Downscaling of a seasonal ensemble forecast at the convection-permitting resolution over the Horn of Africa using the WRF model

2021 ◽  
Author(s):  
Paolo Mori ◽  
Thomas Schwitalla ◽  
Markos Ware ◽  
Kirsten Warrach-Sagi ◽  
Volker Wulfmeyer
Keyword(s):  
Boundary Conditions ◽  
Wrf Model ◽  
Added Value ◽  
Limited Area ◽  
Horn Of Africa ◽  
Ensemble Spread ◽  
Rain Belt ◽  
Physics Ensemble ◽  
June July ◽  
The Right

<p>Studies have shown the benefits of convection-permitting downscaling at the seasonal scale using limited-area models. To evaluate the performance with real forecasts as boundary conditions, four members of the SEAS5 global ensemble were dynamically downscaled over Ethiopia during June, July, and August 2018 at a 3-km resolution. We used a multi‐physics ensemble based on the WRF model to compare the effects of boundary conditions and physics <span><span>parametrization</span></span> producing 16 ensemble members. With ECMWF analyses as a reference, SEAS5 averaged to a +0.17°C bias over Ethiopia whereas WRF resulted in +1.14°C. With respect to precipitation, the WRF model simulated 264 mm compared to 248 mm for SEAS5 and 236 mm for GPM-IMERG. The maximum northward extension of the tropical rain belt decreased by about 2° in both models. Downscaling enhanced the ensemble spread in precipitation by 60% on average, correcting the SEAS5 underdispersion. The WRF ensemble spread over Ethiopia was mostly generated by the perturbed boundary conditions, as their effect is often 50% larger than the physics‐induced variability. The results indicate that boundary condition perturbations are necessary, although not always sufficient, to generate the right amount of ensemble spread in a limited-area model with complex topography. The next step is to use specific methods to calculate the added value provided by the downscaling.</p>

scholarly journals Assessing and Improving the Local Added Value of WRF for Wind Downscaling

2015 ◽  
Vol 54 (7) ◽  
pp. 1556-1568 ◽  
Author(s):  
M. García-Díez ◽  
J. Fernández ◽  
D. San-Martín ◽  
S. Herrera ◽  
J. M. Gutiérrez
Keyword(s):  
General Circulation ◽  
Wrf Model ◽  
Value Added ◽  
Slight Modification ◽  
General Circulation Models ◽  
Added Value ◽  
Limited Area ◽  
Large Set ◽  
Skill Scores ◽  
Resolution Model

AbstractLimited area models (LAMs) are widely used tools to downscale the wind speed forecasts issued by general circulation models. However, only a few studies have systematically analyzed the value added by the LAMs to the coarser-resolution-model wind. The goal of the present work is to investigate how added value depends on the resolution of the driving global model. With this aim, the Weather Research and Forecasting (WRF) Model was used to downscale three different global datasets (GFS, ERA-Interim, and NCEP–NCAR) to a 9-km-resolution grid for a 1-yr period. Model results were compared with a large set of surface observations, including land station and offshore buoy data. Substantial biases were found at this resolution over mountainous terrain, and a slight modification to the subgrid orographic drag parameterization was introduced to alleviate the problem. It was found that, at this resolution, WRF is able to produce significant added value with respect to the NCEP–NCAR reanalysis and ERA-Interim but only a small amount of added value with respect to GFS forecasts. Results suggest that, as model resolution increases, traditional skill scores tend to saturate. Thus, adding value to high-resolution global models becomes significantly more difficult.

