Verification of land-atmosphere coupling in forecast models, reanalyses and land surface models using flux site observations

We confront four model systems in three configurations (LSM, LSM+GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly under-represent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land-atmosphere coupling), and may over-represent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally under-represent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Our analysis illuminates targets for coupled land-atmosphere model development, as well as the value of long-term globally-distributed observational monitoring.

Flux measurements by the NRC Twin Otter atmospheric research aircraft: 1987–2011

Abstract. Over the past 30 years, the Canadian Twin Otter research group has operated an aircraft platform for the study of atmospheric greenhouse gas fluxes (carbon dioxide, ozone, nitrous oxide and methane) and energy exchange (latent and sensible heat) over a wide range of terrestrial ecosystems in North America. Some of the acquired data from these projects have now been archived at the Flight Research Laboratory and Agriculture and Agri-Food Canada. The dataset, which contains the measurements obtained in eight projects from 1987 to 2011 are now publicly available. All these projects were carried out in order to improve our understanding of the biophysical controls acting on land-surface atmosphere fluxes. Some of the projects also attempted to quantify the impacts of agroecosystems on the environment. To provide information on the data available, we briefly describe each project and some of the key findings by referring to previously published relevant work. As new flux analysis techniques are being developed, we are confident that much additional information can be extracted from this unique data set.

An Overview of the Use of the SimSphere Soil Vegetation Atmosphere Transfer (SVAT) Model for the Study of Land-Atmosphere Interactions

Soil Vegetation Atmosphere Transfer (SVAT) models consist of deterministic mathematical representations of the physical processes involved between the land surface and the atmosphere and of their interactions, at time-steps acceptable for the study of land surface processes. The present article provides a comprehensive and systematic review of one such SVAT model suitable for use in mesoscale or boundary layer studies, originally developed by [1]. This model, which has evolved significantly both architecturally and functionally since its foundation, has been widely applied in over thirty interdisciplinary science investigations, and it is currently used as a learning resource for students in a number of educational institutes globally. The present review is also regarded as very timely, since a variation of a method using this specific SVAT model along with satellite observations is currently being considered in a scheme being developed for the operational retrieval of soil surface moisture by the US National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellites that are due to be launched from 2016 onwards.

Comparison of Soil Hydraulic Parameterizations for Mesoscale Meteorological Models

Soil water contents, calculated with seven soil hydraulic parameterizations, that is, soil hydraulic functions together with the corresponding parameter sets, are compared with observational data. The parameterizations include the Campbell/Clapp–Hornberger parameterization that is often used by meteorologists and the van Genuchten/Rawls–Brakensiek parameterization that is widespread among hydrologists. The observations include soil water contents at several soil depths and atmospheric surface data; they were obtained within the Regio Klima Projekt (REKLIP) at three sites in the Rhine Valley in southern Germany and cover up to 3 yr with 10-min temporal resolution. Simulations of 48-h episodes, as well as series of daily simulations initialized anew every 24 h and covering several years, were performed with the “VEG3D” soil–vegetation model in stand-alone mode; furthermore, 48-h episodes were simulated with the model coupled to a one-dimensional atmospheric model. For the cases and soil types considered in this paper, the van Genuchten/Rawls–Brakensiek model gives the best agreement between observed and simulated soil water contents on average. Especially during episodes with medium and high soil water content, the van Genuchten/Rawls–Brakensiek model performs better than the Campbell/Clapp–Hornberger model.