Ensemble simulations with perturbed physical parametrizations: Pre-HyMeX case studies

Hally, Alan; Richard, Évelyne; Fresnay, S.; Lambert, Dominique

doi:10.1002/qj.2257

Cited by 26 publications

(39 citation statements)

References 42 publications

(67 reference statements)

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“…For the other ten members, the time tendencies of the warm rain processes of the ICE3 microphysical scheme were perturbed by a random factor ranging between 0.5 and 1.5. This random factor was generated in the same manner as in Hally et al (2013) and Fresnay et al (2012). Each random factor multiplied simultaneously the sources and sinks of a given microphysical process to ensure mass conversation was met.…”

Section: Configuration Of Ensemblesmentioning

confidence: 99%

“…Different methodologies have been employed, ranging from the use of different physical parameterisation schemes to stochastic perturbations applied upon the time tendencies of physical processes. More recently, Gebhardt et al (2011), Clark et al (2011, Fresnay et al (2012), Leoncini et al (2013) and Hally et al (2013) constructed convection-permitting short-range ensembles. The existence of such a breath of ensemble methodologies demonstrates that the most suitable approach remains open to debate, as no one methodology is found to be superior to the others.…”

Section: Introductionmentioning

confidence: 99%

“…The present work uses the methodology described in Hally et al (2013) and inspired by the previous works of Buizza et al (1999) and Fresnay et al (2012). These studies described ensemble simulations using stochastic perturbations upon the physical processes.…”

Section: Introductionmentioning

confidence: 99%

“…These studies described ensemble simulations using stochastic perturbations upon the physical processes. Hally et al (2013) and Fresnay et al (2012) concentrated on errors associated with the boundary layer turbulence and warm microphysical processes. They investigated the possible use of ensembles containing perturbations upon these processes in the forecasting of HPEs in the Mediterranean region.…”

Section: Introductionmentioning

confidence: 99%

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An ensemble study of HyMeX IOP6 and IOP7a: sensitivity to physical and initial and boundary condition uncertainties

Hally

Richard

Ducrocq³

2014

Nat. Hazards Earth Syst. Sci.

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Abstract. The first Special Observation Period of the HyMeX campaign took place in the Mediterranean betweenSeptember and November 2012 with the aim of better understanding the mechanisms which lead to heavy precipitation events (HPEs) in the region during the autumn months. Two such events, referred to as Intensive Observation Period 6 (IOP6) and Intensive Observation Period 7a (IOP7a), occurred respectively on 24 and 26 September over southeastern France. IOP6 was characterised by moderate to weak low-level flow which led to heavy and concentrated convective rainfall over the plains near the coast, while IOP7a had strong low-level flow and consisted of a convective line over the mountainous regions further north and a band of stratiform rainfall further east. Firstly, an ensemble was constructed for each IOP using analyses from the AROME, AROME-WMED, ARPEGE and ECMWF operational models as initial (IC) and boundary (BC) conditions for the research model Meso-NH at a resolution of 2.5 km. A high level of model skill was seen for IOP7a, with a lower level of agreement with the observations for IOP6. Using the most accurate member of this ensemble as a CTRL simulation, three further ensembles were constructed in order to study uncertainties related to cloud physics and surface turbulence parameterisations. Perturbations were introduced by perturbing the time tendencies of the warm and cold microphysical and turbulence processes. An ensemble where all three sources of uncertainty were perturbed gave the greatest degree of dispersion in the surface rainfall for both IOPs. Comparing the level of dispersion to that of the ICBC ensemble demonstrated that when model skill is low (high) and lowlevel flow is weak to moderate (strong), the level of dispersion of the ICBC and physical perturbation ensembles is (is not) comparable. The level of sensitivity to these perturbations is thus concluded to be case dependent.

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Section: Configuration Of Ensemblesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An ensemble study of HyMeX IOP6 and IOP7a: sensitivity to physical and initial and boundary condition uncertainties

Hally

Richard

Ducrocq³

2014

Nat. Hazards Earth Syst. Sci.

