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At least 379 records · Page 21

The Effect of a Potentially Low Solar Cycle #24 on Orbital Lifetimes of Fengyun 1-C Debris

The magnitude of Solar Cycle #24 will have a non-trivial impact on the lifetimes of debris pieces that resulted from the intentional hypervelocity impact of the Fengyun 1-C satellite in January 2007. Recent solar flux measurements indicate Solar Cycle #24 has begun in the last few months, and will continue until approximately 2019. While there have been differing opinions on whether the intensity of this solar cycle will be higher or lower than usual, the Space Weather Prediction Center within the National Oceanic Atmospheric Administration (NOAA/SWPC) has recently forecast unusually low solar activity, which would result in longer orbital lifetimes. Using models for both the breakup of Fengyun 1-C and the propagation of the resultant debris cloud, the Orbital Debris Program Office at NASA Johnson Space Center conducted a study to better understand the impact of the solar cycle on lifetimes for pieces as small as 1 mm. Using a modified collision breakup model and PROP3D propagation software, the orbits of nearly 2 million objects 1 mm and larger were propagated for up to 200 years. By comparing a normal solar cycle with that of the NOAA/SWPC forecast low cycle, the effect of the solar flux on the lifetimes of the debris pieces is evaluated. The modeling of the low solar cycle shows an additional debris count of 12% for pieces larger than 10 cm by 2019 when compared to the resultant debris count using a normal cycle. The difference becomes more exaggerated (over 15%) for debris count in the smaller size regimes. However, in 50 years, the models predict the differences in debris count from differing models of Solar Cycle #24 to be less than 10% for all size regimes, with less variance in the smaller sizes. Understanding the longevity of the debris cloud will affect collision probabilities for both operational spacecraft and large derelict objects over the next century and beyond.

Whitlock, David↗

Tropospheric Science

Now casting, current weather forecasting, extended range forecasting and climate prediction are discussed with an emphasis on the observational requirements of climate prediction. Intergrated hydrologic cycle measurements, cloud parameter characterization, air sea interaction measurements, tropical winds, and tropospheric gaseous species measurements are discussed.

Leovy, C. B.↗

Precipitation and kinematic structure of microburst producing storms

Single Doppler radar techniques are used to study the precipitation and kinematic structure of microburst-producing storms. Radar data collected by NCAR radars during the Joint Airport Weather Studies (JAWS) experiment are presented along with rawinsonde data taken at Denver, Colorado near the times of microburst occurrence. The radar reflectivity and velocity structure of the storms exhibited great variability, with no unique signature indicating a microburst was imminent. Detection of descending divergent flow is probably not a microburst forecasting tool, nor can the presence of rotation be used as a precursor at present. Convergent flow aloft was a prominent feature in all events. Its occurrence with a descending precipitation shaft and/or at high altitudes is a good indicator of a downdraft. It is concluded that convergent flow is a very important microburst forecasting clue, particularly when coupled with the entrainment of Theta(e) air and a dry-adiabatic lapse rate below cloud base.

Roberts, R. D.↗

Current results from AlRS/AMSU/HSB

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. Pre-launch simulation studies indicated that these results should be achievable. Minor modifications have been made to the pre-launch retrieval algorithm as alluded to in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and temperature profiles are validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. Select fields are also compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis. Assimilation of AIRS temperature soundings in up to 80% cloud cover for the month of January 2003 into the GSFC FVSSI data assimilation system resulted in improved 5 day forecasts globally, both with regard to anomaly correction coefficients and the prediction of location and intensity of cyclones.

Susskind, Joel↗

Atmospheric Soundings from AIRS/AMSU/HSB

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of lK, and 1 km tropospheric layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. Pre-launch simulation studies indicated that these results should be achievable. Minor modifications have been made to the pre-launch retrieval algorithm as alluded to in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and temperature profiles are validated as a function of retrieved effective fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. Select fields are also compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis. Assimilation of AIRS temperature soundings in up to 80% cloud cover for the month of January 2003 into the GSFC FVSSI data assimilation system resulted in improved 5 day forecasts globally, both with regard to anomaly correlation coefficients and the prediction of location and intensity of cyclones.

Susskind, Joel↗

A Goddard Multi-Scale Modeling System with Unified Physics

A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. The following is presented in this report: (1) a brief review of the GCE model and its applications on the impact of aerosols on deep precipitation processes, (2) the Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) a discussion on the Goddard WRF version (its developments and applications).

