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All sources NASA NTRS DOE OSTI

DOE OSTI2025

NOAA PSL Microwave Radiometer Block Island / Thermodynamic retrievals TROPoe

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous brightness temperature measurements at 35 channels observed with a microwave radiometer MP3000A operated by NOAA Physical Sciences Laboratory on the Block Island for WFIP3. Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a sensor attached to the MWR housing. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.

17 WIND ENERGY↗

DOE OSTI2024

Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications

To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). Several barriers have prevented the HRRR's widespread proliferation in the wind energy industry: missing timesteps (prior to 2019), challenging file format for wind energy analysis, limited vertical height resolution, and negative bias versus legacy WIND Toolkit data (2007-2013). NREL has applied re-gridding, interpolation, and bias-correction to the native HRRR data to overcome these limitations. This results in the now-publicly-available bias corrected and interpolated HRRR (BC-HRRR) dataset for weather years 2015 to 2023. Bias correction is necessary for wind resource consistency across weather years to be used simultaneously in planning-focused grid integration studies alongside the original WIND Toolkit data. We show that quantile mapping with the WIND Toolkit as a historical baseline is an effective method for bias correcting the interpolated HRRR data: the BC-HRRR has reduced mean bias versus comparable gridded wind resource datasets (+0.12 m/s versus Vortex) and has very low mean bias versus ground measurement stations (+0.01 m/s) (Buster et al., 2024). BC-HRRR's consistency with the legacy WIND Toolkit allows NREL to extend grid integration analysis to 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. As with historical datasets like the WIND Toolkit, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling) both independently and alongside the legacy WIND Toolkit.

Array↗

NASA NTRS2018

Early Results from NOAA-20 (JPSS-1) Viirs On-Orbit Calibration and Characterization

Since launch in November 2018, the VIIRS on-board the NOAA-20 (or JPSS-1) satellite has completed its initial intensive on-orbit check-outs and several key calibration and validation activities scheduled to help evaluate sensor at launch performance. This paper provides a brief overview of NOAA-20 VIIRS on-orbit operation and calibration activities, presents early results derived from its on-board calibrators and lunar observations, and discusses potential improvements and future effort to assure sensor data product quality.

calibration↗

DOE OSTI2018

Contiguous US summer maximum temperature and heat stress trends in CRU and NOAA Climate Division data plus comparisons to reanalyses

Abstract Warming is a major climate change concern, but the impact of high maximum temperatures depends upon the air’s moisture content. Trends in maximum summertime temperature, moisture, and heat index are tracked over three time periods: 1900–2011, 1950–2011, and 1979–2011; these trends differ notably from annual temperature trends. Trends are emphasized from two CRU datasets (CRUTS3.25 and CRUTS4.01) and two reanalyses (ERA-20C and 20CRv2). Maximum temperature trends tend towards warming that is stronger over the Great Lakes, the interior western and the northeastern contiguous United States. A warming hole in the Midwest generally decreases in size and magnitude when heat stress trends are calculated because the region has increasing moisture. CRU and nearly all reanalyses find cooling in the northern high plains that is not found in NOAA Climate Division trends. These NOAA trends are captured better by CRUTS401. Moistening in the northeast amplifies the heat stress there. Elsewhere the moisture trends are less clear. Drying over northern Texas (after 1996) in CRUTS401 translates into decreasing heat stress there (less so in CRUTS325). Though other reanalyses are not intended for long-term trends, MERRA-2 and ERA-Interim match observed trends better than other reanalyses.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Two-Column Aerosol Project (TCAP): Ground-Based Radiation and Aerosol Validation Using the NOAA Mobile SURFRAD Station Field Campaign Report

