Articles | Volume 1, issue 1
https://doi.org/10.5194/wcd-1-207-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-1-207-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Large impact of tiny model domain shifts for the Pentecost 2014 mesoscale convective system over Germany
Christian Barthlott
CORRESPONDING AUTHOR
Institute of Meteorology and Climate Research (IMK-TRO),
Department of Troposphere Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Andrew I. Barrett
Institute of Meteorology and Climate Research (IMK-TRO),
Department of Troposphere Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Related authors
Takumi Matsunobu, Christian Keil, and Christian Barthlott
Weather Clim. Dynam., 3, 1273–1289, https://doi.org/10.5194/wcd-3-1273-2022, https://doi.org/10.5194/wcd-3-1273-2022, 2022
Short summary
Short summary
This study quantifies the impact of poorly constrained parameters used to represent aerosol–cloud–precipitation interactions on precipitation and cloud forecasts associated with uncertainties in input atmospheric states. Uncertainties in these parameters have a non-negligible impact on daily precipitation amount and largely change the amount of cloud. The comparison between different weather situations reveals that the impact becomes more important when convection is triggered by local effects.
Christian Barthlott, Amirmahdi Zarboo, Takumi Matsunobu, and Christian Keil
Atmos. Chem. Phys., 22, 10841–10860, https://doi.org/10.5194/acp-22-10841-2022, https://doi.org/10.5194/acp-22-10841-2022, 2022
Short summary
Short summary
The relevance of microphysical and land-surface uncertainties for convective-scale predictability is evaluated with a combined-perturbation strategy in realistic convection-resolving simulations. We find a large ensemble spread which demonstrates that the uncertainties investigated here and, in particular, their collective effect are highly relevant for quantitative precipitation forecasting of summertime convection in central Europe.
Christian Barthlott, Amirmahdi Zarboo, Takumi Matsunobu, and Christian Keil
Atmos. Chem. Phys., 22, 2153–2172, https://doi.org/10.5194/acp-22-2153-2022, https://doi.org/10.5194/acp-22-2153-2022, 2022
Short summary
Short summary
The relative impact of cloud condensation nuclei (CCN) concentrations and the shape parameter of the cloud droplet size distribution is evaluated in realistic convection-resolving simulations. We find that an increase in the shape parameter can produce almost as large a variation in precipitation as a CCN increase from maritime to polluted conditions. The choice of the shape parameter may be more important than previously thought for determining cloud radiative characteristics.
Linda Schneider, Christian Barthlott, Corinna Hoose, and Andrew I. Barrett
Atmos. Chem. Phys., 19, 12343–12359, https://doi.org/10.5194/acp-19-12343-2019, https://doi.org/10.5194/acp-19-12343-2019, 2019
Short summary
Short summary
This study addresses the relative impact of orography, soil moisture, and aerosols on precipitation over Germany in different weather regimes. We find that the impact of these perturbations is higher for weak than for strong large-scale forcing. Furthermore, aerosols and soil moisture are both of similar importance for precipitation forecasting, which indicates that their inclusion in operational ensemble forecasting should be assessed in the future.
Sylvia C. Sullivan, Christian Barthlott, Jonathan Crosier, Ilya Zhukov, Athanasios Nenes, and Corinna Hoose
Atmos. Chem. Phys., 18, 16461–16480, https://doi.org/10.5194/acp-18-16461-2018, https://doi.org/10.5194/acp-18-16461-2018, 2018
Short summary
Short summary
Ice crystal formation in clouds can occur via thermodynamic nucleation, but also via mechanical collisions between pre-existing crystals or co-existing droplets. When descriptions of this mechanical ice generation are implemented into the COSMO weather model, we find that the contributions to crystal number from thermodynamic and mechanical processes are of the same order. Mechanical ice generation also intensifies differences in precipitation intensity between dynamic and quiescent regions.
Andreas Macke, Patric Seifert, Holger Baars, Christian Barthlott, Christoph Beekmans, Andreas Behrendt, Birger Bohn, Matthias Brueck, Johannes Bühl, Susanne Crewell, Thomas Damian, Hartwig Deneke, Sebastian Düsing, Andreas Foth, Paolo Di Girolamo, Eva Hammann, Rieke Heinze, Anne Hirsikko, John Kalisch, Norbert Kalthoff, Stefan Kinne, Martin Kohler, Ulrich Löhnert, Bomidi Lakshmi Madhavan, Vera Maurer, Shravan Kumar Muppa, Jan Schween, Ilya Serikov, Holger Siebert, Clemens Simmer, Florian Späth, Sandra Steinke, Katja Träumner, Silke Trömel, Birgit Wehner, Andreas Wieser, Volker Wulfmeyer, and Xinxin Xie
Atmos. Chem. Phys., 17, 4887–4914, https://doi.org/10.5194/acp-17-4887-2017, https://doi.org/10.5194/acp-17-4887-2017, 2017
Short summary
Short summary
This article provides an overview of the instrumental setup and the main results obtained during the two HD(CP)2 Observational Prototype Experiments HOPE-Jülich and HOPE-Melpitz conducted in Germany in April–May and Sept 2013, respectively. Goal of the field experiments was to provide high-resolution observational datasets for both, improving the understaning of boundary layer and cloud processes, as well as for the evaluation of the new ICON model that is run at 156 m horizontal resolution.
C. Barthlott and C. Hoose
Atmos. Chem. Phys., 15, 12361–12384, https://doi.org/10.5194/acp-15-12361-2015, https://doi.org/10.5194/acp-15-12361-2015, 2015
Short summary
Short summary
This paper assesses the resolution dependance of clouds and precipitation over Germany by numerical simulations with the COnsortium for Small-scale MOdeling model for 7 cases of 2013. By means of a series of grid-refinement resolution tests, the variability of clouds and precipitation and how this variability changes with model resolution are investigated. The performance of the model at these resolutions is of general relevance to the research community as well as to operational forecasters
Julia Thomas, Andrew Barrett, and Corinna Hoose
Atmos. Chem. Phys., 23, 1987–2002, https://doi.org/10.5194/acp-23-1987-2023, https://doi.org/10.5194/acp-23-1987-2023, 2023
Short summary
Short summary
We study the sensitivity of rain formation processes during a heavy-rainfall event over mountains to changes in temperature and pollution. Total rainfall increases by 2 % K−1, and a 6 % K−1 increase is found at the highest altitudes, caused by a mixed-phase seeder–feeder mechanism (frozen cloud particles melt and grow further as they fall through a liquid cloud layer). In a cleaner atmosphere this process is enhanced. Thus the risk of severe rainfall in mountains may increase in the future.
