scholarly journals Improved Prediction of Bay of Bengal Tropical Cyclones through Assimilation of Doppler Weather Radar Observations

2015 ◽  
Vol 143 (11) ◽  
pp. 4533-4560 ◽  
Author(s):  
Krishna K. Osuri ◽  
U. C. Mohanty ◽  
A. Routray ◽  
Dev Niyogi
Keyword(s):  
Bay Of Bengal ◽  
Inner Core ◽  
Weather Radar ◽  
Doppler Weather Radar ◽  
Telecommunication System ◽  
Rainfall Prediction ◽  
Warm Core ◽  
Global Telecommunication System ◽  
The Impact ◽  
Ice Phase

Abstract The impact on tropical cyclone (TC) prediction from assimilating Doppler weather radar (DWR) observations obtained from the TC inner core and environment over the Bay of Bengal (BoB) is studied. A set of three operationally relevant numerical experiments were conducted for 24 forecast cases involving 5 unique severe/very severe BoB cyclones: Sidr (2007), Aila (2009), Laila (2010), Jal (2010), and Thane (2011). The first experiment (CNTL) used the NCEP FNL analyses for model initial and boundary conditions. In the second experiment [Global Telecommunication System (GTS)], the GTS observations were assimilated into the model initial condition while the third experiment (DWR) used DWR with GTS observations. Assimilation of the TC environment from DWR improved track prediction by 32%–53% for the 12–72-h forecast over the CNTL run and by 5%–25% over GTS and was consistently skillful. More gains were seen in intensity, track, and structure by assimilating inner-core DWR observations as they provided more realistic initial organization/asymmetry and strength of the TC vortex. Additional experiments were conducted to assess the role of warm-rain and ice-phase microphysics to assimilate DWR reflectivity observations. Results indicate that the ice-phase microphysics has a dominant impact on inner-core reflectivity assimilation and in modifying the intensity evolution, hydrometeors, and warm core structure, leading to improved rainfall prediction. This study helps provide a baseline for the credibility of an observational network and assist with the transfer of research to operations over the India monsoon region.

scholarly journals Comparing the cloud vertical structure derived from several methods based on radiosonde profiles and ground-based remote sensing measurements

2014 ◽  
Vol 7 (8) ◽  
pp. 2757-2773 ◽  
Author(s):  
M. Costa-Surós ◽  
J. Calbó ◽  
J. A. González ◽  
C. N. Long
Keyword(s):  
Remote Sensing ◽  
Vertical Structure ◽  
Cloud Layer ◽  
Cloud Base ◽  
Low Resolution ◽  
Telecommunication System ◽  
Perfect Agreement ◽  
Data Set ◽  
Global Telecommunication System ◽  
The Impact

Abstract. The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, are important characteristics in order to describe the impact of clouds on climate. In this work, several methods for estimating the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering the number and position of cloud layers, with a ground-based system that is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ in the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study, these methods are applied to 193 radiosonde profiles acquired at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site during all seasons of the year 2009 and endorsed by Geostationary Operational Environmental Satellite (GOES) images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The perfect agreement (i.e., when the whole CVS is estimated correctly) for the methods ranges between 26 and 64%; the methods show additional approximate agreement (i.e., when at least one cloud layer is assessed correctly) from 15 to 41%. Further tests and improvements are applied to one of these methods. In addition, we attempt to make this method suitable for low-resolution vertical profiles, like those from the outputs of reanalysis methods or from the World Meteorological Organization's (WMO) Global Telecommunication System. The perfect agreement, even when using low-resolution profiles, can be improved by up to 67% (plus 25% of the approximate agreement) if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement.

scholarly journals Comparing the cloud vertical structure derived from several methods based on measured atmospheric profiles and active surface measurements

2014 ◽  
Vol 7 (4) ◽  
pp. 3681-3725
Author(s):  
M. Costa-Surós ◽  
J. Calbó ◽  
J. A. González ◽  
C. N. Long
Keyword(s):  
Vertical Structure ◽  
Current Data ◽  
Cloud Layer ◽  
Cloud Base ◽  
Low Resolution ◽  
Telecommunication System ◽  
Perfect Agreement ◽  
Data Set ◽  
Global Telecommunication System ◽  
The Impact

Abstract. The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, is an important characteristic in order to describe the impact of clouds on climate. In this work several methods to estimate the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering number and position of cloud layers, with a ground based system which is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ on the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study these methods are applied to 193 radiosonde profiles acquired at the ARM Southern Great Plains site during all seasons of year 2009 and endorsed by GOES images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The perfect agreement (i.e. when the whole CVS is correctly estimated) for the methods ranges between 26–64%; the methods show additional approximate agreement (i.e. when at least one cloud layer is correctly assessed) from 15–41%. Further tests and improvements are applied on one of these methods. In addition, we attempt to make this method suitable for low resolution vertical profiles, like those from the outputs of reanalysis methods or from the WMO's Global Telecommunication System. The perfect agreement, even when using low resolution profiles, can be improved up to 67% (plus 25% of approximate agreement) if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement.

