Solar-Stellar Variability Workshop SORCE Photometry Jerald Harder jerry.harder@lasp.colorado.edu, 1-303-492-1891 With thanks to Mark Rast Juan Fontenla Stéphane Béland

Introduction to the SORCE SIM Comparisons with PSTP & SRPM Topic Outline Introduction to the SORCE SIM Instrument capabilities and limitations Comparisons with PSTP & SRPM SIM observations via Strömgren filter equivalents Moving forward – the Radiometric Solar Imager & TSIS

Instrument overview Instrument Type: Féry Prism Spectrometer Wavelength Range: 200-2400 nm Wavelength Resolution: 0.24-34 nm Detector: ESR, n-p silicon, InGaAs Absolute Accuracy: 2-8% Relative Accuracy : ~0.5-0.02% (240-2400 nm) Long-term Accuracy: 0.3-0.025%/yr (240-2400 nm) Field of View: 1.5x2.5˚ total Pointing Accuracy/Knowledge: 0.016˚/0.008˚ Mass: 21.9kg Dimensions: 88 x 40 x 19 cm Orbit Average Power : 17.5 W Orbit Average Data Rate: 1.5 kbits/s Redundancy: 2 Redundant Channels Harder J. W., G. Thuillier, E.C. Richard, S.W. Brown, K.R. Lykke, M. Snow, W.E. McClintock, J.M. Fontenla, T.N. Woods, P. Pilewskie, 'The SORCE SIM Solar Spectrum: Comparison with Recent Observations' , Solar Physics, 263, Issue 1 (2010), pp 3, doi:10.1007/s11207-010-9555-y Pagaran, J., J. W. Harder, M. Weber, L. E. Floyd, and J. P. Burrows, ‘Intercomparison of SCIAMACHY and SIM vis-IR irradiance over several solar rotational timescales’, A&A, 528, A67 (2011), doi: 10.1051/0004- 6361/201015632, 2011.

A word about resolution… SIM measures the irradiance weighted by the bandpass. Low resolution instruments respond to the density of lines, not to individual lines.

SORCE spacecraft & thermal events Thermal events change instrument performance most typically through wavelength shift & light path through prism. Degradation corrections must account for these changes. Time period of Version 17 remains the most stable and reliable time period of SIM operations.

SIM degradation correction and long-term accuracy Long-term degradation corrections in SIM are based solely on measured instrument quantities. Correction is based on the comparison of two identical (mirror image) spectrometers that have been exposed at different rates. Corrections for photodiode detectors in the same channel are made by comparison with the spectrally flat ESR detector after correcting for the different optical paths through the prism. Degradation effects arise from two sources: the predominant form of degradation arises from exposure of the instruments optical surfaces to hard UV radiation. In the SIM instrument, this component is measured by comparing two identical instruments, a SIM A and a SIM B, that are exposed at different rates. The other from of degradation comes from other non-exposure related contributions, predominantly energetic proton bombardment. This contribution is corrected through inter-detector comparisons within a single SIM channel. This is based on the comparison with an electrical substitution radiometer, very similar to the TSI instruments, but measuring a power level about a factor of a x1000 smaller than for the TSI instruments. The corrections for the SIM instrument are based on measured telemetry items and no assumptions are made about the magnitude, slope, or time dependent behavior of the SSI. Analysis of the demonstrates that the prism degradation, the largest single source of degradation, follows Lambert’s law. It should be noted that this method of degradation correction is very similar to the method used to correct TSI instruments, however, it now has to be done as a function wavelength. Before we can talk about the methods of correcting the data, we must discuss a number of important instrument attributes. At the bottom is a cross sectional view of the SIM A channel, SIM B is a functionally equivalent mirror image of SIM A, and the two channels are contained in the same instrument case. Thus the two channels are in the same chemical and physical environment. Each SIM channel has only one optical element, a Ferry prism, that disperses and focuses light onto a focal plane with four photodiode detectors and the ESR. The spectrum of the sun is obtained by rotating the prism, the ESR overlaps the spectral coverage of each photodiode detector. Loss in sensitivity arises from exposure of the prism to solar photons that are energetic enough to either directly induce compositional changes in the first few monolayers of the glass and/or transmission losses due to polymerization of trace amounts of organic materials on the surface of the prism. Thus the loss of prism transmission is essentially a surface phenomenon localized at one position in the optical system. This has a distinct advantage over multi-element optical system where the light loss is non-uniformly distributed over different optical elements.

