Data Set Information
DATA_SET_NAME GALILEO JUPITER PWS DERIVED PLASMA DENSITY FULL RES V1.0
DATA_SET_ID GO-J-PWS-5-DDR-PLASMA-DENSITY-FULL-V1.0
NSSDC_DATA_SET_ID
DATA_SET_TERSE_DESCRIPTION
DATA_SET_DESCRIPTION Data Set Overview ================= This data set consists of ASCII formatted characteristic frequency and electron plasma density measurements as determined from the Galileo Plasma Wave Science (PWS) instrument spectrum data and calculated from the equations of cold plasma theory. All measurements collected for this volume originate with the 152-channel low rate survey electric spectra. This is a whole mission archive in that coverage for this dataset is simply all times for which plasma density measurements from the Galileo PWS are available when it is in the vicinity of Jupiter. Individual records are gathered into daily files by spacecraft event time (SCET). When well characterized emissions are present in the survey spectra the data rate is one point per electric spectrum, which works out to one point every 18.7 seconds, or one point every 37.3 seconds depending on the instrument's operating mode. During times when emissions could not be characterized no density measurements are provided. Parameters ========== While the data essential to this volume are the electron plasma densities, there are a number of other plasma parameters included within these records. The data set consists of PDS SPREADSHEET objects with one record per time step. The time step is not fixed but varies depending on the measurement method (field 12). Each record begins with the following space and time location parameters in fields 1 through 10: 1. The spacecraft event time (SCET) 2. Spacecraft radial distance from the center of Jupiter 3. Spacecraft Jovigraphic west longitude 4. Spacecraft Jovigraphic local time 5. Spacecraft latitude 6. Spacecraft magnetic local time 7. Spacecraft magnetic latitude 8. Spacecraft Jupiter Solar Ecliptic coordinates, X 9. Spacecraft Jupiter Solar Ecliptic coordinates, Y 10. Spacecraft Jupiter Solar Ecliptic coordinates, Z If available, each record includes the following MAG instrument data in field 11. If MAG data are not available for the given spacecraft event time, then this field is empty: 11. The electron cyclotron frequency, fCE Each data product record contains measurement methods and results in fields 12 through 16: 12. The measurement method (line-plots, spectrograms, or spectrograms with algorithm-assist) 13. The measured frequency value 14. A quality flag for the measurement clairity 15. The name of the measured frequency (fPE, fR=0, fL=0, fUH) 16. An indicator for measurements made in the solar wind Each record contains the resulting characteristic cold-plasma frequencies in fields 16 through 19. Not all frequencies are present for each record, as fields 18, 19 and 20 depend on fCE: 17. The electron plasma frequency, fPE 18. The ordinary mode cutoff frequency, fL=0 19. The extraordinary mode cutoff frequency, fR=0 20. The upper hybrid resonance frequency, fUH Finally, each record contains the corresponding electron plasma number density in field 21: 21. The calculated electron density, Ne Of the four plasma frequencies (fields 17-20), one is a copy of the measured cutoff or resonance (field 13), while the remaining frequencies are calculated using static magnetic field magnitude and the equations of cold plasma theory as described in [BARNHARTETAL2009]. Again, data from the Galileo magnetometer are not always available. During these times fCE, fUH, fR=0 and fL=0 are not present. More detailed definition of data records and field definitions are supplied in the product labels that accompany each data product file on this volume. All data products have the same format. Processing ========== The data on this volume were derived from measuring either plasma electron frequency cutoff (fPE), the Z-mode cutoff (fL=0), or the upper hybrid resonance (fUH). They were produced over a multi-year period by three different investigators; Ansher, Richards, and Barnhart, working under the direction of D. A. Gurnett (Ansher, Richards) and W.S. Kurth (Barnhart). Ansher's data collection measured the cutoff in continuum radiation in regions where fPE > fCE. Richards continued Ansher's work marking continuum cutoff's and in addition added measurements of fUH peaks when present. Both investigators were assisted by technicians who marked cutoffs or peaks in individual spectra, one line plot at a time. Ansher's proceedure and methods are provided in chapter three of the document ANSHER_2001.PDF while Richard's are available section 2.1 of the document RICHARDS_2006.PDF. Both documents are available in the DOCUMENT directory of this volume. Utilizing new software tools, Barnhart extended the dataset to include times when fPE < fCE by considering cutoffs and peaks in Z-mode emissions, and revised some previous measurements by designating them as Z-mode emissions. The newer tools at his disposal presented a