scholarly journals Practical and Intrinsic Predictability of Multiscale Weather and Convectively Coupled Equatorial Waves during the Active Phase of an MJO

2017 ◽  
Vol 74 (11) ◽  
pp. 3771-3785 ◽  
Author(s):  
Yue Ying ◽  
Fuqing Zhang
Keyword(s):  
Regional Scale ◽  
Wrf Model ◽  
Active Phase ◽  
Weather Research And Forecasting ◽  
Equatorial Waves ◽  
Convectively Coupled Equatorial Waves ◽  
Order Of Magnitude ◽  
The Indian Ocean ◽  
Tropical Weather ◽  
Boundary Perturbations

Abstract Through a series of convection-permitting regional-scale ensembles based on the Weather Research and Forecasting (WRF) Model, this study investigates the predictability of multiscale weather and convectively coupled equatorial waves during the active phase of a Madden–Julian oscillation (MJO) event over the Indian Ocean from 12 October to 12 November 2011. It is found that the practical predictability limit, estimated by the spread of the ensemble perturbed with realistic initial and boundary uncertainties, is as much as 8 days for horizontal winds, temperature, and humidity for scales larger than 2000 km that include equatorial Rossby, Kelvin, inertia–gravity, and mixed Rossby–gravity waves. The practical predictability limit decreases rapidly as scale decreases, resulting in a predictable time scale less than 1 day for scales smaller than 200 km. Through further experiments using minute initial and boundary perturbations an order of magnitude smaller than the current realistic uncertainties, the intrinsic predictability limit for tropical weather at larger scales (>2000 km) is estimated to be achievable beyond 2 weeks, but the limit is likely still less than 3 days for the small scales (<200 km).

scholarly journals CORDEX-WRF v1.3: development of a module for the Weather Research and Forecasting (WRF) model to support the CORDEX community

2019 ◽  
Vol 12 (3) ◽  
pp. 1029-1066 ◽  
Author(s):  
Lluís Fita ◽  
Jan Polcher ◽  
Theodore M. Giannaros ◽  
Torge Lorenz ◽  
Josipa Milovac ◽  
...  
Keyword(s):  
Regional Climate ◽  
Regional Scale ◽  
Wrf Model ◽  
Data Access ◽  
Quality Data ◽  
Weather Research And Forecasting ◽  
Time Step ◽  
Mitigation And Adaptation ◽  
Data Requirements ◽  
Weather Research

Abstract. The Coordinated Regional Climate Downscaling Experiment (CORDEX) is a scientific effort of the World Climate Research Program (WRCP) for the coordination of regional climate initiatives. In order to accept an experiment, CORDEX provides experiment guidelines, specifications of regional domains, and data access and archiving. CORDEX experiments are important to study climate at the regional scale, and at the same time, they also have a very prominent role in providing regional climate data of high quality. Data requirements are intended to cover all the possible needs of stakeholders and scientists working on climate change mitigation and adaptation policies in various scientific communities. The required data and diagnostics are grouped into different levels of frequency and priority, and some of them even have to be provided as statistics (minimum, maximum, mean) over different time periods. Most commonly, scientists need to post-process the raw output of regional climate models, since the latter was not originally designed to meet the specific CORDEX data requirements. This post-processing procedure includes the computation of diagnostics, statistics, and final homogenization of the data, which is often computationally costly and time-consuming. Therefore, the development of specialized software and/or code is required. The current paper presents the development of a specialized module (version 1.3) for the Weather Research and Forecasting (WRF) model capable of outputting the required CORDEX variables. Additional diagnostic variables not required by CORDEX, but of potential interest to the regional climate modeling community, are also included in the module. “Generic” definitions of variables are adopted in order to overcome the model and/or physics parameterization dependence of certain diagnostics and variables, thus facilitating a robust comparison among simulations. The module is computationally optimized, and the output is divided into different priority levels following CORDEX specifications (Core, Tier 1, and additional) by selecting pre-compilation flags. This implementation of the module does not add a significant extra cost when running the model; for example, the addition of the Core variables slows the model time step by less than a 5 %. The use of the module reduces the requirements of disk storage by about a 50 %. The module performs neither additional statistics over different periods of time nor homogenization of the output data.

scholarly journals CO2 Transport, Variability, and Budget over the Southern California Air Basin Using the High-Resolution WRF-VPRM Model during the CalNex 2010 Campaign

2018 ◽  
Vol 57 (6) ◽  
pp. 1337-1352 ◽  
Author(s):  
Changhyoun Park ◽  
Christoph Gerbig ◽  
Sally Newman ◽  
Ravan Ahmadov ◽  
Sha Feng ◽  
...  
Keyword(s):  
Los Angeles ◽  
Southern California ◽  
Regional Scale ◽  
Wrf Model ◽  
Net Ecosystem Exchange ◽  
Weather Research And Forecasting ◽  
California Institute Of Technology ◽  
Vegetation Class ◽  
Institute Of Technology ◽  
Photosynthesis And Respiration

