Temperature scaling pattern dependence on representative concentration pathway emission scenarios A letter

To preserve consistency among developed emission scenarios, the scenarios used in climate modeling, and the climate scenarios available for impact research, the pattern scaling technique is useful technique. The basic assumption of pattern scaling is that the spatial response pattern per 1 K increase in the global mean surface air temperature (SAT) (scaling pattern) is the same among emission scenarios, but this assumption requires further validation. We therefore investigated the dependence of the scaling pattern of the annual mean SAT on GHGs emission scenarios of representative concentration pathways (RCP) and the causes of that dependence using the Model for Interdisciplinary research on Climate 5 developed by Japanese research community. In particular, we focused on the relationships of the dependency with effects of aerosols and Atlantic meridional overturning circulation. We found significant dependencies of the scaling pattern on emission scenarios at middle and high latitudes of the Northern Hemisphere, with differences of >15 % over parts of East Asia, North America, and Europe. Impact researchers should take into account those dependencies that seriously affect their research. The mid-latitude dependence is caused by differences in sulfate aerosol emissions per 1 K increase in the global mean SAT, and the high-latitude dependence is mainly caused by nonlinear responses of sea ice and ocean heat transport to global warming. Long-term trends in land-use and land-cover changes did not significantly affect the scaling pattern of annual mean SAT, but they might have an effect at different timescales.     

Modeling of spring bloom in the western subarctic Pacific (off Japan) with observed vertical density structure

Effects of vertical stability on spring blooms of phytoplankton were investigated for the western subarctic Pacific ocean using a one-dimensional (depth) ecosystem model. In the model, vertical stability was expressed by diffusion constants calculated from observed density distribution. Dynamics of phytoplankton in blooms was calculated by the model using the vertical diffusion. Then, the calculated results were compared with the Coastal Zone Color Scanner (CZCS) data. The comparison shows that the shallow surface mixed layer causes early start days of spring blooms at inshore (northern) stations. In addition, spring blooms continue long at inshore (northern) stations since a water column has weak stability. This is because weak stability of a water column causes large nutrient supply from a deep layer and large diffusive transport of phytoplankton biomass from the subsurface maximum.