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The AMSR-E Level-2A product (AE_L2A) contains brightness temperatures available at a variety of resolutions that correspond to the footprint sizes of the observations. Each swath is packaged with associated geolocation fields.
AMSR-E/Aqua L2A Global Swath Spatially-Resampled Brightness Temperatures, Version 3
This is the most recent version of these data.
Changes to this algorithm include:
Complete recalibration to RSS Version 7 standard, as follows:
- Intercalibration with other microwave radiometers, particularly SSM/I F13 and WindSat
- Calibration with improved Radiative Transfer Model (RTM): RSS RTM Version 2011
- Updated ocean emissivity model (Meissner and Wentz 2012)
- Adjustment of the water vapor and oxygen absorptions, particularly the water vapor continuum absorption
- Improved calibration over land, based on heavily vegetated tropical rainforest scenes
- Nonlinearity correction at 18.7 GHz, brightness temperatures approx. 2 degrees K lower over land
- Adjustment to Antenna Pattern Coefficients (APC) for cross-polarization and spillover
- Slight shift to the 18.7 GHz center observation frequency
- Adjustment of effective hot-load temperature
Improved Radio Frequency Interference (RFI) flagging in response to new geostationary sources. For more details, see the Remote Sensing Systems RFI page:
- Replacement of the Geostationary_Satellite_Glint_Angle field with two new fields:
- For each observation, L2A now includes the location where the reflection vector intersects the geostationary sphere
COMPREHENSIVE Level of Service
Data: Data integrity and usability verified; data customization services available for select data
Documentation: Key metadata and comprehensive user guide available
User Support: Assistance with data access and usage; guidance on use of data in tools and data customization services
Geographic Coverage
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Once you have logged in, you will be able to click and download files via a Web browser. There are also options for downloading via a command line or client. For more detailed instructions, please see Options Available for Bulk Downloading Data from HTTPS with Earthdata Login.
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As a condition of using these data, you must cite the use of this data set using the following citation. For more information, see our Use and Copyright Web page.Ashcroft, P. and F. J. Wentz. 2013. AMSR-E/Aqua L2A Global Swath Spatially-Resampled Brightness Temperatures, Version 3. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/AMSR-E/AE_L2A.003. [Date Accessed].
Detailed Data Description
Level-2A brightness temperature files contain three swaths in HDF-EOS format:
All channel observations, except for 89.0 GHz, at a nominal interval of 10 km; 243 observations per approximately 2000 scans.
89 GHz observations from the A feedhorn AMSR-E scans; 486 observations per approximately 2000 scans. Note: Beginning 4 November 2004, the 89 GHz A-horn developed a permanent problem resulting in a loss of those observations. Consequently, after 3 November 2004, the High_Res_A_Swath data fields contain values of 0.
89 GHz observations from the B feedhorn AMSR-E scans; 486 observations per approximately 2000 scans.
- Low Res Swath Data Fields
- High Res A Swath and High Res B Swath Data Fields
- Geolocation Fields
- Global Attributes
Level-2A files contain data elements transferred directly from Level-1A antenna temperatures, but without 1:1 mapping. Users should match the two sets of data by the corresponding time of acquisition. Missing brightness temperature data are indicated by 0. Antenna temperature coefficients, effective hot load temperatures, calibration counts, and antenna coefficients are only provided for users who want to see how brightness temperatures were calculated for this data set. They are not required to view brightness temperatures.
Antenna temperature coefficients are three-dimensional arrays (3,10,2001). The first component represents slope, offset, and a quadratic term. The quadratic term is zero for all channels except 6.9 GHz. Brightness Temperatures (Tb) are not calculated for the first and last scans. All other scans have two non-zero coefficients for all channels, except 6.9 GHz, which has three non-zero coefficients. The last component is the number of scans per granule; it is variable.
For data with scale and offset values, the data values can be obtain in the specified units with the following equation:
data value in units = (stored data value * scale factor) + offset
Example: Tb (kelvin) = (stored data value * 0.01) + 327.68
Scaling factors and offsets are provided with the local attributes of each HDF-EOS file. You should check each file to ensure correct values. See the Software and Tools Web page for help reading these data.
For more information on the L1 data fields' format descriptions transferred to L2A, see Aqua AMSR-E Level 1 Product Format Description Document
This section explains the file naming convention used for this product with an example. The date and time correspond to the first scan of the granule.
Example file names:
Refer to Table 1 for the valid values for the file name variables listed above.
|file version number
|four-digit year
|two-digit month
|two-digit day
|hour, listed in UTC time, of first scan in the file
|minute, listed in UTC time, of first scan in the file
|orbit direction flag (A = ascending, D = descending)
|HDF-EOS data format
|Preliminary - refers to non-standard, near-real-time data available from NSIDC. These data are only available for a limited time until the corresponding standard product is ingested at NSIDC.
|Beta - indicates a developing algorithm with updates anticipated.
|Transitional - period between beta and validated where the product is past the beta stage, but not quite ready for validation. This is where the algorithm matures and stabilizes.
|Validated - products are upgraded to Validated once the algorithm is verified by the algorithm team and validated by the validation teams. Validated products have an associated validation stage. Refer to Table 3 for a description of the stages.
Stage 1
|Product accuracy is estimated using a small number of independent measurements obtained from selected locations, time periods, and ground-truth/field program efforts.
Stage 2
|Product accuracy is assessed over a widely distributed set of locations and time periods via several ground-truth and validation efforts.
Stage 3
|Product accuracy is assessed, and the uncertainties in the product are well-established via independent measurements made in a systematic and statistically robust way that represents global conditions.
Table 4 provides examples of file name extensions for related files that further describe or supplement data files.
|Extensions for Related Files
|Browse data
|Quality assurance information
|Product history data
|Metadata files
Each half-orbit granule is approximately 58 MB using HDF compression.
The daily data rate is approximately 2.5 GB. Each half-orbit granule is approximately 58 MB using HDF compression.
Coverage is global between 89.24°N and 89.24°S. See AMSR-E Pole Hole for a description of holes that occur at the North and South Poles. The swath width is 1445 km.
Spatial Coverage Map
Figure 1 shows a map of a typical day of coverage with 28 half-orbits.
Spatial Resolution
Data are resampled to spatial resolutions ranging from 5.4 km to 56 km. The sampling interval at the Earth's surface is 10 km for all channels. The 89.0 GHz channel also contains data sampled to 5 km. Please see 89 GHz Scan Spacing for a figure that illustrates A and B scan interleaving.
All channels are available at an unsampled Level-1B resolution. The higher-resolution channels are resampled to correspond to the footprint sizes of the lower-resolution channels. The Level-2A algorithm spatially averages the multiple samples of the higher-resolution data into the coarser resolution Instantaneous Field of View (IFOV) of the lower-resolution channels with the Backus-Gilbert method. The resulting brightness temperatures are called effective observations in contrast to the original or actual observations. The following table summarizes these relationships (Marquis et al. 2002):
|89.0 GHz
|36.5 GHz
|23.8 GHz
|18.7 GHz
|10.7 GHz
|6.9 GHz
|75 km x 43 km
56 km
|• o
|51 km x 29 km
38 km
|• o
|27 km x 16 km
21 km
|• o
|14 km x 8 km
12 km
|6 km x 4 km
5.4 km
• Includes Level-2A (smoothed) data
Each swath spans approximately 50 minutes. The number of satellite passes per day is a function of latitude as shown in AMSR-E Observation Times.
See the AMSR-E Data Versions Web page for a summary of temporal coverage for different AMSR-E products and algorithms.
Temporal Resolution
The data sampling interval is 2.6 msec for each 1.5-sec scan period for the 6.9 GHz to 36.5 GHz channels, and 1.3 msec for the 89.0 GHz channel. AMSR-E collects 243 data points per scan for the 6.9 GHz to 36.5 GHz channels, and 486 data points for the 89.0 GHz channel.
