day mixed-phase clouds are produced through the change in the WBF efficiency.

54 ENVIRONMENTAL SCIENCES↗

Monthly Quality-filtered Aggregation of NOAA Climate Data Record (CDR) of AVHRR (Version 5) and VIIRS (Version 1) Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)

This dataset contains gridded monthly Leaf Area Index (LAI) derived from the daily NOAA Climate Data Record (CDR) of AVHRR (Version 5) and VIIRS (Version 1) Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). This data record spans from 1981 to 2024 using data from NOAA polar orbiting satellites: NOAA-7, -9, -11, -14, -16, -17, -18, -19 and S-NPP. The data are projected on a 0.05 degree x 0.05 degree global grid, as in the original CDR. The original CDR is one of the Land Surface CDR products produced by the NASA Goddard Space Flight Center (GSFC) and the University of Maryland (UMD), which is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program. This dataset is in the netCDF-4 file format following ACDD and CF Conventions. This dataset has applied quality assurance information to only include "OK" data from the original CDR in the monthly aggregation.

Vermote, Eric [NASA Goddard Space Flight Center (G↗

Documentation for the machine-readable version of the SAO-HD-GC-DM cross index version 1983

An updated and extended machine readable version of the Smithsonian Astrophysical Observatory star catalog (SAO) is described. A correction of all errors which were found since preparation of the original catalog which resulted from misidentifications and omissions of components in multiple star systems and missing Durchmusterung numbers (the common identifier) in the SAO Catalog are included and component identifications from the Index of Visual Double Stars (IDS) are appended to all multiple SAO entries with the same DM numbers, and lower case letter identifiers for supplemental BD stars are added. A total of 11,398 individual corrections and data additions is incorporated into the present version of the cross index.

Roman, N. G.↗