Surface Data Assimilation Using an Ensemble Kalman Filter Approach with Initial Condition and Model Physics Uncertainties

2007 ◽  
Vol 135 (5) ◽  
pp. 1846-1868 ◽  
Author(s):  
Tadashi Fujita ◽  
David J. Stensrud ◽  
David C. Dowell
Keyword(s):  
Kalman Filter ◽  
Boundary Conditions ◽  
Physical Process ◽  
Ensemble Kalman Filter ◽  
Severe Weather ◽  
Initial Condition ◽  
Ensemble Spread ◽  
Initial And Boundary Conditions ◽  
Physics Ensemble ◽  
Surface Observations

Abstract The assimilation of surface observations using an ensemble Kalman filter (EnKF) approach is evaluated for the potential to improve short-range forecasting. Two severe weather cases are examined, in which the assimilation is performed over a 6-h period using hourly surface observations followed by an 18-h simulation period. Ensembles are created in three different ways—by using different initial and boundary conditions, by using different model physical process schemes, and by using both different initial and boundary conditions and different model physical process schemes. The ensembles are compared in order to investigate the role of uncertainties in the initial and boundary conditions and physical process schemes in EnKF data assimilation. In the initial condition ensemble, spread is associated largely with the displacement of atmospheric baroclinic systems. In the physics ensemble, spread comes from the differences in model physics, which results in larger spread in temperature and dewpoint temperature than the initial condition ensemble, and smaller spread in the wind fields. The combined initial condition and physics ensemble has properties from both of the previous two ensembles. It provides the largest spread and produces the best simulation for most of the variables, in terms of the rms difference between the ensemble mean and observations. Perhaps most importantly, this combined ensemble provides very good guidance on the mesoscale features important to the severe weather events of the day.

scholarly journals Limited-are a modelling of stratocumulus over South-Eastern Pacific

2012 ◽  
Vol 12 (7) ◽  
pp. 3511-3526 ◽  
Author(s):  
M. Andrejczuk ◽  
W. W. Grabowski ◽  
A. Gadian ◽  
R. Burton
Keyword(s):  
Boundary Layer ◽  
Boundary Conditions ◽  
Vertical Velocity ◽  
Wrf Model ◽  
Eastern Pacific ◽  
Limited Area ◽  
Computational Domain ◽  
Lateral Boundary ◽  
South Eastern ◽  
Lateral Boundary Conditions

Abstract. This paper presents application of the Weather Research and Forecasting (WRF) model to limited-area modeling of atmospheric processes over the subtropical south-eastern Pacific, with the emphasis on the stratocumulus-topped boundary layer. The simulations cover a domain from the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) field project conducted in the subtropical south-eastern Pacific in October and November 2008. We focus on a day where the UK's BAe-146 research aircraft encountered Pockets of Open Cells (POCs) at the very western edge of its flight track, rather than on the entire campaign as investigated in previous limited-area modeling studies. Model results are compared to aircraft observations with the main conclusion that the simulated stratocumulus-topped boundary layer is significantly too shallow. This appears to be a combination of an already too shallow boundary layer in the dataset used to provide initial and lateral boundary conditions, and the inability of the WRF model to increase the boundary-layer height. Several sensitivity simulations, applying different subgrid-scale parameterizations available in the model, a larger computational domain and longer simulations, as well as a different dataset providing initial and lateral boundary conditions were all tried to improve the simulation. These changes appeared to have a rather small effect on the results. The model does simulate the formation of mesoscale cloud-free regions that one might consider similar to Pockets of Open Cells observed in nature. However, formation of these regions does not seem to be related to drizzle-induced transition from open- to closed-cell circulations as simulated by LES models. Instead, the cloud-free regions appear to result from mesoscale variations of the lower-tropspheric vertical velocity. Areas of negative vertical velocity with minima (a few cm s−1) near the boundary layer top seem to induce direct evaporation of the cloud layer. It remains to be seen in LES studies whether the mechanism seen in the model is realistic or if it is simply an artifact of interactions between resolved and parameterized processes.

scholarly journals Calibration of a multi-physics ensemble for greenhouse gas atmospheric transport model uncertainty estimation

2018 ◽  
Author(s):  
Liza I. Díaz-Isaac ◽  
Thomas Lauvaux ◽  
Marc Bocquet ◽  
Kenneth J. Davis
Keyword(s):  
Boundary Conditions ◽  
Land Surface ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Wrf Model ◽  
Meteorological Variables ◽  
Multiple Model ◽  
Optimal Ensemble ◽  
Physics Ensemble ◽  
The Impact