Software and Tools
For tools that work with AMSR-E data, including the AMSR-E Swath-to-Grid Toolkit, see the Tools for AMSR-E Data Web page.
For general tools that work with HDF-EOS data, such as hdp which dumps HDF data to binary, see the NSIDC HDF-EOS Web page.
Each HDF-EOS file contains core metadata with Quality Assessment (QA) metadata flags that are set by the Science Investigator-led Processing System (SIPS) at the Global Hydrology and Climate Center (GHCC) prior to delivery to NSIDC. A separate metadata file with an .xml file extension is also delivered to NSIDC with the HDF-EOS file; it contains the same information as the core metadata. Three levels of QA are conducted with the AMSR-E Level-2 and -3 products: automatic, operational, and science QA. If a product does not fail QA, it is ready to be used for higher-level processing, browse generation, active science QA, archive, and distribution. If a granule fails QA, SIPS does not send the granule to NSIDC until it is reprocessed. Level-3 products that fail QA are never delivered to NSIDC (Conway 2002). Only a QA file is produced when there are no L-2A brightness temperature data that qualify for retrieval.
Automatic QA
RSS generates AMSR-E Level-2A files from Level-1A files supplied by the Japan Aerospace Exploration Agency (JAXA). The Level-2A data files contain data flags set by JAXA for the Level-1A files and flags set by RSS. RSS quality assessment is performed when Level-2A files are generated. Resampled observations are generated wherever a valid Level-1A observation exists. This occurs when the Level1A_Scan_Chan_Quality_Flag is acceptable, and the actual observation at that location is within a plausible range. If neighboring observations are not acceptable, either because the entire neighboring scan is not acceptable, or because particular observations are implausible, the weights corresponding to the remaining acceptable observations are renormalized in order to calculate the resampled observation.
JAXA Data Quality Flags
The Data_Quality element contains the primary JAXA data quality flags. Aside from this element, JAXA provides additional quality information through reserved data values. For example, -9999 counts indicate missing data. RSS does not use the JAXA Data_Quality data element in Level-2A processing, but this element is included in the Level-2A data set for the benefit of other users.
RSS Quality Assessment
RSS adds three types of quality assessment indicators for each scan:
- 4-Byte Scan_Quality_Flag
- Identical flag repeated for the Low Swath, High 89A Swath, and High 89B Swath
- 2-Byte Channel_Quality_Flag for each channel
- 10 channels for the Low Swath
- 2 channels for the High 89A Swath
- 2 channels for the High 89B Swath
- 2-Byte Resampled_Channel_Quality_Flag for each resampled channel
- 30 channels for the Low Swath
The summary bit 0 of the Channel_Quality_Flag is automatically set whenever any of the bits in the Scan_Quality_Flag are set. Thus, the user can determine whether the data are useable by examining only the Channel_Quality_Flag without examining the Scan_Quality_Flag.
A Scan_Quality_Flag is provided for each scan. These flags pertain to all observations of a scan including all Level-1A and resampled channels.
|Summary Flag
|All higher bits are equal to zero
|The Scan Summary bit captures the conditions of all the other bits in the Scan_Quality_Flag. It is set to one if any of the bits 2 through 31 are set. The summary flag does not describe those characteristics that apply to a single channel.
|Antenna Spin Rate
|Within range
|Missing or out of range
|Bit 1 is set if the antenna spin rate is out of range, which is defined as 4.167 percent from nominal.
|Within range
|Missing or out of range
|Bit 2 is set if the position or velocity of the navigation data for that scan is out of bounds. The bounds are 6500-8000 km from the Earth's center to the satellite and 4-10 km/sec for spacecraft velocity. Note that these bounds are extremely large, and this flag is intended to identify bogus data rather than real anomalies in the navigation.
|RPY Variability
|Within range
|Out of range
|Bit 3 is set if the roll, pitch, or yaw variability from scan to scan is out of bounds. Only Midori-2 AMSR has this problem. A scan-to-scan variation in either roll, pitch, or yaw that exceeds 0.05 degrees is considered out of bounds.
|Within range
|Out of range
|Bit 4 is set whenever the roll, pitch, or yaw exceeds 2.0 degrees.
|Earth Intersection
|All on earth
|Some not on Earth
|Bit 5 is set if any of the observation locations fail to fall on the Earth. This occurs during large orbit maneuvers.
|Hot Load Thermistors
|Within range
|Missing or out of range
|Bit 6 is set whenever the thermistors on the AMSR hot load are out of bounds, which is defined as their rms variance being greater than 10K or any single thermistor being outside the range 283.17K - 317.16K for AMSR-E and 285.17K - 316.94K for Midori-2 AMSR. When these temperature limits are converted to thermistor counts, they correspond to the minimum and maximum allowable count values.
|Not Used, Always 0
All flags in this data element are set in response to characteristics of the calibration measurements for a specific AMSR channel. In general, calibration measurements (hot and cold) are averaged over adjacent scans to compute the antenna temperatures from raw counts. The default process is to average calibration counts over a range from one scan before the scan to one scan after the scan although only a subset of these calibration measurements is used if some are unacceptable. The Calibration Quality Flags are set on the basis of the same calibration measurements over which the calibration averaging is performed. See the Calibration section of the AMSR-E Instrument Document for details of AMSR-E calibration. Also, it is important to note that the flag called Level1A_Scan_Chan_Quality_Flag was replaced by three new flags:
- Channel_Quality_Flag_6_to_52 for Low_Res_Swath
- Channel_Quality_Flag_89A for High_Res_A_Swath
- Channel_Quality_Flag_89B for High_Res_B_Swath
|Summary Flag
|Questionable or bad
|Bit 0 is a summary flag. This bit is set if any of the bits 2 through 15 are set. Note that bit 11 is set if any of the geolocation error bits in the Scan_Quality_Flag are set. Hence, if any errors are reported by the Scan_Quality_Flag, Bit 0 of all Channel_Quality_Flags is set to 1.
|Bit 1 indicates whether Level-2A brightness temperatures are computed for this channel. When there are severe problems, as indicated by any of the bits 2, 3, 4, or 12 being set, no brightness temperatures is computed and bit 1 is set to 1.
|Scan Number
|Not first or last scan
|First or last scan
|Bit 2 is set for the first and last scans of each Level-2A file. Because the calibration and quality checking of each scan uses both the adjacent scans, the calibration and quality checking can not be performed on the first and last scan of the file.
|Serious Calibration Problem
|No, all is good
|Bit 3 is set if one of the following occurs:
1.The automatic gain control has changed from either the preceding or succeeding scan.
2.The receiver automatic gain control is out of bounds.
3.All calibration counts for either or both the hot load and cold sky are out of bounds.
|Hot-cold Counts Check 1
|> 0
|<= 0
|Bit 4 is set if the cold calibration counts are the same or greater than the hot calibration counts.
|Within bounds
|Out of bounds
|Bit 5 is set if the hot load thermistors are out of range. The acceptable range for the thermistors is described above for bit 6 of the Scan_Quality_Flag.
|Teff Type
|Dynamic Teff
|Static Teff
|Bit 6 equals 0 denotes that the dynamic Teff is used. This is the usual condition. Bit 6 equals 1 denotes that the static Teff is used, which should rarely if ever occur.
