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At least 253 records · Page 14

A comparison between Nimbus 5 THIR and ITPR temperatures and derived winds with rawinsonde data obtained in the AVE 2 experiment

During the period of May 11 and 12, 1974, NASA conducted its second Atmospheric Variability Experiment (AVE II) over the eastern United States. In this time interval, two Nimbus 5 orbits crossed the AVE II area, providing a series of ITPR soundings as well as THIR data. Horizontal temperature mapping of the AVE II cloud field is examined using two grid print map scales. Implied cloud top heights are compared with maximum radar-echo top reports. In addition, shelter temperatures in areas of clear sky are compared with the surface temperatures as determined from 11.5 micrometer radiometer data of the THIR experiment. The ITPR sounding accuracy is evaluated using interpolated radiosonde temperatures at times nearly coincident with the ITPR soundings. It was found that mean differences between the two data sets were as small as 1.3 C near 500 mb and as large as 2.9 C near the tropopause. The differences between ITPR and radiosonde temperatures at constant pressure levels were sufficient to induce significant differences in the horizontal temperature gradient. Cross sections of geostrophic wind along the orbital tracks were developed using a thermal wind buildup based on the ITPR temperature data and the radiosonde temperature data. Differences between the radiosonde and ITPR geostrophic winds could be explained on the basis of differences in the ITPR and radiosonde temperature gradients.

Arnold, J. E.↗

Cycle life versus depth of discharge update on modeling studies

The topics are presented in viewgraph form and cycle life vs. depth of discharge data for the following are presented: data as of three years ago; Air Force/Crane-Fuhr-Smithrick; Ken Fuhr's Data; Air Force/Crane Data; Eagle-Pitcher Data; Steve Schiffer's Data; John Smithrick's Data; temperature effects; and E-P, Yardney, and Hughes 26% Data. Other topics covered include the following: LeRC cycling tests of Yardney Space Station Cells; general statements; general observations; two different models of cycle life vs. depth of discharge; and other degradation modes.

Thaller, Lawrence H.↗

Correlation of S-Band Weather Radar Reflectivity and ACTS Propagation Data in Florida

Previous work has shown that Ka-band attenuation due to rainfall and corresponding S-band reflectivity are highly correlated. This paper reports on work whose goal is to determine the feasibility of estimation and, by extension, prediction of one parameter from the other using the Florida ACTS propagation terminal (APT) and the nearby WSR-88D S-band Doppler weather radar facility operated by the National Weather Service. This work is distinguished from previous efforts in this area by (1) the use of a single-polarized radar, preventing estimation of the drop size distribution (e.g., with dual polarization) and (2) the fact that the radar and APT sites are not co-located. Our approach consists of locating the radar volume elements along the satellite slant path and then, from measured reflectivity, estimating the specific attenuation for each associated path segment. The sum of these contributions yields an estimation of the millimeter-wave attenuation on the space-ground link. Seven days of data from both systems are analyzed using this procedure. The results indicate that definite correlation of S-band reflectivity and Ka-band attenuation exists even under the restriciton of this experiment. Based on these results, it appears possible to estimate Ka-band attenuation using widely available operational weather radar data. Conversely, it may be possible to augment current radar reflectivity data and coverage with low-cost attenuation or sky temperature data to improve the estimation of rain rates.

Wolfe, Eric E.↗

Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Python‐based software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize pre‐existing Python modules as well as to be object‐oriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25‐year history into a common data structure suitable for user‐defined analyses. It features rapid, simplified (i.e., one line of code) production of quick‐look imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publication‐ready figures. Deconvolution of the polarization‐varying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward real‐time AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during May‐June 2014. The second software package is the Marshall Multi‐Radar/Multi‐Sensor (MRMS) Mosaic Python Toolkit, or MMM‐Py for short. MMM‐Py was designed to read, analyze, and display three‐dimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMM‐Py can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMM‐Py can easily stitch multiple tiles together to provide a larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMM‐Py can also write to the native MRMS binary format, and sub‐sectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMM‐Py also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMM‐Py, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Python‐based analysis routines with the U.S. Department of Energy's Py‐ART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFC‐based implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convective‐scale analysis, situational awareness, and forensic meteorology. PyTDA exploits Py‐ART's radar data ingest routines and data model to rapidly produce aviation‐relevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the Py‐ART framework will be highlighted. Python‐based analysis within the Py‐ART framework is also being done for new research related to intercomparison of ground‐based radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds.