scholarly journals A quantitative analysis of the impact of wind turbines on operational Doppler weather radar data

2015 ◽  
Vol 8 (2) ◽  
pp. 593-609 ◽  
Author(s):  
L. Norin
Keyword(s):  
Quantitative Analysis ◽  
Wind Turbines ◽  
Wind Farm ◽  
Negative Impact ◽  
Weather Radar ◽  
Radar Data ◽  
Doppler Weather Radar ◽  
Spectral Moments ◽  
Using Data ◽  
The Impact

Abstract. In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in the radar line of sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on 6 years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. It is shown that this in part can be explained by detection by the radar sidelobes and by scattering off increased levels of dust and turbulence. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. It is shown that, when weather echoes give rise to higher reflectivity values than those of the wind farm, the negative impact of the wind turbines is greatly reduced for all spectral moments.

scholarly journals Impact of Assimilating Upper-Level Dropsonde Observations Collected during the TCI Field Campaign on the Prediction of Intensity and Structure of Hurricane Patricia (2015)

2019 ◽  
Vol 147 (8) ◽  
pp. 3069-3089 ◽  
Author(s):  
Jie Feng ◽  
Xuguang Wang
Keyword(s):  
Heat Release ◽  
Latent Heat ◽  
Inner Core ◽  
Motion Vector ◽  
Latent Heat Release ◽  
Field Campaign ◽  
Cyclone Intensity ◽  
Warm Core ◽  
Upper Level ◽  
The Impact

Abstract The dropsondes released during the Tropical Cyclone Intensity (TCI) field campaign provide high-resolution kinematic and thermodynamic measurements of tropical cyclones within the upper-level outflow and inner core. This study investigates the impact of these upper-level TCI dropsondes on analyses and prediction of Hurricane Patricia (2015) during its rapid intensification (RI) phase using an ensemble–variational data assimilation system. In the baseline experiment (BASE), both kinematic and thermodynamic observations of TCI dropsondes at all levels except the upper levels are assimilated. The upper-level wind and thermodynamic observations are assimilated in additional experiments to investigate their respective impacts. Compared to BASE, assimilating TCI upper-level wind observations improves the accuracy of outflow analyses verified against independent atmospheric motion vector (AMV) observations. It also strengthens the tangential and radial wind near the upper-level eyewall. The inertial stability within the upper-level eyewall is enhanced, and the maximum outflow is more aligned toward the inner core. Additionally, the analyses including the upper-level thermodynamic observations produce a warmer and drier core at high levels. Assimilating both upper-level kinematic and thermodynamic observations also improves the RI forecast. Compared to BASE, assimilating the upper-level wind induces more upright and inward-located eyewall convection, resulting in more latent heat release closer to the warm core. This process leads to stronger inner-core warming. Additionally, the initial warmer upper-level inner core produced by assimilating TCI thermodynamic observations also intensifies the convection and latent heat release within the eyewall, thus further contributing to the improved intensity forecasts.

scholarly journals On the Rapid Weakening of Very Intense Tropical Cyclone Hellen (2014)

2019 ◽  
Vol 147 (8) ◽  
pp. 2717-2737 ◽  
Author(s):  
Adrien Colomb ◽  
Tarik Kriat ◽  
Marie-Dominique Leroux
Keyword(s):  
Tropical Cyclone ◽  
Wind Shear ◽  
Large Scale ◽  
Inner Core ◽  
Potential Temperature ◽  
Vertical Wind Shear ◽  
Warm Core ◽  
Operational Forecasting ◽  
Intensity Changes ◽  
The Impact

Abstract In late March 2014, very intense Tropical Cyclone Hellen threatened the Comoros Archipelago and the Madagascan northwest coastline as it became one of the strongest tropical cyclones (TCs) ever observed over the Mozambique Channel. Its steep intensity changes were not well anticipated by operational forecasting models or by La Reunion regional specialized meteorological center forecasters. In particular, the record-setting rapid weakening over the open ocean was not supported by usual large-scale predictors. AROME, a new nonhydrostatic finescale model, is able to closely reproduce these wide intensity changes. When benchmarked against available observations, the model is also consistent in terms of inner-core structure, environmental features, track, and intensity. In the simulation, a northwesterly 400-hPa environmental wind is associated with unsaturated air, while the classic 200–850-hPa wind shear remains weak, and does not suggest a specifically unfavorable environment. The 400-hPa constraint affects the simulated storm through two pathways. Air with low equivalent potential temperature (θe) is flushed downward into the inflow layer in the upshear semicircle, triggering the decay of the storm. Then, direct erosion of the upper half of the warm core efficiently increases the surface pressure and also plays an instrumental role in the rapid weakening. When the storm gets closer to the Madagascan coastline, low-θe air can be directly advected within the inflow layer. Results illustrate on a real TC case the recently proposed paradigm for TC intensity modification under vertical wind shear and highlight the need for innovative tools to assess the impact of wind shear at all vertical levels.

