Search

The article focuses on the evaluation of different methods for gap filling of long-term actual evapotranspiration time series measured by lysimeters. It explore four different gap filling methods namely potential terrestrial evapotranspiration method, the ratio method, and the FAO-based water balance method, and HYDRUS modeling. It also mentions that gap-filling methods do not perform very differently for dry and wet conditions.

Abstract: The evolution of near‐surface air temperature is influenced by various dynamical, radiative, and surface‐atmosphere exchange processes whose contributions are still not completely quantified. Applying stepwise multiple linear regression to Coupled Model Intercomparison Project phase 5 (CMIP5) model simulations and focusing on radiation (diagnosed by incoming shortwave and incoming longwave radiation) and land surface conditions (diagnosed by soil moisture and albedo) about 79% of the interannual variability and 99% of the multidecadal trend of monthly mean daily maximum temperature over land can be explained. The linear model captures well the temperature variability in middle‐to‐high latitudes and in regions close to the equator, whereas its explanatory potential is limited in deserts. While radiation is an essential explanatory variable over almost all of the analyzed domain, land surface conditions show a pronounced relation to temperature in some confined regions. These findings highlight that considering local‐to‐regional processes is crucial for correctly assessing interannual temperature variability and future temperature trends. [ABSTRACT FROM AUTHOR]

Core Ideas: We saw generally high agreement between lysimeters, despite substantial design differences.Large‐lysimeter processing was optimized in light of highly resolved mini‐lysimeter data.Smoothing filter and setting of ET to zero in wet hours was useful for the large lysimeter.Lysimeter precipitation types were identified using an opto‐electric precipitation monitor.Protrusion of the large lysimeter may cause precipitation under‐catch by flow distortion. Weighing lysimeters are a well‐established means of accurately obtaining local‐scale estimates of actual evapotranspiration (ET), precipitation, and seepage within soils. At the Rietholzbach research catchment in northeastern Switzerland, two weighing lysimeters are in operation. One is a recently installed state‐of‐the‐art monolithic mini‐lysimeter with a tension‐controlled lower boundary; the other is a large backfilled free‐drainage lysimeter in operation since 1976. For this study, the mini‐lysimeter measurements were processed using the Adaptive‐Window and Adaptive‐Threshold (AWAT) filter. The resulting water‐balance estimates were then compared with those of the lower resolution large lysimeter, whose processing has remained unchanged since its installation. A number of additional, retrospectively applicable processing steps for the large lysimeter were then tested to mitigate the main sources of error for this instrument. Those found to be most beneficial were the application of a 10‐min moving average to the mass measurements and the setting of ET and condensation to zero in hours with liquid precipitation. In spite of the differences in design, a generally close agreement between the two lysimeters was observed, which was further improved with the optimized large‐lysimeter processing. A comparison of the lysimeter mass increases associated with liquid precipitation further revealed, however, that the large lysimeter experiences a previously unknown under‐catch of about 11.5%, which could also be important for other lysimeter facilities. This under‐catch led to a reduction in large‐lysimeter seepage during the analyzed period, although the ET flux was not found to be affected. [ABSTRACT FROM AUTHOR]

Terrestrial water storage is an important component of the climate system as it determines the partitioning of the water and energy fluxes at the land surface. Since in situ measurements are scarce, there is a strong need for alternative validation data sources. Here we present a new dataset of monthly basin-scale terrestrial water storage changes (TWSC) derived with the combined atmospheric-terrestrial water-balance approach, also referred to as basin-scale water-balance (BSWB) approach. It is diagnosed from observation-constrained reanalysis data for the atmospheric fields and observed streamflow. A previous BSWB dataset derived from the European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis ERA-40 provided reasonable estimates of TWSC for mid-latitude basins. The here presented BSWB dataset is derived from the latest ECMWF reanalysis ERA-Interim, which is available in real time. The potential real-time availability of TWSC derived from ERA-Interim is of great relevance for several agricultural, hydrological, and climate applications. An uncertainty analysis of the derived TWSC highlights the importance of the atmospheric moisture flux convergence fields from the reanalysis for the resulting product uncertainty. We find that the BSWB estimates have a relative uncertainty of about 4-6% in basins larger than 1·5 × 10 km compared with the mean seasonal cycle. The ERA-Interim based dataset compares better with in situ soil moisture, snow depth, and groundwater measurements in the Ob basin and Illinois than the previous ERA-40 based dataset. We further compare the BSWB datasets to retrievals from the Gravity Recovery And Climate Experiment (GRACE), scatterometer data from the European Remote Sensing (ERS) satellites, and land surface model output from the second phase of the Global Soil Wetness Project (GSWP). We find a better correlation between ERS and the BSWB data than between GRACE and the BSWB data, which might be related to the relatively coarse resolution of GRACE. GSWP model output and the BSWB datasets compare well in most of the studied river basins. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]