The LITFASS project of DWD and the LITFASS-98 experiment: The project strategy and the experimental setup

Beyrich, Frank; Herzog, H. Jürgen; Neisser, J.

doi:10.1007/s00704-002-0690-8

Cited by 66 publications

(38 citation statements)

References 26 publications

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“…Model simulations were carried out using the non-hydrostatic model FOOT3DK of the University of Köln with resolutions of 1 km and 250 m. A realistic distribution of surface heterogeneity was used, based on highresolution (50-100 m) datasets of orography and land use during the LITFASS98 experiment (Beyrich et al, 2002a). This area represents a highly heterogeneous landscape around the MOL of the DWD in the northeast of Germany, about 60 km to the southeast of Berlin, and the main land surface types are pine forests, agricultural areas and grass, but a strong heterogeneity is also present due to lakes and urban areas/villages.…”

Section: Discussionmentioning

confidence: 99%

“…The model area is positioned over the LITFASS experimental area (a 20 × 20 km 2 area defined by the coordinates 52°05 30 N, 52°16 30 N, 13°54 00 E, 14°12 00 E; Beyrich et al, 2002a). This area represents a highly heterogeneous landscape around the Meteorological Observatory Lindenberg (MOL) of the DWD in the northeast of Germany, about 60 km to the southeast of Berlin.…”

Section: Design Of the Model Simulations And Their Evaluationmentioning

confidence: 99%

“…These initial profiles represent approximately conditions for 17 June 1998 during the LITFASS98 experiment (Beyrich et al, 2002a). The 1 km model runs are forced by prescribing geostrophic winds of different strengths at the model top (0, 0.5, 2 and 8 m s −1 ); for most simulations a westerly wind is chosen.…”

Section: Design Of the Model Simulations And Their Evaluationmentioning

confidence: 99%

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Comparison of methods for area-averaging surface energy fluxes over heterogeneous land surfaces using high-resolution non-hydrostatic simulations

Heinemann

Kerschgens

2005

Int. J. Climatol.

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The quantification of subgrid land surface heterogeneity effects on the scale of climate and numerical weather prediction models is of vital interest for the energy budget of the atmospheric boundary layer and for the atmospheric branch of the hydrological cycle. This paper focuses on heterogeneity effects for the exchange processes between land surfaces and the atmosphere. The results are based on high-resolution non-hydrostatic model simulations for the LITFASS area near Berlin. This area represents a highly heterogeneous landscape of 20 × 20 km 2 around the Meteorological Observatory Lindenberg of the German Weather Service (DWD). Model simulations were carried out using the non-hydrostatic model FOOT3DK of the University of Köln with resolutions of 1 km and 250 m.The performance of different area-averaging methods for the turbulent surface fluxes was tested for the LITFASS area, namely the aggregation, mosaic and tile methods. For one tile method (station-tile), the experimental setup of the surface energy balance stations of the LITFASS98 experiment was investigated. Two different simulation types are considered: (1) realistic topography and idealized synoptic forcing; (2) realistic topography and realistic synoptic forcing for LITFASS98 cases. A double one-way nesting procedure is used for nesting FOOT3DK in 'Lokalmodell' of the DWD.The mosaic method shows good results, if the wind speed is sufficiently high. During weak-wind convective conditions, errors are particularly large for the latent heat flux on the 20 × 20 km 2 scale. The aggregation method yields generally higher errors than the mosaic method, which even increase for higher wind speeds. The main reason is the strong surface heterogeneity associated with the lakes and forests in the LITFASS area. The main uncertainty of the station-tile method is the knowledge of the area coverage in combination with the representativity of the stations for the land-use type and surface conditions. The results of this study lead to the recommendation to use a mosaic approach or at least a tile approach for downscaling fluxes over heterogeneous surfaces in mesoscale and regional climate models.

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Section: Discussionmentioning

confidence: 99%

Section: Design Of the Model Simulations And Their Evaluationmentioning

confidence: 99%

Section: Design Of the Model Simulations And Their Evaluationmentioning

confidence: 99%

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Comparison of methods for area-averaging surface energy fluxes over heterogeneous land surfaces using high-resolution non-hydrostatic simulations

Heinemann

Kerschgens

2005

Int. J. Climatol.