time- frequency-amplitude color spectrogram to the user and thus required much less manual labor. The methods he used to review and extend frequency measurements on this volume are very similar to those employed to generate the data on PDS volume VGPW_0201 and are given in the included document, BARNHART_2009.PDF. Most of the following processing narrative is from the point of view of the last investigator to determine plasma densities from PWS spectra, Barnhart, though in fact this is a combined work. ---- The ASCII density data files produced in this volume were derived from measuring the characteristic frequencies from the local plasma. The density was calculated from these data, along with cyclotron frequency data derived from magnetic field data, using the equations of cold plasma theory as described in [BARNHARTETAL2009]. Since the electron plasma frequency fPE, is directly proportional to the electron number density, plasma wave science instrument data alone are sufficient to determine densities when these cutoffs are apparent in the wave spectra. For all other digitized frequencies MAG instrument data were required to calculate the electron density. In order to measure these characteristic frequencies, this effort utilizes a new program that allows the operator to highlight the general vicinity of the cutoff or resonance on a frequency-time spectrogram. Then, an algorithm finds the cutoff or resonance in the region and records the frequency at 1 second intervals. Hence, the automated procedure has a high temporal resolution (18.7 second) and requires a relatively low level of both manual effort and subjective judgment by the operator. There are two different algorithms used: one for cutoff detection and one for resonance or peak detection. The cutoff detection algorithm is controlled by a small number of parameters that can be set by the operator. The first parameter is the cutoff level. In determining possible cutoff candidates, the algorithm scans the region highlighted by the operator and records two separate points, one above the cutoff level and one below. The closer the two points are, temporally, the steeper the slope will be. Therefore, the operator can change the location of the cutoff level to manipulate where the algorithm looks for cutoffs within the highlighted region of interest. The next parameter is the slope magnitude, which designates the minimum magnitude of the finite difference slope where the cutoff must reside. The operator may raise the slope level in order to scan only for sharp cutoffs, or lower it in order to accommodate less steep slopes, depending on the quality of the spectrum data. When there is more than one possible cutoff, the detection program will display them as cutoff candidates. The cutoff level, slope magnitude and cutoff candidates are displayed by the program for viewing by the operator. While the algorithm chooses the lowest frequency cutoff by default, the operator may override the algorithm and choose any of the possible cutoffs to be recorded. While most of the characteristic frequencies are, by definition, the cutoff of propagating wave modes, there are certain circumstances when the characteristic frequency is denoted as the peak of a wave mode in the spectrum. Because of this, there is an algorithm specifically for resonance or peak detection. Many spectra of interest to this study include Z-mode radiation, which has a low-frequency cutoff at fL=0. Barbosa et al. [BARBOSAETAL1990B] demonstrated that taking the peak of the Z-mode as fL=0 yields the highest consistency in the determination of fpe. Hence, when the Z-mode is enhanced, we utilize the peak detection algorithm to identify fL=0 from which fpe and the electron density can be derived. This algorithm can also be used to determine fUH when an enhancement at that frequency is present in the spectrum. In order to measure this resonance or spectral peak, the peak detection algorithm fits a Gaussian curve to the highest peak within the region specified by the program operator. The algorithm then records the frequency of the Gaussian's peak as the peak frequency in the spectrum. The algorithm displays the spectrum and a darker line which is the Gaussian. Because there may be noise which exhibits a large peak in the highlighted spectrum, the spectrum is displayed along with the Gaussian curve and a vertical line designating where the peak was measured. The operator always has the ability to manually change the peak's location and alter the measurement in such cases. While the operator utilizes a color spectrogram to guide the cutoff and peak detectors, we emphasize that this is only used as a means of identifying the appropriate range in frequency for the algorithm to search. The direct use of color spectrograms tends to mislead an operator to perceive a cutoff that is not equivalent to the cutoff in the actual power spectrum [BARBOSAETAL1990B]. Because this may lead to a systematic error in the data, the algorithm