Abstract

The NASA PACE mission is a hyper-spectral radiometer planned for launch in the next decade. It is intended to provide new information on ocean biogeochemical constituents by parsing the details of high resolution spectral absorption and scattering. It is the first of its kind for global applications and as such, poses challenges for design and operation. To support pre-launch mission development and assess on-orbit capabilities, the NASA Global Modeling and Assimilation Office has developed a dynamic simulation of global water-leaving radiances, using an ocean model containing multiple ocean phytoplankton groups, particulate detritus, particulate inorganic carbon (PIC), and chromophoric dissolved organic carbon (CDOC) along with optical absorption and scattering processes at 1 nm spectral resolution. The purpose here is to assess the skill of the dynamic model and derived global radiances. Global bias, uncertainty, and correlation are derived using available modern satellite radiances at moderate spectral resolution. Total chlorophyll, PIC, and the absorption coefficient of CDOC (aCDOC), are simultaneously assimilated to improve the fidelity of the optical constituent fields. A 5-year simulation showed statistically significant (P <0.05) comparisons of chlorophyll (r = 0.869), PIC (r = 0.868), and aCDOC (r = 0.890) with satellite data. Additionally, diatoms (r = 0.890), cyanobacteria (r = 0.732), and coccolithophores (r = 0.716) were significantly correlated with in situ data. Global assimilated distributions of optical constituents were coupled with a radiative transfer model (Ocean-Atmosphere Spectral Irradiance Model, OASIM) to estimate normalized water-leaving radiances at 1 nm for the spectral range 250–800 nm. These unassimilated radiances were within −0.074 mW cm−2 μm1 sr−1 of MODIS-Aqua radiances at 412, 443, 488, 531, 547, and 667 nm. This difference represented a bias of −10.4% (model low). A mean correlation of 0.706 (P < 0.05) was found with global distributions of MODIS radiances. These results suggest skill in the global assimilated model and resulting radiances. The reported error characterization suggests that the global dynamical simulation can support some aspects of mission design and analysis. For example, the high spectral resolution of the simulation supports investigations of band selection. The global nature of the radiance representations supports investigations of satellite observing scenarios. Global radiances at bands not available in current and past missions support investigations of mission capability.

Highlights

  • The 19-year time series of routine global ocean color observations from space has led to advancements in the science of ocean biology beyond expectations

  • We evaluate ocean optical constituents, phytoplankton, total chlorophyll, particulate inorganic carbon (PIC), and absorption coefficient of chromophoric dissolved organic carbon (CDOC) (aCDOC), the latter three of which are provided as data sets from MODIS-Aqua

  • We have described a comprehensive model of optical constituents and their influences on hyper-spectral upwelling radiance in the global oceans

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Summary

INTRODUCTION

The 19-year time series of routine global ocean color observations from space has led to advancements in the science of ocean biology beyond expectations. (e.g., Bracher et al, 2009; Sadeghi et al, 2012; Palacios et al, 2015; Neukermans et al, 2016) To close this knowledge gap, NASA has proposed the PACE mission, a global hyper-spectral sensor to test the ability to retrieve phytoplankton population distributions, as well as other important ocean constituents with optical signatures. We develop a dynamic global model at extreme hyper-spectral resolution (1 nm) to provide a platform to approximate realistic ocean conditions and help with resolving at least some of these issues and understand if such a simulation can assist in resolving many of the issues that inevitably arise in the design and testing of a new mission The objective of this effort is to quantitatively assess the skill of a global model using a forward radiance representation to simulate global ocean water-leaving radiances.

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