Preliminary assessment for sub-seasonal to seasonal precipitation model on four specific conditions over western Indonesia

Preliminary assessment of sub-seasonal to seasonal reforecast precipitation model (S2S) was conducted to analyze the model's performance over western Indonesia on four conditions. The ECMWF S2S model was compared to quality controlled daily precipitation data from 645 observation points over the region. The control and perturbed model for the first three time steps and the last three were utilized to obtain the best performance comparison. The analysis was conducted in monthly period, MJO events, NCS events, and when both of them were active during period of November-December-January-February (NDJF) from 1998 to 2017. The results show that the first three time steps perform much better than the last one with a slightly higher correlation coefficient from the control model with relatively similar RMSE in Natuna Islands. Spatial analysis indicates that both of the control and perturbed models can catch the variation brought by the wet season in the NDJF period, by the MJO, show a hint of NCS effect, and the combination when MJO and NCS were active at the same time. The models can depict the precipitation pattern pretty well with the tendency to overestimate low rainfall intensity and underestimate the high one. The models relatively overestimate the intensity in Sumatra for the whole period. Meanwhile, consistently good spatial performance is shown by the models over Java, both in NDJF periods or MJO events.

A panoramic view of the circumgalactic medium in the photoionized precipitation model

ABSTRACT We consider a model of the circumgalactic medium (CGM) in which feedback maintains a constant ratio of cooling time to free-fall time throughout the halo, so that the entire CGM is marginally unstable to multiphase condensation. This ‘precipitation model’ is motivated by observations of multiphase gas in the cores of galaxy clusters and the haloes of massive ellipticals. From the model, we derive the density and temperature profiles for the CGM around galaxies with masses similar to the Milky Way. After taking into consideration the geometrical position of our Solar system in the Milky Way, we show that the CGM model is consistent with observed O vi, O vii, O viii column densities and the ratio of O vii and O viii column densities only if temperature fluctuations with a lognormal dispersion σln T ∼ 0.6–1.0 are included. We show that O vi column densities observed around star-forming galaxies require systematically greater values of σln T than around passive galaxies, implying a connection between star formation in the disc and the state of the CGM. Photoionization by an extragalactic ultraviolet background radiation does not significantly change these CGM features for galaxies like the Milky Way but has much greater and significant effects on the CGM of lower mass galaxies.

Simulation of Primary Particle Development and Their Impact on Microstructural Evolution of Sc-Modified Aluminum Alloys during Additive Manufacturing

The microstructures of additively manufactured Sc- and Zr-modified aluminum alloys are significantly influenced by the nucleation role of solid intermetallic particles in undercooled liquid. To replicate such effects, a precipitation model relying on L12-Al3Sc particles is developed. An initiation criterion is proposed based on the precipitation kinetics of primary particles to address solute trapping under high solidification rates. Avrami’s equation is then used to estimate the progress of precipitation. The model is integrated into a cellular automata (CA) analysis to simulate the resulting solidified microstructure, in that the precipitation model is performed implicitly within the CA cells. It is shown that, in accordance with the experimental findings, the proposed simulation approach can predict the distinct fine- (FG) and coarse-grained (CG) zones at the fusion boundary and the meltpool core, respectively. The model can also deliver the reported enhancement of the FG zone under lower scanning speed and higher platform temperatures. These findings are explained in terms of particle number densities at different meltpool regions. Moreover, a semi-2D simulation with a very small cell size is suggested to address the extremely fine grain structure within the FG zone.

On the Need to Reparametrize the OVATION Prime (2010) Auroral Precipitation Model

The need to reparametrize the OVATION Prime (2010) empirical auroral precipitation model using the Russian polar cap index (PC index) is considered. For this purpose, the integrated auroral power of particle precipitation obtained from the Polar satellite data for the period from December 1996 to June 1998 is compared with the PC index and the Newell’s coupling function. The analysis revealed that the PC index at the time delays up to 5–20 minutes correlates with the magnitude of auroral power much better (the correlation coefficient R ~ 0.76–0.87) than the Newell’s coupling function (R ~ 0.46–0.82). Thus, for the purpose of nowcasting the zone of active particle precipitation, the PC index showed much higher scores, although the predicting abilities of the Newell’s coupling function for the time delays of more than 20 minutes remain the best.

Regional Precipitation Model Based on Geographically and Temporally Weighted Regression Kriging

High-resolution precipitation field has been widely used in hydrological and meteorological modeling. This paper establishes the spatial and temporal distribution model of precipitation in Hubei Province from 2006 through 2014, based on the data of 75 meteorological stations. This paper applies a geographically and temporally weighted regression kriging (GTWRK) model to precipitation and assesses the effects of timescales and a time-weighted function on precipitation interpolation. This work’s results indicate that: (1) the optimal timescale of the geographically and temporally weighted regression (GTWR) precipitation model is daily. The fitting accuracy is improved when the timescale is converted from months and years to days. The average mean absolute error (MAE), mean relative error (MRE), and the root mean square error (RMSE) decrease with scaling from monthly to daily time steps by 36%, 56%, and 35%, respectively, and the same statistical indexes decrease by 13%, 15%, and 14%, respectively, when scaling from annual to daily steps; (2) the time weight function based on an exponential function improves the predictive skill of the GTWR model by 3% when compared to geographically weighted regression (GWR) using a monthly time step; and (3) the GTWRK has the highest accuracy, and improves the MAE, MRE and RMSE by 3%, 10% and 1% with respect to monthly precipitation predictions, respectively, and by 3%, 10% and 5% concerning annual precipitation predictions, respectively, compared with the GWR results.