Spectral variability nomogram SIM observations consistent with an overall decrease in the temperature gradient in the active (magnetic) solar photosphere. The change in T-gradient occurs in solar atmospheric layers close to the Teff value. Harder et al., GRL,, 2009

Independent observations with anti-solar cycle trends Features contrast varies with wavelength and heliocentric angle and corresponds to the slope of T vs. P. (5 ’s between 525 to 677 nm) Sanchez Cuberes et al., ApJ,2002 Topka et al., ApJ 1997 Moran et al., Sol. Phys., 1992 The photometric sums exhibit similar temporal patterns: they are negatively correlated with solar activity, with strong short-term variability and weak solar-cycle variability. Preminger et al.., ApJ,2011

PSPT feature identification & time series Ca IIK 393.45 nm, 0.273 FWHM Identify Active Regions PSPT feature identification & time series Red Continuum 607.095 nm, 0.458 FWHM Identify Umbra & Penumbra SRPM Mask Image Identify 7 solar Features Feature area determined from intensity analysis of PSPT images Analysis done as a function of disk position and time Full disk irradiance determined from disk position and emitted intensity from each atmospheric model

SIM & PSPT Facula + Plage SIM 280 nm irradiance is proportional to the measured facular area in PSPT

SIM & PSPT sunspot umbra & penumbra #1 Further corrections needed to account for wavelength stability later in mission. 2 arc-sec error in prism rotation angle ≈ 0.145nm ≈ 8% of a prism step

SIM & PSPT sunspot umbra and penumbra #2 Since the quiet-sun intensity varies from disk center to the limb and that profile is wavelength dependent, magnetic structure identifications and contrast measurements are made relative to some arbitrary and inconsistent definition of a quiet-sun center-to-limb variation. Moreover, the quiet-sun is not completely quiet, and over the solar cycle the number of unresolved magnetic flux elements contributing to pixel-integrated intensities likely varies. Decreased irradiance is observed even when sunspot blocking is not indicated by PSPT 607 nm images.

Solar spectral irradiance variability in SRPM The next thing to do is to use the full SRPM analysis to look at different solar scenarios. This graph shows different mixtures of solar features over the course of a solar cycle ranging from late 2000 through the peak of the solar cycle in 2002, and then in the descending phase out to near solar minimum in Sept of 2008. The graph on the top right shows the irradiance differences with for each solar scenario with respect to the minimum. Notice that in the spectral synthesis the UV is enhanced and at the Ca II opacity edge near 400 nm the negative solar cycle differences are found. This is to be compared with the SIM observations during the descending phase of the solar cycle. While the SIM observations generally show larger differences in the UV than the synthesis, the structure in the irradiance curves in the visible show a remarkable level of agreement. The detail of how the solar models from SRPM are very well documented and presented in a recently accepted paper in JGR that is now in press. Fontenla, J. M., et al. , JGR, 2011 SRPM analysis is able to capture offsetting trends observed by SIM, but the magnitude of the effect are different.

Solar spectral irradiance variability in NRL SSI Sunspot Case: 04/30/2005 Facula-Plage: 08/29/2005 This is a similar exercise but now comparing the SIM observations with the NRL SSI model Shown on the top plot is the TSI record that identifies a quiet sun day and then two days one dominated by plage regions and another nearby time that had a large sunspot group that significantly reduced the TSI The bottom two graphs shows the spectral response of the SIM instrument and the NRL model to these two events relative to the solar minimum day. Notice that SIM data shows significantly more variability relative to the quiet sun regardless of the sunspot and facular contribution suggesting that these quiet regions of the sun are still contributing to the irradiance and this is not present in the modeled variability. An interesting thing to note is that if you do a mental subtraction between the sunspot and plage cases for both SIM and the NRL model the difference between them is very similar suggesting that the sunspot and facular components are captured correctly in the NRL model, but the net changes relative to the solar minimum are not. Thus on rotational times scales the NRL model and the SIM observations give a similar answer but the longer term variations are different and a simple scaling of rotational variability does not reproduce the observations. Solar Min Ref: 11/09/2007 J. Lean, GRL., vol. 27, pp 2425, 2000.

Strömgren Filters wrt Brightness Temperature

SIM integrated over Strömgren bands

PSPT observations of facula Some facula and plage have negative contrast at red continuum wavelengths Position of dark faculae on the disk is not a simple function of heliocentric angle The fraction of dark Facula decreases into SC23 minimum and increases into rising phase of SC24 SLIDE 3 is animated: the two images change with successive mouse clicks When the slide first appears, the two images show processed PSPT images of archival quality. Top image is PSPT Ca II image, bottom is PSPT red continuum With the next mouse click, the Ca II image is replaced with the SRPM mask of the 5 solar features identified in Ca II, and the bottom shows the red continuum filter with the CLV removed, image now shows just the intensity variations With the next mouse click, the SRPM mask now shows plage and facular regions identified in the Ca II image that have negative contrast in the red image relative to the ‘quiet’ sun. The appearance of the black regions in the top image are identified as ‘dark’ plage and Facula. Graphs on the right show the abundance of these dark active regions through solar minimum and into the rise of the next cycle. The top graph shows the total amount of these dark facular regions over the full solar disk and the lower graph shows their fraction as a function of the mu angle, thus the occurrence of these dark regions tend to more present at disk center and fewer of them exist at the solar limb. The evolution of these dark facular regions and their CLV properties are captured in SRPM.