The National Oceanic and Atmospheric Administration (NOAA) is preparing for the launch of the Geostationary Operational Environmental Satellite R-Series (GOES-R) satellite in 2015. This satellite will feature higher time (5-minute versus 30-minute sampling) and spatial resolution (0.5 km vs 1 km in the visible channel) than current GOES instruments provide. NOAA’s National Environmental Satellite Data and Information Service has funded the Global Monitoring Division at the Earth System Research Laboratory to provide ground-based validation data for many of the new and old products the new GOES instruments will retrieve specifically related to radiation at the surface and aerosol and its extensive and intensive properties in the column. The Two-Column Aerosol Project (TCAP) had an emphasis on aerosol; therefore, we asked to be involved in this campaign to de-bug our new instrumentation and to provide a new capability that the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Mobile Facilities (AMF) did not possess, namely surface albedo measurement out to 1625 nm. This gave us a chance to test remote operation of our new multi-filter rotating shadowband radiometer/multi-filter radiometer (MFRSR/MFR) combination. We did not deploy standard broadband shortwave and longwave radiation instrumentation because ARM does this as part of every AMF deployment. As it turned out, the ARM standard MFRSR had issues, and we were able to provide the aerosol column data for the first 2 months of the campaign covering the summer flight phase of the deployment. Using these data, we were able to work with personnel at Pacific Northwest National Laboratory (PNNL) to retrieve not only aerosol optical depth (AOD), but single scattering albedo and asymmetry parameter, as well.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

NOAA National Centers for Environmental Information Fisheries Acoustics Archive Network Deep Dive

EPOC uses the Deep Dive process to discuss and analyze current and planned science use cases and anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. Deep Dives help ensure that key stakeholders have a common understanding of the issues and the actions that a campus or regional network may need to undertake to offer solutions. The EPOC team leads the effort and relies on collaboration with the hosting site or network, and other affiliated entities that participate in the process. EPOC organizes, convenes, executes, and shares the outcomes of the review with all stakeholders. Between May 2021 and August 2021, staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff from the National Oceanic and Atmospheric Administration (NOAA)'s N-Wave (the Enterprise network that supports the NOAA mission) and National Centers for Environmental Information (NCEI)'s Fisheries Acoustics Archive for the purpose of a recording a Deep Dive into research drivers. The goal of these meetings was to help characterize the requirements for the research use case, and to enable cyberinfrastructure support staff to better understand the needs of the researchers they support.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Comparison of X1 (OLD) and X3 (NEW) Aerosol Observing Systems at the North Slope of Alaska NOAA Observatory

This report describes a comparison of the overlapping X1 and X3 Aerosol Observing Systems (AOS) at the North Slope of Alaska (NSA) observatory. Due to structural issues with the original observatory building, the National Oceanic and Atmospheric Administration (NOAA) funded the design and construction of a new observatory building. Construction began in 2019 and was completed in 2020. The now decommissioned old NOAA Barrow Observatory (BRW) housed the AOS referred to as an NSA external site X1 from October 1997 through August 2021. A new observatory building next door housed the AOS referred to as an NSA external site X3 starting in October 2020. In this document we will refer to the original observatory system measurements as 'OLD' and the measurements in the new building as 'NEW'.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Reanalysis of NOAA H 2 observations: implications for the H 2 budget

Abstract. Hydrogen (H2) is a promising low-carbon alternative to fossil fuels for many applications. However, significant gaps in our understanding of the atmospheric H2 budget limit our ability to predict the impacts of greater H2 usage. Here we use NOAA H2 dry air mole fraction observations from air samples collected from ground-based and ship platforms during 2010–2019 to evaluate the representation of H2 in the NOAA GFDL-AM4.1 atmospheric chemistry-climate model. We find that the base model configuration captures the observed interhemispheric gradient well but underestimates the surface concentration of H2 by about 10 ppb. Additionally, the model fails to reproduce the 1–2 ppb yr−1 mean increase in surface H2 observed at background stations. We show that the cause is most likely an underestimation of current anthropogenic emissions, including potential leakages from H2-producing facilities. We also show that changes in soil moisture, soil temperature, and snow cover have most likely caused an increase in the magnitude of the soil sink, the most important removal mechanism for atmospheric H2, especially in the Northern Hemisphere. However, there remains uncertainty due to fundamental gaps in our understanding of H2 soil removal, such as the minimum moisture required for H2 soil uptake, for which we performed extensive sensitivity analyses. Finally, we show that the observed meridional gradient of the H2 mixing ratio and its seasonality can provide important constraints to test and refine parameterizations of the H2 soil sink.