Tao, Wei-Kuo↗

Global Daily Atmospheric State Profiles from the Atmospheric Infrared Sounder

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 (micro)m to 15.4 (micro)m and a 13.5 km footprint. AIRS, in conjunction with the Advanced Microwave Sounding Unit (AMSU), produces temperature profiles with 1K/km accuracy on a global scale, as well as water vapor profiles, clouds, dust and trace gas amounts for CO2, CO, SO2, O3 and CH4.[1] AIRS data are used for weather forecasting and studies of global climate change. The AIRS is a 'facility' instrument developed by NASA as an experimental demonstration of advanced technology for remote sensing and the benefits of high resolution infrared spectra to science investigations.

sounder↗

A Goddard Multi-Scale Modeling System with Unified Physics

A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the physical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems. In addition, high - resolution (spatial. 2km, and temporal, I minute) visualization showing the model results will be presented.

Tao, Wei-Kuo↗

A Goddard Multi-Scale Modeling System with Unified Physics

A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the ph ysical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems.

Tao, Wei-Kuo↗

High-Resolution NU-WRF Simulations of a Deep Convective-Precipitation System During MC3E: Comparisons Between Goddard Microphysics Schemes and Observations - Part 1

The Goddard microphysics scheme was recently improved by adding a 4th ice class (frozen dropshail). This new 4ICE scheme was implemented and tested in the Goddard Cumulus Ensemble model (GCE) for an intense continental squall line and a moderate,less-organized continental case. Simulated peak radar reflectivity profiles were improved both in intensity and shape for both cases as were the overall reflectivity probability distributions versus observations. In this study, the new Goddard 4ICE scheme is implemented into the regional-scale NASA Unified - Weather Research and Forecasting model (NU-WRF) and tested on an intense mesoscale convective system that occurred during the Midlatitude Continental Convective Clouds Experiment (MC3E). The NU42WRF simulated radar reflectivities, rainfall intensities, and vertical and horizontal structure using the new 4ICE scheme agree as well as or significantly better with observations than when using previous versions of the Goddard 3ICE (graupel or hail) schemes. In the 4ICE scheme, the bin microphysics-based rain evaporation correction produces more erect convective cores, while modification of the unrealistic collection of ice by dry hail produces narrow and intense cores, allowing more slow-falling snow to be transported rearward. Together with a revised snow size mapping, the 4ICE scheme produces a more horizontally stratified trailing stratiform region with a broad, more coherent light rain area. In addition, the NU-WRF 4ICE simulated radar reflectivity distributions are consistent with and generally superior to those using the GCE due to the less restrictive open lateral boundaries

Regional Scale Model↗

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U. S. Deep South Summer Convection

Inspection of output from various configurations of high-resolution, explicit convection forecast models such as the Weather Research and Forecasting (WRF) model indicates significant sensitivity to the choices of model physics parameterizations employed. Some of the largest apparent sensitivities are related to the specifications of the cloud microphysics and planetary boundary layer physics packages. In addition, these sensitivities appear to be especially pronounced for the weakly-sheared, multicell modes of deep convection characteristic of the Deep South of the United States during the boreal summer. Possible ocean-land sensitivities also argue for further examination of the impacts of using unique ocean-land surface initialization datasets provided by the NASA Short-term Prediction Research and Transition (SPoRT Center to select NOAA/NWS weather forecast offices. To obtain better quantitative understanding of these sensitivities and also to determine the utility of the ocean-land initialization data, we have executed matrices of regional WRF forecasts for selected convective events near Mobile, AL (MOB), and Houston, TX (HGX). The matrices consist of identically initialized WRF 24-h forecasts using any of eight microphysics choices and any of three planetary boundary layer choices. The resulting 24 simulations performed for each event within either the MOB or HGX regions are then compared to identify the sensitivities of various convective storm metrics to the physics choices. Particular emphasis is placed on sensitivities of precipitation timing, intensity, and coverage, as well as amount and coverage of lightning activity diagnosed from storm kinematics and graupel in the mixed phase layer. The results confirm impressions gleaned from study of the behavior of variously configured WRF runs contained in the ensembles produced each spring at the Center for the Analysis and Prediction of Storms, but with the benefit of more straightforward control of the physics package choices. The design of the experiments thus allows for more direct interpretation of the sensitivities to each possible physics combination. The results should assist forecasters in their efforts to anticipate and correct for possible biases in simulated WRF convection patterns, and help the modeling community refine their model parameterizations.

