# Impacts of Compound Hot-Dry Events on Vegetation Productivity over Northern East Asia
## 3 Results
### Performance of CLM5 in Simulating the Eco-Hydrological Processes
This discrepancy suggests a deficiency in the model's ability to accurately simulate eco-hydroological responses in areas dominated by boreal evergreen needleleaf trees. In addition, the model tends to amplify the decrease in GPP in the eastern part of the Mongolian Plateau, which is primarily covered by C3 grasses. Furthermore, the observed increase in GPP in Case2010 is simulated to have an opposite direction of change. Despite these discrepancies, the model successfully captures the decreases in GPP and ET in the eastern part of the Mongolia Plateau, the increase in ET in the northern part of the area, and the overall decrease in SM. \begin{table}
\begin{tabular}{l l l l l l l l l l l l l} \hline \hline \multirow{2}{*}{**Season**} & \multirow{2}{*}{**Region**} & \multicolumn{2}{c}{**Bias**} & \multicolumn{4}{c}{**RB (\%)**} & \multicolumn{4}{c}{**RMSE**} & \multicolumn{4}{c}{**PCC**} \\ \cline{3-13}  & & **ET** & **SM** & **GPP** & **ET** & **SM** & **GPP** & **ET** & **SM** & **GPP** & **ET** & **SM** & **GPP** \\ \hline \multirow{3}{*}{Annual} & All & \(-0.235\) & \(-0.011\) & \(0.315\) & \(-18.13\) & \(-2.62\) & \(22.25\) & \(0.321\) & \(0.113\) & \(0.783\) & \(0.81\) & \(0.59\) & \(0.68\) \\  & Grasslands & \(-0.152\) & \(-0.033\) & \(-0.007\) & \(-14.95\) & \(-10.46\) & \(1.47\) & \(0.234\) & \(0.073\) & \(0.621\) & \(0.76\) & \(0.59\) & \(0.66\) \\  & Woodlands & \(-0.287\) & \(-0.002\) & \(0.476\) & \(-21.17\) & \(-0.05\) & \(30.70\) & \(0.360\) & \(0.124\) & \(0.812\) & \(0.87\) & \(0.58\) & \(0.75\) \\ \hline \multirow{3}{*}{MAM} & All & \(-0.456\) & \(0.040\) & \(0.126\) & \(-37.96\) & \(12.52\) & \(12.95\) & \(0.520\) & \(0.136\) & \(0.672\) & \(0.80\) & \(0.58\) & \(0.69\) \\  & Grasslands & \(-0.430\) & \(-0.001\) & \(-0.155\) & \(-44.39\) & \(2.42\) & \(-28.96\) & \(0.483\) & \(0.070\) & \(0.436\) & \(0.69\) & \(0.58\) & \(0.52\) \\  & Woodlands & \(-0.485\) & \(0.060\) & \(0.195\) & \(-37.51\) & \(16.52\) & \(20.73\) & \(0.545\) & \(0.154\) & \(0.746\) & \(0.84\) & \(0.52\) & \(0.71\) \\ \hline \multirow{3}{*}{JJA} & All & \(-0.253\) & \(-0.094\) & \(0.268\) & \(-7.85\) & \(-24.58\) & \(12.53\) & \(0.553\) & \(0.141\) & \(2.475\) & \(0.61\) & \(0.47\) & \(0.46\) \\  & Grasslands & \(-0.010\) & \(-0.030\) & \(-0.395\) & \(0.53\) & \(-9.02\) & \(-4.06\) & \(0.388\) & \(0.069\) & \(1.804\) & \(0.72\) & \(0.59\) & \(0.63\) \\  & Woodlands & \(-0.389\) & \(-0.133\) & \(0.748\) & \(-12.74\) & \(-34.62\) & \(21.03\) & \(0.617\) & \(0.169\) & \(2.675\) & \(0.65\) & \(0.54\) & \(0.19\) \\ \hline \multirow{3}{*}{SON} & All & \(-0.128\) & \(-0.026\) & \(0.913\) & \(-14.54\) & \(-6.94\) & \(113.32\) & \(0.212\) & \(0.113\) & \(1.046\) & \(0.89\) & \(0.57\) & \(0.79\) \\  & Grasslands & \(-0.065\) & \(-0.043\) & \(0.597\) & \(-9.91\) & \(-14.42\) & \(87.66\) & \(0.160\) & \(0.076\) & \(0.866\) & \(0.83\) & \(0.61\) & \(0.68\) \\  & Woodlands & \(-0.183\) & \(-0.018\) & \(0.991\) & \(-19.97\) & \(-4.50\) & \(122.98\) & \(0.236\) & \(0.124\) & \(1.045\) & \(0.93\) & \(0.58\) & \(0.87\) \\ \hline \multirow{3}{*}{DJF} & All & \(-0.097\) & \(0.036\) & \(-0.051\) & \(-87.93\) & \(8.16\) & \(-51.64\) & \(0.130\) & \(0.182\) & \(0.085\) & \(0.77\) & \(0.54\) & \(0.32\) \\  & Grasslands & \(-0.100\) & \(-0.056\) & \(-0.069\) & \(-90.33\) & \(-19.49\) & \(-82.66\) & \(0.115\) & \(0.094\) & \(0.089\) & \(0.86\) & \(0.56\) & \(0.17\) \\  & Woodlands & \(-0.086\) & \(0.084\) & \(-0.036\) & \(-88.40\) & \(21.19\) & \(-39.48\) & \(0.124\) & \(0.212\) & \(0.065\) & \(0.76\) & \(0.54\) & \(0.38\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Performance metrics were utilized to evaluate the CLM5 simulations compared with observed evapotranspiration (ET), soil moisture (SM), and gross primary productivity (GPP) annually and seasonally from 2003 to 2019. The evaluation encompassed bias, relative bias (RB), root mean square error (RMSE), and pattern correlation coefficients (PCCs). Bias and RMSE were measured in units of ET (mm/day), SM (m\({}^{3}\)/m\({}^{3}\)), and GPP (gC/m\({}^{2}\)/day), respectively.