Paulot, Fabien (ORCID:0000000175344922)↗

NASA NTRS1975

NOAA requirements and programs

Service programs in NOAA that contemplate using the Geostationary Operational Environmental Satellite (GEOS) Data Collection System (DCS) are considered. The GEOS DCS will be operated by the National Environmental Satellite Service of NOAA as an integral part of the national operation environmental satellite program. This plan is concerned with that part of the GEOS program connected with collection and relay of data from remote locations. Service programs include: (1) hydrological data collection; (2) oceanographic data collection; (3) marine observations from data buoys; (4) Tsunami warning service; and (5) meteorological service.

Flanders, A. F.↗

NASA NTRS1974

Extensive summer upwelling on Lake Michigan during 1973 observed by NOAA-2 and ERTS-1 satellites

Two studies are presented that utilize data from the NOAA-2 and ERTS-1 satellites. The studies are concentrated on two summer upwelling episodes in Lake Michigan when considerable contrast was observed in both surface water temperature as observed by NOAA-2 and surface water color as observed by ERTS-1. Physical, biological and chemical processes support the hypothesis that much of the observed 'whitening' is calcium carbonate precipitating as an immediate result of the upwelling.

Strong, A. E.↗

NASA NTRS1975

Operational applications of NOAA-VHRR imagery in Alaska

Near-real time operational applications of NOAA satellite enhanced thermal infrared imagery to snow monitoring for river flood forecasts, and a photographic overlay technique of imagery to enhance snowcover are presented. Ground truth comparisons show a thermal accuracy of approximately + or - 1 C for detection of surface radiative temperatures. The application of NOAA imagery to flood mapping is also presented.

Seifert, R. D.↗

NASA NTRS1982

Classification of simulated and actual NOAA-6 AVHRR data for hydrologic land-surface feature definition

An examination of the possibilities of using Landsat data to simulate NOAA-6 Advanced Very High Resolution Radiometer (AVHRR) data on two channels, as well as using actual NOAA-6 imagery, for large-scale hydrological studies is presented. A running average was obtained of 18 consecutive pixels of 1 km resolution taken by the Landsat scanners were scaled up to 8-bit data and investigated for different gray levels. AVHRR data comprising five channels of 10-bit, band-interleaved information covering 10 deg latitude were analyzed and a suitable pixel grid was chosen for comparison with the Landsat data in a supervised classification format, an unsupervised mode, and with ground truth. Landcover delineation was explored by removing snow, water, and cloud features from the cluster analysis, and resulted in less than 10% difference. Low resolution large-scale data was determined useful for characterizing some landcover features if weekly and/or monthly updates are maintained.

Ormsby, J. P.↗

NASA NTRS1981

The outlook for the NOAA Operational LANDSAT Program

The impact of the current federal budget on the establishment of an operational LANDSAT system is examined with particular emphasis on NOAA responsibilities and efforts to transfer operation of the land satellite system to the private sector. In order to recover the cost of maintenance and operations, the price of system data and products must be raised. Cooperative efforts needed for NASA, EDC, and NOAA to implement the operational system are discussed.

Yates, H. W.↗

NASA NTRS1983

Use of NOAA-N satellites for land/water discrimination and flood monitoring

A tool for monitoring the extent of major floods was developed using data collected by the NOAA-6 advanced very high resolution radiometer (AVHRR). A basic understanding of the spectral returns in AVHRR channels 1 and 2 for water, soil, and vegetation was reached using a large number of NOAA-6 scenes from different seasons and geographic locations. A look-up table classifier was developed based on analysis of the reflective channel relationships for each surface feature. The classifier automatically separated land from water and produced classification maps which were registered for a number of acquisitions, including coverage of a major flood on the Parana River of Argentina.