utilizes the spectrum itself, and does not depend on a color scale to determine the characteristic frequencies. This should reduce systematic error and lead to more accurate results. Data Coverage ============= This data set does not provide complete coverage of the time intervals when Galileo was within Jupiter's magnetosphere. Two criteria were necessary in order for density measurements to be obtained. First, plasma wave data must exist. Because of the failure of Galileo's high gain antenna, there are many intervals for which there are no plasma wave data. Second, a suitable feature must be present in the spectrum which can reliably be used to identify a characteristic frequency of the plasma related to the electron density, such as fPE, fUH, or fL=0. By far the most prevalent emission of use is the non-thermal continuum radiation, whose low frequency cutoff is at fPE. This radiation literally fills the magnetosphere between the magnetopause and higher density regions of the inner magnetosphere, typically beyond 25 RJ (see illustration DOCUMENTS/A_D79_358_1.PNG). However, some regions include other emissions and regions when the plasma frequency does not have a clear cutoff. If the plasma frequency is not measured directly from the spectrum for any reason, it may be calculated from the local magnetic field data (essentially fCE) and one of three other characteristic frequencies using the equations of cold plasma theory. Thus, magnetic field data must exist for regions when fPE is not present, or the electron density cannot be calculated. Typically, continuum radiation is not present inside of approximately 20 to 25 Jovian radii. Data exists typically from approximately 20 to 65 Jovian radii. Inside of about 10 RJ there is often a narrow band feature at fUH which, when fCE is available, can provide fPE. Interpretations =============== Low rate science survey data were used to measure characteristic frequencies (peaks and cutoffs) which relate to the electron plasma density. When dealing with a variety of spectrograms and plasma conditions found in different regions of the Jovian magnetosphere, it is necessary to interpret the present modes and characteristic frequencies correctly in order to determine the most accurate value for the electron plasma density. Below, we will briefly discuss the methods used for interpreting different spectra. The simplest spectra to interpret for the purposes of determining the electron plasma density are those that include non-thermal continuum radiation with a clear low frequency cutoff and with no other emissions obscuring the cutoff. For the purposes of this data set, we agree with the Gurnett et al. [1981B] interpretation that based upon spectra data it is appropriate to assume that the continuum radiation cutoff is fPE and we can accurately determine the local electron plasma density using the appropriate equation from cold plasma theory. The electron plasma density is directly proportional to the square of the electron plasma frequency and therefore in this case the determination of the density does not depend on magnetic field measurements. When there is only one cutoff present in the continuum radiation, we assume that the continuum radiation is propagating in the ordinary mode and that the cutoff is indeed the plasma frequency. An alternate possibility would be to identify this cutoff as the fR=0 cutoff at fR=0. But, most theories [Shaw and Gurnett, 1980; Moses et. al., 1987; Barbosa et al., 1990] favor the L,O mode as the most likely continuum radiation component, hence, we assume that there is always at least some L,O component present when the continuum radiation is detected. Sometimes, more than one wave mode cutoff is present at different frequencies for the same time period. When this is the case, one way to resolve the ambiguity is to use a guess-and-check system as follows: 1. Assume that one frequency cutoff/peak present in the spectrum is a particular characteristic frequency. 2. Use the local magnetic field data (which determines fCE) along with the equations from cold plasma theory to calculate the remaining characteristic frequencies. 3. Look for consistency between the calculated frequencies and the remaining spectral features (cutoffs/peaks) present. A consistent interpretation is one where the calculated frequencies match the cutoffs/peaks present in the spectrum. In some examples there exist two spectral cutoffs which need identification in order to calculate the electron plasma density. By using a Consistency Check, (mainly, assuming fPE is the lower cutoff and calculating the remaining characteristic frequencies) it is found that when the plasma frequency is assumed to be the lower frequency cutoff, the cutoff at higher frequencies matches the calculated R=0 frequency. The guess-and-check system was used by [BARNHARDTETAL2009] with Voyager wide band waveform observations that have significantly higher spectral resolution that do the Galileo survey data