Evaluation of Hexagon Imagery for Regional Mass Balance Study in the Bhutan Himalayas

There is much uncertainty regarding the present and future state of Himalayan glaciers, which supply meltwater for river systems vital to more than 1.4 billion people living throughout Asia. Previous assessments of regional glacier mass balance in the Himalayas using various remote sensing and field-based methods give inconsistent results. In this study, declassified Hexagon stereo imagery is processed to generate a digital elevation model (DEM) in the Bhutan Himalayas. Results indicate that the Hexagon imagery database represents a largely untapped resource for understanding decadal scale patterns of mass balance in the region. Future research will utilize the imagery and DEMs to quantify changes in volume and extent of glaciers in the Bhutan Himalayas by comparing the historical imagery to more recent data and calculating changes in ice volume over an approximately 40 year period

Characterizing the Statistical Properties and Global Distribution of Dansgaard-Oeschger Events

Ice core records from Greenland have shown times of rapid warming during the most recent glacial period, called Dansgaard-Oeschger (D-O) events. D-O events are important to our understanding of both past climate systems and modern climate volatility. In this paper, we present new approaches for sta- tistically evaluating the existence of cyclicity in D-O events and the possible lagged correlation between the Greenland and Antarctica temperature records. Speci cally, we consider permutation testing and bootstrapping methodologies for assessing the cyclicity of D-O events and the correlation between the Green- land and Antarctica records. We nd that there is not enough evidence to conclude that D-O events are cyclical; however, the Antarctica record leads the Greenland record by 545 years with a statistically signi cant correlation of 0.455

A New DEM Extraction Method for Hexagon Spy Imagery and Application to Bhutan Glaciers

Declassified Hexagon stereo spy images have near-global coverage extending back to the 1970’s, yet remain a largely untapped resource for land change studies. Unavailable satellite exterior orientation data for these images make digital elevation model (DEM) extraction difficult in terms of time and accuracy. A new automated workflow for DEM extraction is presented that eliminates the need for manual ground control point selection. The method is applied to reconstruct a DEM from 1974 imagery over a large glacierized region in the Bhutan Himalayas. Glacier changes over several decades are visualized using a DEM differencing method. These results demonstrate the value of Hexagon imagery when applied to land change studies

Characteristics of historical precipitation in high mountain asia based on a 15-year high resolution dynamical downscaling

The mountains of High Mountain Asia serve as an important source of water for roughly one billion people living downstream. This research uses 15 years of dynamically downscaled precipitation produced by the Weather Research and Forecasting (WRF) model to delineate contrasts in precipitation characteristics and events between regions dominated by the Indian Summer Monsoon (ISM) versus westerly disturbances during the cool season (December to March). Cluster analysis reveals a more complex spatial pattern than indicated by some previous studies and illustrates the increasing importance of westerly disturbances at higher elevations. Although prior research suggests that a small number of westerly disturbances dominate precipitation in the western Himalaya and Karakoram, the WRF-downscaled precipitation is less dominated by infrequent large events. Integrated vapor transport (IVT) and precipitation are tightly coupled in both regions during the cool season, with precipitation maximizing for IVT from the south-southwest over the Karakoram and southeast-southwest over the western Himalaya. During the ISM, Karakoram precipitation is not strongly related to IVT direction, whereas over the western Himalaya, primary and secondary precipitation maxima occur for flow from the west-southwest and northwest, respectively. These differences in the drivers and timing of precipitation have implications for hydrology, glacier mass balance, snow accumulation, and their sensitivity to climate variability and change

Fusing Climate Data Products using a Spatially Varying Autoencoder

Autoencoders are powerful machine learning models used to compress information from multiple data sources. However, autoencoders, like all artificial neural networks, are often unidentifiable and uninterpretable. This research focuses on creating an identifiable and interpretable autoencoder that can be used to meld and combine climate data products. The proposed autoencoder utilizes a Bayesian statistical framework, allowing for probabilistic interpretations while also varying spatially to capture useful spatial patterns across the various data products. Constraints are placed on the autoencoder as it learns patterns in the data, creating an interpretable consensus that includes the important features from each input. We demonstrate the utility of the autoencoder by combining information from multiple precipitation products in High Mountain Asia.Comment: 13 pages, 7 figure

Mapping Snowmelt Progression in the Upper Indus Basin with Synthetic Aperture Radar

The Indus River is a vital resource for food security, ecosystem services, hydropower, and economy for millions of people living in Pakistan, India, China, and Afghanistan. Glacier and snowmelt from the high altitude Himalaya, Karakoram, and Hindu Kush mountain ranges are the largest drivers of discharge in the upper Indus Basin (UIB), and contribute significantly to Indus flows. Complex climatology and topography, coupled with the challenges of field study and meteorological measurement in these rugged ranges, elicit notable uncertainties in predicting seasonal runoff as well as cryospheric response to changes in climate. Here we utilize Sentinel-1 synthetic aperture radar (SAR) imagery to track ablation season development of wet snow in the Shigar Watershed of the Karakoram Mountains in Pakistan from 2015 to 2018. We exploit opportune local image acquisition times to highlight diurnal differences in radar indications of wet snow, and examine the spatial and temporal contexts of radar diurnal differences for 2015, 2017, and 2018 ablation seasons. Radar classifications for each ablation season show spatial and temporal patterns that indicate a dry winter snowpack undergoing diurnal surface melt-refreeze cycles, transitioning to surface snow that remains wet both day and night, and finally snow free conditions following melt out. Diurnally differing SAR signals may offer insights into important snowpack energy balance processes that precede melt out, which could provide useful constraints for both glacier mass balance modeling and runoff forecasting in remote alpine watersheds

Sensitivity and response of Bhutanese glaciers to atmospheric warming

Glacierized change in the Himalayas affects river-discharge, hydro-energy and agricultural production, and Glacial Lake Outburst Flood potential, but its quantification and extent of impacts remains highly uncertain. Here we present conservative, comprehensive and quantitative predictions for glacier area and meltwater flux changes in Bhutan, monsoonal Himalayas. In particular, we quantify the uncertainties associated with the glacier area and meltwater flux changes due to uncertainty in climate data, a critical problem for much of High Asia. Based on a suite of gridded climate data and a robust glacier melt model, our results show that glacier area and meltwater change projections can vary by an order of magnitude for different climate datasets. However, the most conservative results indicate that, even if climate were to remain at the present-day mean values, almost 10% of Bhutan's glacierized area would vanish and the meltwater flux would drop by as much as 30%. Under the conservative scenario of an additional 1°C regional warming, glacier retreat is going to continue until about 25% of Bhutan's glacierized area will have disappeared and the annual meltwater flux, after an initial spike, would drop by as much as 65%