Land Surface Data Assimilation of Satellite Derived Surface Soil Moisture : Towards an Integrated Representation of the Arctic Hydrological Cycle
The ability to accurately determine soil water content (soil moisture) over large areas of the Earth’s surface has potential implications in meteorology, hydrology, water and natural hazards management. The advent of space-based microwave sensors, found to be sensitive to surface soil moisture, has...
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Format: | Doctoral or Postdoctoral Thesis |
Language: | English |
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The University of Bergen
2019
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Online Access: | https://hdl.handle.net/1956/20940 |
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ftunivbergen:oai:bora.uib.no:1956/20940 2023-05-15T15:15:58+02:00 Land Surface Data Assimilation of Satellite Derived Surface Soil Moisture : Towards an Integrated Representation of the Arctic Hydrological Cycle Blyverket, Jostein orcid:0000-0003-1777-1971 2019-10-03T11:59:50.645Z application/pdf https://hdl.handle.net/1956/20940 eng eng The University of Bergen Paper I: Blyverket, J.; Hamer, P.D.; Bertino, L.; Albergel, C.; Fairbairn, D.; Lahoz, W.A. An Evaluation of the EnKF vs. EnOI and the Assimilation of SMAP, SMOS and ESA CCI Soil Moisture Data over the Contiguous US. Remote Sensing 2019, 11. doi:10.3390/rs11050478. The article is available in the main thesis. The article is also available at: http://hdl.handle.net/1956/20718 . Paper II: Blyverket, J.; Hamer, P.D.; Schneider, P.; Albergel, C.; Lahoz, W.A. Monitoring Soil Moisture Drought over Northern High Latitudes from Space. Remote Sensing 2019, 11(10). doi.org/10.3390/rs11101200. The article is available in the main thesis. The article is also available at: http://hdl.handle.net/1956/20696 . Paper III: Blyverket, J.; Hamer, P.D.; De Lannoy, G. Quantifying Higher Order Vegetation Scattering Effects in Passive Microwave Observations from SMAP over Northern Latitudes. The article is not available in BORA. container/78/5d/c4/03/785dc403-b6e9-484e-a138-6b99e037eb29 https://hdl.handle.net/1956/20940 cristin:1736949 In copyright http://rightsstatements.org/page/InC/1.0/ Copyright the Author. All rights reserved Doctoral thesis 2019 ftunivbergen https://doi.org/10.3390/rs1105047810.3390/rs11101200 2023-03-14T17:41:56Z The ability to accurately determine soil water content (soil moisture) over large areas of the Earth’s surface has potential implications in meteorology, hydrology, water and natural hazards management. The advent of space-based microwave sensors, found to be sensitive to surface soil moisture, has allowed for long-term studies of soil moisture dynamics at the global scale. There are, however, areas where remote sensing of soil moisture is prone to errors because, e.g., complex topography, surface water, dense vegetation, frozen soil or snow cover affect the retrieval. This is particularly the case for the northern high latitudes, which is a region subject to more rapid warming than the global mean and also is identified as an important region for studying 21st century climate change. Land surface models can help to close these observation gaps and provide high spatiotemporal coverage of the variables of interest. Models are only approximations of the real world and they can experience errors in, for example, their initialization and/or parameterization. In the past 20 years the research field of land surface data assimilation has undergone rapid developments, and it has provided a potential solution to the aforementioned problems. Land surface data assimilation offers a compromise between model and observations, and by minimization of their total errors it creates an analysis state which is superior to the model and observation alone. This thesis focuses on the implementation of a land surface data assimilation system, its applications and how to improve the separate elements that goes into such a framework. My ultimate goal is to improve the representation of soil moisture over northern high latitudes using land surface data assimilation. In my three papers, I first show how soil moisture data assimilation can correct random errors in the precipitation fields used to drive the land surface model. A result which indicates that a land surface model, driven by uncorrected precipitation, can have the same skill as ... Doctoral or Postdoctoral Thesis Arctic Climate change University of Bergen: Bergen Open Research Archive (BORA-UiB) Arctic Remote Sensing 11 5 478 |
institution |
Open Polar |
collection |
University of Bergen: Bergen Open Research Archive (BORA-UiB) |
op_collection_id |
ftunivbergen |
language |
English |
description |