McCaul, E. W., Jr.↗

The Impact of Microphysics and Planetary Boundary Layer Physics on Model Simulation of U.S. Deep South Summer Convection

Inspection of output from various configurations of high-resolution, explicit convection forecast models such as the Weather Research and Forecasting (WRF) model indicates significant sensitivity to the choices of model physics pararneterizations employed. Some of the largest apparent sensitivities are related to the specifications of the cloud microphysics and planetary boundary layer physics packages. In addition, these sensitivities appear to be especially pronounced for the weakly-sheared, multicell modes of deep convection characteristic of the Deep South of the United States during the boreal summer. Possible ocean-land sensitivities also argue for further examination of the impacts of using unique ocean-land surface initialization datasets provided by the NASA Short-term Prediction Research and Transition (SPoRn Center to select NOAAlNWS weather forecast offices. To obtain better quantitative understanding of these sensitivities and also to determine the utility of the ocean-land initialization data, we have executed matrices of regional WRF forecasts for selected convective events near Mobile, AL (MOB), and Houston, TX (HGX). The matrices consist of identically initialized WRF 24-h forecasts using any of eight microphysics choices and any of three planetary boWldary layer choices. The resulting 24 simulations performed for each event within either the MOB or HGX regions are then compared to identify the sensitivities of various convective storm metrics to the physics choices. Particular emphasis is placed on sensitivities of precipitation timing, intensity, and coverage, as well as amount and coverage oflightuing activity diagnosed from storm kinematics and graupel in the mixed phase layer. The results confirm impressions gleaned from study of the behavior of variously configured WRF runs contained in the ensembles produced each spring at the Center for the Analysis and Prediction of Storms, but with the benefit of more straightforward control of the physics package choices. The design of the experiments thus allows for more direct interpretation of the sensitivities to each possible physics combination. The results should assist forecasters in their efforts to anticipate and correct for possible biases in simulated WRF convection patterns, and help the modeling community refine their model parameterizations.

McCaul, Eugene W., Jr.↗

Analysis and Forecast of Two Storms Characterized by Extreme Deepening Rates

Between 25 and 27 December 1999 two very intense cyclones, named Lothar and Martin, swept across northern and western France causing substantial life and property loss. In this work, the finite volume general circulation model and data assimilation system (fvDAS) developed at the Data Assimilation Office of the NASA Goddard Space and Flight Center is being used to investigate these storms. In the first part of this article the dynamics of the storms is analyzed, and some important mechanisms are unveiled. The second part describes a set of eleven data assimilation experiments to study the impact of different data types on the automated analyses. Cloud-track winds provided by EUMETSAT and surface winds from QuikSCAT are being used. These data are assimilated with a range of different parameter settings of the forecast error covariance model. The results show that generally the additional wind data set have positive impacts on the analyses: particularly, the analysis of Lothar can be slightly improved by using the Eumetsat winds, and the analysis of Martin can be strongly improved by using the full-resolution QuikSCAT winds with a more localized influence. The third part of this article is focused on the forecast of Lothar which is very well predicted in the 1-5 day range by the fvDAS system.

Reale, Oreste↗

A technique for determining cloud free vs cloud contaminated pixels in satellite imagery

Since the first earth orbiting satellite sent pictures of the earth back to them, atmospheric scientists have been focused on the possibilities of using that information as both a forecasting tool and as a meteorological research tool. With the latest generation of Geostationary Operational Environmental Satellites (GOES) now entering service, that view of the earth yields views at a frequency and resolution never before available. These satellites have imagers with a five band multi-spectral capability with high spatial resolution. In addition, the sounder has eighteen thermal infrared (IR) channels plus one low-resolution visible band. With a resolution as small as one kilometer, GOES provides scientists with a powerful eye on the atmosphere. Menzel and Purdom (1994) detail both the imager and sounder capability as well as other systems on the GOES satellites. Immediately apparent in the visible channel are the patterns of clouds swirling over both oceans and continents. These clouds range in size from huge planetary systems covering thousands of kilometers to puffy fair weather cumulus clouds on the order of half a kilometer in size. With the IR sensors temperature patterns are observed. High clouds appear very cold, while low stratus field show temperatures near that of the surface. The surface, in turn, generally appears warmer than the clouds. It would seem then a simple manner to determine cloud and surface temperature from the imagery, but such is not the case. While most of the atmospheric constituents are well mixed and homogeneous, water vapor is not. The water molecule, because of its unique structure and vibration modes, affects the transmittance of the atmosphere most notably in the infrared regions. There are regions of the IR spectrum where water vapor acts as a strong absorber, and at others it is nearly transparent. The transparent wavelengths are called windows, and one such window occurs at 11.2 microns. Adjacent to this window at 12.7 microns which is strongly absorbed by water vapor. These two wavelengths form what is known as a split window, the utility of which was used. Using the linearized form of the radiative transfer equation, they were able to use the split window to determine the amount of water vapor present in the atmosphere. Jedlovec developed the physical split-window (PSW) technique which determines the integrated water content (IWC). The PSW method using Visible Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) found on the older versions of the GOES satellites was used. Recently, Jedlovec and colleagues have been attempting to apply the PSW method using full disk IR imagery obtained by the new generation of GOES satellites. IWC is essential for improved analysis and prediction of convective storms which have been observed to develop in regions of both strong and rapidly evolving moisture gradients. It has also been used in the prediction of clouds and precipitation.

