SEARCH · Engineering Papers

Results for “WEATHER FORECASTING”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15

All sources NASA NTRS DOE OSTI

NASA NTRS2016

Second SNPP Cal/Val Campaign: Environmental Data Retrieval Analysis

Satellite ultraspectral infrared sensors provide key data records essential for weather forecasting and climate change science. The Suomi National Polar-orbiting Partnership (Soumi NPP) satellite Environmental Data Records (EDRs) are retrieved from calibrated ultraspectral radiance or Sensor Data Records (SDRs). Understanding the accuracy of retrieved EDRs is critical. The second Suomi NPP Calibration/Validation field campaign was conducted during March 2015 with flights over Greenland. The NASA high-altitude ER-2 aircraft carrying ultraspectral interferometer sounders such as the National Airborne Sounder Testbed-Interferometer (NAST-I) flew under the Suomi NPP satellite that carries the Crosstrack Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS). Herein we inter-compare the EDRs produced from different retrieval algorithms employed on these satellite and aircraft campaign data. The available radiosonde measurements together with the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses are used to assess atmospheric temperature and moisture retrievals from the aircraft and satellite platforms. Preliminary results of this experiment under a winter, Arctic environment are presented.

Zhou, Daniel K.↗

NASA NTRS2000

Sigmoid CME Source Regions at the Sun: Some Recent Results

Identifying Coronal Mass Ejection (CME) precursors in the solar corona would be an important step in space weather forecasting, as well as a vital key to understanding the physics of CMEs. Twisted magnetic field structures are suspected of being the source of at least some CMEs. These features can appear sigmoid (S or inverse-S) shaped in soft X-ray (SXR) images. We review recent observations of these structures and their relation to CMEs, using soft X-ray (SXR) data from the Soft X-ray Telescope (SXT) on the Yohkoh satellite, and EUV data from the EUV Imaging Telescope (EIT) on the SOHO satellite. These observations indicate that the pre-eruption sigmoid patterns are more prominent in SXRs than in EUV, and that sigmoid precursors are present in over 50% of CMEs. These findings are important for CME research, and may potentially be a major component to space weather forecasting. So far, however, the studies have been subject to restrictions that will have to be relaxed before sigmoid morphology can be used as a reliable predictive tool. Moreover, some CMEs do not display a SXR sigmoid structure prior to eruption, and some others show no prominent SXR signature of any kind before or during eruption.

Sterling, Alphonse C.↗

NASA NTRS2011

Solar and Heliospheric Data Requirements: Going Further Than L1

Current operational space weather forecasting relies on solar wind observations made by the ACE spacecraft located at the L1 point providing 30-40 minutes warning time. Some use is also made of SOHO and STEREO solar imaging that potentially can give multiple days of warning time. However, our understanding of the propagation and evolution of solar wind transients is still limited resulting in a typical timing uncertainty of approximately 10 hours. In order to improve this critical understanding, a number of NASA missions are being planned. Specifically the Solar Probe Plus and Solar Orbiter missions will investigate the inner Heliospheric evolution of coronal mass ejections and the acceleration and propagation of solar energetic particles. In addition, a number of multi-spacecraft concepts have been studied that have the potential to significantly improve the accuracy of long-term space weather forecasts.

Szabo, A.↗

NASA NTRS2002

Role of Satellite Rainfall Information in Improving Understanding of the Dynamical Link Between the Tropics and Extratropics Prospects of Improved Forecasts of Weather and Short-Term Climate Variability on Sub-Seasonal Time Scales