Takumi Matsunobu, Christian Keil, and Christian Barthlott
Weather Clim. Dynam., 3, 1273–1289, https://doi.org/10.5194/wcd-3-1273-2022, https://doi.org/10.5194/wcd-3-1273-2022, 2022
Short summary
Short summary
This study quantifies the impact of poorly constrained parameters used to represent aerosol–cloud–precipitation interactions on precipitation and cloud forecasts associated with uncertainties in input atmospheric states. Uncertainties in these parameters have a non-negligible impact on daily precipitation amount and largely change the amount of cloud. The comparison between different weather situations reveals that the impact becomes more important when convection is triggered by local effects.
Christian Barthlott, Amirmahdi Zarboo, Takumi Matsunobu, and Christian Keil
Atmos. Chem. Phys., 22, 10841–10860, https://doi.org/10.5194/acp-22-10841-2022, https://doi.org/10.5194/acp-22-10841-2022, 2022
Short summary
Short summary
The relevance of microphysical and land-surface uncertainties for convective-scale predictability is evaluated with a combined-perturbation strategy in realistic convection-resolving simulations. We find a large ensemble spread which demonstrates that the uncertainties investigated here and, in particular, their collective effect are highly relevant for quantitative precipitation forecasting of summertime convection in central Europe.
Christian Barthlott, Amirmahdi Zarboo, Takumi Matsunobu, and Christian Keil
Atmos. Chem. Phys., 22, 2153–2172, https://doi.org/10.5194/acp-22-2153-2022, https://doi.org/10.5194/acp-22-2153-2022, 2022
Short summary
Short summary
The relative impact of cloud condensation nuclei (CCN) concentrations and the shape parameter of the cloud droplet size distribution is evaluated in realistic convection-resolving simulations. We find that an increase in the shape parameter can produce almost as large a variation in precipitation as a CCN increase from maritime to polluted conditions. The choice of the shape parameter may be more important than previously thought for determining cloud radiative characteristics.
Constanze Wellmann, Andrew I. Barrett, Jill S. Johnson, Michael Kunz, Bernhard Vogel, Ken S. Carslaw, and Corinna Hoose
Atmos. Chem. Phys., 20, 2201–2219, https://doi.org/10.5194/acp-20-2201-2020, https://doi.org/10.5194/acp-20-2201-2020, 2020
Short summary
Short summary
Severe hailstorms may cause damage to buildings and crops. Thus, the forecast of numerical weather prediction (NWP) models should be as reliable as possible.
Using statistical emulation, we identify those model input parameters describing environmental conditions and cloud microphysics which lead to large uncertainties in the prediction of deep convection. We find that the impact of the input parameters on the uncertainty depends on the considered output variable.
Linda Schneider, Christian Barthlott, Corinna Hoose, and Andrew I. Barrett
Atmos. Chem. Phys., 19, 12343–12359, https://doi.org/10.5194/acp-19-12343-2019, https://doi.org/10.5194/acp-19-12343-2019, 2019
Short summary
Short summary
This study addresses the relative impact of orography, soil moisture, and aerosols on precipitation over Germany in different weather regimes. We find that the impact of these perturbations is higher for weak than for strong large-scale forcing. Furthermore, aerosols and soil moisture are both of similar importance for precipitation forecasting, which indicates that their inclusion in operational ensemble forecasting should be assessed in the future.
Andrew I. Barrett, Christopher D. Westbrook, John C. Nicol, and Thorwald H. M. Stein
Atmos. Chem. Phys., 19, 5753–5769, https://doi.org/10.5194/acp-19-5753-2019, https://doi.org/10.5194/acp-19-5753-2019, 2019
Short summary
Short summary
We use radars at three wavelengths to study cloud properties. The full Doppler spectra (rather than calculated averages of the spectra) are compared for the radars. This allows us to estimate the size and number of ice particles within the cloud. By following the evolution of the ice particles, we observe a region where particles rapidly and consistently increase in size. The observations suggest that these large particles form through interlocking of branched arms of smaller ice particles.
Sylvia C. Sullivan, Christian Barthlott, Jonathan Crosier, Ilya Zhukov, Athanasios Nenes, and Corinna Hoose
Atmos. Chem. Phys., 18, 16461–16480, https://doi.org/10.5194/acp-18-16461-2018, https://doi.org/10.5194/acp-18-16461-2018, 2018
Short summary
Short summary
Ice crystal formation in clouds can occur via thermodynamic nucleation, but also via mechanical collisions between pre-existing crystals or co-existing droplets. When descriptions of this mechanical ice generation are implemented into the COSMO weather model, we find that the contributions to crystal number from thermodynamic and mechanical processes are of the same order. Mechanical ice generation also intensifies differences in precipitation intensity between dynamic and quiescent regions.
