Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation

Passive microwave (e.g. AMSR-E) and visible spectrum (e.g. MODIS) measurements of snow states have been used in conjunction with land surface models to better characterize snow pack states, most notably snow water equivalent (SWE). However, both types of measurements have limitations. AMSR-E, for ex...

Full description

Bibliographic Details
Main Authors: Forman, Bart, Rodell, Matt, Reichle, Rofl
Format: Other/Unknown Material
Language:unknown
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/2060/20110008474
id ftnasantrs:oai:casi.ntrs.nasa.gov:20110008474
record_format openpolar
spelling ftnasantrs:oai:casi.ntrs.nasa.gov:20110008474 2023-05-15T15:10:45+02:00 Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation Forman, Bart Rodell, Matt Reichle, Rofl Unclassified, Unlimited, Publicly available April 2011 application/pdf http://hdl.handle.net/2060/20110008474 unknown Document ID: 20110008474 http://hdl.handle.net/2060/20110008474 No Copyright CASI Meteorology and Climatology EGU General Assembly 2011; 3-8 Apr. 2011; Vienna; Austria|Geophysical Research Abstracts; Volume 13 2011 ftnasantrs 2019-07-21T01:05:30Z Passive microwave (e.g. AMSR-E) and visible spectrum (e.g. MODIS) measurements of snow states have been used in conjunction with land surface models to better characterize snow pack states, most notably snow water equivalent (SWE). However, both types of measurements have limitations. AMSR-E, for example, suffers a loss of information in deep/wet snow packs. Similarly, MODIS suffers a loss of temporal correlation information beyond the initial accumulation and final ablation phases of the snow season. Gravimetric measurements, on the other hand, do not suffer from these limitations. In this study, gravimetric measurements from the Gravity Recovery and Climate Experiment (GRACE) mission are used in a land surface model data assimilation (DA) framework to better characterize SWE in the Mackenzie River basin located in northern Canada. Comparisons are made against independent, ground-based SWE observations, state-of-the-art modeled SWE estimates, and independent, ground-based river discharge observations. Preliminary results suggest improved SWE estimates, including improved timing of the subsequent ablation and runoff of the snow pack. Additionally, use of the DA procedure can add vertical and horizontal resolution to the coarse-scale GRACE measurements as well as effectively downscale the measurements in time. Such findings offer the potential for better understanding of the hydrologic cycle in snow-dominated basins located in remote regions of the globe where ground-based observation collection if difficult, if not impossible. This information could ultimately lead to improved freshwater resource management in communities dependent on snow melt as well as a reduction in the uncertainty of river discharge into the Arctic Ocean. Other/Unknown Material Arctic Arctic Ocean Mackenzie river NASA Technical Reports Server (NTRS) Arctic Arctic Ocean Mackenzie River Canada
institution Open Polar
collection NASA Technical Reports Server (NTRS)
op_collection_id ftnasantrs
language unknown
topic Meteorology and Climatology
spellingShingle Meteorology and Climatology
Forman, Bart
Rodell, Matt
Reichle, Rofl
Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation
topic_facet Meteorology and Climatology
description Passive microwave (e.g. AMSR-E) and visible spectrum (e.g. MODIS) measurements of snow states have been used in conjunction with land surface models to better characterize snow pack states, most notably snow water equivalent (SWE). However, both types of measurements have limitations. AMSR-E, for example, suffers a loss of information in deep/wet snow packs. Similarly, MODIS suffers a loss of temporal correlation information beyond the initial accumulation and final ablation phases of the snow season. Gravimetric measurements, on the other hand, do not suffer from these limitations. In this study, gravimetric measurements from the Gravity Recovery and Climate Experiment (GRACE) mission are used in a land surface model data assimilation (DA) framework to better characterize SWE in the Mackenzie River basin located in northern Canada. Comparisons are made against independent, ground-based SWE observations, state-of-the-art modeled SWE estimates, and independent, ground-based river discharge observations. Preliminary results suggest improved SWE estimates, including improved timing of the subsequent ablation and runoff of the snow pack. Additionally, use of the DA procedure can add vertical and horizontal resolution to the coarse-scale GRACE measurements as well as effectively downscale the measurements in time. Such findings offer the potential for better understanding of the hydrologic cycle in snow-dominated basins located in remote regions of the globe where ground-based observation collection if difficult, if not impossible. This information could ultimately lead to improved freshwater resource management in communities dependent on snow melt as well as a reduction in the uncertainty of river discharge into the Arctic Ocean.
format Other/Unknown Material
author Forman, Bart
Rodell, Matt
Reichle, Rofl
author_facet Forman, Bart
Rodell, Matt
Reichle, Rofl
author_sort Forman, Bart
title Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation
title_short Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation
title_full Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation
title_fullStr Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation
title_full_unstemmed Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation
title_sort towards improved snow water equivalent estimation via grace assimilation
publishDate 2011
url http://hdl.handle.net/2060/20110008474
op_coverage Unclassified, Unlimited, Publicly available
geographic Arctic
Arctic Ocean
Mackenzie River
Canada
geographic_facet Arctic
Arctic Ocean
Mackenzie River
Canada
genre Arctic
Arctic Ocean
Mackenzie river
genre_facet Arctic
Arctic Ocean
Mackenzie river
op_source CASI
op_relation Document ID: 20110008474
http://hdl.handle.net/2060/20110008474
op_rights No Copyright
_version_ 1766341708939788288