NOAA Climate Data Record of Microwave Sounding Unit (MSU) Mean Atmospheric Layer Temperature, Version 1.2 (Version Superseded)
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title: NOAA Climate Data Record of Microwave Sounding Unit (MSU) Mean Atmospheric Layer Temperature, Version 1.2 (Version Superseded)
alternateTitle: MSU Mean Layer Temperature - NOAA
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date: 2009-03-05
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Anchor: DOI doi:10.7289/V5RB72J1
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individualName: Cheng-Zhi Zou
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description: This is the project website for NOAA/STAR Microwave Sounding Calibration and Trends (MSCAT). MSU/AMSU/SSU related TCDR Datasets can be downloaded from this website
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abstract: *Note: This dataset version has been superseded by a newer version. It is highly recommended that users access the current version. Users should only use this version for special cases, such as reproducing studies that used this version.* The dataset contains three MSU channel-based, monthly gridded atmospheric layer temperature Climate Data Records generated by merging nine NOAA polar orbiting satellites, TRIOS-N and NOAA-6 through NOAA-14. These are temperatures of middle-troposphere (TMT), upper-troposphere (TUT, also known as temperature troposphere stratosphere), and lower-stratosphere (TLS), corresponding to measurements from MSU channels 2, 3, and 4, respectively. These products have global coverage with a 2.5 latitudes by 2.5 longitude grid resolution. Time period is from November 1978 through September 2006. Adjustments of observations included limb-adjustment, diurnal drift corrections, warm target temperature effect, and residual inter-satellite bias removal.
purpose: The dataset is used for monitoring and investigation of long-term temperature trend and variability for the atmospheric layers as defined by TMT, TUT, and TLS.
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useLimitation: *Note: This dataset version has been superseded by a newer version. It is highly recommended that users access the current version. Users should only use this version for special cases, such as reproducing studies that used this version.*
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useLimitation: The temperatures as defined by the datasets are mean layer temperatures which are not suitable for temperature trend determination at specific atmospheric levels. Satellite retrievals must be conducted to obtain level temperatures.
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otherConstraints: Cite as: Cheng-Zhi Zou, Wenhui Wang, Jian Li, and NOAA CDR Program (2014). NOAA Climate Data Record of MSU Mean Layer Temperatures, Version 1.2. [indicate subset used]. NOAA National Centers for Environmental Information. doi:10.7289/V5RB72J1 [access date].
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otherConstraints: Distribution liability: NOAA and NCEI make no warranty, expressed or implied, regarding these data, nor does the fact of distribution constitute such a warranty. NOAA and NCEI cannot assume liability for any damages caused by any errors or omissions in these data. If appropriate, NCEI can only certify that the data it distributes are an authentic copy of the records that were accepted for inclusion in the NCEI archives.
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otherConstraints: Use liability: NOAA and NCEI cannot provide any warranty as to the accuracy, reliability, or completeness of furnished data. Users assume responsibility to determine the usability of these data. The user is responsible for the results of any application of this data for other than its intended purpose.
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title: Stability of the MSU-derived atmospheric temperature trend
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title: MSU Mean Layer Temperature CDR Overview
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language: eng; USA
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environmentDescription: Computer hardware minimum configuration for data processing is as follows: Processor: 2.0GHz, Memory: 100 MB, Disk Space 100 GB, A system with multiple CPUs is preferred, Operating System can be Linux or Windows, Programming Languages: JAVA and Bash script, Compilers: Sun JAVA Compiler, External Library : NetCDF-JAVA 4.1; Jscience4.3, Storage Requirement : 100GB, Execution Time Requirement: Single CPU ~20 hours for 9 satellites, Varied when using parallel computing
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description: ground condition
beginPosition: 1978-11
endPosition: 2006-09
timeInterval: 1
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nameOfMeasure: Measure of Absolute External Positional Accuracy
measureDescription: Inter-satellite biases for each satellite pair during their overlapped observational period is evaluated as an indicator of the product quality and accuracy of merging algorithm. Mean inter-satellite biases were shown to be zero and standard deviations were minimized compared to those without bias corrections. These indicated high quality and accuracy of the merged products.