Andreas Macke, Patric Seifert, Holger Baars, Christian Barthlott, Christoph Beekmans, Andreas Behrendt, Birger Bohn, Matthias Brueck, Johannes Bühl, Susanne Crewell, Thomas Damian, Hartwig Deneke, Sebastian Düsing, Andreas Foth, Paolo Di Girolamo, Eva Hammann, Rieke Heinze, Anne Hirsikko, John Kalisch, Norbert Kalthoff, Stefan Kinne, Martin Kohler, Ulrich Löhnert, Bomidi Lakshmi Madhavan, Vera Maurer, Shravan Kumar Muppa, Jan Schween, Ilya Serikov, Holger Siebert, Clemens Simmer, Florian Späth, Sandra Steinke, Katja Träumner, Silke Trömel, Birgit Wehner, Andreas Wieser, Volker Wulfmeyer, and Xinxin Xie
Atmos. Chem. Phys., 17, 4887–4914, https://doi.org/10.5194/acp-17-4887-2017, https://doi.org/10.5194/acp-17-4887-2017, 2017
Short summary
Short summary
This article provides an overview of the instrumental setup and the main results obtained during the two HD(CP)2 Observational Prototype Experiments HOPE-Jülich and HOPE-Melpitz conducted in Germany in April–May and Sept 2013, respectively. Goal of the field experiments was to provide high-resolution observational datasets for both, improving the understaning of boundary layer and cloud processes, as well as for the evaluation of the new ICON model that is run at 156 m horizontal resolution.
C. Barthlott and C. Hoose
Atmos. Chem. Phys., 15, 12361–12384, https://doi.org/10.5194/acp-15-12361-2015, https://doi.org/10.5194/acp-15-12361-2015, 2015
Short summary
Short summary
This paper assesses the resolution dependance of clouds and precipitation over Germany by numerical simulations with the COnsortium for Small-scale MOdeling model for 7 cases of 2013. By means of a series of grid-refinement resolution tests, the variability of clouds and precipitation and how this variability changes with model resolution are investigated. The performance of the model at these resolutions is of general relevance to the research community as well as to operational forecasters
Related subject area
Atmospheric predictability
Understanding winter windstorm predictability over Europe
What determines the predictability of a Mediterranean cyclone?
Intrinsic predictability limits arising from Indian Ocean Madden–Julian oscillation (MJO) heating: effects on tropical and extratropical teleconnections
Predictable decadal forcing of the North Atlantic jet speed by sub-polar North Atlantic sea surface temperatures
Exploiting the signal-to-noise ratio in multi-system predictions of boreal summer precipitation and temperature
Uncertainty growth and forecast reliability during extratropical cyclogenesis
Convection-parameterized and convection-permitting modelling of heavy precipitation in decadal simulations of the greater Alpine region with COSMO-CLM
Improved extended-range prediction of persistent stratospheric perturbations using machine learning
Increased vertical resolution in the stratosphere reveals role of gravity waves after sudden stratospheric warmings
The impact of microphysical uncertainty conditional on initial and boundary condition uncertainty under varying synoptic control
Subseasonal precipitation forecasts of opportunity over central southwest Asia
Predictability of a tornado environment index from El Niño–Southern Oscillation (ENSO) and the Arctic Oscillation
Differences in the sub-seasonal predictability of extreme stratospheric events
Impact of Eurasian autumn snow on the winter North Atlantic Oscillation in seasonal forecasts of the 20th century
Bimodality in ensemble forecasts of 2 m temperature: identification
Flow dependence of wintertime subseasonal prediction skill over Europe
Seasonal forecasts of the Saharan heat low characteristics: a multi-model assessment
Emergence of representative signals for sudden stratospheric warmings beyond current predictable lead times
The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6
Seasonal climate influences on the timing of the Australian monsoon onset
Subseasonal prediction of springtime Pacific–North American transport using upper-level wind forecasts
A dynamic and thermodynamic analysis of the 11 December 2017 tornadic supercell in the Highveld of South Africa
How an uncertain short-wave perturbation on the North Atlantic wave guide affects the forecast of an intense Mediterranean cyclone (Medicane Zorbas)
Robust predictors for seasonal Atlantic hurricane activity identified with causal effect networks
Subseasonal midlatitude prediction skill following Quasi-Biennial Oscillation and Madden–Julian Oscillation activity
Lisa Degenhardt, Gregor C. Leckebusch, and Adam A. Scaife
Weather Clim. Dynam., 5, 587–607, https://doi.org/10.5194/wcd-5-587-2024, https://doi.org/10.5194/wcd-5-587-2024, 2024
Short summary
Short summary
This study investigates how dynamical factors that are known to influence cyclone or windstorm development and strengthening also influence the seasonal forecast skill of severe winter windstorms. This study shows which factors are well represented in the seasonal forecast model, the Global Seasonal forecasting system version 5 (GloSea5), and which might need improvement to refine the forecast of severe winter windstorms.
Benjamin Doiteau, Florian Pantillon, Matthieu Plu, Laurent Descamps, and Thomas Rieutord
EGUsphere, https://doi.org/10.5194/egusphere-2024-675, https://doi.org/10.5194/egusphere-2024-675, 2024
Short summary
Short summary
The predictability of Mediterranean cyclones is investigated through a large data set of 2853 cyclones tracks, ensuring robust statistical results. The velocity of the cyclone appears to be determinant in the predictability of its position. In particular the position of specific slow cyclones located in the Gulf of Genoa is remarkably well predicted. It is also shown that the intensity of deep cyclones occuring in winter is particularly poorly predicted in the Mediterranean region.
David Martin Straus, Daniela I. V. Domeisen, Sarah-Jane Lock, Franco Molteni, and Priyanka Yadav
Weather Clim. Dynam., 4, 1001–1018, https://doi.org/10.5194/wcd-4-1001-2023, https://doi.org/10.5194/wcd-4-1001-2023, 2023
Short summary
Short summary
The global response to the Madden–Julian oscillation (MJO) is potentially predictable. Yet the diabatic heating is uncertain even within a particular episode of the MJO. Experiments with a global model probe the limitations imposed by this uncertainty. The large-scale tropical heating is predictable for 25 to 45 d, yet the associated Rossby wave source that links the heating to the midlatitude circulation is predictable for 15 to 20 d. This limitation has not been recognized in prior work.
Kristian Strommen, Tim Woollings, Paolo Davini, Paolo Ruggieri, and Isla R. Simpson
Weather Clim. Dynam., 4, 853–874, https://doi.org/10.5194/wcd-4-853-2023, https://doi.org/10.5194/wcd-4-853-2023, 2023
Short summary
Short summary
We present evidence which strongly suggests that decadal variations in the intensity of the North Atlantic winter jet stream can be predicted by current forecast models but that decadal variations in its position appear to be unpredictable. It is argued that this skill at predicting jet intensity originates from the slow, predictable variability in sea surface temperatures in the sub-polar North Atlantic.