AbstractTo study regional-scale carbon dioxide (CO2) transport, temporal variability, and budget over the Southern California Air Basin (SoCAB) during the California Research at the Nexus of Air Quality and Climate Change (CalNex) 2010 campaign period, a model that couples the Weather Research and Forecasting (WRF) Model with the Vegetation Photosynthesis and Respiration Model (VPRM) has been used. Our numerical simulations use anthropogenic CO2 emissions of the Hestia Project 2010 fossil-fuel CO2 emissions data products along with optimized VPRM parameters at “FLUXNET” sites, for biospheric CO2 fluxes over SoCAB. The simulated meteorological conditions have been validated with ground and aircraft observations, as well as with background CO2 concentrations from the coastal Palos Verdes site. The model captures the temporal pattern of CO2 concentrations at the ground site at the California Institute of Technology in Pasadena, but it overestimates the magnitude in early daytime. Analysis of CO2 by wind directions reveals the overestimate is due to advection from the south and southwest, where downtown Los Angeles is located. The model also captures the vertical profile of CO2 concentrations along with the flight tracks. The optimized VPRM parameters have significantly improved simulated net ecosystem exchange at each vegetation-class site and thus the regional CO2 budget. The total biospheric contribution ranges approximately from −24% to −20% (daytime) of the total anthropogenic CO2 emissions during the study period.

scholarly journals Influence of Bulk Microphysics Schemes upon Weather Research and Forecasting (WRF) Version 3.6.1 Nor'easter Simulations

2016 ◽  
Author(s):  
Stephen D. Nicholls ◽  
Steven G. Decker ◽  
Wei-Kuo Tao ◽  
Stephen E. Lang ◽  
Jainn J. Shi ◽  
...  
Keyword(s):  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Large Variability ◽  
Mixing Ratios ◽  
Simulated Precipitation ◽  
Single Moment ◽  
Double Moment ◽  
Order Of Magnitude ◽  
The Impact ◽  
Weather Research

Abstract. This study evaluated the impact of five, single- or double- moment bulk microphysics schemes (BMPS) on Weather Research and Forecasting (WRF) model (version 3.6.1) winter storm simulations. Model simulations were integrated for 180 hours, starting 72 hours prior to the first measurable precipitation in the highly populated Mid-Atlantic U.S. Simulated precipitation fields were well-matched to precipitation products. However, total accumulations tended to be over biased (1.10–2.10) and exhibited low-to-moderate threat scores (0.27–0.59). Non-frozen hydrometeor species from single-moment BMPS produced similar mixing ratio profiles and maximum saturation levels due to a common parameterization heritage. Greater variability occurred with frozen microphysical species due to varying assumptions among BMPSs regarding ice supersaturation amounts, the dry collection of snow by graupel, various ice collection efficiencies, snow and graupel density and size mappings/intercept parameters, and hydrometeor terminal velocities. The addition of double-moment rain and cloud water resulted in minimal change to species spatial extent or maximum saturation level, however rain mixing ratios tended higher. Although hydrometeor differences varied by up to an order of magnitude among the BMPSs, similarly large variability was not upscaled to mesoscale and synoptic scales.

scholarly journals Dynamics and Predictability of Hurricane Nadine (2012) Evaluated through Convection-Permitting Ensemble Analysis and Forecasts

2015 ◽  
Vol 143 (11) ◽  
pp. 4514-4532 ◽  
Author(s):  
Erin B. Munsell ◽  
Jason A. Sippel ◽  
Scott A. Braun ◽  
Yonghui Weng ◽  
Fuqing Zhang
Keyword(s):  
Ensemble Kalman Filter ◽  
Regional Scale ◽  
Wrf Model ◽  
Heat Fluxes ◽  
Sensitivity Analyses ◽  
Weather Research And Forecasting ◽  
Sensitivity Experiment ◽  
Steering Flow ◽  
General Success ◽  
Initial Intensity

Abstract The governing dynamics and uncertainties of an ensemble simulation of Hurricane Nadine (2012) are assessed through the use of a regional-scale convection-permitting analysis and forecast system based on the Weather Research and Forecasting (WRF) Model and an ensemble Kalman filter (EnKF). For this case, the data that are utilized were collected during the 2012 phase of the National Aeronautics and Space Administration’s (NASA) Hurricane and Severe Storm Sentinel (HS3) experiment. The majority of the tracks of this ensemble were successful, correctly predicting Nadine’s turn toward the southwest ahead of an approaching midlatitude trough, though 10 members forecasted Nadine to be carried eastward by the trough. Ensemble composite and sensitivity analyses reveal the track divergence to be caused by differences in the environmental steering flow that resulted from uncertainties associated with the position and subsequent strength of a midlatitude trough. Despite the general success of the ensemble track forecasts, the intensity forecasts indicated that Nadine would strengthen, which did not happen. A sensitivity experiment performed with the inclusion of sea surface temperature (SST) updates significantly reduced the intensity errors associated with the simulation. This weakening occurred as a result of cooling of the SST field in the vicinity of Nadine, which led to weaker surface sensible and latent heat fluxes at the air–sea interface. A comparison of environmental variables, including relative humidity, temperature, and shear yielded no obvious differences between the WRF-EnKF simulations and the HS3 observations. However, an initial intensity bias in which the WRF-EnKF vortices are stronger than the observed vortex appears to be the most likely cause of the final intensity errors.