Abstract. Atmospheric inversions have been used to assess biosphere-atmosphere CO2 surface exchanges at various scales, but variability among inverse flux estimates remains significant, especially at continental scales. Atmospheric transport errors are one of the main contributors to this variability. To characterize transport errors and their spatio-temporal structures, we present an objective method to generate a calibrated ensemble adjusted with meteorological measurements collected across a region, here the US upper Midwest in midsummer. Using multiple model configurations of the Weather Research and Forecasting (WRF) model, we show that a reduced number of simulations (less than 10 members) reproduces the transport error characteristics of a 45-member ensemble while minimizing the size of the ensemble. The large ensemble of 45-members was constructed using different physics parameterization (i.e., land surface models (LSMs), planetary boundary layer (PBL) schemes, cumulus parameterizations and microphysics parameterizations) and meteorological initial/boundary conditions. All the different models were coupled to CO2 fluxes and lateral boundary conditions from CarbonTracker to simulate CO2 mole fractions. Meteorological variables critical to inverse flux estimates, PBL wind speed, PBL wind direction and PBL height, are used to calibrate our ensemble over the region. Two calibration techniques (i.e., simulated annealing and a genetic algorithm) are used for the selection of the optimal ensemble using the flatness of the rank histograms as the main criterion. We also choose model configurations that minimize the systematic errors (i.e. monthly biases) in the ensemble. We evaluate the impact of transport errors on atmospheric CO2 mole fraction to represent up to 40 % of the model-data mismatch (fraction of the total variance). We conclude that a carefully-chosen subset of the physics ensemble can represent the errors in the full ensemble, and that transport ensembles calibrated with relevant meteorological variables provide a promising path forward for improving the treatment of transport errors in atmospheric inverse flux estimates.

scholarly journals Boundary Conditions for Limited-Area Ensemble Kalman Filters

2006 ◽  
Vol 134 (9) ◽  
pp. 2490-2502 ◽  
Author(s):  
Ryan D. Torn ◽  
Gregory J. Hakim ◽  
Chris Snyder
Keyword(s):  
Boundary Condition ◽  
Boundary Conditions ◽  
Prediction Models ◽  
Domain Boundary ◽  
Weather Prediction ◽  
Wrf Model ◽  
Limited Area ◽  
Ensemble Kalman Filters ◽  
Low Dimensional ◽  
Random Draw

Abstract One aspect of implementing a limited-area ensemble Kalman filter (EnKF) involves the specification of a suitable ensemble of lateral boundary conditions. Two classes of methods to populate a boundary condition ensemble are proposed. In the first class, the ensemble of boundary conditions is provided by an EnKF on a larger domain and is approximately a random draw from the probability distribution function for the forecast (or analysis) on the limited-area domain boundary. The second class perturbs around a deterministic estimate of the state using assumed spatial and temporal covariance relationships. Methods in the second class are relatively flexible and easy to implement. Experiments that test the utility of these methods are performed for both an idealized low-dimensional model and limited-area simulations using the Weather Research and Forecasting (WRF) model; all experiments employ simulated observations under the perfect model assumption. The performance of the ensemble boundary condition methods is assessed by comparing the results of each experiment against a control “global” EnKF that extends beyond the limited-area domain. For all methods tested, results show that errors for the limited-area EnKF are larger near the lateral boundaries than those from a control EnKF, but decay inside the limited-area domain so that errors there are comparable to the control case. The relatively larger errors near the boundaries in the limited-area EnKF originate from not assimilating observations outside the limited-area domain and, in the second class of methods, from deficiencies in boundary spatial and temporal covariances. Overall, these experiments suggest that for observation densities typical in numerical weather prediction models, ensemble boundary conditions can be specified in the absence of a global ensemble without significant penalty in the domain interior by perturbing around an ensemble mean.

