Waves to Weather: Exploring the Limits of Predictability of Weather

Craig, George C.; Fink, Andreas H.; Hoose, Corinna; Janjić, Tijana; Knippertz, Peter; Laurian, Audine; Lerch, Sebastian; Mayer, Bernhard; Miltenberger, Annette K.; Redl, Robert; Riemer, Michael; Tempest, Kirsten; Wirth, Volkmar

doi:10.1175/bams-d-20-0035.1

Cited by 12 publications

(9 citation statements)

References 70 publications

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“…The research leading to these results has been performed within subprojects A2 and B6 of the Transregional Collaborative Research Center SFB/TRR 165 "Waves to Weather" (Craig et al, 2021), funded by the German Science Foundation (DFG). Further, Tijana Janji ć thanks the DFG for her Heisenberg Program Award (JA 1077/4-1), Mainz Institut of Multiscale Modelling: M3odel, and Gutenberg Research College: JGUMainz.…”

Section: Acknowledgementsmentioning

confidence: 99%

Comparison of uncertainty quantification methods for cloud simulation

Janjić

Lukáčová-Medviďová

Ruckstuhl³

et al. 2023

Quart J Royal Meteoro Soc

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Quantification of evolving uncertainties is required for both probabilistic forecasting and data assimilation in weather prediction. In current practice, the ensemble of model simulations is often used as a primary tool to describe the required uncertainties. In this work, we explore an alternative approach, the so‐called stochastic Galerkin (SG) method which integrates uncertainties forward in time using a spectral approximation in the stochastic space.In an idealized two‐dimensional model that couples non‐hydrostatic weakly compressible Navier‐Stokes equations to cloud variables, we first investigate the propagation of initial uncertainty. Propagation of initial perturbations is followed through time for all model variables during two types of forecasts: the ensemble forecast and the SG forecast. Series of experiments indicate that differences in performance of the two methods depend on the system state and truncations used. For example, in more stable conditions, the SG method outperforms the ensemble of simulations for every truncation and every variable. However, in unstable conditions, the ensemble of simulations would need more than 100 members (depending on the model variable) and the SG method more than a truncation at five, to produce comparable but not identical results. As estimates of the uncertainty are crucial for data assimilation, secondly we instigate the use of these two methods with the stochastic ensemble Kalman filter. The use of the SG avoids evolution of the large ensemble that is usually the most expensive component of the data assimilation system and provides comparable results to the ensemble Kalman filter in the cases investigated.This article is protected by copyright. All rights reserved.

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Section: Acknowledgementsmentioning

confidence: 99%

Comparison of uncertainty quantification methods for cloud simulation

Janjić

Lukáčová-Medviďová

Ruckstuhl³

et al. 2023

Quart J Royal Meteoro Soc

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“…During CIRRUS-HL, twice-daily operational forecasts from ECMWF's Integrated Forecasting System (IFS) were transferred to a remote visualization server within computing infrastructure established by the German "Waves to Weather" research program (Craig et al 2021). The forecasts were obtained at 3-h temporal resolution on a 0.15° grid in both longitude and latitude up to a lead time of 144 h, accounting for the planning horizon of 3-4 days in advance of each flight.…”

Section: Visual Analysis Setupmentioning

confidence: 99%

Interactive 3D Visual Analysis of Weather Prediction Data Reveals Midlatitude Overshooting Convection during the CIRRUS-HL Field Experiment

Schäfler

Rautenhaus

2023

Bulletin of the American Meteorological Society

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In summer 2021, microphysical properties and climate impact of high- and midlatitude ice clouds over Europe and the North Atlantic were studied during the Cirrus High Latitude (CIRRUS-HL) airborne field campaign. The related forecasting and flight planning tasks provided a testbed for interactive 3D visual analysis. Operational analyses and forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) were visualized with the open-source software “Met.3D”. A combination of traditional 2D displays with innovative 3D views in the interactive visualization framework facilitated rapid and comprehensive exploration of the NWP data. By this means the benefit of interactive 3D visual forecast products in the routine flight planning procedure was evaluated. Here, we describe the use of 3D tropopause and cloud visualizations during a convective event over the Alps, which became one of the CIRRUS-HL observation targets. For the planning of the research flight on 8 July 2021 our analysis revealed that simulated strong convective updrafts locally disturb the tropopause and inject ice water across the dynamical tropopause into the lower stratosphere. The presented example provides a novel 3D perspective of convective overshooting in a global NWP model and its impact on the tropopause and lower stratosphere. The case study shall encourage the atmospheric science community to further evaluate the use of modern 3D visualization capabilities for NWP analysis.

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“…Importantly, all these different processes at different scales can influence each other. As a consequence, small‐scale disturbances can grow to large scales, presumably limiting our ability to predict the weather (Lorenz, 1969b; Craig et al ., 2021). Our current lack of understanding of multiscale interactions and their physical mechanisms further limits our understanding of error growth and predictability (Zhang et al ., 2007; Durran and Gingrich, 2014; Bierdel et al ., 2017; Selz et al ., 2022), providing the underlying motivation for the present investigation.…”

Section: Introductionmentioning

confidence: 99%

“…Importantly, all these different processes at different scales can influence each other. As a consequence, small-scale disturbances can grow to large scales, presumably limiting our ability to predict the weather (Lorenz, 1969b;Craig et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Scale interactions between the meso‐ and synoptic scales and the impact of diabatic heating

Hirt

Craig

Klein

2023

Quart J Royal Meteoro Soc

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For both the meso‐ and synoptic scales, reduced mathematical models give insight into their dynamical behaviour. For the mesoscale, the weak temperature gradient approximation is one of several approaches, while for the synoptic scale the quasigeostrophic theory is well established. However, the way these two scales interact with each other is usually not included in such reduced models, thereby limiting our current perception of flow‐dependent predictability and upscale error growth. Here, we address the scale interactions explicitly by developing a two‐scale asymptotic model for the meso‐ and synoptic scales with two coupled sets of equations for the meso‐ and synoptic scales respectively. The mesoscale equations follow a weak temperature gradient balance and the synoptic‐scale equations align with quasigeostrophic theory. Importantly, the equation sets are coupled via scale‐interaction terms: eddy correlations of mesoscale variables impact the synoptic potential vorticity tendency and synoptic variables force the mesoscale vorticity (for instance due to tilting of synoptic‐scale wind shear). Furthermore, different diabatic heating rates—representing the effect of precipitation—define different flow characteristics. With weak mesoscale heating relatable to precipitation rates of 𝒪(6mm·h−1), the mesoscale dynamics resembles two‐dimensional incompressible vorticity dynamics and the upscale impact of the mesoscale on the synoptic scale is only of a dynamical nature. With a strong mesosocale heating relatable to precipitation rates of 𝒪(60mm·h−1), divergent motions and three‐dimensional effects become relevant for the mesoscale dynamics and the upscale impact also includes thermodynamical effects.

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Waves to Weather: Exploring the Limits of Predictability of Weather

Cited by 12 publications

References 70 publications

Comparison of uncertainty quantification methods for cloud simulation

Comparison of uncertainty quantification methods for cloud simulation

Interactive 3D Visual Analysis of Weather Prediction Data Reveals Midlatitude Overshooting Convection during the CIRRUS-HL Field Experiment

Scale interactions between the meso‐ and synoptic scales and the impact of diabatic heating

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