Wohlman, Richard A.↗

High Impact Weather Forecasts and Warnings with the GOES-R Geostationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. A major advancement over the current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM). The GLM will operate continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, a GOES-R Risk Reduction Science Team and Algorithm Working Group Lightning Applications Team have begun to develop cal/val performance monitoring tools and new applications using the GLM alone, in conjunction with other instruments, and merged or blended integrated observing system products combining satellite, radar, in-situ and numerical models. Proxy total lightning data from the NASA Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional ground-based lightning networks are being used to develop the pre-launch algorithms, test data sets, and applications, as well as improve our knowledge of thunderstorm initiation and evolution. In this presentation we review the planned implementation of the instrument and suite of operational algorithms.

Goodman, Steven↗

High Impact Weather Forecasts and Warnings with the GOES-R Geostationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. A major advancement over the current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM). The GLM will operate continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, a GOES-R Risk Reduction Science Team and Algorithm Working Group Lightning Applications Team have begun to develop cal/val performance monitoring tools and new applications using the GLM alone, in conjunction with other instruments, and merged or blended integrated observing system products combining satellite, radar, in-situ and numerical models. Proxy total lightning data from the NASA Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional ground-based lightning networks are being used to develop the pre-launch algorithms, test data sets, and applications, as well as improve our knowledge of thunderstorm initiation and evolution. In this presentation we review the planned implementation of the instrument and suite of operational algorithms.

Goodman, Steven J.↗

Preparations for Integrating Space-Based Total Lightning Observations into Forecast Operations

NASA's Short-term Prediction Research and Transition (SPoRT) Center has been a leader in collaborating with the United States National Weather Service (NWS) offices to integrate ground-based total lightning (intra-cloud and cloud-to-ground) observations into the real-time operational environment. For much of these collaborations, the emphasis has been on training, dissemination of data to the NWS AWIPS system, and focusing on the utility of these data in the warning decision support process. A shift away from this paradigm has occurred more recently for several reasons. For one, SPoRT's collaborations have expanded to new partners, including emergency managers and the aviation community. Additionally, and most importantly, is the impending launch of the GOES-R Geostationary Lightning Mapper (GLM). This has led to collaborative efforts to focus on additional forecast needs, new data displays, develop training for GLM uses based on the lessons learned from ground-based lightning mapping arrays, and ways to better relate total lightning data to other meteorological parameters. This presentation will focus on these efforts to prepare the operational end user community for GLM with an eye towards sharing lessons learned as EUMETSAT prepares for the Meteosat Third Generation Lightning Imager. This will focus on both software and training needs. In particular, SPoRT has worked closely with the Meteorological Development Laboratory to create the total lightning tracking tool. This software allows for NWS forecasters to manually track storms of interest and display a time series trend of observations. This tool also has been expanded to work on any gridded data set allowing for easy visual comparisons of multiple parameters in addition to total lightning. A new web display has been developed for the ground-based observations that can be easily extended to satellite observations. This paves the way for new collaborations outside of the NWS, both domestically and internationally, as the web display will be functional on PCs and mobile devices. Furthermore, SPoRT has helped developed the software plug-in to visualize GLM data. Examples using the official GLM proxy product will be used to provide a glimpse as to what real-time GLM and likely MTG-LI data will be in the near future.

GLM↗

Deriving winds for hurricanes using short interval satellite imagery

Results are presented for a study program designed to develop a better means of obtaining wind data needed by hurricane forecasters and to determine the optimum space and time resolution of satellite data used to obtain such winds. The discussion covers cloud tracking with an image display and manipulation system and analysis of IR imagery of Hurricane Eloise. It is shown that greater resolution in time and space of satellite imagery made it possible to derive up to six times as many low-level winds in a hurricane case, to eliminate 'bad winds' caused by mistaking cloud growth for cloud motion, and to remove ambiguities that would have caused difficulty in tracking clouds using only the imagery taken at 30-min intervals. It is suggested to use short-interval imagery (less than 10 min) for wind determination for future research in areas of tropical cyclones.

Gentry, R. C.↗