The tropics and extratropics are two dynamically distinct regimes. The coupling between these two regimes often defies simple analytical treatment. Progress in understanding of the dynamical interaction between the tropics and extratropics relies on better observational descriptions to guide theoretical development. However, global analyses currently contain significant errors in primary hydrological variables such as precipitation, evaporation, moisture, and clouds, especially in the tropics. Tropical analyses have been shown to be sensitive to parameterized precipitation processes, which are less than perfect, leading to order-one discrepancies between estimates produced by different data assimilation systems. One strategy for improvement is to assimilate rainfall observations to constrain the analysis and reduce uncertainties in variables physically linked to precipitation. At the Data Assimilation Office at the NASA Goddard Space Flight Center, we have been exploring the use of tropical rain rates derived from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments in global data assimilation. Results show that assimilating these data improves not only rainfall and moisture fields but also related climate parameters such as clouds and radiation, as well as the large-scale circulation and short-range forecasts. These studies suggest that assimilation of microwave rainfall observations from space has the potential to significantly improve the quality of 4-D assimilated datasets for climate investigations (Hou et al. 2001). In the next few years, there will be a gradual increase in microwave rain products available from operational and research satellites, culminating to a target constellation of 9 satellites to provide global rain measurements every 3 hours with the proposed Global Precipitation Measurement (GPM) mission in 2007. Continued improvements in assimilation methodology, rainfall error estimates, and model parameterizations are needed to ensure that we derive maximum benefits from these observations.

Hou, Arthur Y.↗

NASA NTRS2014

Development and Implementation of Dynamic Scripts to Execute Cycled GSI/WRF Forecasts

The Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model and Gridpoint Statistical Interpolation (GSI) data assimilation (DA) are the operational systems that make up the North American Mesoscale (NAM) model and the NAM Data Assimilation System (NDAS) analysis used by National Weather Service forecasters. The Developmental Testbed Center (DTC) manages and distributes the code for the WRF and GSI, but it is up to individual researchers to link the systems together and write scripts to run the systems, which can take considerable time for those not familiar with the code. The objective of this project is to develop and disseminate a set of dynamic scripts that mimic the unique cycling configuration of the operational NAM to enable researchers to develop new modeling and data assimilation techniques that can be easily transferred to operations. The current version of the SPoRT GSI/WRF Scripts (v3.0.1) is compatible with WRF v3.3 and GSI v3.0.

Zavodsky, Bradley↗

NASA NTRS2014

Development and Implementation of Dynamic Scripts to Execute Cycled GSI/WRF Forecasts

Zavodsky, Bradley↗

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 OSTI2021

Occupant Preference-Aware Load Scheduling for Resilient Communities

The load scheduling of resilient communities in the islanded mode is subject to many uncertainties such as weather forecast errors and occupant behavior stochasticity. To date, it remains unclear how occupant preferences affect the effectiveness of the load scheduling of resilient communities. This paper proposes an occupant thermal preference-aware load scheduler for resilient communities operating in the islanded mode. First, key resilience indicators are selected to quantify its impacts on the load scheduling of a resilient community. A deterministic model predictive control-based load scheduling framework is adopted as the baseline. Then, a chance-constrained controller is proposed to address the occupant-induced uncertainty in room temperature setpoints. Finally, the chance-constrained controller is compared with the deterministic controller on a virtual community testbed based on a real-world net-zero energy community in Florida, U.S. Results have shown that the proposed chance-constrained controller performs better in terms of serving occupants’ thermal preference and the required battery sizes compared to the deterministic controller with the presence of the assumed stochastic occupant behavior. This work indicates that it is necessary to consider the stochasticity of the occupant behavior when designing optimal load schedulers for resilient communities.

Wang, Jing↗

DOE OSTI2016

Comparison of Measured and Numerically Simulated Turbulence Statistics in a Convective Boundary Layer Over Complex Terrain

High resolution numerical simulation can provide insight into important physical processes that occur within the planetary boundary layer (PBL). The present work employs large eddy simulation (LES) nested within the Weather Forecasting and Research (WRF) framework to simulate real conditions in the convective PBL over an area of complex terrain. A multiple nesting approach has been used to downsize the grid spacing size from 12.15 km (mesoscale) to 0.03 km (LES). To minimize artifacts in theWRF-LES solutions resulting from using an inappropriate grid spacing on the WRF-Meso domain, a careful selection of grid spacing has been conducted. The WRF-LES results have been evaluated with in situ and remote sensing observations collected during the US Department of Energy supported Columbia BasinWind Energy Study (CBWES). The comparison for the first and second order moments, turbulence spectrum, and probability density function (pdf) of wind speed show good agreement between the simulation and data. Furthermore, the WRF-LES variables show a great deal of variability in space and time caused by the complex topography in the LES domain. The WRF-LES results show that the flow structures, such as roll vortices and convective cells, over the domain vary depending on both the spatial location and time of the day. In addition to basic studies related to boundary-layer meteorology, results from these simulations can be used in other applications, such as studying the wind energy resources.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2015

