The study proposes the simplification of the multilayer urban canopy model. Four types of multilayer urban canopy models-level 4, level 3, level 2, and level 1-are developed to reduce the computational load of the heat budget calculations at the wall surface. The level 4 model, which accounts for the wall directions and the vertical layer, is simplified in three ways: the level 3 model only accounts for the vertical layers, the level 2 model accounts for the wall directions, and the level 1 model accounts for neither the wall directions nor the vertical layer. From the simplification, compared to the level 4 model, the memory is reduced by 57%, 65%, and 72% for the level 3-level 1 models, respectively, when the vertical canopy layer is seven. At the same time, the CPU time is reduced by 67%, 70%, and 78% for the level 3-level 1 models. Then, each canopy model is compared with observations in Tokyo. The results show that the simulations from the four models are close to the observed ones, and the differences among the four models are very small. An additional model intercomparison study based on idealized simulations indicates that the level 3 model can be used instead of the level 4 model in any condition, whereas the level 2 and level 1 models are proposed to be used under conditions with a large sky view factor.

A climatological and numerical study of "Karakkaze," a type of local wind in Japan, was conducted. First, winter days under a winter-type synoptic pressure pattern with daily minimum relative humidity of less than 40% were classified according to strong wind (wind speed � 9 ms −1 , Karakkaze day), medium wind (6 ms −1 � wind speed < 9 ms −1 ), and weak wind (wind speed < 6 ms −1 ). Secondly, the spatial patterns of the surface wind in each category are confirmed by the Japan Meteorological Agency (JMA)-Automated Meteorological Data Acquisition System (AMeDAS) observation data. In addition, we compared the boundary-layer wind of the three categories using wind speed data from the observation tower of the Meteorological Research Institute (MRI) in Tsukuba and from the JMA wind profiler in Kumagaya. Finally, we performed one-dimensional numerical experiments using a column Planetary Boundary Layer (PBL) model to evaluate the impact of solar radiation and upper-level wind on the formation of the Karakkaze.The results are summarized as follows. On the strong-wind days, strong northwesterly winds appear in the area along the Arakawa River and the Tonegawa River from Maebashi. The surface wind speed has a clear diurnal variation with a peak in the early afternoon. Such a diurnal variation is observed up to a 200 m level, but this diurnal pattern nearly reverses itself between 200 m and 400 m levels. On weak-wind days, the diurnal variation pattern is similar to that in other two categories, but the reversed pattern appears at a 100 m level, not at a 200 m level.Stronger surface winds appear under a clearer winter-type pressure pattern. The correlation coefficient is 0.632 between the daily maximum surface wind speed and the daily mean wind speed at a height of 2759 m, whereas the correlation is 0.284 between the surface wind speed and daily sunshine duration, which, in a previous study, was suggested to be the most significant factor.Numerical experiments indicate that a large amount of solar radiation is a necessary condition for a strong daytime wind, but this is not a sufficient explanation for the difference in the surface wind speed between weak and strong-wind days.

This study presents a method for probabilistic forecasting of solar irradiance based on the joint probability distribution function (PDF) of irradiance predicted by numerical weather prediction (NWP) and irradiance observed. Multidimensional kernel density estimation was used to construct this joint PDF. The probabilistic forecast is obtained by deriving a conditional PDF given a current NWP by using the Bayes rule. The proposed method can naturally handle the nonlinear nature of the relation between observed and predicted irradiance. The method showed better statistical performance in terms of the continuous ranked probability score, reliability, and sharpness than an existing probabilistic forecasting method based on ensemble NWP. Simulation of solar power trading based on pricing of an actual electric power market also confirmed that the proposed method results in greater profit by suppressing penalties imposed due to overbidding.

Sudden changes in wind speed, so‐called wind speed ramps, are a major concern for wind power system operators. The present study applies the mesoscale ensemble forecast method for the prediction of wind speed ramps at wind farms in Japan and evaluates the ability and utility of this method. The mesoscale ensemble forecast in this study (ENS21) consists of 21 members with a horizontal resolution of 10 km for a 5‐year period. The simulated results show that ENS21 produces better accuracy than the deterministic forecast with a horizontal resolution of 10 km (DET_L). On the other hand, the deterministic forecast with a horizontal resolution of 5 km (DET_H) also produces better accuracy than DET_L. From a practical perspective, however, the ENS21 is computationally expensive. Thus, the eight‐member mesoscale ensemble forecast (ENS8) with as same computational cost as a deterministic forecast with a horizontal resolution of 5 km (DET_H) is also evaluated. The simulated results show that ENS8 has almost same accuracy as ENS21 and DET_H in wind speed ramp forecasts. ENS8 has advantages over ENS21 and DET_H because ENS8 is computationally efficient and is able to benefit wind power operators with flexibility in the selection of probability thresholds for decision processes compared with a single. It can be concluded that the mesoscale ensemble forecast method is more useful for prediction of the wind speed ramp than the single deterministic forecast method with the same computational cost if the ensemble members are successfully selected.

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