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All sources NASA NTRS DOE OSTI

NASA NTRS1992

NWP Impact of Cloud Top and Boundary Layer Winds from a Satellite Borne Lidar: an Observing System Simulation Experiment

Observing systems simulation experiments (OSSE's) provide a powerful tool to assess the impact of proposed satellite borne observing systems on meteorological applications models. We describe the results of an OSSE conducted to assess the impact of data from a low power lidar wind sensor on the forecast accuracy of a global spectral numerical weather prediction (NWP) model, the Air Force Geophysics Laboratory Global Data Assimilation System. The instrument would be operating at near-infrared wavelengths thereby increasing the backscatter signal relative to comparable infrared lidar.

Isaacs, R. G.↗

NASA NTRS2009

An Operational Assessment of the MODIS False Color Composite with the Great Falls, Montana National Weather Service

The close and productive collaborations between the NWS Warning and Forecast Office (WFO) in Great Falls, MT and the Short Term Prediction and Research Transition (SPORT) Center at NASA/Marshall Space Flight Center have provided a unique opportunity for science sharing and technology transfer. In particular, SPoRT has provided a false color composite product derived from MODIS data, which is part of NASA's Earth Observing System. This product is designed to delineate snow and ice covered ground, bare ground and clouds. The Great Falls WFO has been a test bed of the MODIS false color composite as a tool in operations to monitor the development and dissipation of snow cover In particular, preliminary applications have shown that the product can be used to monitor snow cover in remote locations as well as ice in rivers. This information can lead to improved assessments of flooding potential during post event conditions where rapid melting and runoff are anticipated. The potential of this product on future geostationary satellites may substantially contribute to the NWS mission by providing enhanced situational awareness. The operational use of this product has been transitioned at WFO Great Falls through a process of product implementation, discussions with the service hydrologist and forecasters, and post event analysis. A concentrated assessment period from January to March, 2008 was initiated to investigate the impact of the MODIS false color product on WFO Great Falls' operations. This presentation will emphasize the impact the MODIS false color product had in the WFO's situational awareness and how best this information can be used to influence operational decisions.

Loss, GIna↗

NASA NTRS1991

Predicting cloud-to-ground lightning with neural networks

A neural network is being trained to predict lightning at Cape Canaveral for periods up to two hours in advance. Inputs consist of ground based field mill data, meteorological tower data, lightning location data, and radiosonde data. High values of the field mill data and rapid changes in the field mill data, offset in time, provide the forecasts or desired output values used to train the neural network through backpropagation. Examples of input data are shown and an example of data compression using a hidden layer in the neural network is discussed.

Barnes, Arnold A., Jr.↗

NASA NTRS1990

Nonlinear dynamics of global atmospheric and Earth-system processes

Researchers are continuing their studies of the nonlinear dynamics of global weather systems. Sensitivity analyses of large-scale dynamical models of the atmosphere (i.e., general circulation models i.e., GCM's) were performed to establish the role of satellite-signatures of soil moisture, sea surface temperature, snow cover, and sea ice as crucial boundary conditions determining global weather variability. To complete their study of the bimodality of the planetary wave states, they are using the dynamical systems approach to construct a low-order theoretical explanation of this phenomenon. This work should have important implications for extended range forecasting of low-frequency oscillations, elucidating the mechanisms for the transitions between the two wave modes. Researchers are using the methods of jump analysis and attractor dimension analysis to examine the long-term satellite records of significant variables (e.g., long wave radiation, and cloud amount), to explore the nature of mode transitions in the atmosphere, and to determine the minimum number of equations needed to describe the main weather variations with a low-order dynamical system. Where feasible they will continue to explore the applicability of the methods of complex dynamical systems analysis to the study of the global earth-system from an integrative viewpoint involving the roles of geochemical cycling and the interactive behavior of the atmosphere, hydrosphere, and biosphere.