Lang, Timothy J.↗

Thermal Testing and Analysis Techniques for Wires and Wire Bundles

Determining wire and wire bundle amperage capacity (i.e., “ampacity”) currently relies on the use of standards to derate wire ampacity when in a bundle configuration. The feasibility of developing physics-based and regression thermal models of single wires and wire bundles to determine ampacity using a customized test apparatus was investigated during a pathfinder study. A wire bundle test apparatus was developed for measuring the temperatures of single wires and wire bundles and collected wire conductor temperature data under high vacuum and atmospheric conditions and varying environmental temperatures and currents for the two most common wire types used on spacecraft.

Thermal↗

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Department

Flooding and drought are two key forecasting challenges for the Kenya Meteorological Department (KMD). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the boundary layer of the atmosphere providing a source of heat and moisture. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface within weakly-sheared environments, such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in numerical weather prediction models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-end events over east Africa. KMD currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Nonhydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over eastern Africa. Two organizations at the National Aeronautics and Space Administration Marshall Space Flight Center in Huntsville, AL, SERVIR and the Short-term Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMD for enhancing its regional modeling capabilities. To accomplish this goal, SPoRT and SERVIR will provide experimental land surface initialization datasets and model verification capabilities to KMD. To produce a land-surface initialization more consistent with the resolution of the KMD-WRF runs, the NASA Land Information System (LIS) will be run at a comparable resolution to provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Additionally, real-time green vegetation fraction data from the Visible Infrared Imaging Radiometer Suite will be incorporated into the KMD-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service. Finally, model verification capabilities will be transitioned to KMD using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. The transition of these MET tools will enable KMD to monitor model forecast accuracy in near real time. This presentation will highlight preliminary verification results of WRF runs over east Africa using the LIS land surface initialization.

Case. Jonathan↗

LWIR detector behavior at very low frequencies

Measurements have been made of the signal and noise characteristics of extrinsic photoconductive silicon detectors. The measurements were made at several background levels, bias voltages and detector operating temperatures. Data are shown at modulation frequencies as low as 0.01 Hz, operating temperatures as low as 2.5K and background photon flux densities down to 8 x 10 to the 7th photons/sec-sq cm. Data on the temporal characteristics of the detector signal are presented. In addition, some interesting data on 'spontaneous noise spikes' are also shown.

Arrington, D. C.↗

Optimal weighting of data to detect climatic change - Application to the carbon dioxide problem

It is suggested that a weighting of surface temperature data, using information about the expected level of warming in different seasons and geographical regions and statistical information about the amount of natural variability in surface temperature, can improve the chances of early detection of carbon dioxide concentration-induced climatic warming. A preliminary analysis of the optimal weighting method presented suggests that it is 25 per cent more effective in revealing surface warming than the conventional method, in virtue of the fact that 25 per cent more data must conventionally be analyzed in order to arrive at a similar probability of detection. An approximate calculation suggests that the warming ought to have already been detected, if the only sources of significant surface temperature variability had time scales of less than one year.

Bell, T. L.↗

Estimates of solar wind heating inside 0.3 AU

Helios 1 proton temperature data have been normalized in order to determine a base temperature-velocity curve at 0.3 AU and to provide quantitative estimates on the close-in heating at different solar wind velocities. The results suggest that the slope of the solar wind temperature gradients for high-speed streams inside 0.3 AU is about half of that found beyond it. The very-low-speed wind is shown to expand adiabatically all the way out. It is also found that intermediate speed winds have enhanced heating rates in proportion to their velocities.