scholarly journals A quantitative analysis of the impact of wind turbines on operational Doppler weather radar data

2014 ◽  
Vol 7 (8) ◽  
pp. 8743-8776
Author(s):  
L. Norin
Keyword(s):  
Quantitative Analysis ◽  
Wind Turbines ◽  
Wind Farm ◽  
Negative Impact ◽  
Weather Radar ◽  
Radar Data ◽  
Doppler Weather Radar ◽  
Spectral Moments ◽  
Using Data ◽  
The Impact

Abstract. In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in radar line-of-sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind- and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on six years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. We show that this is partly explained by changes in the atmospheric refractive index, bending the radar beams closer to the ground. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. We show that when weather echoes give rise to higher reflectivity values than that of the wind farm, the negative impact of the wind turbines disappears for all spectral moments.

scholarly journals The Impact of Low Latency Satellite Sounder Observations on Local Severe Storm Forecasts in Regional NWP

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 650 ◽  
Author(s):  
Pei Wang ◽  
Jun Li ◽  
Timothy J. Schmit
Keyword(s):  
Positive Impact ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Advanced Technology ◽  
Low Latency ◽  
Telecommunication System ◽  
Global Telecommunication System ◽  
Direct Broadcast ◽  
The Impact ◽  
Data Latency

The forecasts of local severe storms (LSS) are highly dependent on how well the pre-convection environment is characterized in the numerical weather prediction (NWP) model analysis. The usefulness of the forecasts is highly dependent on how frequently the forecast is updated. Therefore, the data latency is critical for assimilation into regional NWP models for it to be able to assimilate more data within the data cut-off window. These low latency data can be obtained through direct broadcast sites and direct receiving systems. Observing system experiments (OSE) were performed to study the impact of data latency on the LSS forecasts. The experiments assimilated all existing observations including conventional data (from the global telecommunication system, GTS) and satellite sounder radiance data (AMSU-A (The Advanced Microwave Sounding Unit-A), ATMS (Advanced Technology Microwave Sounder), CrIS (Cross-track Infrared Sounder), and IASI (Infrared Atmospheric Sounding Interferometer)). They were carried out in a nested domain with a horizontal resolution of 9 km and 3 km in the weather research and forecasting (WRF) model. The forecast quality scores of the LSS precipitation forecasts were calculated and compared with different data cut-off widows to evaluate the impact of data latency. The results showed that low latency can lead to an improved and positive impact on precipitation and other forecasts, which indicates the potential application of LEO direct broadcast (DB) data in a high-resolution regional NWP for LSS forecasts.

scholarly journals WHIRL WIND DETECTION AND IDENTIFICATION IN INDONESIA UTILIZING SINGLE POLARIZATION DOPPLER WEATHER RADAR VOLUMETRIC DATA

2016 ◽  
Vol XLI-B8 ◽  
pp. 1221-1227
Author(s):  
Abdullah Ali ◽  
Sabitul Hidayati
Keyword(s):  
Remote Sensing ◽  
Wind Profile ◽  
Weather Radar ◽  
Horizontal Wind ◽  
Cloud Base ◽  
Doppler Weather Radar ◽  
National Agency ◽  
Wind Detection ◽  
Single Polarization ◽  
The Impact

Whirl wind occurrence frequency in Indonesia tends increasing in the last five years. Geospatial data from National Agency for Disaster Management (BNPB) recorded 72 cases with the impact of the two victims died, ten injured, 485 people were evacuated, and 1285 buildings were destroyed at period of January-June 2015. Based on the impact, early warning through remote sensing by using single polarization Doppler weather radar is need to be efforted. Whirl wind detection is done by identifying the characteristic pattern of the rotating convective cloud system by hook echo, analyzing the exsistance of vortex and rotation, and the strength of turbulence. The results show horizontal wind profile with a rotational pattern at CAPPI (V) and HWIND (V) by the altitude of 0.5 km, strong turbulence through product CAPPI (W) 0.5 km ranged of 1.75-2.05 ms-1, the vertical wind profile by product VVP (V) with a maximum value updraft reaches more than 20 knots at a 100-200 meters height, strong horizontal wind shear through HSHEAR (V) and CAPPI (HSHEAR) altitude of 0.5 km with a range of 6.23 to 10.12 ms-1/km. SWI and SSA show that the cloud base height is very low ranged from 200-600 meters with a maximum reflectivity reached 61.5 dBZ by top cloud height reached 14 km, while the product CAPPI (Z) 0.5 km and CMAX (Z) is very difficult to identify patterns hook echo. The results of remote sensing are very representative with the physical properties of whirl wind even whirl wind in a smaller scale.

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