Comparison of algorithms for estimating ocean primary production from surface chlorophyll, temperature, and irradiance

Abstract

[1] Results of a single-blind round-robin comparison of satellite primary productivity algorithms are presented. The goal of the round-robin exercise was to determine the accuracy of the algorithms in predicting depth-integrated primary production from information amenable to remote sensing. Twelve algorithms, developed by 10 teams, were evaluated by comparing their ability to estimate depth-integrated daily production (IP, mg C m À2 ) at 89 stations in geographically diverse provinces. Algorithms were furnished information about the surface chlorophyll concentration, temperature, photosynthetic available radiation, latitude, longitude, and day of the year. Algorithm results were then compared with IP estimates derived from 14 C uptake measurements at the same stations. Estimates from the best-performing algorithms were generally within a factor of 2 of the 14 C-derived estimates. Many algorithms had systematic biases that can possibly be eliminated by reparameterizing underlying relationships. The performance of the algorithms and degree of correlation with each other were independent of the algorithms' complexity.

Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models

“…Previous primary production intercomparison exercises matched in situ carbon uptake rates with NPP estimated mostly from ocean color models (OCMs) [e.g., Balch et al, 1992;Campbell et al, 2002;Saba et al, 2011] and, more recently, from some coupled biogeochemical ocean general circulation models (BOGCMs) [Carr et al, 2006;Friedrichs et al, 2009;Saba et al, 2010] in various regions of the ocean except the Arctic Ocean. Popova et al [2012] and Vancoppenolle et al [2013] reported the results from various BOGCMs and Earth System Models (ESMs) that were compared for the Arctic domain against satellite-derived NPP albeit with known issues.…”

A comparison of global estimates of marine primary production from ocean color

“…A series of round-robin experiments have been carried out to evaluate and compare models which estimate primary productivity from ocean color (Campbell et al, 2002). In these experiments, in situ measurements of carbon uptake were used to test the ability of the participating models to predict depth-integrated primary production (PP) based on information accessible via remote sensing.…”

“…The first round-robin experiment used data from only 25 stations. The second primary production algorithm round robin (PPARR2) used data from 89 stations with wide geographic coverage (Campbell et al, 2002). There were 10 participant teams and 12 models.…”

Estimasi Produktivitas Primer Perairan Berdasarkan Konsentrasi Klorofil-a Yang Diekstrak Dari Citra Satelit Landsat-8 Di Perairan Kepulauan Karimun Jawa

“…Selain itu, kendala dari model hubungan antara konsentrasi klorofil-a dan produktivitas primer perairan yaitu salah satunya karena sensor satelit hanya mampu mendeteksi pada kedalaman permukaan laut atau kedalaman satu atenuasi cahaya (Kuring et al, 1990). Menurut (Campbell et al, 2002) konsentrasi klorofil-a permukaan hanya mampu menjelaskan kurang lebih 30 % produktivitas primer laut sedangkan produktivitas primer berlangsung sampai 4,6x kedalaman atenuasi cahaya atau kedalaman kompensasi (Kuring et al, 1990;Balch et al, 1992). Kedalaman kompensasi sendiri merupakan kedalaman dimana intensitas cahaya tinggal 1% dari intensitas cahaya di permukaan dimana proses fotosintesis dan respirasi seimbang (Kirk, 2011;Parson et al, 1984).…”

“…Konsentrasi klorofil-a paling tinggi berada pada lapisan kedalaman tengah zona eufotik dimana hal tersebut dikarenakan intensitas cahaya yang terlalu tinggi pada lapisan permukaan dan intensitas yang semakin menurun ketika mendekati lapisan kedalaman kompensasi (Asriyana dan Yuliana, 2012). Pengetahuan distribusi vertikal konsentrasi klorofil-a seharusnya dapat digunakan untuk membuat algoritma produktivitas primer perairan (Campbell et al, 2002). Menurut Sathyendranath dan Platt (1989), dua cara dalam memprediksi distribusi biomassa fitoplankton pertama adalah distribusi vertikal pada biomassa fitoplankton adalah seragam dalam percampuran air yang baik pada lapisan permukaan, oleh karena itu konsentrasi klorofil pada banyak kedalaman adalah seimbang sampai subsurface dan masih mungkin dilakukan dengan pengukuran satelit kemudian yang kedua adalah kondisi stratifikasi dimana lapisan subsurface maksimum biasanya terdapat pada kisaran kedalaman dari permukaan sampai lapisan eufotik (1% atau intensitas cahaya tinggal 1%).…”