Rupper

Project Summary

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Objectives: The proposed work aims to quantify the temporal and spatial variability in precipitation over High Mountain Asia (HMA), and impacts of this variability on glacier mass balance over the modern era (1980-present).

Motivation: Precipitation is a critical component of many physical and environmental systems within HMA, including glacier systems that serve as a freshwater resource to populations living within and downstream of these glaciated mountains. Unfortunately, there are large uncertainties in precipitation estimates over much of HMA, which has limited our ability to quantify the spatial and temporal variability in climate across the region, giving rise to significant uncertainty in the causes of glacier change and associated impacts on downstream populations. Here we propose to (1) provide statistical analyses necessary to place glaciological, hydrological, and hazards studies in HMA into context of the precipitation data used, (2) improve precipitation estimates in HMA over the modern era, a period of significant glacier change, and (3) quantify glacier sensitivity to precipitation variability and trends, and assess the role of precipitation in recent glacier change.

Methods: We will employ statistical climate modeling, regional climate modeling, and glacier mass balance modeling approaches to significantly improve our understanding of precipitation and glacier change across HMA. Specifically, we propose to use latent factor analysis and Bayesian hierarchical modelling approach to synthesize all available precipitation observations (weather station, remote sensing, reanalysis) into a new gridded product and objectively quantify the precipitation uncertainties across space and time. This new climate product will be used to define the variability and trends in precipitation across HMA covering the full modern era. Given the resolutions of the available gridded products, the statistical model will provide new gridded data with highest certainty at a relatively coarse (~0.5 degree) resolution. In order to capture important orographic and dynamical influences at higher resolution, we propose to dynamically downscale the gridded climate product using the Weather Research and Forecasting (WRF) model at unprecedented spatial resolutions. We will provide continuous regional climate model simulations from 1980-present with nested domains progressively increasing in resolution down to 1.3 km. The dynamical model outputs will provide a source for deriving the required inputs for glacier modeling, and will enable complementary investigation of the monsoonal, orographic, and westerly disturbance dynamics that account for temporal and spatial variations in precipitation and in glacier mass balance. Finally, we will use two glacier mass balance models to quantify the role of precipitation in glacier mass balance changes in HMA over the modern era, and test the sensitivity of HMA glaciers to precipitation seasonality, magnitudes, variability, and trends.

Value to NASA: The proposed work incorporates NASA products (e.g., MERRA, TRMM) into a compilation of available precipitation data that will be provided directly to the HiMAT team and GMELT Toolbox, along with the model codes and outputs. The data, products, and tools will directly support other studies in the region, including studies of snow, glaciers, permafrost, ecosystems, and hazards. In addition, the focus of the proposed work is directly in line with NASA objectives to better characterize and understand processes controlling precipitation, through optimization of high-resolution meteorological models for HMA spanning 1980-present with the specific goal of understanding the drivers of glacier change.