 |
| Titel |
Assimilating GRACE, hydrology and hydrometeorology datasets for estimating monthly water storage changes over continents |
| VerfasserIn |
Balaji Devaraju, Nico Sneeuw, Mohammad Javad Tourian, Johannes Riegger, Benjamin Fersch, Harald Kunstmann |
| Konferenz |
EGU General Assembly 2010
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 12 (2010) |
| Datensatznummer |
250041508
|
|
|
|
|
|
| Zusammenfassung |
| One of the primary aims of GRACE gravity field satellite mission is to measure monthly
water storage changes in catchments at regional/continental scales, which are then
used for closing the monthly water balance at these scales. The presence of high
frequency noise in GRACE data necessitates filtering, which inevitably introduces a
bias in the filtered water storage change estimates. The bias, due to filtering, in the
estimates is a major hurdle in utilising them for closing the water balance. In order to
quantify this bias and to evaluate the GRACE water storage change estimates, reliable
measurements of precipitation, runoff and evapotranspiration are needed. While
precipitation data is available globally, runoff data is available only partially and
evapotranspiration data at regional/continental scales is available only from model
data.
In this contribution, the problems of bias due to filtering of GRACE data and
data-deficiency for evaluation are negotiated. This is done by devising certain conditions from
the available hydrological and hydrometeorological datasets, and using these conditions as
constraints on the parameters of a data assimilation scheme involving GRACE, hydrology and
hydrometeorology datasets. Data assimilation is carried out using constrained least squares
estimation, which then allows to quantify the contribution of the individual datasets towards
the assimilated dataset. The constrained estimation is expected to bring consistency to the
assimilated dataset. |
|
|
|
|
|
|