Saltzman, Barry↗

NASA NTRS2016

MISTiC Winds, a Micro-Satellite Constellation Approach to High Resolution Observations of the Atmosphere Using Infrared Sounding and 3D Winds Measurements

MISTiC(TM) Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiCs extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sunsynchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's AIRS that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenasat much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key remaining technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

Maschhoff, K. R.↗

DOE OSTI2026

Observations of Offshore Low‐Level Jets Off the U.S. East Coast Reveal Systematic Biases in ERA5 and HRRR

Low-level jets (LLJs)—wind speed maxima typically occurring a few hundred meters above the surface—are common off the U.S. East Coast and influence many atmospheric processes with societal importance, including cloud formation, aviation safety, and search-and-rescue. However, their vertical structure and frequency remain poorly quantified due to limited offshore observations. This study presents new scanning Doppler LiDAR and infrared spectroradiometer data from the 2024 summer deployment of an offshore barge during the Wind Forecast Improvement Project 3. These coupled wind and temperature profiles provide unprecedented resolution to assess LLJ behavior and model performance. LLJs occurred in over 21% of observed profiles, with a weak diurnal preference for nighttime and early morning hours and maximum winds typically near 300 m. Both ERA5 and High-Resolution Rapid Refresh analysis underestimate jet wind speeds and misrepresent the boundary layer thermal structure. These results highlight persistent model biases and the critical need for high-resolution offshore observations.

17 WIND ENERGY↗

DOE OSTI2023

Cross-Scale Land-Atmosphere Experiment (CSLAEX) (Final Report)

It is now well recognized that land-atmosphere interactions play an important role in both weather and climate. These interactions take place over a wide range of spatial and temporal scales. Most of the current formulations of the momentum, heat and moisture transport laws are informed by observations with a limited temporal or spatial scale, and hence may have limited applicability. The objective of this work is to improve the multi-scale representation of the near-surface heat transfer in the ground and in the atmosphere using a combination of modeling and field observations. Our knowledge and predictive capacity in land-atmosphere coupling is limited by our capacity to observe the full-scale spectrum at play. In order to bridge this fundamental gap in our observation capacity I will work to: create the first long-term Integrated Cross-Scale land-Atmosphere Experiment (CSLAEX) since I will work to: measure the components of the surface energy balance at a spatial scale relevant to remote sensing and meteorological applications (5km), along with observations of the nested subscale processes with Distributed Temperature Sensors (DTS). This proposal aims to fill the gaps in modeling and observing land-atmosphere interactions across scales via a novel Cross-Scale Land-Atmosphere Experiment (CSLAEX) to be implemented as part of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site near Lamont, Oklahoma. The proposed research effort aims at exploring land-atmosphere processes across multiple spatial scales and to investigate the effect of landscape heterogeneity using Distributed Temperature Sensor measurements. The novel instrumentation of the Surface Energy Balance and simultaneous observations of the atmospheric state (boundary layer, cloud, convection) available at the DOE ARM SGP site will be used to create CSLAEX. This dataset will be used to frame and evaluate new transport laws and parameterizations for the boundary layer and the land surface, which can be implemented into the Weather and Research Forecasting (WRF) model and Community Atmospheric Model (CAM). The result of this study should impact multiple fields: meteorology, climate, and hydrology.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1984

Multisensor satellite data integration for sea surface wind speed and direction determination

Techniques to integrate meteorological data from various satellite sensors to yield a global measure of sea surface wind speed and direction for input to the Navy's operational weather forecast models were investigated. The sensors were launched or will be launched, specifically the GOES visible and infrared imaging sensor, the Nimbus-7 SMMR, and the DMSP SSM/I instrument. An algorithm for the extrapolation to the sea surface of wind directions as derived from successive GOES cloud images was developed. This wind veering algorithm is relatively simple, accounts for the major physical variables, and seems to represent the best solution that can be found with existing data. An algorithm for the interpolation of the scattered observed data to a common geographical grid was implemented. The algorithm is based on a combination of inverse distance weighting and trend surface fitting, and is suited to combing wind data from disparate sources.

Glackin, D. L.↗

NASA NTRS2012

Large Scale Variability of Mid-Tropospheric Carbon Dioxide as Observed by the Atmospheric Infrared Sounder (AIRS) on the NASA EOS Aqua Platform

The Atmospheric Infrared Sounder (AIRS) is a hyperspectral infrared instrument on the EOS Aqua Spacecraft, launched on May 4, 2002. AIRS has 2378 infrared channels ranging from 3.7 microns to 15.4 microns and a 13.5 km footprint. AIRS, in conjunction with the Advanced Microwave Sounding Unit (AMSU), produces temperature profiles with 1K/km accuracy, water vapor profiles (20%/2km), infrared cloud height and fraction, and trace gas amounts for CO2, CO, SO2, O3 and CH4 in the mid to upper troposphere. AIRS wide swath(cedilla) +/-49.5 deg , enables daily global daily coverage for over 95% of the Earth's surface. AIRS data are used for weather forecasting, validating climate model distribution and processes, and observing long-range transport of greenhouse gases. In this study, we examine the large scale and regional horizontal variability in the AIRS Mid-tropospheric Carbon Dioxide product as a function of season and associate the observed variability with known atmospheric transport processes, and sources and sinks of CO2.