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“…1). b) The Lindenberg location in Northern Germany Beyrich et al 2002) was chosen as a representative of mid-high latitudes; of the two stations the Falkenberg station was used because it had data for the entire period. c) The Darwin site from the ARM Tropical Western Pacific dataset (http://www.arm .gov/sites/twp.stm) was chosen as a good representative for convectively dominated weather regimes with monsoon seasonality.…”

Section: Choice Of Sitesmentioning

confidence: 99%

Validating Basic Surface Variables in the Australian Bureau of Meteorology Model with CEOP EOP3 In-situ Data

Rikus

2007

Journal of the Meteorological Society of Japan

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The Coordinated Enhanced Observing Period (CEOP) Project has initiated the collection of model output location time series (MOLTS) data from numerical weather prediction and assimilation centers, including the Australian Bureau of Meteorology. These were designed to complement the collection of insitu observational data sets at the same 41 locations. This study is a preliminary attempt to assess the differences and similarities between the MOLTS and time series of the in-situ data. The MOLTS from the Bureau's global model for a number of atmospheric surface variables are compared with in-situ data for 6 locations for the entire year of EOP3 (October 2002 to September 2003. Using surface pressure as a prototype a number of preliminary comparisons of different properties of the two types of data are performed. The model fields from the 6 hour assimilation forecast series and from the concatenated 12 to 36 hour forecasts are first compared with hourly in-situ observations in simple gross terms; simple statistics and scatter plots have been obtained to identify areas for further investigation. Global wavelet power spectra are compared to show the behavior of the dominant modes of variability and the average annual diurnal variations of the variables are derived. Some case studies with other variables with increasing sensitivity to sub-grid scales and increasing dependency on surface properties are then documented. The model and in-situ time series show similar behavior for surface pressure with greater differences for the other variables. Precipitation shows the greatest differences.

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“…Bastiaanssen et al (1997) derive area-aggregated surface fluxes from remote sensing and compare with EFEDA surface observations. More recent examples in this nonexhaustive list include Observations at Several Interacting Scales (OASIS; Leuning et al 2004) and Lindenberg Inhomogeneous Terrain-Fluxes between Atmosphere and Surface: A Long-Term Study (LITFASS; Beyrich et al 2002). These studies have all in common the case study view.…”

Section: Introductionmentioning

confidence: 99%

Area-Averaged Surface Fluxes in a Semiarid Region with Partly Irrigated Land: Lessons Learned from EFEDA

Jochum¹,

Bruin

Holtslag

et al. 2006

Journal of Applied Meteorology and Climatology

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The European Field Experiment in a Desertification-Threatened Area (EFEDA) provides a comprehensive land surface dataset for a semiarid Mediterranean environment with natural vegetation and cultivated dry and irrigated land. This paper discusses the methods and practical aspects of deriving areaaveraged fluxes for a range of areas from the whole EFEDA region to several numerical weather prediction model grid cells (on 10-100-km scales). A time series of grid-scale surface fluxes for the entire observational period of 1 month was obtained from weighted surface averages, using a crop phenology-based land use classification together with a homogenized set of surface observations representative of the four major vegetation classes. The flux-aggregated surface observations were compared with two other approaches to obtain grid-scale fluxes (airborne flux observations and radiosondes in conjunction with a simple mixedlayer model). The area-aggregated fluxes (in particular of latent heat) depend strongly on the location of the area boundaries whenever a significant fraction of irrigated land is present. This result confirms clearly the importance of adequately accounting for tiles of irrigated land in surface schemes and corresponding physiographic databases of large-scale models. A simple way to accommodate for minimum information on the canopy water status is proposed in terms of the distinction of at least two seasonal classes of irrigated crops-one of spring and one of summer growing cycles. The main lesson from this aggregation exercise concerns the role of irrigation. First, this study quantifies the uncertainties in the space-time pattern and its effects on aggregated surface fluxes for the first time on the grounds of observational data. Second, it demonstrates practical ways to accomplish the parameterization of irrigation in flux aggregation schemes, by identifying the key data along with their possible sources and by defining a practical implementation procedure.

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The LITFASS project of DWD and the LITFASS-98 experiment: The project strategy and the experimental setup

Cited by 66 publications

References 26 publications

Comparison of methods for area-averaging surface energy fluxes over heterogeneous land surfaces using high-resolution non-hydrostatic simulations

Comparison of methods for area-averaging surface energy fluxes over heterogeneous land surfaces using high-resolution non-hydrostatic simulations

Validating Basic Surface Variables in the Australian Bureau of Meteorology Model with CEOP EOP3 In-situ Data

Area-Averaged Surface Fluxes in a Semiarid Region with Partly Irrigated Land: Lessons Learned from EFEDA

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