Juan Camilo Acosta Navarro and Andrea Toreti
Weather Clim. Dynam., 4, 823–831, https://doi.org/10.5194/wcd-4-823-2023, https://doi.org/10.5194/wcd-4-823-2023, 2023
Short summary
Short summary
Droughts and heatwaves have become some of the clearest manifestations of a changing climate. Near-term adaptation strategies can benefit from seasonal predictions, but these predictions still have limitations. We found that an intrinsic property of multi-system forecasts can serve to better anticipate extreme high-temperature and low-precipitation events during boreal summer in several regions of the Northern Hemisphere with different levels of predictability.
Mark J. Rodwell and Heini Wernli
Weather Clim. Dynam., 4, 591–615, https://doi.org/10.5194/wcd-4-591-2023, https://doi.org/10.5194/wcd-4-591-2023, 2023
Short summary
Short summary
Midlatitude storms and their downstream impacts have a major impact on society, yet their prediction is especially prone to uncertainty. While this can never be fully eliminated, we find that the initial rate of growth of uncertainty varies for a range of forecast models. Examination of the model of the European Centre for Medium-Range Weather Forecasts (ECMWF) suggests ways in which uncertainty growth could be reduced, leading to sharper and more reliable forecasts over the first few days.
Alberto Caldas-Alvarez, Hendrik Feldmann, Etor Lucio-Eceiza, and Joaquim G. Pinto
Weather Clim. Dynam., 4, 543–565, https://doi.org/10.5194/wcd-4-543-2023, https://doi.org/10.5194/wcd-4-543-2023, 2023
Short summary
Short summary
We evaluate convection-permitting modelling (CPM) simulations for the greater Alpine area to assess its added value compared to a 25 km resolution. A new method for severe precipitation detection is used, and the associated synoptic weather types are considered. Our results document the added value of CPM for precipitation representation with higher intensities, better rank correlation, better hit rates, and an improved amount and structure, but with an overestimation of the rates.
Raphaël de Fondeville, Zheng Wu, Enikő Székely, Guillaume Obozinski, and Daniela I. V. Domeisen
Weather Clim. Dynam., 4, 287–307, https://doi.org/10.5194/wcd-4-287-2023, https://doi.org/10.5194/wcd-4-287-2023, 2023
Short summary
Short summary
We propose a fully data-driven, interpretable, and computationally scalable framework to characterize sudden stratospheric warmings (SSWs), extract statistically significant precursors, and produce machine learning (ML) forecasts. By successfully leveraging the long-lasting impact of SSWs, the ML predictions outperform sub-seasonal numerical forecasts for lead times beyond 25 d. Post-processing numerical predictions using their ML counterparts yields a performance increase of up to 20 %.
Wolfgang Wicker, Inna Polichtchouk, and Daniela I. V. Domeisen
Weather Clim. Dynam., 4, 81–93, https://doi.org/10.5194/wcd-4-81-2023, https://doi.org/10.5194/wcd-4-81-2023, 2023
Short summary
Short summary
Sudden stratospheric warmings are extreme weather events where the winter polar stratosphere warms by about 25 K. An improved representation of small-scale gravity waves in sub-seasonal prediction models can reduce forecast errors since their impact on the large-scale circulation is predictable multiple weeks ahead. After a sudden stratospheric warming, vertically propagating gravity waves break at a lower altitude than usual, which strengthens the long-lasting positive temperature anomalies.
Takumi Matsunobu, Christian Keil, and Christian Barthlott
Weather Clim. Dynam., 3, 1273–1289, https://doi.org/10.5194/wcd-3-1273-2022, https://doi.org/10.5194/wcd-3-1273-2022, 2022
Short summary
Short summary
This study quantifies the impact of poorly constrained parameters used to represent aerosol–cloud–precipitation interactions on precipitation and cloud forecasts associated with uncertainties in input atmospheric states. Uncertainties in these parameters have a non-negligible impact on daily precipitation amount and largely change the amount of cloud. The comparison between different weather situations reveals that the impact becomes more important when convection is triggered by local effects.
Melissa L. Breeden, John R. Albers, and Andrew Hoell
Weather Clim. Dynam., 3, 1183–1197, https://doi.org/10.5194/wcd-3-1183-2022, https://doi.org/10.5194/wcd-3-1183-2022, 2022
Short summary
Short summary
We use a statistical dynamical model to generate precipitation forecasts for lead times of 2–6 weeks over southwest Asia, which are needed to support humanitarian food distribution. The model signal-to-noise ratio is used to identify a smaller subset of forecasts with particularly high skill, so-called subseasonal forecasts of opportunity (SFOs). Precipitation SFOs are often related to slowly evolving tropical phenomena, namely the El Niño–Southern Oscillation and Madden–Julian Oscillation.
Michael K. Tippett, Chiara Lepore, and Michelle L. L’Heureux
Weather Clim. Dynam., 3, 1063–1075, https://doi.org/10.5194/wcd-3-1063-2022, https://doi.org/10.5194/wcd-3-1063-2022, 2022
Short summary
Short summary
The El Niño–Southern Oscillation (ENSO) and Arctic Oscillation (AO) are phenomena that affect the weather and climate of North America. Although ENSO hails from from the tropical Pacific and the AO high above the North Pole, the spatial patterns of their influence on a North American tornado environment index are remarkably similar in computer models. We find that when ENSO and the AO act in concert, their impact is large, and when they oppose each other, their impact is small.