carbon dioxide↗

NASA NTRS2001

Evaluation of NCAR Icing/SLD Forecasts, Tools and Techniques Used During The 1998 NASA SLD Flight Season

Supercooled Large Droplet (SLD) icing conditions were implicated in at least one recent aircraft crash, and have been associated with other aircraft incidents. Inflight encounters with SLD can result in ice accreting on unprotected areas of the wing where it can not be removed. Because this ice can adversely affect flight characteristics of some aircraft, there has been concern about flight safety in these conditions. The FAA held a conference on in-flight icing in 1996 where the state of knowledge concerning SLD was explored. One outcome of these meetings was an identified need to acquire SLD flight research data, particularly in the Great Lakes Region. The flight research data was needed by the FAA to develop a better understanding of the meteorological characteristics associated with SLD and facilitate an assessment of existing aircraft icing certification regulations with respect to SLD. In response to this need, NASA, the Federal Aviation Administration (FAA), and the National Center for Atmospheric Research (NCAR) conducted a cooperative icing flight research program to acquire SLD flight research data. The NASA Glenn Research Center's Twin Otter icing research aircraft was flown throughout the Great Lakes region during the winters of 1996-97 and 1997-98 to acquire SLD icing and meteorological data. The NASA Twin Otter was instrumented to measure cloud microphysical properties (particle size, LWC (Liquid Water Content), temperature, etc.), capture images of wing and tail ice accretion, and then record the resultant effect on aircraft performance due to the ice accretion. A satellite telephone link enabled the researchers onboard the Twin Otter to communicate with NCAR meteorologists. who provided real-time guidance into SLD icing conditions. NCAR meteorologists also provided preflight SLD weather forecasts that were used to plan the research flights, and served as on-board researchers. This document contains an evaluation of the tools and techniques NCAR forecasters used to predict the location of SLD icing conditions during the winter of 1997-1998. The objectives of this report are to: (1) assess the tools used to forecast in-flight icing. (2) assess the success/failure rate of the forecasts, and (3) discuss suggested changes to forecast techniques.

Bernstein, Ben C.↗

NASA NTRS2001

The Role of Remote Sensing Displays in Earth Climate and Planetary Atmospheric Research

The communities of scientists who study the Earth's climate and the atmospheres of the other planets barely overlap, but the types of questions they pose and the resulting implications for the use and interpretation of remote sensing data sets have much in common. Both seek to determine the characteristic behavior of three-dimensional fluids that also evolve in time. Climate researchers want to know how and why the general patterns that define our climate today might be different in the next century. Planetary scientists try to understand why circulation patterns and clouds on Mars, Venus, or Jupiter are different from those on Earth. Both disciplines must aggregate large amounts of data covering long time periods and several altitudes to have a representative picture of the rapidly changing atmosphere they are studying. This emphasis separates climate scientists from weather forecasters, who focus at any one time on a limited number of images. Likewise, it separates planetary atmosphere researchers from planetary geologists, who rely primarily on single images (or mosaics of images covering the globe) to study two-dimensional planetary surfaces that are mostly static over the duration of a spacecraft mission yet reveal dynamic processes acting over thousands to millions of years. Remote sensing displays are usually two-dimensional projections that capture an atmosphere at an instant in time. How scientists manipulate and display such data, how they interpret what they see, and how they thereby understand the physical processes that cause what they see, are the challenges I discuss in this chapter. I begin by discussing differences in how novices and experts in the field relate displays of data to the real world. This leads to a discussion of the use and abuse of image enhancement and color in remote sensing displays. I then show some examples of techniques used by scientists in climate and planetary research to both convey information and design research strategies using remote sensing displays.

