# The Spatiotemporal Variability of Temperature and Precipitation Over the Upper Indus Basin:
## 2 Materials and Methods
### WRF Model Configuration  
The Advanced Research Weather Research & Forecasting model (ARW-WRF, hereafter WRF) Version 3.8.1 [26] was used to downscale 16 years (2000-2015) of CFSR data dynamically [27], which have approximately a 38 km horizontal grid resolution. These simulations were a continuous run with a spin-up year (i.e., 2000) to equilibrate the soil moisture, snow cover, and temperature at the beginning of the simulation. The motivation for using CFSR data in this study was taken from [PERSON] and [PERSON] [34], wherein they evaluated several datasets over the Tibetan Plateau. They found CFSR and the Interim European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis datasets (ERA-Interim) to simulate atmospheric changes effectively. They showed that both datasets presented smaller RMS error and mean bias. The main reason for selecting the CFSR dataset, specifically in this study, was its resolution. The CFSR dataset had a higher spatial resolution (0.5\({}^{\circ}\) by 0.5\({}^{\circ}\)) than ERA-Interim (0.75\({}^{\circ}\) by 0.75\({}^{\circ}\)). The WRF model used in this study was configured with three nested domains with gradually increasing horizontal resolution from 36 km through 12 km to convection-permitting 4 km so that the innermost domain did not rely on a cumulus parameterization. The model configuration presented in Figure 1 was specifically chosen to limit the influence of boundary conditions on the results by assuring large margins between the nested domains. In addition, the relaxation zone of five points used in this study was very small compared to the domain sizes. The choice of the innermost domain size stemmed from work by [PERSON] et al. [15], who emphasized that a fine grid cell resolution was required to resolve orographic precipitation in this region. The detailed model strategy and parametrization schemes used in this study are given in Table 1. \begin{table}
\begin{tabular}{c c} \hline \hline A. Physical parameterization schemes \\ \hline Land surface model (LSM) & Noah multi-parameterization (Noah-MP) [35] \\ Planetary boundary layer (PBL) & Yonsei University (YSU) scheme [36] \\ Microphysics & Thompson microphysics scheme [37] \\ Longwave radiation & Rapid radiative transfer model (RRTM) [38] \\ Shortwave radiation & [PERSON] scheme [39] \\ Surface Layer & Revised MM5 scheme [40] \\ Cumulus parameterization & Kain–Fritsch scheme [41] in d01 and d02 \\ \hline B. Grids and Nesting Strategy \\ \hline Nesting & Two-way nesting; \\  & Nested in a cascade approach (d01-d02-d03) \\  & d01 36 km resolution (146 \(\times\) 115) \\ Horizontal grid cell resolution & d02 12 km resolution (270 \(\times\) 219) \\  & d03 4 km resolution (526 \(\times\) 403) \\ Map projection & Lambert conformal \\ Number of vertical layers & 38 \\ Top-level pressure & 10,000 Pa \\ Center point of domains & 30.75\({}^{\circ}\)N, 76.00\({}^{\circ}\)E \\  & Parent time step ratio of 1:3 \\ Timestep & 120 s in d01, 40 s in d02, and 13.33 s in d03 \\  & Outer domain (d01) has 146 by 115 grid spaces; \\ Size of domains & middle domain (d02) has 271 by 220 grid spaces; \\  & inner domain (d03) has 526 by 403 grid spaces \\ \hline C. Sensitivity Analysis \\ \hline Simulation 1 & [PERSON] and Noah-MP \\ Simulation 2 & [PERSON] and Noah-MP \\ Simulation 3 & Goddard and Noah-MP \\ Simulation 4 & [PERSON] and CLM4 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Model strategy. d01, Domain 01. Research showed that WRF was highly sensitive to the selection of the land surface model (LSM) and cloud microphysical scheme [15]. Based on limited computational resources, four simulation experiments (Table 1. Section C) were performed for the year 2004 with a combination of three cloud microphysical schemes ([PERSON], [PERSON], and Goddard) and two land surface models (Noah-multi-parameterization (Noah-MP) and (Community Land Model version 4 (CLM4)) over the UIB. The RMS error and Pearson's r between WRF, stations, and TRMM data were estimated at Skardu station for the year 2004.