Rachel Wai-Ying Wu, Zheng Wu, and Daniela I.V. Domeisen
Weather Clim. Dynam., 3, 755–776, https://doi.org/10.5194/wcd-3-755-2022, https://doi.org/10.5194/wcd-3-755-2022, 2022
Short summary
Short summary
Accurate predictions of the stratospheric polar vortex can enhance surface weather predictability. Stratospheric events themselves are less predictable, with strong inter-event differences. We assess the predictability of stratospheric acceleration and deceleration events in a sub-seasonal prediction system, finding that the predictability of events is largely dependent on event magnitude, while extreme drivers of deceleration events are not fully represented in the model.
Martin Wegmann, Yvan Orsolini, Antje Weisheimer, Bart van den Hurk, and Gerrit Lohmann
Weather Clim. Dynam., 2, 1245–1261, https://doi.org/10.5194/wcd-2-1245-2021, https://doi.org/10.5194/wcd-2-1245-2021, 2021
Short summary
Short summary
Northern Hemisphere winter weather is influenced by the strength of westerly winds 30 km above the surface, the so-called polar vortex. Eurasian autumn snow cover is thought to modulate the polar vortex. So far, however, the modeled influence of snow on the polar vortex did not fit the observed influence. By analyzing a model experiment for the time span of 110 years, we could show that the causality of this impact is indeed sound and snow cover can weaken the polar vortex.
Cameron Bertossa, Peter Hitchcock, Arthur DeGaetano, and Riwal Plougonven
Weather Clim. Dynam., 2, 1209–1224, https://doi.org/10.5194/wcd-2-1209-2021, https://doi.org/10.5194/wcd-2-1209-2021, 2021
Short summary
Short summary
While the assumption of Gaussianity leads to many simplifications, ensemble forecasts often exhibit non-Gaussian distributions. This work has systematically identified the presence of a specific case of
non-Gaussianity, bimodality. It has been found that bimodality occurs in a large portion of global 2 m temperature forecasts. This has drastic implications on forecast skill as the minimum probability in a bimodal distribution often lies at the maximum probability of a Gaussian distribution.
Constantin Ardilouze, Damien Specq, Lauriane Batté, and Christophe Cassou
Weather Clim. Dynam., 2, 1033–1049, https://doi.org/10.5194/wcd-2-1033-2021, https://doi.org/10.5194/wcd-2-1033-2021, 2021
Short summary
Short summary
Forecasting temperature patterns beyond 2 weeks is very challenging, although occasionally, forecasts show more skill over Europe. Our study indicates that the level of skill varies concurrently for two distinct forecast systems. It also shows that higher skill occurs when forecasts are issued during specific patterns of atmospheric circulation that tend to be particularly persistent.
These results could help forecasters estimate a priori how trustworthy extended-range forecasts will be.
Cedric G. Ngoungue Langue, Christophe Lavaysse, Mathieu Vrac, Philippe Peyrillé, and Cyrille Flamant
Weather Clim. Dynam., 2, 893–912, https://doi.org/10.5194/wcd-2-893-2021, https://doi.org/10.5194/wcd-2-893-2021, 2021
Short summary
Short summary
This work assesses the forecast of the temperature over the Sahara, a key driver of the West African Monsoon, at a seasonal timescale. The seasonal models are able to reproduce the climatological state and some characteristics of the temperature during the rainy season in the Sahel. But, because of errors in the timing, the forecast skill scores are significant only for the first 4 weeks.
Zheng Wu, Bernat Jiménez-Esteve, Raphaël de Fondeville, Enikő Székely, Guillaume Obozinski, William T. Ball, and Daniela I. V. Domeisen
Weather Clim. Dynam., 2, 841–865, https://doi.org/10.5194/wcd-2-841-2021, https://doi.org/10.5194/wcd-2-841-2021, 2021
Short summary
Short summary
We use an advanced statistical approach to investigate the dynamics of the development of sudden stratospheric warming (SSW) events in the winter Northern Hemisphere. We identify distinct signals that are representative of these events and their event type at lead times beyond currently predictable lead times. The results can be viewed as a promising step towards improving the predictability of SSWs in the future by using more advanced statistical methods in operational forecasting systems.
Alberto Caldas-Alvarez, Samiro Khodayar, and Peter Knippertz
Weather Clim. Dynam., 2, 561–580, https://doi.org/10.5194/wcd-2-561-2021, https://doi.org/10.5194/wcd-2-561-2021, 2021
Short summary
Short summary
The prediction capabilities of GPS, operational (low-resolution) and targeted (high-resolution) radiosondes for data assimilation in a Mediterranean heavy precipitation event at different model resolutions are investigated. The results show that even if GPS provides accurate observations, their lack of vertical information hampers the improvement, demonstrating the need for assimilating radiosondes, where the location and timing of release was more determinant than the vertical resolution.
Joel Lisonbee and Joachim Ribbe
Weather Clim. Dynam., 2, 489–506, https://doi.org/10.5194/wcd-2-489-2021, https://doi.org/10.5194/wcd-2-489-2021, 2021
Short summary
Short summary
Why do some monsoon seasons start early, while others start late? For the Australian monsoon, some previous research suggested the El Niño–Southern Oscillation in the months before the onset influenced the monsoon timing. This research tests if this is still correct and if other large-scale climate patterns also influenced onset timing. We found that a strong La Niña pattern usually coincided with an early onset but weak La Niña and El Niño patterns did not show a consistent pattern.
John R. Albers, Amy H. Butler, Melissa L. Breeden, Andrew O. Langford, and George N. Kiladis
Weather Clim. Dynam., 2, 433–452, https://doi.org/10.5194/wcd-2-433-2021, https://doi.org/10.5194/wcd-2-433-2021, 2021
Short summary
Short summary
Weather variability controls the transport of ozone from the stratosphere to the Earth’s surface and water vapor from oceanic source regions to continental land masses. Forecasting these types of transport has high societal value because of the negative impacts of ozone on human health and the role of water vapor in governing precipitation variability. We use upper-level wind forecasts to assess the potential for predicting ozone and water vapor transport 3–6 weeks ahead of time.