No.of Cold Counts
|>= 8
|< 8
|Bit 7 is set if there are fewer than 8 cold counts that are in bounds.
|No. of Hot Counts
|>= 8
|< 8
|Bit 8 is set if there are fewer than eight hot counts that are in bounds.
|Hot-cold Counts Check 2
|>= 100
|< 100
|Bit 9 is set if the difference between hot and cold counts is less than 100.
|Hot-cold Counts Check 3
|>= Channel minimum
|< Channel minimum
|Bit 10 is set if the difference between hot and cold counts is less than a channel-dependent threshold.
|No problem exists
|Problem exists
|Bit 11 is set if there is a geolocation error as reported by the Scan_Quality_Flag.
|Bit 12 is set to 1 if Teff is not available. This should rarely if ever occur.
|Not Assigned, Always 0
A Resampled_Channel_Quality_Flag is provided with the L2A data, but it is redundant with the Channel_Quality_Flag and does not usually need to be used. For the lower frequency channels, the first two bits (0 and 1) of the Channel_Quality_Flag are copied to the first two bits of the corresponding Resampled_Channel_Quality_Flag. For the 89A Channels, the first two bits (0 and 1) of the Channel_Quality_Flag are copied to the first two bits of the corresponding Resampled_Channel_Quality_Flag. For the 89B Channels, the first two bits (0 and 1) of the Channel_Quality_Flag are copied to bits 2 and 3 of the corresponding Resampled_Channel_Quality_Flag.
|Equal to corresponding bits of corresponding channels
|Not assigned
Before working with any channel of data, users should confirm that both the Scan_Quality_Flag and the Channel_Quality_Flag indicate that the scan is acceptable.
Operational QA
AMSR-E Level-2A data arriving at GHCC are subject to operational QA prior to use in processing higher-level products. Operational QA varies by product, but it typically checks for the following criteria in a given file (Conway 2002):
- File is correctly named and sized
- File contains all expected elements
- File is in the expected format
- Required EOS fields of time, latitude, and longitude are present and populated
- Structural metadata is correct and complete
- The file is not a duplicate
- The HDF-EOS version number is provided in the global attributes
- The correct number of input files were available and processed
Science QA
AMSR-E Level-2A data arriving at GHCC are also subject to science QA prior to use in processing higher-level products. If less than 50 percent of a granule's data is good, the science QA flag is marked suspect when the granule is delivered to NSIDC. In the SIPS environment, the science QA includes checking the maximum and minimum variable values, the percentage of missing data, and out-of-bounds data per variable value. At the Science Computing Facility (SCF) and also at GHCC, science QA involves reviewing the operational QA files, generating browse images, and performing the following additional automated QA procedures (Conway 2002):
- Historical data comparisons
- Detection of errors in geolocation
- Verification of calibration data
- Trends in calibration data
- Detection of large scatter among data points that should be consistent
Geolocation errors are corrected during Level-2A processing to prevent processing anomalies such as extended execution times and large percentages of out-of-bounds data in the products derived from Level-2A data.
The Team Lead SIPS (TLSIPS) developed tools for use at SIPS and SCF for inspecting the data granules. These tools generate a QA browse image in Portable Network Graphics (PNG) format and a QA summary report in text format for each data granule. Each browse file shows Level-2A and Level-2B data. These are forwarded from RSS to GHCC along with associated granule information where they are converted to HDF raster images prior to delivery to NSIDC.
Please refer to the AMSR-E Validation Data Web page for information about data used to check the accuracy and precision of AMSR-E observations.
Data Acquisition and Processing
Please refer to the AMSR-E Instrument Description document.
Data Source
AMSR-E/Aqua L1A Raw Observation Counts are used as input to calculating the Level-2A brightness temperatures.
The objective of the Level-2A algorithm is to bring the Level-1A antenna temperatures to a set of common spatial resolutions using a set of weighted coefficients. The algorithm resamples Level-1A antenna temperatures and converts them to Level-2A brightness temperatures.
The resampled antenna temperature (Tac) is defined as a weighted sum of observed antenna temperatures (Tai):
ai = weighting coefficients
Antenna temperature observations are corrected for cold-space spillover and cross-polarization effects to obtain brightness temperatures averaged over the normalized crossover-polarization antenna pattern. The observed brightness temperatures(Tbi) are expressed as:
Tb(ρ) = brightness temperature at location ρ
Gi(ρ) = antenna gain pattern corresponding to the specific observation
Antenna temperature coefficients, effective hot load temperatures, calibration counts, and antenna coefficients are only provided for users who want to see how brightness temperatures were calculated for this data set. They are not required to view brightness temperatures.
Each Level-2A (effective) observation within a single instrument scan is calculated using coefficients that describe the relative weights of the neighboring Level-1A (actual) observations. Coefficients are unique for every position along the instrument scan, yet they do not vary from scan to scan. The Backus-Gilbert method produces the weighting coefficients for Level-1A data. Antenna patterns and relative geometry are known a priori, allowing weighting coefficients to be calculated before observations are collected. Although the Backus-Gilbert method can, in principle, be used to construct effective observations corresponding to gain patterns either smaller or larger than those in the actual observations, the noise amplification from smaller gain patterns (deconvolution) is typically very high.
Calculation of weighting coefficients requires specification of the shape of the target pattern, the location of the target pattern relative to the actual measurements, the set of actual observations used, and the smoothing parameter for each constructed observation. Actual observations within an 80 km radius of the constructed pattern are considered for possible contributors to the construction. Observations that are too far from the target pattern to play a role in the construction are assigned a weight of zero by the algorithm. Weighting coefficients are computed based on a simulation of the antenna patterns for a portion of a circular orbit around a spherical earth.
The smoothing factor at each point across the scan of each Level-2A data set is chosen in the following way: The algorithm applies the same amount of smoothing at the center to observations close to the edges. This ensures that noise decreases as the spatial density of the actual observations increases toward the edges. For construction of observations at the extreme edges, sufficient smoothing is added to keep noise at the edges from exceeding the noise at the center. For a given Level-1A channel, noise decreases as the resolution of the constructed pattern becomes larger, and the number of useful actual observations increases (Ashcroft and Wentz 2000).
Processing Steps
The algorithm reads an entire file (one half orbit) of Level-1A data at a time and uses calibration coefficients to convert antenna temperatures to brightness temperatures. Coefficients embedded in the data are discarded, and new values are calculated. The algorithm applies weighting coefficients from a table of values to resample the Level-1A data using Equation 1. The weighting coefficients corresponding to each constructed observation are stored as a 29 x 29 array, which applies weights to actual observations ± 14 scans and ± 14 locations along the scan from the constructed observation. Most of the coefficients in the array are zero. In an ideal case, weighting coefficients are applied to each corresponding constructed target pattern within the scan. Level-1A data produce unsmoothed Level-1B brightness temperatures and smoothed Level-2A brightness temperatures using Equation 2 ( Ashcroft and Wentz 2000).
Version History
Changes to this algorithm include:
Complete recalibration to RSS Version 7 standard, as follows:
- Intercalibration with other microwave radiometers, particularly SSM/I F13 and WindSat
- Calibration with improved Radiative Transfer Model (RTM): RSS RTM Version 2011
- Updated ocean emissivity model (Meissner and Wentz 2012)
- Adjustment of the water vapor and oxygen absorptions, particularly the water vapor continuum absorption
- Improved calibration over land, based on heavily vegetated tropical rainforest scenes
- Nonlinearity correction at 18.7 GHz, brightness temperatures approx. 2 degrees K lower over land
- Adjustment to Antenna Pattern Coefficients (APC) for cross-polarization and spillover
- Slight shift to the 18.7 GHz center observation frequency
- Adjustment of effective hot-load temperature
Improved Radio Frequency Interference (RFI) flagging in response to new geostationary sources. For more details, see the Remote Sensing Systems RFI page:
- Replacement of the Geostationary_Satellite_Glint_Angle field with two new fields:
- For each observation, L2A now includes the location where the reflection vector intersects the geostationary sphere
Error Sources
The Level-2A data set includes unsmoothed Level-1B data derived from antenna temperatures. See the AMSR-E Instrument Description Web page for a description of the error sources associated with radiometer calibration.
