1,539 research outputs found
Efficient dynamical downscaling of general circulation models using continuous data assimilation
Continuous data assimilation (CDA) is successfully implemented for the first
time for efficient dynamical downscaling of a global atmospheric reanalysis. A
comparison of the performance of CDA with the standard grid and spectral
nudging techniques for representing long- and short-scale features in the
downscaled fields using the Weather Research and Forecast (WRF) model is
further presented and analyzed. The WRF model is configured at 25km horizontal
resolution and is driven by 250km initial and boundary conditions from
NCEP/NCAR reanalysis fields. Downscaling experiments are performed over a
one-month period in January, 2016. The similarity metric is used to evaluate
the performance of the downscaling methods for large and small scales.
Similarity results are compared for the outputs of the WRF model with different
downscaling techniques, NCEP reanalysis, and Final Analysis. Both spectral
nudging and CDA describe better the small-scale features compared to grid
nudging. The choice of the wave number is critical in spectral nudging;
increasing the number of retained frequencies generally produced better
small-scale features, but only up to a certain threshold after which its
solution gradually became closer to grid nudging. CDA maintains the balance of
the large- and small-scale features similar to that of the best simulation
achieved by the best spectral nudging configuration, without the need of a
spectral decomposition. The different downscaled atmospheric variables,
including rainfall distribution, with CDA is most consistent with the
observations. The Brier skill score values further indicate that the added
value of CDA is distributed over the entire model domain. The overall results
clearly suggest that CDA provides an efficient new approach for dynamical
downscaling by maintaining better balance between the global model and the
downscaled fields
Data Assimilation in high resolution Numerical Weather Prediction models to improve forecast skill of extreme hydrometeorological events.
The complex orography typical of the Mediterranean area supports the
formation, mainly during the fall season, of the so-called back-building
Mesoscale Convective Systems (MCS) producing torrential rainfall often
resulting into flash floods. These events are hardly predictable from a hydrometeorological
standpoint and may cause significant amount of fatalities and
socio-economic damages. Liguria region is characterized by small catchments
with very short hydrological response time, and it has been proven to be very
exposed to back-building MCSs occurrence. Indeed this region between 2011
and 2014 has been hit by three intense back-building MCSs causing a total
death toll of 20 people and several hundred million of euros of damages.
Building on the existing relationship between significant lightning activity and
deep convection and precipitation, the first part of this work assesses the
performance of the Lightning Potential Index, as a measure of the potential for
charge generation and separation that leads to lightning occurrence in clouds,
for the back-building Mesoscale Convective System which hit Genoa city (Italy)
in 2014. An ensemble of Weather Research and Forecasting simulations at
cloud-permitting grid spacing (1 km) with different microphysical
parameterizations is performed and compared to the available observational
radar and lightning data. The results allow gaining a deeper understanding of
the role of lightning phenomena in the predictability of back-building Mesoscale
Convective Systems often producing flash flood over western Mediterranean
complex topography areas. Despite these positive and promising outcomes for
the understanding highly-impacting MCS, the main forecasting issue, namely
the uncertainty in the correct reproduction of the convective field (location,
timing, and intensity) for this kind of events still remains open. Thus, the second
part of the work assesses the predictive capability, for a set of back-building
Liguria MCS episodes (including Genoa 2014), of a hydro-meteorological
forecasting chain composed by a km-scale cloud resolving WRF model,
including a 6 hour cycling 3DVAR assimilation of radar reflectivity and
conventional ground sensors data, by the Rainfall Filtered Autoregressive
Model (RainFARM) and the fully distributed hydrological model Continuum. A
rich portfolio of WRF 3DVAR direct and indirect reflectivity operators, has been
explored to drive the meteorological component of the proposed forecasting
chain. The results confirm the importance of rapidly refreshing and data
intensive 3DVAR for improving first quantitative precipitation forecast, and,
subsequently flash-floods occurrence prediction in case of back-building MCSs
events. The third part of this work devoted the improvement of severe hydrometeorological
events prediction has been undertaken in the framework of the
European Space Agency (ESA) STEAM (SaTellite Earth observation for
Atmospheric Modelling) project aiming at investigating, new areas of synergy
between high-resolution numerical atmosphere models and data from
spaceborne remote sensing sensors, with focus on Copernicus Sentinels 1, 2
and 3 satellites and Global Positioning System stations. In this context, the
Copernicus Sentinel satellites represent an important source of data, because
they provide a set of high-resolution observations of physical variables (e.g. soil
moisture, land/sea surface temperature, wind speed, columnar water vapor) to
be used in NWP models runs operated at cloud resolving grid spacing . For this
project two different use cases are analyzed: the Livorno flash flood of 9 Sept
2017, with a death tool of 9 people, and the Silvi Marina flood of 15 November
2017. Overall the results show an improvement of the forecast accuracy by
assimilating the Sentinel-1 derived wind and soil moisture products as well as
the Zenith Total Delay assimilation both from GPS stations and SAR
Interferometry technique applied to Sentinel-1 data
Storm microphysics and kinematics at the ARM-SGP site using dual polarized radar observations at multiple frequencies
