Institut für Umweltphysik (IUP) Institut für Fernerkundung (IFE)

1. CarbonSat L1L2 Study Final Presentation, 3-Jul-2013 Universität Bremen, FB1 Physik und Elektrotechnik Institut für Umweltphysik (IUP) Institut für Fernerkundung (IFE) • CarbonSat: • Potentials of aRapid-Readout-Imager (RRI) • ESA Study CarbonSat Earth Explorer 8 Candidate Mission • “Level-2 and Level-1B Requirements Consolidation Study“ • ESA Contract No 4000105676/12/NL/AF Max Reuter, Michael Buchwitz, Heinrich Bovensmann University of Bremen, Bremen, Germany Hartmut Boesch University of Leicester, Leicester, UK 1

2. Motivation • XCO2 and XCH4 retrievals are sensitive to the knowledge of atmospheric scattering (aerosol, cirrus et c.), clouds and surface albedo. • Original CarbonSat proposal (2010) includes a dedicated Cloud & Aerosol Imager (GOSAT CAI heritage), but was descoped before phase A. • Study investigated usage of external information (met. Imagers, data bases), but lack of spatial/temporal co-registration identified. • Idea: generate temporally/spatially un-binned data in a few small spectral windows sensitive to clouds, aerosols, surface albedo, to get co-registered high resolution information

3. Introduction • Some detectors allow a spatially and temporally oversampled readout (here called Rapid-Readout (RR)) • Even though RR has reduced SNR performance, sub pixel information can still be extremely valuable • Reduced SNR performance can be partly compensated by spectral binning • Within this presentation, the benefits of 16 potential RR-channels will be discussed • Ideally, the selection of channels is programmable (detector, position, binning) and only limited by the data-rate

4. Detection of Sub-Pixel-Clouds • Clouds are spatially variable and bright (e.g. Ackerman et al., Rossow et al., Kriebel et al., …) : RRI-4, RRI-6 • Clouds are high (e.g., Preusker et al.):RRI-4, RRI-5, RRI-6 • Cirrus clouds are above the main atmospheric water vapor (e.g., Ackerman et al.): RRI-13

5. Microphysical Cloud Classification • Cloud thermodynamic phase detection (ice absorbs at 1.6µm, e.g. Nakajima and King):RRI-6, RRI-9 • Reflectivity of clouds vary with droplet radius within the SWIR (e.g., Nakjima and King, Schüller et al.):RRI-6, RRI-9, RRI-16

6. CO2 and CH4 • Potential for a simple HR light path proxy method at point sources of CO2 or CH4(e.g., Krings et al.): RRI-7, RRI-8, RRI-9, RRI-10, RRI-11, RRI-12, RRI-14, RRI-15, RRI-16 • Potential for spatial up-scaling of full physics CO2 and CH4 results:RRI-7, RRI-8, RRI-9, RRI-10, RRI-11, RRI-12, RRI-14, RRI-15, RRI-16

7. … and more • Potential for a simple HR chlorophyll fluorescence retrieval (e.g., Frankenberg et al., Joiner et al.): RRI-1, RRI-2, RRI-3 • The simple HR retrieval could also be used for up-scaling of a more sophisticated LR retrieval • Support for co-registration analysis • Analysis and detection of inhomogeneous scenes

8. Proposed Channels NIR

9. Proposed Channels SWIR1

10. Proposed Channels SWIR2

11. Summary • The implementationof rapid readoutimagingcapabilitiesishighlyrecommended • MRD 1.2 takesthat on-board

12. SNR and Data Rate • Assuming 8 x spatial and 3x temporal readouts gives 24 sub-pixels within a CS pixel. • SNR reduces by sqrt(24) if no spectral binning is applied. • Spectral binning can enhance SNR to nominal values. • 24 sub-pixels times 16 channels would enhance total data-rate by about 6-7% • Under the assumption of a lower SNR, the transmitted dynamic range can potentially be reduced from 14 to 12 bits resulting in an 5-6% higher data rate in total.