Error on a constructed brightness temperature observation arises from two sources. The first source of error is a mismatch between the ideal antenna pattern and the construction, and the second is random measurement error. The variance of a constructed brightness temperature is independent of the actual temperature field, depending only on the weighting coefficients and the observation error of each observed brightness temperature. The effect of random measurement error is more easily quantified than the effect of fit error. Increased smoothing reduces the noise factor but degrades the fit. This tradeoff is most noticeable at the edges of the scan. Fit and noise factor near the center of the scan are optimized for fit. See the Derivation Techniques and Algorithms section of this document for more information. As a result of the spatial averaging that produces the Level-2A data, errors of neighboring observations within any single channel are somewhat correlated. Errors between channels are not correlated in any case. While the Level-2A data set is well-suited for applications that require a combination of multiple channels of observations, the user should recognize that errors on observations within a single channel are not necessarily independent (Ashcroft and Wentz 2000).
Along-Scan Error
An along-scan error is caused by AMSR-E's cold mirror or warm load entering the FOV of the feedhorns, or by the main reflector seeing part of the spacecraft. The RSS performed an analysis of the AMSR-E along-scan error and developed a correction.
In spite of RSS's best efforts to accomplish a robust AMSR-E along-scan temperature correction, users should note that some contamination remains in the 14 pixels at the beginning of each scan line. Users should determine whether to include those pixels based on their specific research application and the effects of the contamination described below.
In early 2007, researchers at NSIDC conducted an along-scan error analysis by examining brightness temperature distributions for each sample position in three different, relatively uniform climatic regions over a sufficiently long time period to eliminate effects from random, transient events. The three regions included a portion of Antarctica, an area of the Indian Ocean south of Australia, and an area of African jungle in the Salonga National Park region of the Democratic Republic of the Congo.
NSIDC concluded that even after the RSS along-scan correction, a significant cold bias remains in brightness temperature measurements in all channels over Antarctic regions from the beginning of each scan line. There is also some evidence of a cold bias in 7 GHz channels over jungle areas. There does not appear to be a bias in any channels observing ocean areas.
Along-scan Error Analysis and Applied Correction Made by RSS
To determine the magnitude of this effect at the swath edges, RSS computed the difference between the AMSR-E antenna temperature and the radiative transfer model. This difference was plotted versus along-scan cell positions in Figure 2, where the antenna temperature differences have been averaged over the first year of AMSR-E operation. The cell positions go from 1 to 243. The antenna temperature differences are shown for all 14 AMSR-E channels. Each channel is color-coded and is offset by 1 K so that the results can be easily visualized. The straight horizontal lines in Figure 2 are the zero reference lines. The spacing between the horizontal lines is 1 K.
In general, most channels show little along-scan variation. However there are three channels (7 GHz v-pol, 7 GHz h-pol, and 11 GHz v-pol) that show a significant cold bias at the swath edges. Some of the other channels exhibit similar but smaller behavior. The most affected is the 7 GHz v-pol which has a cold bias of about 10 K at the beginning of the scan.
Based on the results shown in Figure 2, a correction table was made.This table provides an antenna temperature adjustment for each AMSR-E channel that is a function of the along-scan cell position. This adjustment eliminates the along-scan error in the mean sense. RSS repeated this analysis and stratified the data into two half-year time periods and into two orbit segments (ascending and descending). The variation in the along-scan error for these four stratifications is about 0.1 K, thereby showing the along-scan error is a constant feature. This along-scan adjustment was implemented into the standard AMSR-E processing algorithm. However, some caution should still be exercised when using pixels 1-14 for the 7 GHz channel for which there may be some residual along-scan error.
Position-in-Orbit Description
The AMSR-E Level-2A product follows the granule conventions designed and set in L-1A. Each file provides some overlap to the previous and next file. This supports the ability to do 1 to 1 file processing. The overlap provides each granule with a ~10 scan look into the forward and backward neighboring files.
This ~10 scan overlap at the edges of the file belongs with the neighboring files, and eliminates the need to open and read the files before and after the file in use. When deciding which portion of the overlap to use, choose the half of the overlap that is contiguous with the swath in the file and ignore the overlap at the edge of the file.
A misregistration relative to coastlines and other land features was recognized in the AMSR-E brightness temperature imagery. The error in geolocation was about 5 - 7 km and was due to a misalignment of the AMSR-E sensor relative to the spacecraft. The problem was fixed by a trial-and-error method in which various roll, pitch, and yaw corrections were applied to the AMSR-E alignment until proper registration was obtained.
A separate geolocation analysis was done for each channel, which showed that for a given frequency the v-pol and h-pol channels are well aligned. Furthermore, the 19, 23, and 37 GHz Channels are also well aligned with each other. Corrections to the geolocation for Channels 19 GHz through 89 GHz were implemented in Version B06 algorithm.
In Version B07, the 7 and 11 GHz Channels were resampled to match the locations of the higher frequencies since it was determined that the 7-GHz and 11-GHz horns are pointing in a slightly different direction than the 19, 23, and 37 GHz horns. This required re deriving the sampling weights with the center of the target cell positioned at the location of the 19 GHz Channel rather than at the 7 or 11 GHz footprint position. One drawback is that the un-resampled 7 and 11 GHz observations are missing an exact specification of latitudes and longitudes.
AMSR-E's calibration system has a cold mirror that provides a clear view of deep space (a known temperature of 2.7 K) and a hot reference load that acts as a blackbody emitter; its temperature is measured by eight precision thermostats. After launch, large thermal gradients due to solar heating developed within the hot load, making it difficult to determine from the thermostat readings the average effective temperature, or the temperature the radiometer sees.
Before 07 January 2005 (B01 and B02 algorithms)
Remote Sensing Systems (RSS) used coincident Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Special Sensor Microwave/Imager (SSM/I) satellite data over oceans to estimate the effective hot load temperature. A radiative transfer model used these data to compute the intensity of radiation entering the feedhorns. The model took into account different view geometries and channel differences between AMSR-E, SSM/I, and TMI. This process essentially provided earth-target calibration points, which were combined with the cold mirror temperature to compute a two-point linear extrapolation that yielded the hot load effective temperature for 10.7 to 89 GHz.
Before March 2006 (B03 through B06)
To estimate the effective hot load temperature, RSS assumed that the effective temperature is independent of channel polarization and then used climatic cloud and water vapor data along with daily SST and NCEP winds, to define the effective temperature as a function of the observed polarization differences.
After March 2006 (B07 and newer algorithms)
Computing the Effective Temperature of the AMSR-E Hot Load
An on-orbit calibration is required for AMSR-E because of a design flaw in the AMSR-E hot load. For the initial method, the effective temperature of the AMSR-E hot load was estimated using SSM/I and TMI, sea-surface temperature (SST), wind, vapor, and cloud water observations. Although the old method of computing Teff worked well, it created a dependency on the SMM/I and TMI observations which could delay processing. Thus, a hot load calibration procedure that did not rely on other satellites was desirable.
The primary reason SSM/I and TMI were required was to specify the water vapor and cloud water. The other two relevant parameters, SST and wind, can be obtained with sufficient accuracy from NCEP Final Analysis fields. To remove the dependence on the SSM/I and TMI vapor and cloud retrievals, modifications were made to the way in which the effective temperature is computed. The new method is based on the assumption that the effective temperature does not depend on polarization, for example, it is the same for v-pol and h–pol. This assumption seems to be valid based on both empirical data (v-pol and h-pol effective temperatures coming from the SSM/I-TMI method are similar) and physical considerations (hot-load is an unpolarized source). Under this assumption, the method can be modified to make it insensitive to the specification of vapor and cloud.
The first step of the process is to estimate the value of Effective Temperature (Teff) for each AMSR-E observation. The following expression is used to estimate the effective temperature
TC is the brightness temperature for the cold space observation
TAi,rtm is the antenna temperature computed from the RTM given the ancillary information such as SST, wind, vapor, and cloud.