2014 Fall.Includes bibliographical references.This research utilizes observations from the Atmospheric Radiation Measurement (ARM) Climate Research Facility at the Southern Great Plains location to investigate the kinematic and microphysical processes present in various types of weather systems. The majority of the data used was collected during the Mid-latitude Continental Convective Cloud Experiment (MC3E), and utilizes the network of scanning radars to arrive at a multi-Doppler wind retrieval and is compared to vertical wind measurements from a centrally located profiling radar. Microphysical compositions of the storms are analyzed using a multi-wavelength hydrometeor identification algorithm utilizing the strengths of each of the radar wavelengths available (X, C, S). When available, a comparison is done between observational analysis and simulated model output from the Weather Research Forecasting model with Spectral-bin Microphysics (WRF-SBM) using bulk statistics to look at reflectivity, vertical motions, and microphysics
WRF-Model Data Assimilation Studies of Landfalling Atmospheric Rivers and Orographic Precipitation Over Northern California
In this study, data assimilation methods of 3-D variational analysis (3DVAR), observation nudging, and analysis (grid) nudging were evaluated in the Weather Research and Forecasting (WRF) model for a high-impact, multi-episode landfalling atmospheric river (AR) event for Northern California from 28 November to 3 December, 2012. Eight experiments were designed to explore various combinations of the data assimilation methods and different initial conditions. The short-to-medium range quantitative precipitation forecast (QPF) performances were tested for each experiment. Surface observations from the National Oceanic and Atmospheric Administration\u27s (NOAA) Hydrometeorology Network (HMT), National Weather Service (NWS) radiosondes, and GPS Radio Occultation (RO) vertical profiles from the Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) satellites were used for assimilation. Model results 2.5 days into the forecast showed slower timing of the 2nd AR episode by a few hours and an underestimation in AR strength. For the entire event forecasts, the non-grid-nudging experiments showed the lowest mean absolute error (MAE) for rainfall accumulations, especially those with 3DVAR. Higher-resolution initial conditions showed more realistic coastal QPFs. Also, a 3-h nudging time interval and time window for observation nudging and 3DVAR, respectively, may be too large for this type of event, and it did not show skill until 60-66 h into the forecast
Simulating aerosol–radiation–cloud feedbacks on meteorology and air quality over eastern China under severe haze conditionsin winter
The aerosol-radiation-cloud feedbacks on meteorology and air quality over
eastern China under severe winter haze conditions in January 2013 are
simulated using the fully coupled online Weather Research and
Forecasting/Chemistry (WRF-Chem) model. Three simulation scenarios including
different aerosol configurations are undertaken to distinguish the aerosol's
radiative (direct and semi-direct) and indirect effects. Simulated spatial
and temporal variations of PM2.5 are generally consistent with surface
observations, with a mean bias of −18.9 μg m−3 (−15.0%)
averaged over 71 big cities in China. Comparisons between different
scenarios reveal that aerosol radiative effects (direct effect and
semi-direct effects) result in reductions of downward shortwave flux at the
surface, 2 m temperature, 10 m wind speed and planetary boundary layer (PBL)
height by up to 84.0 W m−2, 3.2°C, 0.8 m s−1, and 268 m,
respectively. The simulated impact of the aerosol indirect effects is
comparatively smaller. Through reducing the PBL height and stabilizing lower
atmosphere, the aerosol effects lead to increases in surface concentrations
of primary pollutants (CO and SO2). Surface O3 mixing ratio is
reduced by up to 6.9 ppb (parts per billion) due to reduced incoming solar radiation and lower
temperature, while the aerosol feedbacks on PM2.5 mass concentrations
show some spatial variations. Comparisons of model results with observations
show that inclusion of aerosol feedbacks in the model significantly improves
model performance in simulating meteorological variables and improves
simulations of PM2.5 temporal distributions over the North China Plain,
the Yangtze River delta, the Pearl River delta, and central China. Although
the aerosol–radiation–cloud feedbacks on aerosol mass concentrations are
subject to uncertainties, this work demonstrates the significance of
aerosol–radiation–cloud feedbacks for real-time air quality forecasting
under haze conditions
Evaluación de esquemas de microfÃsica WRF en la simulación de una lÃnea de turbonada sobre IRAN utilizando datos de radar y de reanálisis
Se registró una lÃnea de turbonada en el puerto de Dayyer, al suroeste de Irán, el 19 de marzo de 2017. En el presente documento, hemos simulado los rasgos caracterÃsticos asociados con la lÃnea de turbonada mediante el modelo de investigación y pronóstico meteorológico (WRF) utilizando cinco microfÃsicas diferentes (MP) esquemas. Para validar las caracterÃsticas simuladas de la lÃnea de turbonada, la reflectividad de la sección transversal de latitud-altura y longitud-altura y el valor de precipitación derivado de la reflectividad observada recopilada por el radar meteorológico Doppler en Bushehr, datos de la estación meteorológica sinóptica en el puerto de Dayyer junto con NCEP-NCAR y ERA -Se utilizaron datos de reanálisisINTERIM. Para verificar la precipitación simulada, se calculó la curva Fractions Skill Score (FSS). El examen de los resultados de la simulación de la presión geopotencial y al nivel del mar muestra que las simulaciones del modelo que utilizan diferentes esquemas de MP concuerdan bien con los reanálisis de verificación. Además, la distribución espacial de las precipitaciones de las simulaciones y las observaciones de verificación no mostraron grandes diferencias. Sin embargo, existen diferencias significativas en los detalles de las simulaciones, como la reflectividad máxima de las celdas convectivas, la extensión vertical de las celdas de tormenta, la velocidad y dirección del viento, los valores de precipitación y las curvas FSS. Sin embargo, todas las simulaciones han mostrado celdas convectivas sobre el puerto de Dayyer en el momento de la aparición de la lÃnea de turbonada, pero solo la simulación del modelo que usa el esquema Lin MP es consistente con la reflectividad del radar y la extensión vertical correspondientes. El gráfico FSS mostró que la habilidad cambia con la escala espacial. Los resultados utilizando el esquema de microfÃsica Lin cruzaron la lÃnea FSSuniform a escalas más bajas en comparación con otros esquemas de M
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