Verification of Convection-Allowing WRF Model Forecasts of the Planetary Boundary Layer Using Sounding Observations

Coniglio, Michael C.; Correia, James; Marsh, Patrick T.; Kong, Fanyou

doi:10.1175/waf-d-12-00103.1

Cited by 155 publications

(159 citation statements)

References 37 publications

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“…The YSU scheme is typically regarded as one of the better overall performers in intercomparison studies [Hu et al, 2010;Gibbs et al, 2011;Xie et al, 2012;Coniglio et al, 2013;Cohen et al, 2015], though we have done additional testing using five alternative schemes to evaluate how sensitive our results are to a given boundary layer formulation. While there is variability in the magnitude of moisture and temperature change as well as boundary layer height in each set of simulations, the day 1 processes that increase moisture flux into the lower free troposphere appear consistent across most schemes with the exception of MYJ (Fig.…”

Section: Sensitivity To Boundary Layer Schemementioning

confidence: 99%

“…While there is variability in the magnitude of moisture and temperature change as well as boundary layer height in each set of simulations, the day 1 processes that increase moisture flux into the lower free troposphere appear consistent across most schemes with the exception of MYJ (Fig. S7), which lacks a vertical moisture dipole, possibly because it under-predicts the boundary layer height and entrainment at the boundary layer top [e.g., Hu et al, 2010;Coniglio et al, 2013]. Over a 10-day timescale, all schemes produce a similar drying region along the northeastern coast of tropical South America, though the magnitude of increase over the Andes and western tropical South America varies (Fig.…”

Section: Sensitivity To Boundary Layer Schemementioning

confidence: 99%

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Why does Amazon precipitation decrease when tropical forests respond to increasing CO2?

Langenbrunner¹,

Pritchard²,

Kooperman³

et al. 2018

Preprint

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Key Points:• Increasing CO 2 over the Amazon causes a drier, warmer, and expanded boundary layer and reduces basin-wide rainfall within the first day • On synoptic timescales, enhanced lower free troposphere moisture is advected westward by the low-level jet, increasing Andean rainfall • A wetter Andes, dryer Amazon pattern is consistent across regional and global climate models and parameterized versus resolved convectionCorresponding author: Baird Langenbrunner, blangenb@uci.edu EarthArXiv PREPRINTEarthArXiv PREPRINT of confidential manuscript submitted to Earth's Future AbstractEarth system models predict a zonal dipole of precipitation change over tropical South America, with decreases over the Amazon and increases over the Andes. Much of this has been attributed to the physiological response of the rainforest to elevated CO 2 , which describes a basin-wide reduction in stomatal conductance and transpiration. While robust in Earth system model experiments, details of the underlying atmospheric mechanismspecifically how it evolves in the context of land-atmosphere interaction and the diurnal cycle-are unresolved. We investigate this using idealized model simulations and find that within 24 hours of a CO 2 increase, changes occur over the Amazon that engender synoptic timescale feedbacks. Decreased evapotranspiration from the rainforest throttles near-surface moisture, inducing a drier, warmer, and deeper boundary layer. Above this, enhanced turbulent diffusivity increases vapor in the lower free troposphere. Together, these processes reduce convective activity and cause immediate decreases in Amazon rainfall. Over the synoptic timescale, these changes leave behind lower tropospheric moisture, which is advected westward by the background jet and increases Andean precipitation. This produces a dipole of precipitation change consistent across global and regional models as well as parameterized and resolved convection, though details are sensitive to model topography and boundary layer formulation. The mechanism reported here stresses the importance of fast timescale processes affecting stability over a period of hours that can influence longer-term vegetation-climate interactions. These results help clarify the Amazon's physiological response to rising CO 2 and provide insight into possible causes of historical model biases and end-of-century uncertainty in this region.

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Section: Sensitivity To Boundary Layer Schemementioning

confidence: 99%

Section: Sensitivity To Boundary Layer Schemementioning

confidence: 99%

Why does Amazon precipitation decrease when tropical forests respond to increasing CO2?

Langenbrunner¹,

Pritchard²,

Kooperman³

et al. 2018

Preprint

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“…The PBL representation is a determinant factor in accurately simulating mesoscale weather phenomena owing to the critical role that these fluxes exert in the unfolding of severe phenomena. The choice of a PBL scheme can substantially affect temperature and moisture profiles in the lower troposphere and the effects of turbulence in daytime convective conditions (Hu et al 2010;Coniglio et al 2013).…”

Section: B Mps Experimentsmentioning

confidence: 99%

A Comparison of Ensemble Strategies for Flash Flood Forecasting: The 12 October 2007 Case Study in Valencia, Spain

