That's an excellent summary of the various
different satellite analyses.
Not exact matches
That turns out to be a generally useful capability, and a
different part of the Map team is able to reuse that for a
satellite - imagery
analysis task where they wanted to find roof tops in the U.S. or around the world to estimate the location of solar panel installations on rooftops.
«Software can come in many
different forms; it can simulate data, it can incorporate your algorithms, or it can be used for statistical
analysis of your results — it's really a geomatics tool that can be used from end to end,» says Cannon, a professor of geomatics engineering at Calgary and an expert in the research and development of
satellite navigation tools used by land, marine, and airborne vehicles.
Using many
different types of
analysis, they found that their model closely matched the
satellite observations.
Despite several new
analyses with improved cross-calibration of the 13 instruments on
different satellites used since 1979 and compensation for changes in observing time and
satellite altitude, some uncertainties remain in trends.
The mean insolation at Earth orbit is about 1366 W / m ^ 2; the peak - to - peak variation over the 11 year solar cycle is about 3 W / m ^ 2; the authors discuss two running averages derived from
different satellite data sets and
analysis derived by Willson and Mordvinov (2003) and Frohlich and Lean (1998) respectively.
Looking above Earth's surface at certain layers of the atmosphere, several
different analyses examined NOAA
satellite - based data records for the lower and middle troposphere and the lower stratosphere.
There has been a debate on the trend estimates from a number of
different studies based on the Microwave Sounding Unit (MSU) instrument carried by a number of
satellites, and
different researchers have come up with
different trend estimates depending on how they have carried out the
analysis.
The mean insolation at Earth orbit is about 1366 W / m ^ 2; the peak - to - peak variation over the 11 year solar cycle is about 3 W / m ^ 2; the authors discuss two running averages derived from
different satellite data sets and
analysis derived by Willson and Mordvinov (2003) and Frohlich and Lean (1998) respectively.
Much of the team's
analysis was conducted using data from two
different satellites - ICEStat, and GRACE which measure changes in ice mass using lasers and change in the earth's gravimetric field respectively.
The monthly mean averages and trend
analysis input files necessary for the purposes of this study were then created using the daily comparison measurements with two
different sets of only coincident datasets being considered: the monthly mean and associated standard deviation of the ground - based measurements and the equivalent one for the
satellite measurements.
Such an assessment should involve a detailed
analysis of the sensitivity of global - mean temperatures derived from these three
different measurement systems to the various choices made in the processing of the raw data — e.g., corrections for instrument changes, adjustments for orbital decay effects in the
satellite measurements, and procedures for interpolating station data onto grids.
I agree with you that the last decade really doesn't tell you that much about the long term trends, given the size of the error bars, but it does allow for some interesting
analysis of the difference between individual temperature records during that period (e.g. ENSO responses of
satellites vs. surface measurements, effects of
different ways of treating arctic temperatures, etc.).
There are other
satellite analyses that have found
different numbers but I've not had a chance to look into that recently at all...
We repeat the
analysis for the NCEP and
satellite epochs to establish that the approach is robust for datasets of
different lengths, and we examine the evolution of decadal power in the natural influences to assess their projections onto each other as sources of error in prior results.
Although several
different algorithms have been used to derive sea ice concentrations from the
satellite measurements, our
analyses based on the Hurrell et al. (2008) data are consistent with previous studies.
A comparison of Australian mean temperature from a range of
different datasets — including local and international datasets (which use
different methods of data selection, preparation and
analysis) and both station - based and
satellite data — is provided below (Figure 12).
The
satellite temperature record comes from a succession of
different satellites and problems with inter-calibration between the
satellites are important, especially NOAA - 9, which accounts for most of the difference between various
analyses.
Uncertainties should decrease closer to near - current dates (e.g. from denser and more accurate sampling)-- but note that these products also employ
different QC and
analysis methods, rely to varying degrees on
satellite data, on sea - ice data to constrain polar SST, and on bias adjustments for historical changes in measurement methods.