scholarly journals Downscaling of seasonal ensemble forecasts to the convection‐permitting scale over the Horn of Africa using the WRF model

2020 ◽  
Author(s):  
Paolo Mori ◽  
Thomas Schwitalla ◽  
Markos Budusa Ware ◽  
Kirsten Warrach‐Sagi ◽  
Volker Wulfmeyer
Keyword(s):  
Wrf Model ◽  
Horn Of Africa ◽  
Ensemble Forecasts

scholarly journals Assimilating X- and S-Band Radar Data for a Heavy Precipitation Event in Italy

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1727
Author(s):  
Valerio Capecchi ◽  
Andrea Antonini ◽  
Riccardo Benedetti ◽  
Luca Fibbi ◽  
Samantha Melani ◽  
...  
Keyword(s):  
Extreme Event ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Radar Data ◽  
Flash Floods ◽  
Precipitation Event ◽  
Weather Research And Forecasting ◽  
Limited Area ◽  
Heavy Precipitation Event ◽  
The Town

During the night between 9 and 10 September 2017, multiple flash floods associated with a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours was recorded. This rainfall intensity is associated with a return period of higher than 200 years. As a consequence, all the largest streams of the Livorno municipality flooded several areas of the town. We used the limited-area weather research and forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. A more accurate description of the low-level flows and a better assessment of the atmospheric water vapor field showed how the assimilation of radar data can improve quantitative precipitation forecasts.

On Fourier Series in Eigenfunctions of Elliptic Boundary Value Problems

2003 ◽  
Vol 10 (3) ◽  
pp. 401-410
Author(s):  
M. S. Agranovich ◽  
B. A. Amosov
Keyword(s):  
Fourier Series ◽  
Boundary Conditions ◽  
Fourier Coefficients ◽  
Elliptic Boundary ◽  
A Priori ◽  
Adjoint Problem ◽  
Elliptic Boundary Value ◽  
Right Hand ◽  
The Difference ◽  
The Right

Abstract We consider a general elliptic formally self-adjoint problem in a bounded domain with homogeneous boundary conditions under the assumption that the boundary and coefficients are infinitely smooth. The operator in 𝐿2(Ω) corresponding to this problem has an orthonormal basis {𝑢𝑙} of eigenfunctions, which are infinitely smooth in . However, the system {𝑢𝑙} is not a basis in Sobolev spaces 𝐻𝑡 (Ω) of high order. We note and discuss the following possibility: for an arbitrarily large 𝑡, for each function 𝑢 ∈ 𝐻𝑡 (Ω) one can explicitly construct a function 𝑢0 ∈ 𝐻𝑡 (Ω) such that the Fourier series of the difference 𝑢 – 𝑢0 in the functions 𝑢𝑙 converges to this difference in 𝐻𝑡 (Ω). Moreover, the function 𝑢(𝑥) is viewed as a solution of the corresponding nonhomogeneous elliptic problem and is not assumed to be known a priori; only the right-hand sides of the elliptic equation and the boundary conditions for 𝑢 are assumed to be given. These data are also sufficient for the computation of the Fourier coefficients of 𝑢 – 𝑢0. The function 𝑢0 is obtained by applying some linear operator to these right-hand sides.

A parameterization of slantwise convection in the WRF model

2021 ◽  
Author(s):  
Ting-Chen Chen ◽  
Man-Kong Yau ◽  
Daniel J. Kirshbaum
Keyword(s):  
General Circulation ◽  
Wrf Model ◽  
Real Data ◽  
General Circulation Models ◽  
Added Value ◽  
Cumulus Parameterization ◽  
Moisture Loss ◽  
Precipitation Event ◽  
Cyclonic Storm ◽  
Slantwise Convection

