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The limited atmospheric predictability has been addressed by the development of ensemble prediction systems (EPS) that are now routinely applied for medium-range synoptic-scale numerical weather prediction (NWP). With the increase of computational power, interest is growing in the design of high-resolution (cloud resolving) NWP models and their associated short-range EPS. This development raises a series of fundamental questions, especially concerning the type of error growth and the validity of the tangent-linear approximation. To address these issues, a comparison between perturbed medium-range (10 day) synoptic-scale integrations (taken from the operational ECMWF EPS with a horizontal resolution of about 80 km) and short-range (1 day) high-resolution simulations (based on the Lokal Modell of the Consortium for Small-Scale Modeling with a grid spacing of 2.2 km) is conducted. The differences between the two systems are interpreted in a nondimensional sense and illustrated with the help of the Lorenz attractor.
Typical asymptotic perturbation-doubling times of cloud-resolving and synoptic-scale simulations amount to about 4 and 40 h, respectively, and are primarily related to convective and baroclinic instability. Thus, in terms of growth rates, integrating a 1-day cloud-resolving forecast may be seen as equivalent to performing a 10-day synoptic-scale simulation. However, analysis of the prevailing linearity reveals that the two systems are fundamentally different in the following sense: the tangent-linear approximation breaks down at 1.5 h for cloud resolving against 54 h for synoptic-scale forecasts. In terms of nonlinearity, a 10-day synoptic-scale integration thus corresponds to a very short cloud-resolving simulation of merely about 7 h. The higher degree of nonlinearity raises questions concerning the direct application of standard synoptic-scale forecasting methodologies (e.g., optimal perturbations, 4D variational data assimilation, or targeted observations) to 1-day cloud-resolving forecasting.
The limited atmospheric predictability has been addressed by the development of ensemble prediction systems (EPS) that are now routinely applied for medium-range synoptic-scale numerical weather prediction (NWP). With the increase of computational power, interest is growing in the design of high-resolution (cloud resolving) NWP models and their associated short-range EPS. This development raises a series of fundamental questions, especially concerning the type of error growth and the validity of the tangent-linear approximation. To address these issues, a comparison between perturbed medium-range (10 day) synoptic-scale integrations (taken from the operational ECMWF EPS with a horizontal resolution of about 80 km) and short-range (1 day) high-resolution simulations (based on the Lokal Modell of the Consortium for Small-Scale Modeling with a grid spacing of 2.2 km) is conducted. The differences between the two systems are interpreted in a nondimensional sense and illustrated with the help of the Lorenz attractor.
Typical asymptotic perturbation-doubling times of cloud-resolving and synoptic-scale simulations amount to about 4 and 40 h, respectively, and are primarily related to convective and baroclinic instability. Thus, in terms of growth rates, integrating a 1-day cloud-resolving forecast may be seen as equivalent to performing a 10-day synoptic-scale simulation. However, analysis of the prevailing linearity reveals that the two systems are fundamentally different in the following sense: the tangent-linear approximation breaks down at 1.5 h for cloud resolving against 54 h for synoptic-scale forecasts. In terms of nonlinearity, a 10-day synoptic-scale integration thus corresponds to a very short cloud-resolving simulation of merely about 7 h. The higher degree of nonlinearity raises questions concerning the direct application of standard synoptic-scale forecasting methodologies (e.g., optimal perturbations, 4D variational data assimilation, or targeted observations) to 1-day cloud-resolving forecasting.
Abstract
In 2011, the German Federal Ministry of Transport, Building and Urban Development laid the foundation of the Hans-Ertel Centre for Weather Research [Hans-Ertel-Zentrum für Wetterforschung (HErZ)] in order to better connect fundamental meteorological research and teaching at German universities and atmospheric research centers with the needs of the German national weather service Deutscher Wetterdienst (DWD). The concept for HErZ was developed by DWD and its scientific advisory board with input from the entire German meteorological community. It foresees core research funding of about €2,000,000 yr−1 over a 12-yr period, during which time permanent research groups must be established and DWD subjects strengthened in the university curriculum. Five priority research areas were identified: atmospheric dynamics and predictability, data assimilation, model development, climate monitoring and diagnostics, and the optimal use of information from weather forecasting and climate monitoring for the benefit of society. Following an open call, five groups were selected for funding for the first 4-yr phase by an international review panel. A dual project leadership with one leader employed by the academic institute and the other by DWD ensures that research and teaching in HErZ is attuned to DWD needs and priorities, fosters a close collaboration with DWD, and facilitates the transfer of fundamental research into operations. In this article, we describe the rationale behind HErZ and the road to its establishment, present some scientific highlights from the initial five research groups, and discuss the merits and future development of this new concept to better link academic research with the needs and challenges of a national weather service.