First SNPP Cal/Val Campaign: Satellite and Aircraft Sounding Retrieval Intercomparison

Satellite ultraspectral infrared sensors provide key data records essential for weather forecasting and climate change science. The Suomi National Polar-orbiting Partnership (SNPP) satellite Environmental Data Record (EDR) is retrieved from calibrated ultraspectral radiance so called Sensor Data Record (SDR). It is critical to understand the accuracy of retrieved EDRs, which mainly depends on SDR accuracy (e.g., instrument random noise and absolute accuracy), an ill-posed retrieval system, and radiative transfer model errors. There are few approaches to validate EDR products, e.g., some common methods are to rely on radiosonde measurements, ground-based measurements, and dedicated aircraft campaign providing in-situ measurements of atmosphere and/or employing similar ultraspectral interferometer sounders. Ultraspectral interferometer sounder aboard aircraft measures SDR to retrieve EDR, which is often used to validate satellite measurements of SDR and EDR. The SNPP Calibration/Validation Campaign was conducted during May 2013. The NASA high-altitude aircraft ER-2 that carried ultraspectral interferometer sounders such as the NASA Atmospheric Sounder Testbed-Interferometer (NAST-I) flew under the SNPP satellite that carries the Cross-track Infrared Sounder (CrIS). Here we inter-compare the EDRs produced with different retrieval algorithms from SDRs measured by the sensors from satellite and aircraft. The available dropsonde and radiosonde measurements together with the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis were also used to draw the conclusion from this experiment.

Zhou, Daniel K.↗

DOE OSTI2012

Atmospheric dispersion modeling: Challenges of the Fukushima Daiichi response

In this research, the U.S. Department of Energy’s (DOE) National Atmospheric Release Advisory Center (NARAC) provided a wide range of predictions and analyses as part of the response to the Fukushima Daiichi Nuclear Power Plant accident including: daily Japanese weather forecasts and atmospheric transport predictions to inform planning for field monitoring operations and to provide U.S. government agencies with ongoing situational awareness of meteorological conditions; estimates of possible dose in Japan based on hypothetical U.S. Nuclear Regulatory Commission scenarios of potential radionuclide releases to support protective action planning for U.S. citizens; predictions of possible plume arrival times and dose levels at U.S. locations; and source estimation and plume model refinement based on atmospheric dispersion modeling and available monitoring data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Comparison of Vaisala radiosondes RS41 and RS92 at the ARM Southern Great Plains site

In the fall of 2013, the Vaisala RS41 (fourth generation) radiosonde was introduced as a replacement for the RS92-SGP radiosonde with improvements in measurement accuracy of profiles of atmospheric temperature, humidity, and pressure. In order to help characterize these improvements, an intercomparison campaign was undertaken at the US Department of Energy's Atmospheric Radiation Measurement (ARM) Climate Research Facility site in north-central Oklahoma, USA. During 3–8 June 2014, a total of 20 twin-radiosonde flights were performed in a variety of atmospheric conditions representing typical midlatitude continental summertime conditions. The results show that for most of the observed conditions the RS92 and RS41 measurements agree much better than the manufacturer-specified combined uncertainties with notable exceptions when exiting liquid cloud layers where the “wet-bulbing” effect appears to be mitigated for several cases in the RS41 observations. The RS41 measurements of temperature and humidity, with applied correction algorithms, also appear to show less sensitivity to solar heating. In addition, these results suggest that the RS41 does provide important improvements, particularly in cloudy conditions. For many science applications – such as atmospheric process studies, retrieval development, and weather forecasting and climate modeling – the differences between the RS92 and RS41 measurements should have little impact. However, for long-term trend analysis and other climate applications, additional characterization of the RS41 measurements and their relation to the long-term observational records will be required.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2009