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“…The uncertainties involved in numerical simulations and predictions are rooted not only in the uncertainty of initial error (Morss and Battisti 2004;Aberson 2011) but also in model error (Williams et al 2001;Berthelot et al 2005;Carrassi and Vannitsem 2011;Jarvinen et al 2012;Hally et al 2013;Wan et al 2012) and belong to the Bfirst kind^and Bsecond kind^categories of weather and climate predictability problems (Mu et al 2002). The uncertainties in model errors mainly arise not only from the mathematical descriptions of earth system processes (Cramer et al 2001) but also from the uncertainties related to physical parameters in the model (Zaehle et al 2005).…”

Section: Introductionmentioning

confidence: 99%

A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund–Potsdam–Jena (LPJ) model as an example

Sun

2016

Theor Appl Climatol

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An important source of uncertainty, which causes further uncertainty in numerical simulations, is that residing in the parameters describing physical processes in numerical models. Therefore, finding a subset among numerous physical parameters in numerical models in the atmospheric and oceanic sciences, which are relatively more sensitive and important parameters, and reducing the errors in the physical parameters in this subset would be a far more efficient way to reduce the uncertainties involved in simulations. In this context, we present a new approach based on the conditional nonlinear optimal perturbation related to parameter (CNOP-P) method. The approach provides a framework to ascertain the subset of those relatively more sensitive and important parameters among the physical parameters. The Lund-Potsdam-Jena (LPJ) dynamical global vegetation model was utilized to test the validity of the new approach in China. The results imply that nonlinear interactions among parameters play a key role in the identification of sensitive parameters in arid and semiarid regions of China compared to those in northern, northeastern, and southern China. The uncertainties in the numerical simulations were reduced considerably by reducing the errors of the subset of relatively more sensitive and important parameters. The results demonstrate that our approach not only offers a new route to identify relatively more sensitive and important physical parameters but also that it is viable to then apply Btarget observations^to reduce the uncertainties in model parameters.

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Investigation of the predictability and physical mechanisms of an extreme-rainfall-producing mesoscale convective system along the Meiyu front in East China: An ensemble approach

Luo

Chen

2015

J. Geophys. Res. Atmos.

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Forecast uncertainties and physical mechanisms of a quasi-linear extreme-rain-producing mesoscale convective system (MCS) along the Meiyu front in East China, during the midnight-to-morning hours on 8 July 2007, are studied using ensembles of 24 h convection-permitting simulations with a nested grid spacing of 1.11 km. The simulations reveal a strong sensitivity to uncertainties in the initial state despite the synoptic environment being favorable for heavy rainfall production. Linear changes of a less skillful member's initial state toward that of a skillful member lead to a monotonic improvement in the precipitation simulation, with the most significant contribution arising from changes in the moisture field. Sensitivity to physics parameterizations representing subgrid-scale processes fail to account for the larger simulation errors (missing the MCS) with the physics variation examined but could result in a large spread in the location and amount of accumulative rainfall. A robust feature of the best-performing members that reasonably simulate the MCS-associated heavy rainfall is the presence of a cold dome ahead of the Meiyu front generated by previous convection. The cold dome promotes nocturnal convective initiation by lifting high equivalent potential temperature air in the southwesterly flow to its level of free convection. The skillful members reproduce the convective backbuilding and echo-band training processes that are observed during this event and many other heavy rainfall events over China. In contrast, the less skillful members that miss the development of the MCS either do not simulate the previous convection or produce a cold dome that is too shallow to initiate the MCS.

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Ensemble simulations with perturbed physical parametrizations: Pre-HyMeX case studies

Cited by 26 publications

References 42 publications

An ensemble study of HyMeX IOP6 and IOP7a: sensitivity to physical and initial and boundary condition uncertainties

An ensemble study of HyMeX IOP6 and IOP7a: sensitivity to physical and initial and boundary condition uncertainties

A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund–Potsdam–Jena (LPJ) model as an example

Investigation of the predictability and physical mechanisms of an extreme-rainfall-producing mesoscale convective system along the Meiyu front in East China: An ensemble approach

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