Freeman, John W.↗

Theoretical study of polar and global ozone changes using a coupled radiative-dynamical 2-D model

An existing 2-D model has recently been updated to incorporate ozone-temperature feedbacks with more comprehensive radiative transfer calculations and more detailed temperature data input. Researchers address the following issues: (1) given the observed temperature changes for the past eight years, quantitatively how much ozone change can be produced by the dynamical effect of the temperature change over the Arctic and Antarctic; (2) how much of the reported change in globally averaged ozone can be accounted for by temperature changes; (3) the role of the diabatic circulation changes in the lower stratosphere in determining the timing of the polar spring maximum and minimum; and (4) the role of the seasonal change in the diabatic circulation in causing the fall minimum over the Arctic and Antarctic.

Yang, H.↗

The Influence of Sea Ice on Primary Production in the Southern Ocean: A Satellite Perspective

Sea ice in the Southern Ocean is a major controlling factor on phytoplankton productivity and growth, but the relationship is modified by regional differences in atmospheric and oceanographic conditions. We used the phytoplankton biomass (binned at 7-day intervals), PAR and cloud cover data from SeaWiFS, ice concentrations data from SSM/I and AMSR-E, and sea-surface temperature data from AVHRR, in combination with a vertically integrated model to estimate primary productivity throughout the Southern Ocean (south of 60"s). We also selected six areas within the Southern Ocean and analyzed the variability of the primary productivity and trends through time, as well as the relationship of sea ice to productivity. We found substantial interannual variability in productivity from 1997 - 2005 in all regions of the Southern Ocean, and this variability appeared to be driven in large part by ice dynamics. The most productive regions of Antarctic waters were the continental shelves, which showed the earliest growth, the maximum biomass, and the greatest areal specific productivity. In contrast, no large, sustained blooms occurred in waters of greater depth (> 1,000 m). We suggest that this is due to the slightly greater mixed layer depths found in waters off the continental shelf, and that the interactive effects of iron and irradiance (that is, increased iron requirements in low irradiance environments) result in the limitation of phytoplankton biomass over large regions of the Southern Ocean.

Smith, Walker O., Jr.↗

Case studies using GOES infrared data and a planetary boundary layer model to infer regional scale variations in soil moisture

Modeled temperature data from a one-dimensional, time-dependent, initial value, planetary boundary layer model for 16 separate model runs with varying initial values of moisture availability are applied, by the use of a regression equation, to longwave infrared GOES satellite data to infer moisture availability over a regional area in the central U.S. This was done for several days during the summers of 1978 and 1980 where a large gradient in the antecedent precipitation index (API) represented the boundary between a drought area and a region of near normal precipitation. Correlations between satellite derived moisture availability and API were found to exist. Errors from the presence of clouds, water vapor and other spatial inhomogeneities made the use of the measurement for anything except the relative degree of moisture availability dubious.

Rose, F. G.↗

El Nino and the Global Ocean Observing System

Until a decade ago, an often-quoted expression in oceanography is that very few observations are recorded throughout the ocean. Now, the sentiment is no longer valid in the uppermost 10% of the tropical Pacific Ocean nor at the surface of the global ocean. One of the remarkable legacies of the 1985-1994 Tropical Oceans Global Atmosphere (TOGA) Program is an in situ marine meteorological and upper oceanographic measurement array throughout the equatorial Pacific to monitor the development and maintenance of El Nino episodes. The TOGA Observing System, which initially consisted of moored- and drifting-buoy arrays, a network of commercial ships, and coastal and island stations, now includes a constellation of satellites and data-assimilating models to simulate subsurface oceanographic conditions. The El Nino and La Nina tropical Pacific Ocean observing system represents the initial phase of an integrated global ocean observing system. Remarkable improvements have been made in ocean model simulation of subsurface currents, but some problems persist. For example, the simulation of the South Equatorial Current (SEC) remains an important challenge in the 2S-2N Pacific equatorial wave guide. During El Nino the SEC at the equator is reduced and sometimes the direction is reversed, becoming eastward. Both conditions allow warm water stored in the western Pacific to invade the eastern region, creating an El Nino episode. Assimilation of data is a tenet of faith to correct simulation errors caused by deficiencies in surface fluxes (especially wind stress) and parameterizations of subgrid-scale physical processes. In the first of two numerical experiments, the Pacific SEC was simulated with and without assimilation of subsurface temperature data. Along the equator, a very weak SEC occurred throughout the eastern Pacific, independent of assimilation of data. However, as displayed in the diagram, in the western Pacific there was no satisfactory agreement between the two simulations. To help determine reliability of the simulated SEC in the western Pacific, current measurements recorded during the 9-19 October 1994 voyage of the French research vessel L'Atalante are also shown in the diagram. With data assimilation, the simulated SEC was in much better agreement with L'Atalante observations. The simulated SEC with data assimilation was far from perfect, in part because of the sparsity of subsurface temperature observations. In the next experiment, TOPEX/POSEIDON sea surface height data in combination with subsurface temperatures will be assimilated to assess further improvement of the simulation of the SEC.