Transitioning Models and Model Output to Space Weather Operations: Challenges and Opportunities

The transition of space weather models or of information derived from space weather models to space weather forecasting is the last step of the chain from model development to model deployment in forecasting operations. As such, it is an extremely important element of the quest to increase our national capability to forecast and mitigate space weather hazards. It involves establishing customer requirements, and analyses of available models, which are, in principle, capable of delivering the required product. Models will have to be verified and validated prior to a selection of the best performing model. Further considerations include operational hardware, and the availability of data streams to drive the model. The final steps include the education of forecasters, and the implementation on gateway hardware prior to operational use. This presentation will provide a discussion of opportunities for rapid progress from the viewpoint of the Community Coordinated Modeling Center.

Hesse, Michael↗

DOE OSTI2018

CAUSES: On the Role of Surface Energy Budget Errors to the Warm Surface Air Temperature Error Over the Central United States

Many weather forecasting and climate models simulate a warm surface air temperature (T2m) bias over mid-latitude continents during the summertime, especially over the Great Plains. We present here one of a series of papers from a multi-model intercomparison project (CAUSES: Cloud Above the United States and Errors at the Surface), which aims to evaluate the role of cloud, radiation, and precipitation biases in contributing to T2m bias using a short-term hindcast approach with observations mainly from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site during the period of April to August 2011. The present study examines the contribution of surface energy budget errors to the bias. All participating models simulate higher net shortwave and longwave radiative fluxes at the surface but there is no consistency on signs of biases in latent and sensible heat fluxes over the Central U.S. and ARM SGP. Nevertheless, biases in net shortwave and downward longwave fluxes, as well as surface evaporative fraction (EF) are the main contributors to T2m bias. Radiation biases are largely affected by cloud simulations, while EF is affected by soil moisture modulated by seasonal accumulated precipitation and evaporation. An approximate equation is derived to further quantify the magnitudes of radiation and EF contributions to T2m bias. Our analysis suggests that radiation errors are always an important source of T2m error for long-term climate runs with EF errors either of equal or lesser importance. However, for the short-term hindcasts, EF errors are more important provided a model has a substantial EF bias.

Ma, H. -Y.↗

DOE OSTI2025

Comparing micro climate weather conditions from the weather research and forecasting (wrf) model with typical meteorological year (tmy) data for building energy simulations

Conference paper titled, Comparing microclimate weather conditions from the weather research and forecasting (WRF) model with typical meteorological year (TMY) data for building energy simulations accepted for Building Simulation 2025 Conference in Brisbane, Australia in Aug 2025.

Li, Hang↗

NASA NTRS2017

CubeSat Infrared Atmospheric Sounder (CIRAS) NASA InVEST Technology Demonstration

Infrared sounders measure the upwelling radiation of the Earth in the Midwave Infrared (MWIR) and Longwave Infrared (LWIR) region of the spectrum with global daily coverage from space. The observed radiances are assimilated into weather forecast models and used to retrieve lower tropospheric temperature and water vapor for climate studies. There are several operational sounders today including the Atmospheric Infrared Sounder (AIRS) on Aqua, the Crosstrack Infrared Sounder (CrIS) on Suomi NPP and JPSS, and the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp spacecraft. The CubeSat Infrared Atmospheric Sounder (CIRAS) is a NASA In-flight Validation of Earth Science Technologies (InVEST) program to demonstrate three new instrument technologies in an imaging sounder configuration. The first is a 2D array of High Operating Temperature Barrier Infrared Detector (HOT-BIRD) material, selected for its high uniformity, low cost, low noise and higher operating temperatures than traditional materials. The detectors are hybridized to a commercial ROIC and commercial camera electronics. The second technology is a MWIR Grating Spectrometer (MGS) designed to provide imaging spectroscopy for atmospheric sounding in a CubeSat volume. The MGS employs an immersion grating or grism, has no moving parts, and is based on heritage spectrometers including the OCO-2. The third technology is a Black Silicon infrared blackbody calibration target. The Black Silicon offers very low reflectance over a broad spectral range on a flat surface and is more robust than carbon nanotubes. JPL will also develop the mechanical, electronic and thermal subsystems for the CIRAS payload. The spacecraft will be a commercially available CubeSat. The integrated system will be a complete 6U CubeSat capable of measuring temperature and water vapor profiles with good lower tropospheric sensitivity. The low cost of CIRAS enables multiple units to be flown to improve temporal coverage or measure 3D Atmospheric Motion Vector (AMV) winds. CIRAS will launch in 2019 and is only a technology demonstration. However, what we learn will benefit future instruments that support operational weather forecasting and climate studies.

