Assessing High-Latitude Winter Precipitation from Global Precipitation Analyses Using GRACE

Swenson, Sean

doi:10.1175/2009jhm1194.1

Cited by 30 publications

(28 citation statements)

References 25 publications

(39 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar, overestimation of precipitation undercatch correction in GPCP has been reported by Swenson (2010). Taking into account the mismatch in temporal and spatial domains, as well as the experimental definitions, reducing GPCP snowfall in our study by 33 % is roughly consistent with both studies.…”

Section: Model Optimizationsupporting

confidence: 91%

Understanding terrestrial water storage variations in northern latitudes across scales

Trautmann

Koirala

Eicker

et al. 2018

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. The GRACE satellites provide signals of total terrestrial water storage (TWS) variations over large spatial domains at seasonal to inter-annual timescales. While the GRACE data have been extensively and successfully used to assess spatio-temporal changes in TWS, little effort has been made to quantify the relative contributions of snowpacks, soil moisture, and other components to the integrated TWS signal across northern latitudes, which is essential to gain a better insight into the underlying hydrological processes. Therefore, this study aims to assess which storage component dominates the spatio-temporal patterns of TWS variations in the humid regions of northern mid-to high latitudes.To do so, we constrained a rather parsimonious hydrological model with multiple state-of-the-art Earth observation products including GRACE TWS anomalies, estimates of snow water equivalent, evapotranspiration fluxes, and gridded runoff estimates. The optimized model demonstrates good agreement with observed hydrological spatio-temporal patterns and was used to assess the relative contributions of solid (snowpack) versus liquid (soil moisture, retained water) storage components to total TWS variations. In particular, we analysed whether the same storage component dominates TWS variations at seasonal and inter-annual temporal scales, and whether the dominating component is consistent across small to large spatial scales.Consistent with previous studies, we show that snow dynamics control seasonal TWS variations across all spatial scales in the northern mid-to high latitudes. In contrast, we find that inter-annual variations of TWS are dominated by liquid water storages at all spatial scales. The relative contribution of snow to inter-annual TWS variations, though, increases when the spatial domain over which the storages are averaged becomes larger. This is due to a stronger spatial coherence of snow dynamics that are mainly driven by temperature, as opposed to spatially more heterogeneous liquid water anomalies, that cancel out when averaged over a larger spatial domain. The findings first highlight the effectiveness of our model-data fusion approach that jointly interprets multiple Earth observation data streams with a simple model. Secondly, they reveal that the determinants of TWS variations in snow-affected northern latitudes are scale-dependent. In particular, they seem to be not merely driven by snow variability, but rather are determined by liquid water storages on interannual timescales. We conclude that inferred driving mechanisms of TWS cannot simply be transferred from one scale to another, which is of particular relevance for understanding the short-and long-term variability of water resources.

show abstract

Section: Model Optimizationsupporting

confidence: 91%

Understanding terrestrial water storage variations in northern latitudes across scales

Trautmann

Koirala

Eicker

et al. 2018

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…This reduction agrees with Behrangi et al (2016), who found GPCP to overestimate snowfall over Eurasian high latitudes. Similar, overestimation of precipitation undercatch correction in GPCP has also been reported by Swenson (2010). Therefore, psf allows to reduce inconsistencies between the precipitation forcing and the water storages as given by GlobSnow SWE and GRACE TWS.…”

Section: Model Optimizationsupporting

confidence: 72%

Understanding terrestrial water storage variations in northern latitudes across scales

Trautmann¹,

Koirala²,

Eicker³

et al. 2017

Preprint

View full text Add to dashboard Cite

Abstract. The GRACE satellites provide signals of total terrestrial water storage (TWS) variations over large spatial domains at seasonal to inter-annual time scales. While the GRACE data have been extensively and successfully used to assess spatio-temporal changes in TWS, little effort has been made to quantify the relative contributions of snow pack, soil moisture and other components to the integrated TWS signal across northern latitudes, which is essential to gain a better 15 insight into the underlying hydrological processes. Therefore, this study aims to assess which storage component dominates the spatio-temporal patterns of TWS variations in the humid regions of northern mid-to-high latitudes.To do so, we constrained a rather parsimonious hydrological model with multiple state-of-the-art Earth observation products including GRACE TWS anomalies, estimates of snow water equivalent, evapotranspiration fluxes, and gridded runoff estimates. The optimized model demonstrates good agreement with observed hydrological patterns, and was used to assess 20 the relative contributions of solid (snow pack) versus liquid (soil moisture, retained water) storage components to total TWS variations. In particular, we analysed whether the same storage component dominates TWS variations at seasonal and interannual temporal scales, and whether the dominating component is consistent across small to large spatial scales.Consistent with previous studies, we show that snow dynamics control seasonal TWS variations across spatial scales in the northern mid-to-high latitudes. In contrast, we find that inter-annual variations of TWS are dominated by liquid water 25 storages, comprising mainly of soil moisture. However, as the spatial domain over which the storages are averaged becomes larger, the relative contribution of snow to inter-annual TWS variations increases. This is due to a stronger spatial coherence of snow anomalies as opposed to spatially more heterogeneous liquid water anomalies that cancel out over large spatial domains.The findings first highlight the effectiveness of our model-data fusion approach that jointly interprets multiple Earth 30 observation data streams with a simple model. Secondly, they reveal that the determinants of TWS variations in snowaffected northern latitudes are scale dependent. We conclude that inferred driving mechanisms of TWS cannot simply be transferred from one scale to another, which is of particular relevance for understanding the short and long-term variability of water resources.Hydrol. Earth Syst. Sci. Discuss., https://doi

show abstract

“…The changes in bias and RMSE (and anomaly R) between MERRA and MERRA-Land are primarily due to the GPCP-based precipitation corrections and are not related to the snow parameter changes (not shown). The snow depth bias may be higher in MERRA-Land because the precipitation gauge undercatch may have been overcorrected in the GPCP precipitation in northern high latitudes (Swenson 2010). A potential bias in the WMO snow depth observations, however, offers another explanation.…”

Section: Snowmentioning

confidence: 99%

Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

et al. 2011

View full text Add to dashboard Cite

The Modern-Era Retrospective Analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis that provides, in addition to atmospheric fields, global estimates of soil moisture, latent heat flux, snow, and runoff for 1979-present. This study introduces a supplemental and improved set of land surface hydrological fields (''MERRA-Land'') generated by rerunning a revised version of the land component of the MERRA system. Specifically, the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ECMWF Re-Analysis-Interim (ERA-I). MERRA-Land and ERA-I root zone soil moisture skills (against in situ observations at 85 U.S. stations) are comparable and significantly greater than that of MERRA. Throughout the Northern Hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 18 U.S. basins) of MERRA and MERRA-Land is typically higher than that of ERA-I. With a few exceptions, the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using MERRA output for land surface hydrological studies.

show abstract

Assessing High-Latitude Winter Precipitation from Global Precipitation Analyses Using GRACE

Cited by 30 publications

References 25 publications

Understanding terrestrial water storage variations in northern latitudes across scales

Understanding terrestrial water storage variations in northern latitudes across scales

Understanding terrestrial water storage variations in northern latitudes across scales

Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

Contact Info

Product

Resources

About