A compelling need for the Radiometric Solar Imager (RSI) Is the time dependence because the faculae (or unresolved underlying flux distributions) are changing, or because the CLV against which their contrast is measured is changing? Ground based instrumentation can only measure photometric contrast compared to some definition of the background “quiet-sun.” we do not know the center-to-limb variation of the “quiet-sun,” against which these contrasts are measured we do not know whether the structures, or the background against which they are measured, or both, are changing with solar cycle these differences are important in our interpretation of the solar spectral irradiance

RSI Concept Full disk photometric images with relative pixel-to-pixel precision of 1:103 Separate radiometer which shares imager filter wheel and precision aperture determines throughput of filter A filter transmission measurement prevents ambiguities in filter bandpass Advantage: Spectrometer does not require absolute calibration Can have high resolution, but limited bandpass

RSI Design 100 mm diameter entrance pupil and a 12.5mm aperture stop where the filters are positioned Placing the filters at the aperture stop significantly reduces the spatial uniformity requirements for the filters compared to placing them just before the focal plane array, and make them much smaller than placing them at the entrance Light path (ray angles) through filters is however slightly different in telescope than into radiometer

TSIS SIM derives heritage from SORCE SIM TSIS SIM designed for long-term spectral irradiance measurements (climate research) Incorporate lessons learned from SORCE SIM (& other LASP programs) into TSIS SIM to meet measurement requirements for long-term JPSS SSI record Specific required capabilities over SORCE SIM Reduce uncertainties in prism degradation correction to meet long-term stability requirement Ultra-clean optical environment to mitigate contamination Addition of 3rd channel to reduce calibration uncertainties Improve noise characteristics of ESR and photodiode detectors to meet measurement precision requirement Improved ESR thermal & electrical design Larger photodiode dynamic range integrating ADC’s (21 bits) Improve absolute accuracy pre-launch calibration NIST SI-traceable Unit and Instrument level pre-launch spectral calibrations (SIMRF-SIRCUS) SORCE SIM TSIS SIM

Conclusions The SIM observations indicate solar cycle trends both in- and out of phase with the TSI. Interpretable in terms of the solar brightness temperature and temperature gradients with the solar atmosphere SIM integrated over Strömgren v, b, & y filters reflect anti-solar cycle behavior with the u-filter in phase. The v, b, & y filters may not be adequate proxies of the TSI for sun-like stars SIM ultraviolet observations show a high degree of consistency with: Facula and plage areas measured by PSPT Calculated spectral irradiance estimated form SRPM SIM irradiance at 607 nm tends to under-estimate the reported PSPT sunspot areas and decreased irradiance is observed even when sunspot blocking is not indicated by PSPT 607 nm images. Plans Continued analysis of SIM data to determine behavior in SC24 is essential 2017 deployment of TSIS SIM is mandatory to further this research – but gaps are inevitable and difficult to resolve for SSI measurements The development of radiometric imagery is the next logical step for understanding solar variability and understanding the stellar connection

EXTRAS

Estimated trend uncertainties in the Visible Best observation for degradation corrections for SIM is 04/2004 to 05/2007, but magnitude of uncertainties similar in the 2007-2011 period Uncertainty in the visible comparable to 2σ noise levels but reaches a minimum level at ≈2×10-4. Errors in the 2003-2004 and after 2011 time period require further refinements Improved wavelength registration will reduce uncertainties in the visible

Improvements to be implemented in Version 20 (release planned for late spring 2014) Implement dynamical wavelength shifter based on instrument dispersion equations to account for thermal/mechanical stresses induced by spacecraft power cycling – Must be applied to every spectrum Particularly important for visible and infrared wavelengths from Sept 2011 to present time Reanalysis of photodiode and prism glass refractive index temperature coefficients due to decreased temperature stability Correct for non-exposure related photodiode degradation Not well represented in Version 19 Perform AB comparisons and determine ray path through the prism Particularly important for first year of the mission and after full-time power cycling of the instrument Version 20 analysis for UV and IR spectral regions has not started

The RSI will: Elucidate the underlying causes of solar spectral variability by making first radiometric measurements of the resolved solar disk First radiometric determination of center-to limb profiles of the quiet-sun and solar magnetic elements as a function of solar cycle First determine of the photospheric temperature gradient both within and outside of magnetic flux structures using opacity conjugate wavelengths Determine the veracity and cause of spectral irradiance trends for terrestrial climate modeling