Lesetja E. Lekoloane, Mary-Jane M. Bopape, Tshifhiwa Gift Rambuwani, Thando Ndarana, Stephanie Landman, Puseletso Mofokeng, Morne Gijben, and Ngwako Mohale
Weather Clim. Dynam., 2, 373–393, https://doi.org/10.5194/wcd-2-373-2021, https://doi.org/10.5194/wcd-2-373-2021, 2021
Short summary
Short summary
We analysed a tornadic supercell that tracked through the northern Highveld region of South Africa for 7 h. We found that atmospheric conditions were conducive for tornado-associated severe storms over the region. A 4.4 km resolution model run by the South African Weather Service was able to predict this supercell, including its timing. However, it underestimated its severity due to underestimations of other important factors necessary for real-world development of these kinds of storms.
Raphael Portmann, Juan Jesús González-Alemán, Michael Sprenger, and Heini Wernli
Weather Clim. Dynam., 1, 597–615, https://doi.org/10.5194/wcd-1-597-2020, https://doi.org/10.5194/wcd-1-597-2020, 2020
Short summary
Short summary
In September 2018 an intense Mediterranean cyclone with structural similarities to a hurricane, a so-called medicane, caused severe damage in Greece. Its development was uncertain, even just a few days in advance. The reason for this was uncertainties in the jet stream over the North Atlantic 3 d prior to cyclogenesis that propagated into the Mediterranean. They led to an uncertain position of the upper-level disturbance and, as a result, of the position and thermal structure of the cyclone.
Peter Pfleiderer, Carl-Friedrich Schleussner, Tobias Geiger, and Marlene Kretschmer
Weather Clim. Dynam., 1, 313–324, https://doi.org/10.5194/wcd-1-313-2020, https://doi.org/10.5194/wcd-1-313-2020, 2020
Short summary
Short summary
Seasonal outlooks of Atlantic hurricane activity are required to enable risk reduction measures and disaster preparedness. Many seasonal forecasts are based on a selection of climate signals from which a statistical model is constructed. The crucial step in this approach is to select the most relevant predictors without overfitting. Here we show that causal effect networks can be used to identify the most robust predictors. Based on these predictors we construct a competitive forecast model.
Kirsten J. Mayer and Elizabeth A. Barnes
Weather Clim. Dynam., 1, 247–259, https://doi.org/10.5194/wcd-1-247-2020, https://doi.org/10.5194/wcd-1-247-2020, 2020
Short summary
Short summary
Tropical storms are key for harnessing midlatitude weather prediction skill 2–8 weeks into the future. Recently, stratospheric activity was shown to impact tropical storminess and thus may also be important for midlatitude prediction skill on these timescales. This work analyzes two forecast systems to assess whether they capture this additional skill. We find there is enhanced prediction out through week 4 when both the tropical and stratospheric phenomena are active.
Cited articles
Barrett, A. I., Gray, S. L., Kirshbaum, D. J., Roberts, N. M., Schultz, D. M., and Fairman Jr., J. G.: Synoptic versus orographic control on stationary
convective banding, Q. J. Roy. Meteorol. Soc., 141, 1101–1113,
https://doi.org/10.1002/qj.2409, 2015. a, b
Barrett, A. I., Wellmann, C., Seifert, A., Hoose, C., Vogel, B., and Kunz, M.: One step at a time: How model timestep significantly affects
Convection-Permitting simulations, J. Adv. Model. Earth Syst., 11, 641–658, https://doi.org/10.1029/2018MS001418, 2019. a
Barthlott, C. and Hoose, C.: Aerosol effects on clouds and precipitation over
central Europe in different weather regimes, J. Atmos. Sci., 75, 4247–4264, https://doi.org/10.1175/JAS-D-18-0110.1, 2018. a
Barthlott, C., Hauck, C., Schädler, G., Kalthoff, N., and Kottmeier, C.:
Soil moisture impacts on convective indices and precipitation over complex
terrain, Meteorol. Z., 20, 185–197, https://doi.org/10.1127/0941-2948/2011/0216, 2011. a
Barthlott, C., Mühr, B., and Hoose, C.: Sensitivity of the 2014 Pentecost
storms over Germany to different model grids and microphysics schemes, Q. J.
Roy. Meteorol. Soc., 143, 1485–1503, https://doi.org/10.1002/qj.3019, 2017. a, b, c, d
Bednarczyk, C. N. and Ancell, B. C.: Ensemble Sensitivity Analysis Applied to
a Southern Plains Convective Event, Mon. Weather Rev., 143, 230–249,
https://doi.org/10.1175/MWR-D-13-00321.1, 2015. a
Bennett, L. J., Browning, K. A., Blyth, A. M., Parker, D. J., and Clark, P. A.: A review of the initiation of precipitating convection in the United
Kingdom, Q. J. Roy. Meteorol. Soc., 132, 1001–1020, https://doi.org/10.1256/qj.05.54,
2006. a
Berner, J., Achatz, U., Batté, L., Bengtsson, L., de la Cámara, A.,
Christensen, H. M., Colangeli, M., Coleman, D. R. B., Crommelin, D.,
Dolaptchiev, S. I., Franzke, C. L. E., Friederichs, P., Imkeller, P.,
Järvinen, H., Juricke, S., Kitsios, V., Lott, F., Lucarini, V., Mahajan,
S., Palmer, T. N., Penland, C., Sakradzija, M., von Storch, J.-S.,
Weisheimer, A., Weniger, M., Williams, P. D., and Yano, J.-I.: Stochastic
Parameterization: Toward a New View of Weather and Climate Models, B. Am. Meteorol. Soc., 98, 565–588, https://doi.org/10.1175/BAMS-D-15-00268.1, 2017. a
Bouttier, F. and Raynaud, L.: Clustering and selection of boundary conditions
for limited area ensemble prediction, Q. J. Roy. Meteorol. Soc., 144,
2381–2391, https://doi.org/10.1002/qj.3304, 2018. a, b
Buizza, R., Miller, M., and Palmer, T.: Stochastic representation of model
uncertainties in the ECMWF ensemble prediction system, Q. J. Roy. Meteorol.