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statement: The Microwave Sounding Units (MSU) on board the NOAA Polar Orbiting Satellite series (POES) have been the primary instruments for measuring upper-air temperature profiles under all weather conditions, excluding precipitation, during 1978-2007. MSU was a microwave Dicke radiometer with four-channels to make passive measurements in the 5.5 millimeter oxygen region. The radiance measured by each frequency channel comes from a different layer of the atmosphere, depending on the strength of the absorption at that frequency. The percentage contribution of individual levels within the layer to the measured layer temperature is represented by a vertical weighting function, which is typically bell-shaped, peaking at a certain level in the height coordinate. Among these, MSU channel 1 (50.3 GHz) measured surface temperature, while channels 2, 3 and 4 measured temperatures of the middle-troposphere (TMT), upper-troposphere (TUT), and lower-stratosphere (TLS) with their weighting functions peaking respectively near 550, 250, and 100 hPa. By merging MSU observations from different satellites, long-term temperature time series are obtained for these layers for climate trend monitoring and investigation. Due to stability, continuity, global coverage, and insensitive to clouds, these time series are broadly used as an indicator of global warming.
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description: The following steps and algorithms are needed to derive the atmospheric layer temperature TCDR: 1) Extracting limb-adjusted MSU swath brightness temperatures on scan positions for channels 2, 3 and 4 from the IMICA calibrated MSU orbital Level-1c datasets. 2) Adjusting the MSU brightness temperatures for diurnal drift effect at each scan position. 3) Binning limb- and diurnal-adjusted brightness temperatures at scan positions into grid cells of 2.50x2.50 spatial resolution in monthly interval for each satellite and then averaging the binned data at each grid cell to produce Level-3 layer temperature data for each satellite. 4) Removing residual inter-satellite biases including instrument temperature effect using satellite overlap observations of the Level-3 data. 5) Bias-removed, multiple satellite Level-3 temperature data are then averaged to generate a 28-year long, merged and homogeneous layer temperature TCDR from 1978 to 2007. The final product is saved as NetCDF format
rationale: The main purpose of the merging algorithm or processing steps is to derive homogeneous temperature CDR from the sequential overlapping MSU observations onboard NOAA polar orbiting satellites channel by channel. Deriving such time series requires a number of steps: 1) Inter-calibrating the satellite sensors, 2) Removing instrument temperature effects on observations, 3) Adjusting the observations to a common reference time (usually chosen as local noon time) to minimize diurnal effect related to satellite orbital drifts, 4) Adjusting observations made at different viewing angles to nadir views (limb effect), 5) Removing residual inter-satellite biases and their drifts. The Level-1c radiances data used for deriving the layer temperature TCDR were already inter-calibrated by the Integrated Microwave Inter-Calibration Approach (IMICA, formerly known as simultaneous nadir overpass approach; Zou and Wang 2013). In addition, limb-adjusted brightness temperatures are also provided in the IMICA calibrated Level-1c files. As such, only adjustments other than sensor inter-calibrations and limb-adjustments were needed for satellite merging. The IMICA calibrated MSU radiances and limb adjustments were described in details in the C-ATBD associated with the MSU Level-1c radiance dataset (Zou and Wang 2013). This has substantially simplified the processing procedure for developing MSU layer temperature TCDR.
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title: MSU Mean Layer Temperature Data Flow Diagram
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linkage: https://www.ncei.noaa.gov/pub/data/sds/cdr/CDRs/MSU%20Mean%20Layer%20Temperature%20-%20NOAA/DataFlowDiagram.pdf
description: The Data Flow Diagram for MSU CDR shows an overview of the steps used to produce the dataset.
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title: NOAA MSU Mean Layer Temperature C-ATBD
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date: 2014-03
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edition: Revision 1.0
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linkage: https://www.ncei.noaa.gov/pub/data/sds/cdr/CDRs/MSU%20Mean%20Layer%20Temperature%20-%20NOAA/AlgorithmDescription.pdf
description: The C-ATBD for the MSU Mean Layer Temperature CDR describes the algorithms and processing steps used in production of the dataset.
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description: See Algorithm Citation
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description: The level 1c Brightness Temperature CDR provided the source data for the three channel-based, monthly gridded atmospheric layer temperature TCDR
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title: NOAA Fundamental Climate Data Record (FCDR) of MSU Level 1c Brightness Temperature, Version 1.0
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date: 2014-03-01
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sourceStep: ps001
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DateTime: 2015-04-22T00:00:00
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maintenanceNote: Bulk metadata change applied on 2023-06-23. See version control repository history for metadata change details.