used here. Hence, it is less likely that the Galileo spectral resolution will allow the routine use of guess-and-check. In addition to the non-thermal continuum radiation with a low frequency cutoff at fPE, another mode of propagating waves (called Z-mode) is sometimes also present. Based upon results from our consistency checks and in agreement with the previous work of Barbosa et. al. [1990], we conclude that there are two types of Z-mode radiation: weak, broadband Z-mode and intense, narrow band Z-mode. We interpret the L=0 frequency as the cutoff of the weak, broadband radiation, however, when the Z-mode emission becomes intense we have found that taking the L=0 frequency as the peak of the intense emission gives the most consistent estimate for fL=0. This is because as the intensity of this peak increases, the width of the emission appears to broaden due to limitations in the Fourier transform. Barbosa et al. [1990] demonstrated that taking the peak of the Z-mode as fL=0 yields the highest consistency in the determination of fPE, which concurs with our consistency checks. Thus, in regions where Z-mode is present, we can determine the electron density by either measuring the cutoff of the broadband Z-mode as fL=0 or the peak of the narrow band intense Z-mode as fL=0, and using the equations of cold plasma theory. When Galileo approaches the lobe of the magnetosphere, the density as well as fPE drops precipitously and approaches or even drops below the cyclotron frequency. Perraut et al. [PERRAUTETAL1998] studied one such case obtained by the Galileo plasma wave instrument. In order to determine the proper identification of the characteristic frequencies and determine the electron plasma density, we utilize our previous consistency check method. When an interpretation is found to be consistent with the spectrum, we assume temporal continuity of the cutoffs, and extend the interpretation into regions where a consistency check is not possible due to lack of features in the spectrum or a lack of magnetic field data. While there is no method for determining the density with certainty in these regions, we believe that assuming that the spectrum does not change greatly in a span on the order of minutes is appropriate and suitable to determine the density. Through an extensive analysis of Galileo spectra, there exist three possibilities for the interpretation of the low frequency cutoff of the emissions in the lobe. One interpretation, adopted by Perraut et al. [PERRAUTETAL1998], is to label the low frequency cutoff as the electron plasma frequency. This investigation has found numerous time periods when this interpretation is consistent with the spectrum, meaning that the other (calculated) frequencies match features present in the spectra. However, there are also a number of time regions where labeling the low frequency cutoff as the L=0 frequency gives calculated frequency values which match the features in the spectrum. Also, there are regions when interpreting the low frequency cutoff as either fPE or fL=0 does not give calculated frequencies which are consistent with the spectrum. This ambiguity when interpreting spectra cannot be removed at this time, however, we have attempted to systematically evaluate each time region. Ancillary Data ============== None Coordinate System ================= Included in this data set are two coordinate systems that ensure an accurate location of the density data points. The first system of coordinates consists of distance, longitude and magnetic latitude and is referred to commonly as the Jovigraphic coordinate system, or one that is fixed to the rotation of the planet. We have used the System III Jovigraphic coordinate system which uses the planet's magnetic field to measure the rotation. The radial distance is defined as the distance from the center of Jupiter to the spacecraft (in kilometers) divided by the radius of Jupiter at the equator (71492km). In the usual astronomical convention, the longitude is a west longitude which increases with time from an observer above the system, rather than just the angle of rotation about the z-axis. The other coordinate system included is referred to as the Jovicentric Solar Ecliptic (JSE) system. This rotating coordinate system has its x-axis point from Jupiter toward the Sun, and its y-axis is chosen to be in the ecliptic plane pointing toward dusk (thus opposing planetary motion). Its z-axis is parallel to the ecliptic pole. All X, Y, and Z coordinates are measured in Jovian radii (1 Rj = 71492km). Software ======== No software is included with this dataset, instead files are formatted as ASCII spreadsheet and contain data calibrated into physical units. Archive users should be able to work with this dataset without specialized software. Media/Format ============ This dataset was delivered 'on-line' as individual ASCII encoded text files with the exception of the browse plots, which are encoded in PNG (portable network graphic) format.
