Abstract

The early-to-mid Pliocene (3–5.3 Ma) is the most recent geologic period of significant global warmth. Proxy records of Pliocene sea surface temperature (SST) indicate significant and still unexplained warm anomalies of 3°C–9°C in midlatitude eastern boundary currents, where present-day cool temperatures are maintained by wind-driven upwelling. Here we quantify the effect of large-scale Pliocene-like SST patterns on the surface wind stress around the California, Humboldt, Canary, and Benguela midlatitude coastal upwelling sites. A high-resolution atmosphere model forced with Pliocene SST simulates changes in surface winds that imply reductions of 10% to 50% in both coastal upwelling, driven by alongshore wind stress, and offshore upwelling driven by wind stress curl. These changes result primarily from a reduced meridional temperature gradient which weakens the subtropical highs, and a reduction in zonal land-sea temperature contrast which weakens geostrophic alongshore winds. These results suggest that Pliocene coastal warm anomalies may result in part from atmospheric circulation changes which reduce upwelling intensity. The coastal wind stress and offshore wind stress curl are shown to respond differently to incremental changes in SST, topography, and land surface anomalies. Significant decreases in simulated cloud fraction within the subtropical highs suggest that a weaker land-sea temperature contrast could be maintained by cloud radiative feedbacks.

Highlights

  • Since the the discovery of the 2.7 K cosmic microwave background (CMB) by Penzias & Wilson (1965), rapid progress in instrumental sensitivity has permitted the detection of progressively subtler effects

  • BICEP2 employs a combination of high magnetic permeability and superconducting shielding to block external magnetic fields, and its scan strategy allows for nearly perfect filtering (“ground subtraction”) of pickup that is constant in time and a function of telescope pointing direction, as is expected of most magnetic fields

  • We have extended our pipeline to optionally incorporate the effects of various instrumental systematics into these simulated data, which allows us to model their effects on the final power spectra and r estimate

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Summary

INTRODUCTION

Since the the discovery of the 2.7 K cosmic microwave background (CMB) by Penzias & Wilson (1965), rapid progress in instrumental sensitivity has permitted the detection of progressively subtler effects. The degree scale primary CMB temperature anisotropies are polarized at the ∼1% level (Kovac et al 2002), with fluctuations of the order of 1 μK. This polarization, which arises as a natural consequence of the same acoustic oscillations that source the temperature anisotropies (Bond & Efstathiou 1984), is curl-free (E-mode) and its angular power spectrum is uniquely predicted given the temperature (T) spectrum with the addition of no additional cosmological parameters. Effects that convert CMB temperature anisotropy into a false polarization signal are of particular importance This is especially true for B-mode measurements because both the temperature and the expected inflationary Bmode spectra peak at similar angular scales. In a series of four appendices we provide the formal definition of our elliptical Gaussian beam parametrization (Appendix A), an expanded discussion of beam shape mismatch (Appendix B), the mathematical and practical details of deprojection (Appendix C), and a discussion of the uncertainties in the beam mismatch simulations (Appendix D)

INSTRUMENT DESIGN AND OBSERVATIONAL STRATEGY
Instrument Design
Observational Strategy and Data Cuts
Natural mitigation
Time-domain filtering
Deprojection
Jackknife maps
Time-domain simulations
NOISE ESTIMATION
BEAM SYSTEMATICS IN MAPS
Incoherence Across the Focal Plane
Symmetry
Monopole Symmetric difference Beam
Dipole Symmetric difference Beam
Quadrupole Symmetric difference Beam
Summary
DEPROJECTION TECHNIQUE
Beam Parametrization
Algorithm
SIMULATION PIPELINE
Input Maps and Interpolation
Elliptical Gaussian Beam Convolution
Arbitrary Beam Shape Convolution
JACKKNIFE TESTS
DEPROJECTION PERFORMANCE
Template Map Non-idealities
Consistency with Beam Maps
10. SYSTEMATICS ERROR BUDGET
10.1. Undeprojected Residual Beam Mismatch
10.1.1. Undeprojected Residual in Signal Maps
10.1.2. Undeprojected Residual in Jackknife Maps
10.1.3. Undeprojected Residual Correction
10.2. Further consideration of Gain mismatch
10.3. Gain Variation
10.4. Crosstalk
10.5. Ghost Beams
10.6.2. Random Polarization Angle Error
10.8. Thermal Instability
10.9. Detector Transfer Functions
10.10. Magnetic Pickup
10.11. Electromagnetic Interference
11. CONCLUSIONS
Differential Pointing
Beamwidth
Ellipticity
Differential Gain
Differential Beamwidth
Differential Ellipticity
Practical Implementation
Full Text
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