Soc., 125, 2887–2908, https://doi.org/10.1002/qj.49712556006, 1999. a
Caron, J.-F.: Mismatching Perturbations at the Lateral Boundaries in
Limited-Area Ensemble Forecasting: A Case Study, Mon. Weather Rev., 141,
356–374, https://doi.org/10.1175/MWR-D-12-00051.1, 2013. a
Clark, P., Roberts, N., Lean, H., Ballard, S. P., and Charlton-Perez, C.:
Convection-permitting models: a step-change in rainfall forecasting, Meteorol. Appl., 23, 165–181, https://doi.org/10.1002/met.1538, 2016. a
Crook, N. A.: Sensitivity of moist convection forced by boundary layer
processes to low-level thermodynamic fields, Mon. Weather Rev., 124,
1767–1785, https://doi.org/10.1175/1520-0493(1996)124<1767:SOMCFB>2.0.CO;2, 1996. a
Crook, N. A. and Klemp, J. B.: Lifting by convergence lines, J. Atmos. Sci.,
57, 873–890, https://doi.org/10.1175/1520-0469(2000)057<0873:LBCL>2.0.CO;2, 2000. a
Doswell III, C. A.: The Distinction between Large-Scale and Mesoscale
Contribution to Severe Convection: A Case Study Example, Weather Forecast., 2, 3–16, https://doi.org/10.1175/1520-0434(1987)002<0003:TDBLSA>2.0.CO;2, 1987.
Dowell, D. C., Zhang, F., Wicker, L. J., Snyder, C., and Crook, N. A.: Wind
and temperature retrievals in the 17 May 1981 Arcadia, Oklahoma supercell: Ensemble Kalman filter experiments, Mon. Weather Rev., 132, 1982–2005, https://doi.org/10.1175/1520-0493(2004)132<1982:WATRIT>2.0.CO;2, 2004. a
Gebhardt, C., Theis, S., Paulat, M., and Ben Bouallègue, Z.: Uncertainties in COSMO-DE precipitation forecasts introduced by model perturbations and variation of lateral boundaries, Atmos. Res., 100, 168–177, https://doi.org/10.1016/j.atmosres.2010.12.008, 2011. a
Groenemeijer, P.: Summary of the evaluation of DWD NWP products and
visualizations at the ESSL Testbed 2014, 28 pp., available at:
https://www.essl.org/cms/publications (last access: 17 April 2020), 2014. a
Henneberg, O., Ament, F., and Grützun, V.: Assessing the uncertainty of
soil moisture impacts on convective precipitation using a new ensemble
approach, Atmos. Chem. Phys., 18, 6413–6425, https://doi.org/10.5194/acp-18-6413-2018,
2018. a, b
Hill, A. J., Weiss, C. C., and Ancell, B. C.: Ensemble Sensitivity Analysis
for Mesoscale Forecasts of Dryline Convection Initiation, Mon. Weather Rev.,
144, 4161–4182, https://doi.org/10.1175/MWR-D-15-0338.1, 2016. a
Hohenegger, C., Lüthi, D., and Schär, C.: Predictability Mysteries in
Cloud-Resolving Models, Mon. Weather Rev., 134, 2095–2107, https://doi.org/10.1175/MWR3176.1, 2006. a
Hoskins, B. J., Draghici, I., and Davies, H. C.: A new look at the
omega-equation, Q. J. Roy. Meteorol. Soc., 104, 31–38,
https://doi.org/10.1002/qj.49710443903, 1978. a
Keil, C., Baur, F., Bachmann, K., Rasp, S., Schneider, L., and Barthlott, C.:
Relative contribution of soil moisture, boundary-layer and microphysical
perturbations on convective predictability in different weather regimes, Q.
J. Roy. Meteorol. Soc., 145, 3102–3115, https://doi.org/10.1002/qj.3607, 2019. a
Kirshbaum, D. J., Adler, B., Kalthoff, N., Barthlott, C., and Serafin, S.:
Moist Orographic Convection: Physical Mechanisms and Links to Surface-Exchange Processes, Atmosphere, 9, 80, https://doi.org/10.3390/atmos9030080,
2018. a
Kühnlein, C., Keil, C., Craig, G. C., and Gebhardt, C.: The impact of
downscaled initial condition perturbations on convective-scale ensemble
forecasts of precipitation, Q. J. Roy. Meteorol. Soc., 140, 1552–1562,
https://doi.org/10.1002/qj.2238, 2014. a, b
Marsigli, C., Montani, A., Nerozzi, F., Paccagnella, T., Tibaldi, S., Molteni, F., and Buizza, R.: A strategy for high‐resolution ensemble prediction. Part II: Limited‐area experiments in four Alpine flood events, Q. J. Roy. Meteorol. Soc., 127, 2095–2115, https://doi.org/10.1002/qj.49712757613, 2001. a
Mathias, L., Ermert, V., Kelemen, F. D., Ludwig, P., and Pinto, J. G.:
Synoptic analysis and hindcast of an intense bow echo above Western Europe: The Pentecost storm 2014, Weather Forecast., 32, 1121–1141,
https://doi.org/10.1175/WAF-D-16-0192.1, 2017. a, b, c
Mellor, G. L. and Yamada, T.: A hierarchy of turbulence closure models for
planetary boundary layers, J. Atmos. Sci., 31, 1791–1806,
https://doi.org/10.1175/1520-0469(1974)031<1791:AHOTCM>2.0.CO;2, 1974. a
Miguez-Macho, G., Stenchikov, G. L., and Robock, A.: Spectral nudging to
eliminate the effects of domain position and geometry in regional climate
model simulations, J. Geophys. Res., 109, d13104, https://doi.org/10.1029/2003JD004495,
2004. a, b
Montani, A., Cesari, D., Marsigli, C., and Paccagnella, T.: Seven years of
activity in the field of mesoscale ensemble forecasting by the COSMO-LEPS
system: Main achievements and open challenges, Tellus A, 63, 605–624,
https://doi.org/10.1111/j.1600-0870.2010.00499.x, 2011. a, b
Reich, H., Rhodin, A., and Schraff, C.: LETKF for the nonhydrostatic regional
model COSMO-DE, COSMO Newsletter 11, 27–31, 148 pp., available at:
http://www.cosmo-model.org (last access: 17 April 2020), 2011. a