The subscript i denotes AMSR channel.
The term ρi is the following ratio of the radiometer counts
subscripts C, H, and E denote cold-space counts, hot-load counts, and earth-viewing counts, respectively.
Equation 1 is a linear extrapolation based on the cold-calibration point and the earth-calibration point.
The next step is to form a linear combination of effective temperatures that are relatively insensitive to variations in vapor, cloud, and to some degree wind. For a given frequency, this linear combination of Teff is represented by the following equation
subscript j denotes channel frequency, pij and qij are static regression coefficients
W is wind speed. The summations are over the 10 AMSR channels from 7 to 37 GHz. However, a slightly modified version is used for the 89 GHz Channels. The function ∧(W) smoothly goes from 0 to 1 as the wind speed goes from 3 to 11 m/s. Thus, the first term in Equation 3 corresponds to low-to-moderate winds, and the second term corresponds to moderate-to-high winds. Two wind speed terms are used because the wind speed response of the RTM is highly non-linear. The wind speed value comes from NCEP Final Analysis fields.
The regression coefficients pij and qij are found from computer simulations so as to minimize the error in the estimation of effective temperature due to variations in wind, vapor, and cloud. The method for finding the coefficients is similar to that used to find the regression coefficients for the geophysical retrieval algorithms. In essence, Equation 3 is an algorithm for estimating the hot load effective temperature.
The next step is to correlate with the thermistor temperatures and orbit position. This is done by using the following expression
subscript k denotes the eight hot-load thermistors
Tk are the thermistor temperatures
α - 90 degrees is the orbit position angle relative to the ascending node crossing of the ecliptic plane.
There are 27 regression coefficients to be found for each frequency: akj, bkj, and ck. These regression coefficients are allowed to vary in time. A ±150 orbit moving time window is used to specify the coefficients. The weighting function for the time window is triangular, going to zero at 150 orbits before the current orbit and 150 orbits after the current orbit. Thus, the time scale for the variation in the akj, bkj, and ckj coefficients is approximately 10 days.
There are three additional improvements that were implemented. The first relates to the SSTs that were used to specify TAi,rtm. The SST values come from Reynolds' weekly Optimum Interpolation (OI) SST product. Since this SST product is a weekly value, it does not include any diurnal components. For the AMSR-E early afternoon orbit, diurnal variations in SST can be large when there are light winds. Accordingly, a diurnal adjustment is applied to the OI SST model the diurnal variability of SST.
The last improvement is to apply a smoothing function to the estimation of the radiometer gain, which is given by the following equation
The gain is expected to vary smoothly over the orbit. Random errors in the estimation of shows up as rapid variations in G. A smoothing function is applied to G to remove the variability on short time scales (minutes), thereby further reducing the error in the estimation.
Recalibration of AMSR-E Hot Load and Along-Scan Adjustments
The correction of the AMSR-E geolocation problems required that the AMSR-E sensor alignment be rolled relative to the spacecraft frame by 0.09 degrees. Changing the roll of the sensor results in a change in the incidence angle. With this roll adjustment, the true incidence angle was found to vary across the swath contrary to the assumption that it was nearly constant. This modification of the incidence angle has small but significant effects on the AMSR-E calibration. The calibration is based on measurements of the ocean surface, and the emission from the ocean surface varies with incidence angle. To address the change in incidence angle, AMSR-E was completely recalibrated and a new hot load effective temperature table was found. The along-scan antenna temperature adjustment was also recalculated using the new roll angle Thus, the along-scan errors in the antenna temperatures are significantly reduced except near the swath edge where the cold mirror interferes with the field of view.
Earth incidence angle is computed and included in Level-2A files in data field Earth_Incidence. These variable earth incidence angle data should be used appropriately, especially for geophysical retrievals depending upon incidence angle. Using the previously assumed constant incidence angle will likely result in along scan bias. The Level-2A Brightness Temperature data set is intended to be a faithful representation of the brightness temperatures observed by the instrument. Thus, due to the sensor-to-spacecraft roll, incidence angle is variable along scan, and brightness temperatures are correspondingly variable along scan. This along scan variability in observed brightness temperatures is not removed and should be accounted for by using the computed Earth_Incidence.
Implementation of Flagging Algorithm for RFI from Geostationary TV Satellites
As part of the SST and wind validation activity, anomalous retrievals were found off the West Coast of Europe and in the Mediterranean Sea. After some investigation, these erroneous retrievals were determined to be due to Radio Frequency Interference (RFI) from a European satellite TV service. ASMR-E is receiving the broadcast from two European geostationary satellites that operate near the 10.7 GHz band. The satellite TV signal is reflecting off the ocean surface into the AMSR-E field of view. AMSR-E bandwidth at 10.7 GHz is 100 MHz, whereas the protected band is only 20 MHz. The TV signal is coming from the unprotected part of the 100-MHz band.
The TV RFI was determined to be coming from two satellites: one positioned at a longitude of 13 degrees E above the equator and the other at 19 degrees E. An algorithm was developed that computes the angle between AMSR-E look vector and the specular reflection vector for the TV RFI. This angle is called the RFI angle. Small RFI angles correspond to cases in which the TV RFI is being reflected off the ocean surface directly towards AMSR-E.
When the RFI angle is less than 12 degrees, in general the observation should be flagged as RFI contaminated. However in the North Sea, the RFI is particularly strong. For this region, an RFI angle of 17 degrees is the threshold.
Correction for August-September 2003 Aqua Pitch Error
An anomaly occurred between 12 August 12 and 6 September 2003 due to an error in knowledge of the spacecraft pitch. In the Level-1A data, the definitive ephemeris was used for this period so the geolocation values are correct. However, the fact that the anomaly caused Aqua to be inadvertently pitched during this time period was not accounted for in the Level-1A data. In the Level-2A algorithm, the satellite pitch anomaly during this period was modeled as a ramp function and corrected.
Correction for Lunar Radiation Entering the AMSR-E Cold Mirror
Twice each month the moon enters the Field of View (FOV) of the AMSR-E cold mirror. The moon's surface temperature varies from 120 K night to 370 K day and has a relatively high emissivity. As a result, the moon acts as a source of contamination to the cold sky measurement.
A correction was applied to remove the lunar contamination. The correction depends upon the following factors:
- The angle between the vector going from the satellite to the moon and the boresight vector of the cold mirror. This is the dominant term. When this angle becomes small, a few degrees or less, lunar contamination becomes significant. This angle is called the lunar angle.
- The phase of the moon. A full moon is hotter than a new moon and hence has a higher brightness temperature.
- The distance from the satellite to the moon. Radiation intensity falls off as the inverse of the square of the distance.
The lunar antenna temperature contribution to the cold sky observations is computed and then is scaled in terms of cold counts. The lunar cold counts are subtracted from the AMSR-E cold count observations to obtain a cold count value free of lunar contamination. For the case of 89 GHz, when the lunar angle is less than one degree, the lunar contamination is too large to perform the correction and these observations are flagged as bad and are not processed. The excluded observations are extremely rare. The accuracy of this correction is estimated to be in the order of 0.1 K.
Adjustment to Match the 89A and 89B Observations During Resampling
When the 89 GHz Channels are resampled to lower spatial resolutions, the observations from the A-horn and the B-horn are combined. However, the incidence angles for these two horns are different with the B-horn incidence angle being about 0.6 degrees smaller than the A-horn. To compensate for the difference in incidence angle, the following adjustments were made to the A-horn measurements before resampling
These expressions were found from doing linear regression of actual A-horn and B-horn observations over the first two mission years of AMSR-E. The application of these equations normalizes the A-horn measurements to the B-horn incidence angle.
