Sampling/Variability of CLARREO Solar Spectral Benchmark

Zhonghai JinCosty LoukachineBruce Wielicki

NASA Langley research Center / SSAI, Inc.March 16, 2009

Objectives: Understand the interannual variability and sampling error expected in the CLARREO solar spectral benchmark to evaluate the ability of CLARREO to detect various climate trends;clarify the sampling requirement for CLARREO mission design.How much is the natural interannual variability of solar spectral benchmark over different spatial and temporal scales (global and regional, yearly and monthly)?How large is the decadal solar spectral climate signal? How this signal compare to the natural interannual variation?Whats the time frame for the climate signal to be large enough to be detected by CLARREO solar benchmark? Whats the optimal wavelengths and spectral resolution for different climate signal detection?How large is the nadir sampling error? How the sampling error compare to the climate signal and the natural interannual variation?

Input parameters (monthly mean):Aerosol, PW, Surface properties, Cloud properties (, RE, amount, phase) from CERES ARBAVG;Ozone from SMOBA.Five regions:Polar north (>60N) (NP)Mid-latitude north (30N-60N) (NML)Tropic (30N 30S) (TRO)Mid-latitude south (30S60S) (SML)Polar south (> 60S) (SP)6 Modtran calculations in each region each month: Clear open oceanClear land (include sea ice)Water cloud oceanWater cloud landIce cloud oceanIce cloud landSpectral reflectancefor 68 months (Mar 2000 to Oct 2005)in 5 regions and globalfor ocean and landfor clear/cloudy/all skiesfor 0.2-5.0m in every 5cm-1Interannual Variability of Solar RefectanceInputOut

An Example of TOA Spectral Reflectance (all sky)O3O2H2OH2O+CO2Major absorption bands labeled

Reflectance AnomalyInterannual variations are related to changes of clouds, aerosol, snow, water vapor, ozone etc., depending significantly on region.H2O +Ice cloudWavelength (m)Examples of Monthly Mean Regional Reflectance Anomaly (2000 - 2005)

An Example of Monthly Mean Global Reflectance Anomaly (2000 - 2005)Reflectance AnomalyNote: interannual variation for global monthly mean reflectance is within 0.005 or about 2% of the reflectance.

Annual Mean Global Reflectance Anomaly (2000 - 2005)

2 of monthly mean reflectance anomaly

Note: the 2 variation for annual mean reflectance is much smaller, indicating that the natural variability is dropped.

Model and Schiamachy anomalies match better over ocean.

Note: Schiamachy orbit is different from Terra, and footprint size is much larger than CERES.

Same as last slide, but for April.

Same as last slide, but for July.

Same as last slide, but for Oct.

Anomaly in Oct. is much smaller.

2. Solar Spectral Signal of Climate ChangeResults above showed that the modeled interannual solar reflectance variation from CERES data is realistic.

How this interannual variation compare to the decadal change of climate spectrum based on IPCC climate change scenario?

What is the optimal wavelengths and spectral resolution to detect different climate signals?

Whats the difference of the climate signals for different regions?Using the six year average of CERES data as input and plus the decadal perturbation of the input parameters based on IPCC climate change scenario, we have calculated the climate change spectra (regional and global) for various climate parameters.

Decadal reflectance change due to CO2 change (+17ppm/decade).(This example is for global annual mean)

3. Sampling Effect: Nadir vs Full SwathTo investigate the sampling effect and the nadir sampling error, we calculated and compared the reflectance spectra between nadir only sampling and full swath sampling. The input properties for these calculations are from CERES SFC data. For full swath, data from all view angles are used, while for nadir view, only data within 5 degree of nadir (about an area of 100km diameter) are used.

An example of monthly mean regional reflectance anomaly comparison between full swath and nadir sampling. Full swathNadir view

An example of monthly mean global reflectance anomaly comparison between full swath and nadir sampling (January). Full swathNadir viewReflectance AnomalyWavelength (m)

Annual mean global reflectance anomaly comparison between full swath and nadir sampling. Reflectance AnomalyWavelength (m)Full swathNadir view

Examples of nadir sampling error for monthly mean reflectance.

The nadir sampling error is defined as the reflectance anomaly difference between nadir views and all views (full swath). Nadir Sampling Error for Monthly Mean ReflectanceWavelength (m)Ndir-All Reflectance Anomaly Difference

Nadir Sampling Error for Annual Mean Reflectance

Relative Nadir Sampling Error for Annual Mean Reflectance (%)

Same as last slide, but for global ocean.

Same as last slide, but for global land.

We calculated nearly 6 years of monthly mean high resolution solar reflectance spectra and 5 decades of climate change spectra for 5 regions and global, for ocean and land, and for nadir views only and full swath.The inter-annual variability and nadir sampling error for various regions are investigated and are shown being comparable with Schimachy and CERES observations.Monthly mean global solar reflectance anomaly is within 0.005 in most spectra (i.e., 2% of reflectance), but it is larger for polar and land regions, where have more surface variations.Annual mean global solar reflectance anomaly is within 0.002 (< 1% of reflectance); the 2 anomaly is similar to one decade of climate change signal estimated from IPCC AR4 climate change scenario in the visible, but larger than that in most of NIR spectra.3. Conclusion

For annual mean and most monthly mean global reflectances, the year to year variation trends are consistent between full swath and nadir sampling over most spectra, indicating that the nadir sampling can catch most of the interannual variations over global scale.The 2 nadir sampling error for annual mean global reflectance in the visible and transparent bands is less than 0.4%; lower over ocean, higher over land. But it could be much higher for regional/seasonal spectrum.The interannual variability, climate change spectrum and sampling error are all dependent on wavelength and spatial/temporal scale for averaging. Solar benchmark observation over 2 decades or more is required to detect the global climate signal over most solar spectra.For many regional climate trend detection (e.g., aerosol effect, surface albedo), the sampling error of 100km nadir view (assuming one orbit) appears to be too large, indicating the requirement for a separate instrument for solar benchmark (from calibration) or an additional orbit.

Acknowledgement:

We thank the Sciamachy science team for the solar radiance data, NASA Langley DAAC for CERES data, and Dr. Sky Yang for SMOBA ozone data.