Simulations of wintertime precipitation in the vicinity of Japan: Sensitivity to fine‐scale distributions of sea surface temperature

Abstract

[1] In the present study, the winter precipitation in the vicinity of Japan is simulated by the Weather Research Forecasting model by using two sets of sea surface temperature (SST) data with different spatial resolutions. On comparing the simulated mean precipitations, we found that SST resolution has a significant influence on the simulated precipitation along the northwestern coast of Japan; in this region, the coarse-resolution SST data have a systematic cold bias. In the simulation using high-resolution SST data, the moisture supply to the atmosphere increases over the relatively warm coastal SST. The increase in the moisture supply leads to an increase in the moisture convergence near the mountain ranges in Japan on the Japan Sea side, leading to an increase in precipitation amount. The result suggests that coastal SST must be carefully used for dynamic downscaling of the climate simulation, in particular, in Japan, which is surrounded by boundary currents. We also found that a small-scale SST anomaly in the Kuroshio-Oyashio Extension (KOE) region near Japan enhances the interannual variance of local precipitation in the regions downwind of the SST anomaly. The associated anomalous ascent extends to the midtroposphere and is accompanied by an increase in cloud ice, suggesting that the interannual SST variation over the KOE region may affect the free atmosphere. Moisture budget analysis indicates the influence of moisture advection by mean wind on the spatial phase difference between the SST and precipitation anomalies.

A review on regional dynamical downscaling in intraseasonal to seasonal simulation/prediction and major factors that affect downscaling ability

“…Apparently inputs from LBCs every six hours impose great constraints on an RCM's temporal variability. This situation is quite consistent in many dynamic downscaling studies, in which SST was specified from the same data set as LBC data (e.g., Chou et al, 2002;Xue et al, 2007;Iizuka, 2010). Imposed LBCs in a fixed time interval greatly hamper the RCM's ability to add value in temporal variability.…”

Meteorological impacts of sea-surface temperature associated with the humid airflow from Tropical Cyclone Talas (2011)

“…Estimates of coastal SST are strongly dependent on the data products used (e.g., Xie et al, 2008) due to the differences in interpolation methods and resolution. Differences in coastal SST have a large influence on clouds and precipitation, and this effect has been thoroughly investigated for both cold air outbreaks and winter monsoons Hirose, 2008, 2009;Iizuka, 2010;Lee and Ryu, 2010;Xu et al, 2010;Cha et al, 2011;Yamamoto et al, 2011;Takahashi et al, 2013). However, the effects of differences in SST products on the humid summer airflows associated with tropical cyclones have yet to be fully investigated.…”

Validating the dynamic downscaling ability of WRF for East Asian summer climate

“…In this kind of dynamic downscaling method (DDM), regional climate models (RCMs) are forced by surface boundary conditions from a coupled ocean and/or land surface model, together with lateral boundary conditions (LBCs) from GCMs or reanalyses, which are also applied as initial conditions of RCMs. The RCMs have been widely used for both past climate simulations (Chou et al 2002;Iizuka 2010;De Sales and Xue 2013) and future climate projection (Liang et al 2008;Chen et al 2010;Boberg and Christensen, 2012;Mearns et al 2012;Yu and Wang 2013). However, many issues related to the downscaling capability of this method usually cause skepticism for the application of RCMs (Laprise et al 2000;Castro et al 2005;Rockel et al 2008;Xue et al 2014), mainly because it is unclear that whether the DDM is really capable of adding more climate information at different scales compared with the GCM results or reanalysis, especially for long-term run, and if so under what conditions?…”