# The Spatiotemporal Variability of Temperature and Precipitation Over the Upper Indus Basin:
## 1 Introduction  
The Himalaya-Karakoram-Hindukush (HKHK) region has significant strategic importance due to large amounts of snow and glacial ice [1]. Often referred to as Earth's \"third pole\" [2] (to indicate its massive ice and snow storage comparable to the North and South poles), it provides freshwater supply for agriculture, energy production, and drinking purposes for 1.5 billion people living in its catchments [3]. The HKHK region is also hydrologically important due to the presence of major rivers such as the Indus, Ganges, and Brahmaputra. The Indus Basin Irrigation System (IBIS) is one of the largest irrigation systems in the world, which supports not only over 90% of Pakistan's agricultural production [3], but also the majority of the water needs for Pakistan [4]. Over the catchment area up to the Tarbella Reservoir (known as UIB), the contribution from snow and glacier melt runoffs accounts for about 70-80%, and the Karakoram Mountains alone contribute to more than 50% of runoff [3]. Despite the hydrological importance, thereis no consensus on the assessment of the stability of the glaciers in the region. Previous studies have shown conflicting results for glaciers located in the Karakoram ranges, concluding that they are stable, retreating, or even advancing (the so-called Karakoram Anomaly [5; 6]). The Indus River Basin (IRB) has experienced increasing temperatures and features immense spatial variability in climate [7]. Because the Indus River is largely dependent on cryosphere melt, it is highly vulnerable to climate change [8]. The Global Climate Risk Index (CRI) 2018 [9] has ranked Pakistan in the top ten countries most affected by climate change. Global climate models (GCMs) are the basic tools to simulate and project climate change, but their low spatial resolution makes them unable to resolve mesoscale flow patterns [10]. Several studies have downscaled GCM simulations over the IRB (for example, [11; 12; 13]); they found that temperature will continue to increase, but precipitation will be highly uncertain over this region. In addition, GCMs do not have the capability to resolve the orographic precipitation in complex mountainous regions such as UIB. This uncertainty in projected changes in climatic variables, especially precipitation, causes substantial uncertainty in runoff estimations. In addition, the UIB is a data-scarce region where very few rain gauges are installed. These gauges are unevenly distributed and primarily at low-elevation valley locations, raising concerns about their representativeness of higher elevation orographic effects [14]. The lack of sufficient meteorological observations is usually the most challenging for flood forecasting and water resources management over this region. Complex topography, coupled with the challenges of field study in this region, has led to considerable uncertainty in assessing glacial mass balance and even meteorological trends. Moreover, the available global reanalysis datasets are useful to assess the large scale flow patterns over this region, but their coarse resolution cannot effectively characterize the complex orography and other local dynamics [14; 15]. Regional climate models such as the Advanced Research Weather Research & Forecasting model (ARW-WRF; hereafter WRF) can be applied to simulate climatic parameters in complex terrain at high resolution. High-resolution atmospheric modeling can fill the gap of observational data scarcity to advance the understanding of atmospheric variability. The WRF model has successfully been applied worldwide [16; 17; 18; 19; 20] and to the Tibetan Plateau [21; 22; 23; 24; 25]. [PERSON] et al. [25] applied the WRF model to perform 32 years (1979-2011) of simulations over the Tibetan Plateau at 30 km grid cell resolution, but this resolution is still somewhat coarse for capturing orographic precipitation patterns [23]. [PERSON] et al.