Implementation of using UT1 time to compute the Earth rotation angle.
Aqua's position, velocity, and attitude vectors are given in terms of the J2000 inertial coordinate system. To compute Earth latitudes and particularly longitudes, it is necessary to compute the Earth rotation relative to the J2000 systems. The proper calculation requires using the UT1 time, which can be as much as one second different from UTC time. To obtain UT1, the Level-2A algorithm accesses the U.S. Naval Observatory database each day to obtain the current UT1. One advantage of this procedure is that it is independent of leap seconds; therefore, there is no discontinuity in the geolocation parameters when a leap second occurs.
Intercalibration with SSM/I F13 and WindSat
F13 and WindSat provide a backbone of consistent long-term observations, relatively free from diurnal effects. Local observation times for F10, F11, F14, F15, and F16 all drift by two to six hours over the years, so these instruments have been measuring a continuously differing viewpoint in Earth's diurnal cycle. The larger the diurnal drift, the more challenging it is to distinguish from sensor drift. AMSR-E is in a stable orbit on Aqua, so diurnal drift is not a problem. However, AMSR-E observes local times of 1:30 a.m./p.m.; AMSR-E day and night passes observe significantly more pronounced diurnal variations than F13 and Windsat passes at approximately 6:00 a.m./p.m.. For more information about intercalibration choices and methodology, please refer to the RSS Crossing Times Web page.
References and Related Publications
Contacts and Acknowledgments
Dr. Peter Ashcroft
Remote Sensing Systems
Santa Rosa, CA 95401
Dr. Frank Wentz
Remote Sensing Systems
Santa Rosa, CA 95401
Document Information
March 2003


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Home >> Course Descriptions >> College of Education
Sports Management.
Three semester hours.
This course deals with the development of local, state, and national policies concerning athletic eligibility, contest management, and other managerial concerns. Prerequisites: Senior standing.
Home - General Information - Student Services -
Academic Undergraduate Regulations -
Undergraduate Degrees - Academic Graduate Regulations -
Graduate Degrees - Course Descriptions - Faculty -
Appendix A - Appendix B - Appendix C - Appendix D

subset: commoncrawl


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System Requirements
- 2GHz or faster processor with SSE2 support; dual-core processor required for HDV or AVCHD editing; Intel Core i7 required for XAVC-S
- Microsoft Windows 7 with Service Pack 1, Windows 8, or Windows 10 (64-bit versions only)
- Microsoft DirectX 9 or 10 compatible sound and display driver
- Windows Media Player (required if importing/exporting Windows Media formats)
Mac OS
- 64-bit multicore Intel processor
- Mac OS X v10.11 through macOS v10.13
For both Windows and Mac OS
- 4GB of RAM
- 10GB of available hard-disk space to install applications; additional 12GB to download all optional content 1280x800 display resolution (at 100% scale factor)
- DVD-ROM drive (for installation from DVD)
- DVD burner required to burn DVDs
- Internet connection required for product activation and content download**
Language Versions
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Mac OS
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Adobe Premiere Elements supported import/export formats include:
AVCHD (import only), DV-AVI (import/export on Windows, import only on Mac OS), DVD, H.264, HDV, MPEG-1 (import only), MPEG-2, MPEG-4, MP3, QuickTime, Windows Media (Windows only), and many more. Import/export of some formats may require activation via an Internet connection. Activation is fast, easy, and free.
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* This product may integrate with or allow access to certain Adobe or third-party hosted online services ("Online Services"). Online Services are available only to users 13 and older and require agreement to additional terms of use and the Adobe Privacy Policy (see www.adobe.com/go/terms). Online Services are not available in all countries or languages, may require user registration and may be discontinued or modified in whole or in part without notice. Additional fees or subscription charges may apply. 4k supported cameras include GoProHero 4 Black, Samsung S8, DJI OSMO X3, DJI Mavic Pro, DJI Phantom 4, iPhone 8+, iPhone X.


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LOS ANGELES (AP) — Woody Harrelson and Elizabeth Banks jumped at the chance to take supporting roles in "The Hunger Games," a film about children who are forced to compete in a live televised death match in the not-too-distance future.
LOS ANGELES (AP) — Woody Harrelson and Elizabeth Banks jumped at the chance to take supporting roles in "The Hunger Games," a film about children who are forced to compete in a live televised death match in the not-too-distance future.
Why? They were moved by Suzanne Collins' book series and the script that the author helped co-write for the movie, opening in theaters Friday.
"We all agree the book is such a page turner and it's just the storytelling," Banks said in a recent interview.
"You know there are oppressive governments all over the world. We have this class warfare happening between the 1 percent and the 99 percent," she said. "We've got rebellious teenagers who are finally standing up for something. I think that everything that's going on (in the film) resonates in today's world and with today's audiences."
Harrelson plays Haymitch Abernathy, a mentor to "Hunger Games" contestants Katniss (Jennifer Lawrence) and Peeta (Josh Hutcherson). Haymitch is eccentric, crass and drinks too much, but knows how the games work.
Harrelson said his only issue with the film, and what he and director Gary Ross talked about a lot, was the degree to which Haymitch would be drunk "because I'm always one who likes to go over the top and luckily he pulled me back."
The film's seasoned performers are big supporters of star Jennifer Lawrence.
Donald Sutherland, who plays President Snow, said the "Winter's Bone" Oscar nominee should change her name to Jennifer Lawrence Olivier after the late actor Laurence Olivier.
He said his favorite scene involving Lawrence is when her Katniss character bonds with a younger "Games" contestant named Rue.
"It's lucky I didn't storm the screen, you know? It was so moving, she did it so beautifully. What a wonderful actor she is."
Harrelson called Lawrence's performance "perfect," and said "the sky's the limit for her."
"I don't know what will happen for her career, but I can't imagine that it won't go for another 80 years," he said.
The actors understand the success of "The Hunger Games" will likely mean more films in the franchise, and they are OK with that.
"It's horrible to have future work," joked Lenny Kravitz, who plays a stylist in the movie.
"Or to know a paycheck is coming," added Banks.


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Tuesday, June 1, 2010
TWD White Chocolate Brownies
24 comments:
- Romaine said...
Enjoyed your comment about the orange sugar. I love doing that too.
- June 1, 2010 at 5:01 AM
- Karen said...
Yum! Orange Buttercream sounds delicious to top these!
- June 1, 2010 at 8:00 AM
- chocolatechic said...
I melted my butter and chocolate in the microwave. I never do it on the stove.
Saves time and a bowl to wash.
Yours look wonderful.
- June 1, 2010 at 8:19 AM
- SiHaN said...
well i must say the orange buttercream looks excellent.
- June 1, 2010 at 9:27 AM
- Tia said...
poptarts! and orange sugar. yum. yum... the colors and presentation look fantastic!
mine morphed into Salty/Sweet Brown Butter Frosted Brownies!
- June 1, 2010 at 10:12 AM
- Joy said...
Hi Cindy!
Thanks so much for stopping by my blog and leaving such a sweet comment- you made my day! I love your site as well, and I can truly relate to your passion for baking. The little "About Me" paragraph you wrote brought a smile to my face (I used to long for an easy bake oven as well... isn't it funny that now, I consider the kitchen supply place my "toy store" :) Some things never change).
Beautiful White Chocolate Brownies- the citrus accent sounds like a lovely addition. Great job!
I hope you'll visit "Hot Oven, Warm Heart" often- I always love hearing from another enthusiastic baker! And I'll certainly be back here soon too!
- June 1, 2010 at 10:45 AM
- Valerie said...
The orange buttercream cream looks luscious! Beautiful work. You're not alone, I also have too much fun rubbing zest into sugar. It makes the kitchen smell so fresh.
- June 1, 2010 at 11:49 AM
- mike said...