Amengual

Carrió

Ravazzani

et al. 2017

Journal of Hydrometeorology

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On 12 October 2007, several flash floods affected the Valencia region, eastern Spain, with devastating impacts in terms of human, social, and economic losses. An enhanced modeling and forecasting of these extremes, which can provide a tangible basis for flood early warning procedures and mitigation measures over the Mediterranean, is one of the fundamental motivations of the international Hydrological Cycle in the Mediterranean Experiment (HyMeX) program. The predictability bounds set by multiple sources of hydrological and meteorological uncertainty require their explicit representation in hydrometeorological forecasting systems. By including local convective precipitation systems, short-range ensemble prediction systems (SREPSs) provide a state-of-the-art framework to generate quantitative discharge forecasts and to cope with different sources of external-scale (i.e., external to the hydrological system) uncertainties. The performance of three distinct hydrological ensemble prediction systems (HEPSs) for the small-sized Serpis River basin is examined as a support tool for early warning and mitigation strategies. To this end, the FlashFlood Event-Based Spatially Distributed Rainfall-Runoff Transformation-Water Balance (FEST-WB) model is driven by ground stations to examine the hydrological response of this semiarid and karstic catchment to heavy rains. The use of a multisite and novel calibration approach for the FEST-WB parameters is necessary to cope with the high nonlinearities emerging from the rainfall-runoff transformation and heterogeneities in the basin response. After calibration, FEST-WB reproduces with remarkable accuracy the hydrological response to intense precipitation and, in particular, the 12 October 2007 flash flood. Next, the flood predictability challenge is focused on quantitative precipitation forecasts (QPFs). In this regard, three SREPS generation strategies using the WRF Model are analyzed. On the one side, two SREPSs accounting for 1) uncertainties in the initial conditions (ICs) and lateral boundary conditions (LBCs) and 2) physical parameterizations are evaluated. An ensemble Kalman filter (EnKF) is also designed to test the ability of ensemble data assimilation methods to represent key mesoscale uncertainties from both IC and subscale processes. Results indicate that accounting for diversity in the physical parameterization schemes provides the best probabilistic high-resolution QPFs for this particular flash flood event. For low to moderate precipitation rates, EnKF and pure multiple physics approaches render undistinguishable accuracy for the test situation at larger scales. However, only the multiple physics QPFs properly drive the HEPS to render the most accurate flood warning signals. That is, extreme precipitation values produced by these convective-scale precipitation systems anchored by complex orography are better forecast when accounting just for uncertainties in the physical parameterizations. These findings contribute to the identification of ensemble strategies ...

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“…The PBL height has a rather large influence on boundary layer development and has received some attention (e.g. Gryning 11 and Coniglio et al 12 ). To the author's knowledge, no relevant work has focused on model validation of static stability across the PBL top and model performance in reproducing the inversion sharpness at the PBL top.…”

Section: Introductionmentioning

confidence: 99%

Offshore validation of a 3 km ERA‐Interim downscaling—WRF model's performance on static stability

Barstad

2015

Wind Energy

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In the evaluation of performance of numerical models, static stability has gained less interest and attention than many other atmospheric parameters. Nevertheless, this parameter may in fact have rather large implications as it controls such features as gravity waves and turbulence. In this paper, a closer look has been taken at the behavior of static stability in a 3 km gridded numerical downscaling of the ERA-Interim reanalysis. The simulation performed with the Weather Research and Forecasting model has been nudged towards large scale analysis (spectral nudging) and satellite-derived ocean surface winds (Quick Scatterometer). The validation of low-level static stability was conducted in the North Sea using data from the FINO1 mast for year 2008, and a deeper part of the atmosphere was validated using the Ekofisk oil platform radiosonde data for years [2007][2008][2009][2010]. The offshore mast comparison shows that the model over-predicts the number of unstable cases and that the unstable cases are not unstable enough. The model simulated a clear dependency between vertical wind shear and static stability; however, this was not the case in the observations. The model produced too few events with weak turbulence, but rather put the emphasis on intermediate turbulent intensities. With the radiosonde data measuring the static stability over a deeper part of the atmosphere, similar results as for lower levels showed. In addition, the temperature gradient across the inversion at the boundary layer top was too shallow in the model, potentially letting too much wave energy escape the boundary layer.

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Verification of Convection-Allowing WRF Model Forecasts of the Planetary Boundary Layer Using Sounding Observations

Cited by 155 publications

References 37 publications

Why does Amazon precipitation decrease when tropical forests respond to increasing CO2?

Why does Amazon precipitation decrease when tropical forests respond to increasing CO2?

A Comparison of Ensemble Strategies for Flash Flood Forecasting: The 12 October 2007 Case Study in Valencia, Spain

Offshore validation of a 3 km ERA‐Interim downscaling—WRF model's performance on static stability

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