Jaakko Ikonen

Effects of Meteorological and Ancillary Data, Temporal Averaging, and Evaluation Methods on Model Performance and Uncertainty in a Land Surface Model

AbstractA single-model 16-member ensemble is used to investigate how external model factors can affect model performance. Ensemble members are constructed with the land surface model (LSM) Joint UK Land Environment Simulator (JULES), with different choices of meteorological forcing [in situ, NCEP Climate Forecast System Reanalysis (CFSR)/CFSv2, or Water and Global Change (WATCH) Forcing Data ERA-Interim (WFDEI)] and ancillary datasets (in situ or remotely sensed), and with four time step modes. Effects of temporal averaging are investigated by comparing the hourly, daily, monthly, and seasonal ensemble performance against snow depth and water equivalent, soil temperature and moisture, and latent and sensible heat fluxes from one forest site and one clearing in the boreal ecozone of Finnish Lapland. Results show that meteorological data are the largest source of uncertainty; differences in ancillary data have little effect on model results. Although generally informative and representative, aggregated perf...

New Snow Water Equivalent Processing System With Improved Resolution Over Europe and its Applications in Hydrology

The presence and amount of snow, given in terms of snow water equivalent (SWE), is an essential physical characteristic influencing climate and hydrological processes. For the recent decades, remote sensing has proven to be a valuable tool for deriving regional and global scale information on SWE. However, determining SWE reliably from remote sensing data for many local-scale applications remains a challenge. Microwave radiometers are currently the best option to determine SWE since they respond to snow depth and density. Further, weather phenomena and solar illumination are not of concern. However, for some purposes the typical spatial resolution of space-borne radiometers (in the order of tens of kilometers) is not sufficient. In this study, the spatial resolution of existing operational SWE products (GlobSnow and H-SAF product portfolios) is improved by performing assimilation of ground truth observations of snow depth and space borne derived SWE estimates in a resolution grid of 0.05° × 0.05° (approximately 5 km × 5 km). Some modifications to the SWE algorithm and the applied auxiliary data (such as an improved forest stem volume map) are introduced. We will present how the improved resolution enhances spatial details in the retrieved SWE, while the validation results show that in terms of accuracy, the new product is on similar level than the existing operational products. Finally, the gained new SWE estimates are ingested into the HOPS hydrological model in the Ounasjoki river basin. The results indicate that simulation of snow melt driven river discharge can be improved by ingesting the retrieved SWE data into a hydrological model.

Long term changes in Northern hemisphere snow cover from SWE timeseries constrained with SE data

Reliable information on snow cover across the Northern Hemisphere and Arctic and sub-Arctic regions is needed for climate monitoring, for understanding the Arctic climate system, and for the evaluation of the role of snow cover and its feedback in climate models. In addition to being of significant interest for climatological investigations, reliable information on snow cover is of high value for the purpose of hydrological forecasting and numerical weather prediction. Terrestrial snow covers up to 50 million km2 of the Northern Hemisphere in winter and is characterized by high spatial and temporal variability. Making satellite observations the only means for providing timely and complete observations of the global snow cover.

Assessing global satellite-based snow water equivalent datasets in ESA SnowPEx project

There is a significant difference in SWE retrieval performance between the different satellite-based products. The assessment using the Russian and Finnish snow transect data covers an extremely large and varied geographical region and spans a total of ten years (2002-2011). Additionally, the reference data are well suited for assessing coarse resolution data, as they are not point-wise measurements but distributed measurements from the snow transects or snow courses.

Hydrological applications of super resolution SWE processing system over Europe

Reliable global and regional scale SWE maps can be calculated by the assimilation of space borne derived SWE estimates and ground based SD observations. The spatial resolution of these products is ~25 km per pixel which is good enough for climate research but for hydrology a higher resolution is often optimal. A regional SWE processing system with nominal resolution of ~ 5 km per pixel over Europe is described in this paper. In addition the validation results show that the sensitivity to SWE is on the same level as with the lower resolution products. SWE data are also assimilated with HOPS hydrological model and the results show an improvement in river discharge estimates.