So glad they worked out for you! They look wonderful - and happy that you bypassed the meringue - do what works for YOU! Nicely presented!
- June 1, 2010 at 1:02 PM
- Becky said...
so delicious. very cool orange buttercream.
- June 1, 2010 at 2:53 PM
- Heather said...
Love the idea of an orange drizzle. They look great!
- June 1, 2010 at 3:08 PM
- Marthe said...
That orange glaze looks really yummy as do your brownies! Thanks for baking with me this week!
- June 1, 2010 at 4:09 PM
- The Mortensens said...
Your pictures look great! l love rubbing sugar and zest together too! It's one of my favorite things to do while baking.
- June 1, 2010 at 6:15 PM
- Pamela said...
Skipped the meringue here, too. I like the idea of the topping, though! Yum.
- June 1, 2010 at 7:22 PM
- Katrina said...
Ooh, the orange glaze sound yummy.
These did have great flavor, kind bummed mine were underbaked.
- June 1, 2010 at 10:23 PM
- margot said...
The brownies look great with the glaze! They were pretty cakey brownies, so it sounds like it would be an excellent combination.
- June 1, 2010 at 11:00 PM
- Christina and Jacob said...
I definitely want to know your recipe for orange buttercream because that just sound soooo delicious, and especially on top of these "brownies". :)
- June 2, 2010 at 12:55 AM
- jill said...
beautifully done momma! I love that orange buttercream idea...makes it look like something for breakfast, and who doesn't love white chocolate for breakfast!!
- June 2, 2010 at 7:34 AM
- Clivia said...
You're right. Next time I'll leave the topping off too and go with some fresh cream.
They look delicious!
- June 2, 2010 at 2:19 PM
- Jacque said...
Oooh, yummy, your buttercream looks so tasty and perfect. Nice!
- June 2, 2010 at 5:47 PM
- megan said...
these look so good! Just the name alone is enough to make me want to try them!
- June 3, 2010 at 8:09 AM
- Kayte said...
I like your ideas, so I think I will give this another try with the meringue on top and see how it goes. Mine was a real mess, not done in the middle, all fell apart from pan to plate, and the meringue caved in...the guys, however, ate it all (mostly with a spoon), b/c, well guys tend to eat things you and I would question...LOL. Yours look really beautifully delicious.
- June 3, 2010 at 8:59 AM
- Nickki said...
They look amazing! Just perfect.
- June 3, 2010 at 12:10 PM
- Flourchild said...
Yum they look fantastic! I may have to make these after all!
- June 3, 2010 at 9:57 PM
They look great with the buttercream! Whipped cream would be good too.
- June 4, 2010 at 7:31 AM


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Faith-based initiatives analyzed
their worst, faith-based initiatives could become "a Trojan horse strategy for the 'theocracizing' of America," New Jersey Secretary of State DeForest "Buster" Soaries told a Princeton audience Wednesday night. However, he said, administered properly, the inclusion of religious groups in government contracting serves broad and important secular purposes.
"Our highly secularized culture should never reject the offers of faith communities simply because we have outgrown Puritanism and have become a sophisticated, scientific, technological society," Soaries said. "There are still non-empirical realities that form the foundation of a people spiritual forces that link us to one another moral imperatives that require our best effort in response."
Soaries, who is also a Baptist minister, cited great secular achievements that had religious foundations, including the founding of the YMCA, the Red Cross and Princeton University, as examples of how religious groups can contribute to societal good without imposing religious doctrines. He also told an audience of students, faculty and community members in Robertson Hall of his experience in administering faith-based initiatives to help find foster families for boarder babies and to help a major bank employ more people of color. He said that the church-state separation debate often distorts the Constitution, which he said protects religious groups from government and not the opposite.
An adviser to the Bush Administration on faith-based work, Soaries said the new federal approach is not designed to force zealot opinions on the masses but will ensure that religious groups who can meet government contract specifications are not ostracized. "To exclude them from participation is religious discrimination and nothing less," Soaries said.
Responding to questions, Soaries said that religious groups who participate in faith-based initiatives also must uphold laws, including anti-discrimination measures. He said that the government should not create systems whereby particular religious groups would gain monopolies over certain services thus limiting the freedoms of others. "The emphasis and focus should be, almost exclusively, on outcomes," Soaries said. "If you go to a Catholic hospital for heart transplant surgery, you can measure if it worked."
The lecture closed this academic year's "Crossroads of Religion and Politics Lecture Series," co-sponsored by the Woodrow Wilson School and the Center for the Study of Religion .
Contact: Justin Harmon (609) 258-3601


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Snap: Clayton & Son in morning light
The topsoil and mulch business located at the confluence of Routes 240 and 250 in Western Albemarle gleams in morning light. Photo of John W. Clayton & Son (est. 1940) shot March 27.
More Snaps
2 comments
Alexander July 19th, 2010 | 7:26pm
I think I have only left negative comments on this website, so I'll be making my first positive one today: I really enjoy the snapshots you all have been putting up...our local culture/atmosphere is really beautiful and it is nice that it is here for all to see.
NancyDrew July 19th, 2010 | 2:57pm
Now this is a business that fits spendidly into our picturesque rural landscape. 250 in Albemarle County is still one of the most beautiful drives around, let us all make sure it isn't ruined.


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Oops... that isn't a valid coupon.
It's no stretch to knit the cutest toy giraffe ever. Make a big, soft friend and expand your circular knitting skills to double-pointed needles.
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El Cajon is the largest city in East County with approximately 100,000 residents. Nicknamed "The Big Box," it sits in a valley surrounded by mountains and is 15 miles east of Downtown San Diego. Within its 15 square miles are numerous parks, community centers and churches, almost two dozen elementary schools, six middle schools and six high schools. It also has three higher education institutions and two golf courses. The median household income is around $60,000.
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Melissa J Thompson Photography
Melissa J Thompson Photography
WELCOME!Growing up, as I recall, I never had too much to say. An observant child; I have always had a great sense for depth of field, and a different perspective than those around me. I was very shy and quiet. Lanky and awkward. I have fond memories of painting four-foot murals in my mother's sewing room, and riding my horse on the abundant horseback riding trails in the rural area where I grew up. "Melissa's a Social Butterfly". I will never forget when a friend described me as such. A self-described planner, an eternal realist, I give people what they want — decisive moments captured within an optical lens. Timeless archives cherished for generations to come. I look forward to working with you and capturing your decisive moments!! *Bio photo by: Kristen Honeycutt Photo Co.
© 2019 Melissa J Thompson Photography|ProPhoto Photographer Site by NetRivet Blogs


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Nice Radio Telescope
Half-Life 2: Capture the Flag 2.0 brings the familiar Capture the Flag game play along with six other game modes in the new 2.0 release. True to its roots, the game pits the Rebels against the Combine in a fast-paced battle over the flags within the graphics rich environment of the Source engine. In this final release of the game, features introduced in all of the previous beta test versions have been now fully implemented. The mod in a nutshell is an homage to the fast-paced run and gun style of Capture the Flag such as found in Quake and Unreal Tournament. The mod is also 100% free to install and play under the free Source SDK!
Nice Radio Telescope
realy smart design)
It's all about the pistol. :)
Only registered members can share their thoughts. So come on! Join the community today (totally free - or sign in with your social account on the right) and join in the conversation.
Shots of the maps that will be included in the HL2CTF 2.0 Release.


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'The biggest positive surprises for the Sabres almost all involved young players who are nowhere near as good as they will be, and probably sooner rather than later. Rookie defenseman Marc Andre Gragnani had a goal and six assists and made us wonder why he wasn't with the big club earlier.'
Archives for April 27, 2011
Sabres season ends; new owner's job just beginning
'That leaves the Sabres preparing for an offseason under a new owner with deep pockets, a willingness to spend and an objective to deliver Buffalo a championship.'