Pagano, Thomas S.↗

DOE OSTI2013

ON SUN-TO-EARTH PROPAGATION OF CORONAL MASS EJECTIONS

We investigate how coronal mass ejections (CMEs) propagate through, and interact with, the inner heliosphere between the Sun and Earth, a key question in CME research and space weather forecasting. CME Sun-to-Earth kinematics are constrained by combining wide-angle heliospheric imaging observations, interplanetary radio type II bursts, and in situ measurements from multiple vantage points. We select three events for this study, the 2012 January 19, 23, and March 7 CMEs. Different from previous event studies, this work attempts to create a general picture for CME Sun-to-Earth propagation and compare different techniques for determining CME interplanetary kinematics. Key results are obtained concerning CME Sun-to-Earth propagation: (1) the Sun-to-Earth propagation of fast CMEs can be approximately formulated into three phases: an impulsive acceleration, then a rapid deceleration, and finally a nearly constant speed propagation (or gradual deceleration); (2) the CMEs studied here are still accelerating even after the flare maximum, so energy must be continuously fed into the CME even after the time of the maximum heating and radiation has elapsed in the corona; (3) the rapid deceleration, presumably due to interactions with the ambient medium, mainly occurs over a relatively short timescale following the acceleration phase; and (4) CME-CME interactions seem a common phenomenon close to solar maximum. Our comparison between different techniques (and data sets) has important implications for CME observations and their interpretations: (1) for the current cases, triangulation assuming a compact CME geometry is more reliable than triangulation assuming a spherical front attached to the Sun for distances below 50-70 solar radii from the Sun, but beyond about 100 solar radii we would trust the latter more; (2) a proper treatment of CME geometry must be performed in determining CME Sun-to-Earth kinematics, especially when the CME propagation direction is far away from the observer; and (3) our approach to comparing wide-angle heliospheric imaging observations with interplanetary radio type II bursts provides a novel tool in investigating CME propagation characteristics. Future CME observations and space weather forecasting are discussed based on these results.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Potential for western US seasonal snowpack prediction

Western US snowpack—snow that accumulates on the ground in the mountains—plays a critical role in regional hydroclimate and water supply, with 80% of snowmelt runoff being used for agriculture. While climate projections provide estimates of snowpack loss by the end of the century and weather forecasts provide predictions of weather conditions out to 2 weeks, less progress has been made for snow predictions at seasonal timescales (months to 2 years), crucial for regional agricultural decisions (e.g., plant choice and quantity). Seasonal predictions with climate models first took the form of El Niño predictions 3 decades ago, with hydroclimate predictions emerging more recently. While the field has been focused on single-season predictions (3 months or less), we are now poised to advance our predictions beyond this timeframe. Utilizing observations, climate indices, and a suite of global climate models, we demonstrate the feasibility of seasonal snowpack predictions and quantify the limits of predictive skill 8 months in advance. This physically based dynamic system outperforms observation-based statistical predictions made on July 1 for March snowpack everywhere except the southern Sierra Nevada, a region where prediction skill is nonexistent for every predictor presently tested. Additionally, in the absence of externally forced negative trends in snowpack, narrow maritime mountain ranges with high hydroclimate variability pose a challenge for seasonal prediction in our present system; natural snowpack variability may inherently be unpredictable at this timescale. This work highlights present prediction system successes and gives cause for optimism for developing seasonal predictions for societal needs.

Kapnick, Sarah B.↗