Tappan, G.↗

NASA NTRS1983

NOAA satellite-derived operational sea surface temperature products

The National Oceanic and Atmospheric Administration (NOAA) began processing global measurements of emitted radiation in the 10.5 to 12.5 micron atmospheric window for purposes of deriving weekly composite and mean monthly sea surface temperature fields in the early 1970s. Atmospheric attenuation corrections, begun with empirical means, were accomplished chiefly with the aid of coarser resolution measurements from atmospheric sounders aboard the same polar orbiting spacecraft. Cloud filtering depended heavily upon the use of histogram techniques applied to 11 x 11 arrays of 8 km resolution Scanning Radiometer Infrared (SRIR) data. Details of the SRIR processing for SST are found in a NOAA Technical Memorandum.

Mcclain, E. P.↗

NASA NTRS1984

Case studies of NOAA 6/TIROS N data impact on numerical weather forecasts

The impact of satellite temperatures from systems which predate the launching of the third generation of vertical sounding instruments aboard TIROS N (13 Oct 1978) and NOAA 6 (27 June 1979) is reported. The first evaluation of soundings from TIROS N found that oceanic, cloudy retrievals over NH mid latitudes show a cold bias in winter. It is confirmed for both satellite systems using a larger data base. It is shown that RMS differences between retrievals and colocated radiosonde observations within the swath 30-60N during the 1979-80 winter were generally 2-3K in clear air and higher for cloudy columns. A positive impact of TIROS N temperatures on the analysis of synoptic weather systems is shown. Analyses prepared from only satellite temperatures seemed to give a better definition to weather systems' thermal structure than that provided by corresponding NMC analyses without satellite data. The results of a set of 14 numerical forecast experiments performed with the PE model of the Israel Meteorological Service (IMS) are summarized; these were designed to test the impact of TIROS N and NOAA 6 temperatures within the IMS analysis and forecast cycle. The satellite data coverage over the NH, the mean area/period S1 and RMS verification scores and the spatial distribution of SAT versus NO SAT forecast differences are discussed and it is concluded that positive forecast impact occurs over ocean areas where the extra data improve the specification which is otherwise available from conventional observations. The forecast impact for three cases from the same set of experiments was examined and it is found that satellite temperatures, observed over the Atlantic Ocean contribute to better forecasts over Iceland and central Europe although a worse result was verified over Spain. It is also shown that the better scores of a forecast based also on satellite data and verified over North America actually represent a mixed impact on the forecast synoptic patterns. A superior 48 hr 500 mb forecast over the western US due to the better initial specification afforded by satellite observed temperatures over the North Pacific Ocean is shown.

Druyan, L. M.↗

NASA NTRS1984

Dependence of NOAA-AVHRR recorded radiance on scan angle, atmospheric turbidity and unresolved cloud

Experimental evidence on the scan angle and sun angle dependence of radiance recorded by the Advanced Very High Resolution Radiometer (AVHRR) devices on the NOAA-6 and NOAA-7 satellites is presented. The effects of atmospheric turbidity at various scan angles is shown, and simulations of angular anisotropy and recorded radiance are compared with the recorded digital data from the AVHRR obtained over the Great Plains area of the US. Evidence is presented on the effects of unresolved cloud on the recorded radiance and vegetative indices from uniform, vegetative targets.

Piwinski, D. J.↗

NASA NTRS1983

Monitoring global vegetation using NOAA-7 AVHRR data

The NOAA-7 polar orbiting, sun-synchronous, operational satellite carries the 5 channel Advanced Very High Resolution Radiometer (AVHRR). Data are acquired globally at a resolution of 4 km on a daily basis. This data provides the means of frequently monitoring global vegetation on continental scales. Techniques for compositing and cloud screening a vegetation index for Africa are presented. The sample data set covers 9 days beginning August 16, 1983 and is compared with a semi-operational vegetation index product produced by NOAA.

Gatlin, J. A.↗