Flyers finish off Sabres' season
'"It's not a good a feeling to have to chase the final few minutes of your season," defenseman Chris Butler said. "It's disappointing to know that we had a good chance to win this series, and to be where we are now just sucks."'
Fortune turns against Miller
'"We almost got away with that first period and maybe it would have been a different game," Miller said. "I thought we were going to get away with it and it was a tough bounce. … It changed direction on me a bit. I was reaching to play it to the corner and it ended up diving down off Mike."'
Classy Grier disconsolate at end of a good run
'"You know, the guys battled hard all year," said Grier, his voice cracking. "I gotta block that shot on the first goal. I tried to catch it. It went off my glove and went in. It gave them some momentum. It's just disappointing. I don't know how much longer I have to play."'
Serious injuries would have carried over to next round
'Ruff revealed the leg gash suffered by Jason Pominville in Game Five was serious, and that a tendon had been sliced. The winger needs surgery and the injury would have kept him sidelined 4-6 months had the injury happened during the regular season. Ruff also said center Tim Connolly would have been out six weeks with an undisclosed injury after taking Mike Richards' hit Sunday.'
Breaking down Game Seven
'Turning point: Danny Briere worked ex-teammate Paul Gaustad on a faceoff in the Buffalo zone, the draw going to defenseman Braydon Coburn. His shot found the net with just 18.5 seconds left in the first period, giving the Flyers a well-deserved 1-0 lead and a springboard to a blowout.'
Future softens blow of first round exit
'But when it came down to it, the Flyers' skill and experience overcame Buffalo's mettle.'
Replacements provided little reinforcement
'"We threw in two bodies that hadn't played," Ruff said. "That's not easy, and you're asking them to play a major role in a Game 7. Jochen Hecht hasn't even had a practice with the team and Derek's been out for four months. I know he's been doing conditioning and everything, but there's nothing like playing games."'
Wednesday's Philadelphia Coverage
Flyers eliminate Sabres with 5-2 win in Game 7 (Philadelphia Inquirer)
Invisible man Coburn makes a big showing (Philadelphia Inquirer)
Calm Boucher steady between the pipes (Philadelphia Inquirer)
Flyers get it done (Philadelphia Inquirer)
Return of Pronger gives the power play a big jolt (Philadelphia Inquirer)
Photo gallery (Philadelphia Inquirer)
Flyers rattle Sabres to advance with Game 7 win (Philadelphia Daily News)
Flyers thrive with their backs to the wall (Philadelphia Daily News)
Boucher saves best for crucial game (Philadelphia Daily News)
Briere does little things right, even as he faces old friends (Philadelphia Daily News)
Lapierriere a finalist for NHL's Masterson Trophy (Philadelphia Daily News)
Flyers-Sabres: Game 7 recap (Philadelphia Daily News)
Flyers-Sabres: Game 7's 3 stars (Philadelphia Daily News)
This die-hard wouldn't pass up the Flyers, even during Passover (Philadelphia Daily News)
Briere, Boucher stifle Sabres to end series (Delaware County Daily Times)
Flyers-Sabres series chock full of entertainment (Delaware County Daily Times)
Laviolette the driving force behind Flyers' resurgence (Delaware County Daily Times)
Flyers' Pronger back in familiar role (Delaware County Daily Times)
Flyers dominate Sabres 5-2, head to Round 2 (Cherry Hill Courier Post)
Game 7 win worth all the struggles (Cherry Hill Courier Post)
Laperriere's perseverence recognized (Cherry Hill Courier Post)
Flyers save the best for last (Bucks County Courier Times)
Laperriere a finalist for Masterton (Bucks County Courier Times)
It was fitting this one went seven games (Bucks County Courier Times)
Briere shines in deciding game (Bucks County Courier Times)
Flyers handle Sabres in Game 7 to advance (CSN Philadelphia)
Flyers' power play clicks at just the right time (CSN Philadelphia)
Briere comes up big on faceoffs (CSN Philadelphia)
The Game Analysis (PhiladelphiaFlyers.com)
Photo gallery (PhiladelphiaFlyers.com)
Photo gallery (Sabres.com)
Photo gallery (AP)
Photo gallery (Buffalo News)
This time, Game 7 goes Boucher's way (NHL.com)
Flyers come up big on faceoffs, power play (NHL.com)
Pronger happy to help Flyers oust Sabres (NHL.com)


text:
Food industry under siege
First lady Michelle Obama's move to limit junk food marketing in schools and revamp nutrition labels is just the latest salvo in an intensifying battle royale with the food industry.
The Obama administration — arguably the most active on food policy in the past century — has issued a slew of new rules over the past few years to reform everything from the steps companies take to guarantee the safety of imported food to the banning of trans fat to completely overhauling what children eat in public schools.
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With regulation after regulation in the federal pipeline and calls for soda taxes and mandatory labeling for genetically modified foods in certain cities and states, the industry is bracing for an onslaught of changes that are expected to cost billions and involve both reformulating products and disclosing more information to consumers than ever before.
( Also on POLITICO: FLOTUS goes big on label changes)
"I can certainly see how the industry might feel like they are being targeted by the administration," said Bruce Silverglade, a principal at Olsson Frank Weeda Terman Matz, which advises food companies in Washington.
"I wish the administration would take a step back," said Baylen Linnekin, executive director of Keep Food Legal, a food freedom advocacy group, and a professor at American University. "I would imagine [the food industry] has the same whiplash as someone like me or you who has just been trying to keep up with these changes."
Though highly engaged in all the policymaking, the food industry is more than a bit overwhelmed and has to be careful about how it is perceived if it fights back against policies that are pitched as a way of curbing obesity rates and giving consumers more information. Although industry groups are publicly saying they welcome the Nutrition Facts update unveiled this week and Obama's efforts, many companies are expected to fight tooth and nail on the details.
( Also on POLITICO: Obama flexes policy muscle)
But the industry is going to have to be careful in how it fights.
"I don't think anyone is going to be foolish enough to attack the first lady — that's just stupid," said one longtime food company consultant who asked to remain anonymous. "It's sort of a laundry list of everything the industry didn't want."
The administration, however, is proving it's not afraid to make bold policy changes when it comes to food.
"This administration has done more than any administration in history to make our food more affordable, nutritious and transparent. This is all part of an unbelievable record of achievement that is unmatched," said Scott Faber, vice president of government affairs for Environmental Working Group and a former lobbyist for the food industry.
The dramatic attack on food policy has been felt by the food and beverage industry, which has spent more on lobbying the federal government under the Obama administration than ever before. Between 2009 and 2013, food and beverage companies plunked down a staggering $185 million on federal lobbying, according to the Center for Responsive Politics.
( WATCH: Michelle Obama makes nutrition announcement)
Lobbying has been a winning strategy for the food sector, noted Michael Jacobson, executive director of the Center for Science in the Public Interest, a consumer advocacy group.
Back when President Barack Obama was running for reelection, allies of the food giants shot down an effort by an interagency working group led by the Federal Trade Commission that would have set voluntary guidelines for the healthfulness of foods marketed to children. Even though the effort has been long-dead, food lobbyists managed to get language in the last omnibus bill saying FTC could not revive the effort unless it first conducts a cost-benefit analysis.
The next battle over food labels is going to be tough, Jacobson said.
The food industry will most likely have a big bill to pay with the new labeling changes. The bold revamp of the nutrition facts panel announced Thursday is expected to cost the food companies roughly $2 billion, by the Food and Drug Administration's own estimates. The agency also calculates that the changes would bring about $20 billion in economic benefit to the public.
( PHOTOS: Michelle Obama works out)
Several food manufacturers would not be pleased because, for the first time, they would be required to list added sugars, which industry officials say will be difficult to measure.