Biological dinitrogen (N2) fixation is an important new nitrogen source in oligotrophic subtropical oceans. In numerical model studies, the east-west gradient of iron deposition as atmospheric Asian dust strongly affects the zonal distribution of N2 fixation activity in the North Pacific, but the in-situ relationship at a basin-scale is not well examined. We examined the trans-Pacific longitudinal variation in N2 fixation activity from 120°W to 137°E at 23°N in summer with environmental parameters that potentially influence diazotrophy. The dissolved inorganic iron concentration in surface water was consistently low (<0.4 nM) throughout the study area. The modelled deposition flux of iron as atmospheric dust (dust-Fe) largely increased westward, whereas labile phosphorus (phosphate and labile phosphoric monoesters) in the surface water decreased westward. N2 fixation varied between 34.6–298 µmol N m-2 day-1 and was high (>200 µmol m-2 day-1) in the central area (150–180°W), where both dust-Fe input and the phosphorus stock were in intermediate ranges. The rates of N2 fixation showed an increasing trend with dust-Fe input in the eastern and western parts of 180°, indicating that increasing dust input enhanced N2 fixation activity. However, compared with that of the eastern region, the effect of enhancement on activity was smaller in the western region, where phosphate concentration in the euphotic zone was low (<50 nM), presumably due to the higher iron requirement to utilize organic phosphorus. Our data show that phosphorus availability substantially controls the longitudinal distribution of N2 fixation through co-limitation with iron in the subtropical North Pacific.

A broad range of attempts have been made to quantify the macroeconomic impacts of climate change, such as those of intensifying weather extremes and of yield losses of major crops, which have been synthesized by the efforts to estimate the Social Cost of Carbon (e.g., the US Interagency Working Group, 2016). However, up to the present, few insights have been fed into these debates as to the economic impacts associated with climatic responses of aerosol emissions from wildfires. In this study, we shed light on the potential scale of macroeconomic impacts of Siberian wildfires’ climatic effects by drawing on results of sensitivity experiments on enhanced biomass burning (BB) emissions over the defined Siberian domain using a global aerosol climate model, MIROC-SPRINTARS, in which the model was coupled with the ocean model (i.e., Atmosphere-Ocean coupled Global Climate Model: AOGCM) – the scientific results of these simulations are also discussed in detail by our companion paper, Yasunari and Takemura (2019), in the same session at this AGU Fall Meeting 2019. We used sets of simulation results differing in the conditions of BB emissions and climate, in which three different reference levels of BB emissions over the defined Siberian domain were used under the present (RCP scenario in 2005) or future climate (RCP2.6 and RCP8.5 in 2030) conditions. Differentials of annual average temperatures estimated by the simulations were used to compute monetary-equivalent economic impacts attributable to climatic effects of BB by applying the functions of the RICE-2010 model (the 2010 version of the regional integrated model of climate and the economy model: Nordhaus, PNAS, 2010), which is a regionally disaggregated version of the most widely used climate-economy model, the DICE model. The economic impacts were estimated for the most affected countries and regions by Siberian wildfires, such as Russia, China and Europe.

Biases in aerosol optical depths (AOD) and land surface albedos in the AeroCom models are manifested in the top-of-atmosphere (TOA) clear-sky reflected shortwave (SW) fluxes. Biases in the SW fluxes from AeroCom models are quantitatively related to biases in AOD and land surface albedo by using their radiative kernels. Over ocean, AOD contributes about 25% to the 60°S-60°N mean SW flux bias for the multi-model mean (MMM) result. Over land, AOD and land surface albedo contribute about 40% and 30%, respectively, to the 60°S-60°N mean SW flux bias for the MMM result. Furthermore, the spatial patterns of the SW flux biases derived from the radiative kernels are very similar to those between models and CERES observation, with the correlation coefficient of 0.6 over ocean and 0.76 over land for MMM using data of 2010. Satellite data used in this evaluation are derived independently from each other, consistencies in their bias patterns when compared with model simulations suggest that these patterns are robust. This highlights the importance of evaluating related variables in a synergistic manner to provide an unambiguous assessment of the models, as results from single parameter assessments are often confounded by measurement uncertainty. We also compare the AOD trend from three models with the observation-based counterpart. These models reproduce all notable trends in AOD (i.e. decreasing trend over eastern United States and increasing trend over India) except the decreasing trend over eastern China and the adjacent oceanic regions due to limitations in the emission dataset.