Richard, E., Chaboureau, J. P., Flamant, C., Champollion, C., Hagen, M.,
Schmidt, K., Kiemle, C., Corsmeier, U., Barthlott, C., and Di Girolamo, P.:
Forecasting summer convection over the Black Forest: a case study from the Convective and Orographically-induced Precipitation Study (COPS) experiment, Q. J. Roy. Meteorol. Soc., 137, 101–117, https://doi.org/10.1002/qj.710, 2011. a
Rodwell, M. J., Magnusson, L., Bauer, P., Bechtold, P., Bonavita, M., Cardinali, C., Diamantakis, M., Earnshaw, P., Garcia-Mendez, A., Isaksen, L., Këllén, E., Klocke, D., Lopez, P., McNally, T., Persson, A., Prates, F., and Wedi, N.: Characteristics of occasional poor medium-range weather forecasts for Europe, B. Am. Meteorol. Soc., 94, 1393–1405, https://doi.org/10.1175/BAMS-D-12-00099.1, 2013. a, b
Romine, G. S., Schwartz, C. S., Berner, J., Fossell, K. R., Snyder, C.,
Anderson, J. L., and Weisman, M. L.: Representing Forecast Error in a
Convection-Permitting Ensemble System, Mon. Weather Rev., 142, 4519–4541,
https://doi.org/10.1175/MWR-D-14-00100.1, 2014. a
Rossa, A., Bruen, M., Frühwald, D., Macpherson, B., Holleman, I.,
Michelson, D., and Michaelides, S.: Use of Radar Observations in Hydrological and NWP Models, available at: http://www.cost.eu/media/publications (last access: 17 April 2020), 2005. a
Schättler, U., Doms, G., and Schraff, C.: A description of the
nonhydrostatic regional COSMO-model, Part VII: User's Guide, 181 pp., available at: http://www.cosmo-model.org (last access: 17 April 2020), 2019. a
Schlüter, I. and Schädler, G.: Sensitivity of Heavy Precipitation
Forecasts to Small Modifications of Large-Scale Weather Patterns for the Elbe
River, J. Hydrometeorol., 11, 770–780, https://doi.org/10.1175/2010JHM1186.1, 2010. a
Schneider, L., Barthlott, C., Hoose, C., and Barrett, A. I.: Relative impact of aerosol, soil moisture, and orography perturbations on deep convection,
Atmos. Chem. Phys., 19, 12343–12359, https://doi.org/10.5194/acp-19-12343-2019, 2019. a
Seifert, A. and Beheng, K. D.: A two-moment cloud microphysics parameterization for mixed-phase clouds. Part I: Model description, Meteorol. Atmos. Phys., 92, 67–82, https://doi.org/10.1007/s00703-005-0112-4, 2006. a
Seth, A. and Giorgi, F.: The Effects of Domain Choice on Summer Precipitation
Simulation and Sensitivity in a Regional Climate Model, J. Climate, 11,
2698–2712, https://doi.org/10.1175/1520-0442(1998)011<2698:TEODCO>2.0.CO;2, 1998.
a
Tiedtke, M.: A comprehensive mass flux scheme for cumulus parameterization in
large-scale models, Mon. Weather Rev., 117, 1779–1800,
https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2, 1989. a
Torn, R. D., Hakim, G. J., and Snyder, C.: Boundary Conditions for Limited-Area Ensemble Kalman Filters, Mon. Weather Rev., 134, 2490–2502,
https://doi.org/10.1175/MWR3187.1, 2006. a, b
Torn, R. D., Romine, G. S., and Galarneau, T. J.: Sensitivity of Dryline
Convection Forecasts to Upstream Forecast Errors for Two Weakly Forced MPEX
Cases, Mon. Weather Rev., 145, 1831–1852, https://doi.org/10.1175/MWR-D-16-0457.1, 2017. a
Trentmann, J., Keil, C., Salzmann, M., Barthlott, C., Bauer, H.-S., Lawrence,
M., Leuenberger, D., Wernli, H., Wulfmeyer, V., Corsmeier, U., and Kottmeier,
C.: Multi-model simulations of a convective situation in low-mountain terrain
in central Europe, Meteorol. Atmos. Phys., 103, 95–103,
https://doi.org/10.1007/s00703-008-0323-6, 2009. a
Weckwerth, T.: The effect of small-scale moisture variability on thunderstorm
initiation, Mon. Weather Rev., 128, 4017–4030,
https://doi.org/10.1175/1520-0493(2000)129<4017:TEOSSM>2.0.CO;2, 2000. a
Wicker, L. J. and Skamarock, W. C.: Time-splitting methods for elastic models
using forward time schemes, Mon. Weather Rev., 130, 2088–2097,
https://doi.org/10.1175/1520-0493(2002)130<2088:TSMFEM>2.0.CO;2, 2002. a
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON
(ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M:
Description of the non-hydrostatic dynamical core, Q. J. Roy. Meteorol. Soc.,
141, 563–579, https://doi.org/10.1002/qj.2378, 2015. a
Zhang, F., Snyder, C., and Sun, J.: Impacts of Initial Estimate and
Observation Availability on Convective-Scale Data Assimilation with an
Ensemble Kalman Filter, Mon. Weather Rev., 132, 1238–1253,
https://doi.org/10.1175/1520-0493(2004)132<1238:IOIEAO>2.0.CO;2, 2004. a
Short summary
The mesoscale convective system (MCS) that affected Germany at Pentecost 2014 was one of the most severe for decades. However, the predictability of this system was very low. By moving the model domain by just one grid point changed whether the MCS was successfully simulated or not. The decisive factor seems to be small differences in the initial track of the convection: cooler air near the coast inhibited development there, but tracks slightly more inland found more favorable conditions.
The mesoscale convective system (MCS) that affected Germany at Pentecost 2014 was one of the...