Abstract In this study, we introduce a parameterization scheme for slantwise convection (SC) to be considered for models that are too coarse to resolve slantwise convection explicitly (with a horizontal grid spacing coarser than 15 km or less). This SC scheme operates in a locally defined 2D cross-section perpendicular to the deep-layer-averaged thermal wind. It applies momentum tendency to adjust the environment toward slantwise neutrality with a prescribed adjustment timescale. Condensational heating and the associated moisture loss are also considered. To evaluate the added value of the SC scheme, we implement it in the Weather Research and Forecasting (WRF) model to supplement the existing cumulus parameterization schemes for upright convection and test for two different numerical setups: a 2D idealized, unforced release of conditional symmetric instability (CSI) in an initially conditionally stable environment, and a 3D real-data precipitation event containing both CSI and conditional instability along the cold front of a cyclonic storm near the UK. Both test cases show significant improvements for the coarse-gridded (40-km) simulations when parameterizing slantwise convection. Compared to the 40-km simulations with only the upright convection scheme, the counterparts with the additional SC scheme exhibit a larger extent of CSI neutralization, generate a stronger grid-resolved slantwise circulation, and produce greater amounts of precipitation, all in better agreement with the corresponding fine-gridded reference simulations. Given the importance of slantwise convection in midlatitude weather systems, our results suggest that there exist potential benefits of parameterizing slantwise convection in general circulation models.

scholarly journals The forecaster's added value in QPF

2010 ◽  
Vol 25 ◽  
pp. 29-36 ◽  
Author(s):  
M. Turco ◽  
M. Milelli
Keyword(s):  
Hypothesis Test ◽  
Bootstrap Method ◽  
Decision Makers ◽  
Added Value ◽  
Precipitation Forecast ◽  
Limited Area ◽  
Alert System ◽  
Skill Scores ◽  
Global Telecommunication System ◽  
Meteorological Models

Abstract. To the authors' knowledge there are relatively few studies that try to answer this question: "Are humans able to add value to computer-generated forecasts and warnings?". Moreover, the answers are not always positive. In particular some postprocessing method is competitive or superior to human forecast. Within the alert system of ARPA Piemonte it is possible to study in an objective manner if the human forecaster is able to add value with respect to computer-generated forecasts. Every day the meteorology group of the Centro Funzionale of Regione Piemonte produces the HQPF (Human Quantitative Precipitation Forecast) in terms of an areal average and maximum value for each of the 13 warning areas, which have been created according to meteo-hydrological criteria. This allows the decision makers to produce an evaluation of the expected effects by comparing these HQPFs with predefined rainfall thresholds. Another important ingredient in this study is the very dense non-GTS (Global Telecommunication System) network of rain gauges available that makes possible a high resolution verification. In this work we compare the performances of the latest three years of QPF derived from the meteorological models COSMO-I7 (the Italian version of the COSMO Model, a mesoscale model developed in the framework of the COSMO Consortium) and IFS (the ECMWF global model) with the HQPF. In this analysis it is possible to introduce the hypothesis test developed by Hamill (1999), in which a confidence interval is calculated with the bootstrap method in order to establish the real difference between the skill scores of two competitive forecasts. It is important to underline that the conclusions refer to the analysis of the Piemonte operational alert system, so they cannot be directly taken as universally true. But we think that some of the main lessons that can be derived from this study could be useful for the meteorological community. In details, the main conclusions are the following: – despite the overall improvement in global scale and the fact that the resolution of the limited area models has increased considerably over recent years, the QPF produced by the meteorological models involved in this study has not improved enough to allow its direct use: the subjective HQPF continues to offer the best performance for the period +24 h/+48 h (i.e. the warning period in the Piemonte system); – in the forecast process, the step where humans have the largest added value with respect to mathematical models, is the communication. In fact the human characterization and communication of the forecast uncertainty to end users cannot be replaced by any computer code; – eventually, although there is no novelty in this study, we would like to show that the correct application of appropriated statistical techniques permits a better definition and quantification of the errors and, mostly important, allows a correct (unbiased) communication between forecasters and decision makers.

Sign in / Sign up

Export Citation Format

Share Document