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.

scholarly journals Relationship between the Track and Structural Evolution of Hurricane Sandy (2012) Using a Regional Ensemble

2018 ◽  
Vol 146 (12) ◽  
pp. 4279-4302 ◽  
Author(s):  
Alex M. Kowaleski ◽  
Jenni L. Evans
Keyword(s):  
Large Scale ◽  
Wrf Model ◽  
Structural Evolution ◽  
Hurricane Sandy ◽  
Weather Research And Forecasting ◽  
Extratropical Transition ◽  
Ensemble Forecasts ◽  
High Predictability ◽  
Regression Mixture ◽  
The Relationship

Abstract An ensemble of 72 Weather Research and Forecasting (WRF) Model simulations is evaluated to examine the relationship between the track of Hurricane Sandy (2012) and its structural evolution. Initial and boundary conditions are obtained from ECMWF and GEFS ensemble forecasts initialized at 0000 UTC 25 October. The 5-day WRF simulations are initialized at 0000 UTC 27 October, 48 h into the global model forecasts. Tracks and cyclone phase space (CPS) paths from the 72 simulations are partitioned into 6 clusters using regression mixture models; results from the 4 most populous track clusters are examined. The four analyzed clusters vary in mean landfall location from southern New Jersey to Maine. Extratropical transition timing is the clearest difference among clusters; more eastward clusters show later Sandy–midlatitude trough interaction, warm seclusion formation, and extratropical transition completion. However, the intercluster variability is much smaller when examined relative to the landfall time of each simulation. In each cluster, a short-lived warm seclusion forms and contracts through landfall while lower-tropospheric potential vorticity concentrates at small radii. Despite the large-scale similarity among the clusters, relevant intercluster differences in landfall-relative extratropical transition are observed. In the easternmost cluster the Sandy–trough interaction is least intense and the warm seclusion decays the most by landfall. In the second most eastward cluster Sandy retains the most intact warm seclusion at landfall because of a slightly later (relative to landfall) and weaker trough interaction compared to the two most westward clusters. Nevertheless, the remarkably similar large-scale evolution of Sandy among the four clusters indicates the high predictability of Sandy’s warm seclusion extratropical transition before landfall.

scholarly journals Sources of Tropical Subseasonal Skill in the CFSv2

2020 ◽  
Vol 148 (4) ◽  
pp. 1553-1565 ◽  
Author(s):  
Carl J. Schreck ◽  
Matthew A. Janiga ◽  
Stephen Baxter
Keyword(s):  
Indian Ocean ◽  
Low Frequency ◽  
Equatorial Pacific ◽  
Convectively Coupled Equatorial Waves ◽  
Subseasonal Variability ◽  
The Pacific ◽  
Fourier Filtering ◽  
The Indian Ocean ◽  
Rainfall Anomalies ◽  
Combined Data

Abstract This study applies Fourier filtering to a combination of rainfall estimates from TRMM and forecasts from the CFSv2. The combined data are filtered for low-frequency (LF, ≥120 days) variability, the MJO, and convectively coupled equatorial waves. The filtering provides insight into the sources of skill for the CFSv2. The LF filter, which encapsulates persistent anomalies generally corresponding with SSTs, has the largest contribution to forecast skill beyond week 2. Variability within the equatorial Pacific is dominated by its response to ENSO, such that both the unfiltered and the LF-filtered forecasts are skillful over the Pacific through the entire 45-day CFSv2 forecast. In fact, the LF forecasts in that region are more skillful than the unfiltered forecasts or any combination of the filters. Verifying filtered against unfiltered observations shows that subseasonal variability has very little opportunity to contribute to skill over the equatorial Pacific. Any subseasonal variability produced by the model is actually detracting from the skill there. The MJO primarily contributes to CFSv2 skill over the Indian Ocean, particularly during March–May and MJO phases 2–5. However, the model misses opportunities for the MJO to contribute to skill in other regions. Convectively coupled equatorial Rossby waves contribute to skill over the Indian Ocean during December–February and the Atlantic Ocean during September–November. Convectively coupled Kelvin waves show limited potential skill for predicting weekly averaged rainfall anomalies since they explain a relatively small percent of the observed variability.

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