The ability to accurately determine soil water content (soil moisture) over large areas of the Earth’s surface has potential implications in meteorology, hydrology, water and natural hazards management. The advent of space-based microwave sensors, found to be sensitive to surface soil moisture, has allowed for long-term studies of soil moisture dynamics at the global scale. There are, however, areas where remote sensing of soil moisture is prone to errors because, e.g., complex topography, surface water, dense vegetation, frozen soil or snow cover affect the retrieval. This is particularly the case for the northern high latitudes, which is a region subject to more rapid warming than the global mean and also is identified as an important region for studying 21st century climate change. Land surface models can help to close these observation gaps and provide high spatiotemporal coverage of the variables of interest. Models are only approximations of the real world and they can experience errors in, for example, their initialization and/or parameterization. In the past 20 years the research field of land surface data assimilation has undergone rapid developments, and it has provided a potential solution to the aforementioned problems. Land surface data assimilation offers a compromise between model and observations, and by minimization of their total errors it creates an analysis state which is superior to the model and observation alone. This thesis focuses on the implementation of a land surface data assimilation system, its applications and how to improve the separate elements that goes into such a framework. My ultimate goal is to improve the representation of soil moisture over northern high latitudes using land surface data assimilation. In my three papers, I first show how soil moisture data assimilation can correct random errors in the precipitation fields used to drive the land surface model. A result which indicates that a land surface model, driven by uncorrected precipitation, can have the same skill as ... |
author2 |
orcid:0000-0003-1777-1971 |
format |
Doctoral or Postdoctoral Thesis |
author |
Blyverket, Jostein |
spellingShingle |
Blyverket, Jostein Land Surface Data Assimilation of Satellite Derived Surface Soil Moisture : Towards an Integrated Representation of the Arctic Hydrological Cycle |
author_facet |
Blyverket, Jostein |
author_sort |
Blyverket, Jostein |
title |
Land Surface Data Assimilation of Satellite Derived Surface Soil Moisture : Towards an Integrated Representation of the Arctic Hydrological Cycle |
title_short |
Land Surface Data Assimilation of Satellite Derived Surface Soil Moisture : Towards an Integrated Representation of the Arctic Hydrological Cycle |
title_full |
Land Surface Data Assimilation of Satellite Derived Surface Soil Moisture : Towards an Integrated Representation of the Arctic Hydrological Cycle |
title_fullStr |
Land Surface Data Assimilation of Satellite Derived Surface Soil Moisture : Towards an Integrated Representation of the Arctic Hydrological Cycle |
title_full_unstemmed |
Land Surface Data Assimilation of Satellite Derived Surface Soil Moisture : Towards an Integrated Representation of the Arctic Hydrological Cycle |
title_sort |
land surface data assimilation of satellite derived surface soil moisture : towards an integrated representation of the arctic hydrological cycle |
publisher |
The University of Bergen |
publishDate |
2019 |
url |
https://hdl.handle.net/1956/20940 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change |
genre_facet |
Arctic Climate change |
op_relation |
Paper I: Blyverket, J.; Hamer, P.D.; Bertino, L.; Albergel, C.; Fairbairn, D.; Lahoz, W.A. An Evaluation of the EnKF vs. EnOI and the Assimilation of SMAP, SMOS and ESA CCI Soil Moisture Data over the Contiguous US. Remote Sensing 2019, 11. doi:10.3390/rs11050478. The article is available in the main thesis. The article is also available at: http://hdl.handle.net/1956/20718 . Paper II: Blyverket, J.; Hamer, P.D.; Schneider, P.; Albergel, C.; Lahoz, W.A. Monitoring Soil Moisture Drought over Northern High Latitudes from Space. Remote Sensing 2019, 11(10). doi.org/10.3390/rs11101200. The article is available in the main thesis. The article is also available at: http://hdl.handle.net/1956/20696 . Paper III: Blyverket, J.; Hamer, P.D.; De Lannoy, G. Quantifying Higher Order Vegetation Scattering Effects in Passive Microwave Observations from SMAP over Northern Latitudes. The article is not available in BORA. container/78/5d/c4/03/785dc403-b6e9-484e-a138-6b99e037eb29 https://hdl.handle.net/1956/20940 cristin:1736949 |
op_rights |
In copyright http://rightsstatements.org/page/InC/1.0/ Copyright the Author. All rights reserved |
op_doi |
https://doi.org/10.3390/rs1105047810.3390/rs11101200 |
container_title |
Remote Sensing |
container_volume |
11 |
container_issue |
5 |
container_start_page |
478 |
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1766346292821229568 |