Halpern, David↗

Polarimetric Scanning Radiometer C and X Band Microwave Observations During SMEX03

Soil Moisture Experiments 2003 (SMEX03) was the second in a series of field campaigns using the NOAA Polarimetric Scanning Radiometer (PSR/CX) designed to validate brightness temperature data and soil moisture retrieval algorithms for the Advanced during SMEX03 were: calibration and validation of AMSR-E brightness temperature observations over different climate/vegetation regions of the US. (Alabama, Georgia, Oklahoma), identification of possible sources of Radio Frequency Interference (RFI), comparison of X-band observations from TRMM Microwave Imager (TMI), AMSR-E and PSR/CX, and exploring the potential of soil moisture retrieval algorithms using C and X band imagery in diverse landscapes. In the current investigation, more than one hundred flightlines of PSR/CX data were extensively processed to produce gridded brightness temperature products for the four study regions. Variations associated with soil moisture were not as large as hoped for due to the lack of significant rainfall in Oklahoma. Observations obtained over Alabama include a wide range of soil moisture and vegetation conditions for C and X band frequencies. These results clearly showed a lack of sensitivity to rainfall/soil moisture under forest canopy cover. Quantitative comparisons made between the PSR/CX, AMSR-E for validated that both the PSR/CX and AMSR-E data were well calibrated. X band comparisons of the PSR/CX high resolution and AMSR-E and TMI low-resolution data indicated a linear scaling for the range of conditions studied in SMEX03. These results will form the basis for further soil moisture investigations.

Jackson, Thomas J.↗

Delineation of cold-prone areas using nighttime SMS/GOES thermal data Effects of soils and water

Infrared digital data from geostationary satellites were used to demonstrate the usefulness of remotely sensed surface temperature data to delineate microscale and mesoscale climates. Nocturnal winter data (December-February) from 1976-77 to 1978-79 over Florida revealed noticeable contrasts in surface temperature patterns. Colder areas were associated with low soil moisture content in the upper layers of excessively drained and well drained sandy soils, whereas warmer areas were associated with bodies of water, wetlands, or poorly drained soils. An unexpected surface temperature pattern for one night where the north-central Florida climatic zone was colder than the north Florida climatic zone was found to be caused by differences in antecedent frontal rainfall. Differences in surface radiant energy fluxes over these two areas at 0200 EST 20 December 1977, based on average satellite-sensed surface temperatures, were compared with differences in soil heat fluxes that were computed from 1.5 m climatological temperatures and soil thermal properties by use of a simplified surface energy balance equation.

Chen, E.↗

A 94/183 GHz multichannel radiometer for Convair flights

A multichannel 94/183 GHz radiometer was designed, built, and installed on the NASA Convair 990 research aircraft to take data for hurricane penetration flights, SEASAT-A underflights for measuring rain and water vapor, and Nimbus-G underflights for new sea ice signatures and sea surface temperature data (94 GHz only). The radiometer utilized IF frequencies of 1, 5, and 8.75 GHz about the peak of the atmospheric water vapor absorption line, centered at 183.3 GHz, to gather data needed to determine the shape of the water molecule line. Another portion of the radiometer operated at 94 GHz and obtained data on the sea brightness temperature, sea ice signatures, and on areas of rain near the ocean surface. The radiometer used a multiple lens antenna/temperature calibration technique using 3 lenses and corrugated feed horns at 94 GHz and 183 GHz. Alignment of the feed beams at 94 GHz and 183 GHz was accomplished using a 45 deg oriented reflecting surface which permitted simultaneous viewing of the feeds on alternate cycles of the chopping intervals.

Gagliano, J. A.↗