DelGenio, Anthony D.↗

NASA NTRS1973

Use of Polarization Lidar for Investigation of Meteorological Formations

This paper presents the results of theoretical and experimental, investigations of depolarization characteristics of different meteorological formations. Experimental investigations are carried out with a monostatic lidar. The ruby laser radiation is polarized in a vertical plane. The radiation reflected is accepted by a lens system of 150 rom in diameter and a viewing angle of 12' and further it is divided by Wollaston prism into the components polarized orthogonally. In this case the principal plane of the prism is exposed parallel with the laser polarization plane. Investigations show the degree of radiation polarization, reflected from water clouds, to be changed within 1/0.7 (seldom up to 0.6) depending on their density. In most cases a signal reflected from the cloud leading edge is polarized completely. The time shift is observed between polarized and crosspolarized components of a Fignal, reflected from a cloud, depending on the density of a meteorological object. While penetrating into the cloud depth a degree of polarization decreases up to 0.8-0.7, and the character of this decrease is different for various types of clouds. For crystal clouds the shift between the components of the reflected signal is not observed and the magnitude of polarization degree amounts to 0.1/0.3 in comparison with water clouds. The polarization degree of radiation reflected by fog is not less than 0.6, and that in the rains of average intensity (about 5 mm/h) is always about 1. The authors have suggested an algorithm of numerical solution of nonstationary transfer equation in the vector form to forecast the influence of multiple scattering effects on polarization characteristics of the lidar light signal. The method of statistical simulation (Monte-Carlo technique) forms the basis of the algorithm. Numerical estimates obtained for a model of stratocumulus at lambda = 0.6943 microns under boundary conditions close to the conditions of natural experiment being discussed proved to be in a good agreement with the results of observation. Specifically, Fig. 1 shows the profiles of polarization (p) versus depth (L) of the following drop formations: fog (curve 1) with horizontal meteorological visibility of 4 km two stratocumulus at a height of 1100 m with the attenuation factors delta = 0.01m(exp -1) (curve 2) and delta = 0.05m(exp -1) (curve 3). Curve 3 shows the results of numerical estimates and the value of their statistical error.

Balin, Yu. S.↗

NASA NTRSDate not supplied

Toward Enhancing the Use of IASI and CrIS Surface-Sensitive Radiances Over Land in the NASA GMAO GEOS Data Assimilation Framework

Assimilating surface-sensitive radiances over land is still challenging for both infrared (IR) and microwave (WV) radiances essentially because of the large uncertainties of the land physical surface emissivity model used in the Community Radiative Transfer Model (CRTM) and the uncertainties of land surface state properties. Currently very few IR radiances are assimilated over land. Large number of IR radiances are rejected by the surface sensitivity checks as well as the cloud detection check. In this study, we identified the appropriate Infrared Atmospheric Sounding Interferometer (IASI) and Cross-track Infrared Sounder (CrIS) surface-sensitive channels to retrieve Land Surface Temperature (LST). Then, we studied the impacts of these retrieved LST and retuned cloud detection on the simulation and assimilation of IASI and CrIS in the NASA GEOS in clear sky conditions. The preliminary results are shown to enhance the rate of IASI and CrIS assimilated channels over land. The impacts on the quality of the resulting analysis and subsequent forecast will be presented at the meeting.

Niama Boukachaba↗

DOE OSTI2020

Updraft and Downdraft Core Size and Intensity as Revealed by Radar Wind Profilers: MCS Observations and Idealized Model Comparisons

This study explores the updraft and downdraft properties of mature stage mesoscale convective systems (MCSs) in terms of draft core width, shape, intensity, and mass flux characteristics. The observations use extended radar wind profiler (RWP) and surveillance radar datasets from the U.S. Department of Energy Atmospheric Radiation Measurement program for midlatitude (Oklahoma, USA) and tropical (Amazon, Brazil) sites. MCS drafts behave qualitatively similar to previous aircraft and RWP cloud summaries. The Oklahoma MCSs indicate larger and more intense convective up- and downdraft cores, and greater mass flux than Amazon MCS counterparts. However, similar size-intensity relationships and draft vertical profile behaviors are observed for both regions. Additional similarities include weak positive correlations between core intensity and core width (correlation coefficient r ~ 0.5), and increases in draft intensity with altitude. A model-observational intercomparison for draft properties (core width, intensity, mass flux) is also performed to illustrate the potential usefulness of statistical observed draft characterizations. Idealized simulations with the Weather Research and Forecasting model aligned with midlatitude MCS conditions are performed at model grid spacings (?x) that range from 4 km to 250 m. It is shown that the simulations performed at ?x = 250 m at similar mature MCS lifecycle stages are those that exhibit draft intensity, width, mass flux, and shape parameter performances best matching with observed properties.

radar, arm, wind profiler, goamazon↗

DOE OSTI2024

Electron cloud simulations in the Fermilab booster

As part of Fermilab's Proton Improvement Plan-II (PIP-II),the Fermilab Booster synchrotron will operate at a higherintensity, increasing from 4.5 x 10^12 to 6.7 x 10^12 protons per pulse (ppp). A potential challenge for achievinghigh intensity performance arises from rapid transverse instabilities induced by electron cloud (EC). This researchpresents EC simulations using PyECLOUD, which is anadvanced computational tool that incorporates measurements of the secondary electron yield (SEY) from theBooster's combined function magnet material. By systematically varying beam parameters in PyECLOUD, such asbunch structure, SEY, bunch length, and intensity, it becomes possible to forecast the impact of EC effects on thebeam stability of the PIP-II era Booster.