DATA_SET_RELEASE_DATE 2017-03-17T00:00:00.000Z
START_TIME 1996-05-25T12:00:00.000Z
STOP_TIME 2002-11-06T12:00:00.000Z
MISSION_NAME GALILEO
MISSION_START_DATE 1977-10-01T12:00:00.000Z
MISSION_STOP_DATE 2003-09-21T12:00:00.000Z
TARGET_NAME JUPITER
TARGET_TYPE PLANET
INSTRUMENT_HOST_ID GO
INSTRUMENT_NAME RADIO AND PLASMA WAVE SCIENCE
PLASMA WAVE RECEIVER
INSTRUMENT_ID PWS
INSTRUMENT_TYPE PLASMA WAVE SPECTROMETER
NODE_NAME planetary plasma interactions
ARCHIVE_STATUS IN PEER REVIEW
CONFIDENCE_LEVEL_NOTE Confidence Level Overview ========================= There are two important caveats for potential users of these data to consider. First, this data set was compiled through and shortly after the end of the Galileo mission. The individuals who did the majority of the work are no longer available. A thorough examination of all of the data, comparing the digitized frequency with the plasma wave spectrum needs to be carried out. Second, subsequent to the work on this data set, a detailed examination of Voyager wideband spectrogram data was carried out [BARNHARTETAL1998]. The Voyager exercise was useful in that it implemented the 'guess-and-check' method described above. Some effort was made to apply this to the Galileo data, but the lower spectral resolution of the Galileo survey data means that the technique is less useful. In short, this data set may suffer from improper spectral interpretation and care should be used to consider whether the results are reasonable, or not. In order to determine the density, we used an analysis tool that measured characteristic frequencies within Galileo plasma wave spectra. This frequency detection tool contained both a cutoff and peak detection algorithm which could measure either the cutoff or the peak of a spectrum, respectively. For this investigation, only the cutoff algorithm was used. Peak detection was made by-hand, meaning an operator manually labeled spectrum peaks from individual line plots. A confidence level was recorded for the measured frequency whether it was determined by the algorithm or was digitized manually. In order to record the confidence of the frequency measurements, data quality indices were given to each data point. The indices range from 0 to 3 with 0 being a cutoff with the highest confidence and 3 being the least. The amount of noise in the spectrum dictates the quality rating given to a particular data point. Points with a minimal amount of noise are given values of 0, whereas points where the spectral noise is so great that the cutoff is unclear are given a 1 or 2 index depending on the severity of the noise. A data quality index of 3 is given when there are obstructions in the spectrum blocking the ability for an accurate measurement, or when there is such a significant amount of background spectral noise that the spectra must be time-averaged over a longer period of time in order to interpret the cutoff. A data quality index of 's' was used for regions when Galileo was outside the magnetosphere and within the solar wind. The calculated densities are technically not magnetospheric densities but are included in this data set and may be useful for some end-users. Limitations =========== Since the low rate electric survey data are collected via sweep frequency spectrum analyzers, the spacing between the frequency bins in the receivers represents the ultimate accuracy with which a cutoff can be determined. As described in the PWS_INST.CAT, this spacing is not linear but instead increases with increasing channel center frequency. For example the lowest bands of the SFR (Sweep Frequency Receiver) are separated by about 3.4 Hz, while the upper bands of the HFR (High Frequency Receiver) are separated by over 400,000 Hz. At any given frequency, the accuracy of a measured cut-off or peak is only known up to the frequency discrimination capability of the receivers themselves. Because the electron density is proportional to the square of the plasma frequency, the uncertainty in the density expressed as a percentage, is twice the spectral resolution delta-f/f expressed as a percentage. It is important to note that if the plasma frequency is not present in the spectrum, the electron plasma density must be calculated using another characteristic frequency and the cyclotron frequency, which is directly proportional to the local magnetic field. If magnetic field data do not exist for a region where the plasma frequency cannot be measured, the density can not be determined. There are a small number of regions containing anomalous magnetic field data which may affect the density calculation. These magnetic field dropouts are sharp, momentary decreases or increases in the magnetic field which are instrumental effects and do not represent realistic occurrences. They are characterized by a magnetic fluctuation of several orders of magnitude in a span of less than one minute. Regions of anomalous magnetic field data which affected density measurements were changed manually from their anomalous values to the floater value -1 and the subsequent frequency and density calculations were changed appropriately.
CITATION_DESCRIPTION Ansher, J.A., Barnhardt, B.L., Richards, B.H., Gurnett, D.A., Kurth, W.S., GO-J-PWS-5-DDR-PLASMA-DENSITY-FULL-V1.0, GALILEO JUPITER PWS DERIVED PLASMA DENSITY FULL RES V1.0, NASA Planetary Data System, 2017.
ABSTRACT_TEXT Plasma electron number density from Jupiter's magnetosphere, derived from measurements of radio and plasma waves obtained by Galileo
PRODUCER_FULL_NAME DR WILLIAM S. KURTH
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