Abstract
In 2011, the German Federal Ministry of Transport, Building and Urban Development laid the foundation of the Hans-Ertel Centre for Weather Research [Hans-Ertel-Zentrum für Wetterforschung (HErZ)] in order to better connect fundamental meteorological research and teaching at German universities and atmospheric research centers with the needs of the German national weather service Deutscher Wetterdienst (DWD). The concept for HErZ was developed by DWD and its scientific advisory board with input from the entire German meteorological community. It foresees core research funding of about €2,000,000 yr−1 over a 12-yr period, during which time permanent research groups must be established and DWD subjects strengthened in the university curriculum. Five priority research areas were identified: atmospheric dynamics and predictability, data assimilation, model development, climate monitoring and diagnostics, and the optimal use of information from weather forecasting and climate monitoring for the benefit of society. Following an open call, five groups were selected for funding for the first 4-yr phase by an international review panel. A dual project leadership with one leader employed by the academic institute and the other by DWD ensures that research and teaching in HErZ is attuned to DWD needs and priorities, fosters a close collaboration with DWD, and facilitates the transfer of fundamental research into operations. In this article, we describe the rationale behind HErZ and the road to its establishment, present some scientific highlights from the initial five research groups, and discuss the merits and future development of this new concept to better link academic research with the needs and challenges of a national weather service.
Abstract
Numerical weather prediction models operate on grid spacings of a few kilometers, where deep convection begins to become resolvable. Around this scale, the emergence of coherent structures in the planetary boundary layer, often hypothesized to be caused by cold pools, forces the transition from shallow to deep convection. Yet, the kilometer-scale range is typically not resolved by standard surface operational measurement networks. The measurement campaign Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL) aimed at addressing this gap by observing atmospheric variability at the hectometer-to-kilometer scale, with a particular emphasis on cold pools, wind gusts, and coherent patterns in the planetary boundary layer during summer. A unique feature was the distribution of 150 self-developed and low-cost instruments. More specifically, FESSTVaL included dense networks of 80 autonomous cold pool loggers, 19 weather stations, and 83 soil sensor systems, all installed in a rural region of 15-km radius in eastern Germany, as well as self-developed weather stations handed out to citizens. Boundary layer and upper-air observations were provided by eight Doppler lidars and four microwave radiometers distributed at three supersites; water vapor and temperature were also measured by advanced lidar systems and an infrared spectrometer; and rain was observed by a X-band radar. An uncrewed aircraft, multicopters, and a small radiometer network carried out additional measurements during a 4-week period. In this paper, we present FESSTVaL’s measurement strategy and show first observational results including unprecedented highly resolved spatiotemporal cold-pool structures, both in the horizontal as well as in the vertical dimension, associated with overpassing convective systems.
Abstract
Numerical weather prediction models operate on grid spacings of a few kilometers, where deep convection begins to become resolvable. Around this scale, the emergence of coherent structures in the planetary boundary layer, often hypothesized to be caused by cold pools, forces the transition from shallow to deep convection. Yet, the kilometer-scale range is typically not resolved by standard surface operational measurement networks. The measurement campaign Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL) aimed at addressing this gap by observing atmospheric variability at the hectometer-to-kilometer scale, with a particular emphasis on cold pools, wind gusts, and coherent patterns in the planetary boundary layer during summer. A unique feature was the distribution of 150 self-developed and low-cost instruments. More specifically, FESSTVaL included dense networks of 80 autonomous cold pool loggers, 19 weather stations, and 83 soil sensor systems, all installed in a rural region of 15-km radius in eastern Germany, as well as self-developed weather stations handed out to citizens. Boundary layer and upper-air observations were provided by eight Doppler lidars and four microwave radiometers distributed at three supersites; water vapor and temperature were also measured by advanced lidar systems and an infrared spectrometer; and rain was observed by a X-band radar. An uncrewed aircraft, multicopters, and a small radiometer network carried out additional measurements during a 4-week period. In this paper, we present FESSTVaL’s measurement strategy and show first observational results including unprecedented highly resolved spatiotemporal cold-pool structures, both in the horizontal as well as in the vertical dimension, associated with overpassing convective systems.