43 PARTICLE ACCELERATORS↗

NASA NTRS2003

A Physical Validation Program for the GPM Mission

The GPM mission is currently planned for start in the late 2007 - early 2008 time frame. Its main scientific goal is to help answer pressing scientific problems arising within the context of global and regional water cycling. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like core satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe -- continuously. The constellation's orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. A major requirement before the retrieved rainfall information generated by the GPM mission can be used effectively by prognostic models to improve weather forecasts, hydrometeorological forecasts, and climate model reanalysis simulations is a capability to quantify the error characteristics of the retrievals. A solution for this problem has been upheld in past precipitation missions because of the lack of suitable error modeling systems incorporated into the validation programs and data distribution systems. An overview of how NASA intends to overcome this problem for the GPM mission using a physically-based error modeling approach within a multi-faceted validation program is described. The solution is to first identify specific user requirements and then determine the most stringent of these requirements that embodies all essential error characterization information needed by the entire user community. In the context of NASA s scientific agenda for the GPM mission, the most stringent user requirement is found within the data assimilation community. The fundamental theory of data assimilation vis-a-vis ingesting satellite precipitation information into the pre-forecast initializations is based on quantifying the conditional bias and precision errors of individual rain retrievals, and the space-time structure of the precision error (i.e., the spatial-temporal error covariance). By generating the hardware and software capability to produce this information in a near real-time fashion, and to couple the derived quantitative error properties to the actual retrieved rainrates, all key validation users can be satisfied. The talk will describe the essential components of the hardware and software systems needed to generate such near real-time error properties, as well as the various paradigm shifts needed within the validation community to produce a validation program relevant to the precipitation user community.

Smith, Eric A.↗

NASA NTRS2012

Remote Sensing of Snow Cover: Snow Extent - Section

Snow was easily identified in the first image obtained from the Television Infrared Operational Satellite-1 (TIROS-1) weather satellite in 1960 because the high albedo of snow presents a good contrast with most other natural surfaces. Subsequently, the National Oceanic and Atmospheric Administration (NOAA) began to map snow using satellite-borne instruments in 1966. Snow plays an important role in the Earth s energy balance, causing more solar radiation to be reflected back into space as compared to most snow-free surfaces. Seasonal snow cover also provides a critical water resource through meltwater emanating from rivers that originate from high-mountain areas such as the Tibetan Plateau. Meltwater from mountain snow packs flows to some of the world s most densely-populated areas such as Southeast Asia, benefiting over 1 billion people (Immerzeel et al., 2010). In this section, we provide a brief overview of the remote sensing of snow cover using visible and near-infrared (VNIR) and passive-microwave (PM) data. Snow can be mapped using the microwave part of the electromagnetic spectrum, even in darkness and through cloud cover, but at a coarser spatial resolution than when using VNIR data. Fusing VNIR and PM algorithms to produce a blended product offers synergistic benefits. Snow-water equivalent (SWE), snow extent, and melt onset are important parameters for climate models and for the initialization of atmospheric forecasts at daily and seasonal time scales. Snowmelt data are also needed as input to hydrological models to improve flood control and irrigation management.

Hall, Dorothy K.↗

NASA NTRS1992

Polar stratospheric cloud processed air and potential vorticity in the Northern Hemisphere lower stratosphere at mid-latitudes during winter

The present study compares small-scale (less than 100 km) features in ER-2 measurements of ClO, O3, H2O, N2O, and NO(y) outside the lower stratospheric Arctic vortex of 1988-1989 with features on potential vorticity maps from ECMWF. The potential vorticity maps are obtained from T106 analyses and forecasts. Some of the plots were truncated to lower resolution (T63 or T42) which smooths out the finer-scale structure. Comparison of these lower resolution plots shows how much detail is lost by excessive smoothing. It is also evident that the forecast plots lose fine-scale structure due to dissipation in the model resulting mainly from horizontal diffusion. It is concluded that blobs of air on the maps at latitudes between the vortex edge and 25 deg N having potential vorticities characteristic of the vortex did indeed originate from the vortex, but that the real atmosphere is more sharply differentiated than the meteorological analyses, implying that the potential vorticity maps underestimate the amount of peeled-off material.

Tuck, A. F.↗