scholarly journals Relating observations of contrail persistence to numerical weather analysis output

2008 ◽  
Vol 8 (5) ◽  
pp. 18385-18407
Author(s):  
D. P. Duda ◽  
R. Palikonda ◽  
P. Minnis
Keyword(s):  
Meteorological Data ◽  
Atmospheric Stability ◽  
Quantitative Agreement ◽  
Atmospheric Conditions ◽  
Formation Theory ◽  
Advanced Regional Prediction System ◽  
Numerical Weather ◽  
Regional Prediction ◽  
Upper Limits ◽  
Upper Tropospheric Humidity

Abstract. The potential for using high-resolution meteorological data from two operational numerical weather analyses (NWA) to diagnose and predict persistent contrail formation is evaluated using two independent contrail observation databases. Contrail occurrence statistics derived from surface and satellite observations between April 2004 and June 2005 are matched to the humidity, vertical velocity, wind shear and atmospheric stability derived from analyses from the Rapid Update Cycle (RUC) and the Advanced Regional Prediction System (ARPS) models. The relationships between contrail occurrence and the NWA-derived statistics are analyzed to determine under which atmospheric conditions persistent contrail formation is favored within NWAs. Humidity is the most important factor determining whether contrails are short-lived or persistent, and persistent contrails are more likely to appear when vertical velocities are positive, and more likely to spread when the atmosphere is less stable. Although artificial upper limits on upper tropospheric humidity within the NWAs prevent a direct quantitative agreement of model data with contrail formation theory, logistic regression or similar statistical methods may improve the prediction of contrail occurrence.

scholarly journals Relating observations of contrail persistence to numerical weather analysis output

2009 ◽  
Vol 9 (4) ◽  
pp. 1357-1364 ◽  
Author(s):  
D. P. Duda ◽  
R. Palikonda ◽  
P. Minnis
Keyword(s):  
High Resolution ◽  
Wind Shear ◽  
Meteorological Data ◽  
Atmospheric Stability ◽  
Satellite Observations ◽  
Prediction System ◽  
Atmospheric Conditions ◽  
Advanced Regional Prediction System ◽  
Numerical Weather ◽  
Regional Prediction

Abstract. The potential for using high-resolution meteorological data from two operational numerical weather analyses (NWA) to diagnose and predict persistent contrail formation is evaluated using two independent contrail observation databases. Contrail occurrence statistics derived from surface and satellite observations between April 2004 and June 2005 are matched to the humidity, vertical velocity, wind shear and atmospheric stability derived from analyses from the Rapid Update Cycle (RUC) and the Advanced Regional Prediction System (ARPS) models. The relationships between contrail occurrence and the NWA-derived statistics are analyzed to determine under which atmospheric conditions persistent contrail formation is favored within NWAs. Humidity is the most important factor determining whether contrails are short-lived or persistent, and persistent contrails are more likely to appear when vertical velocities are positive. The model-derived atmospheric stability and wind shear do not appear to have a significant effect on contrail occurrence.

scholarly journals Basic Diagnosis and Prediction of Persistent Contrail Occurrence Using High-Resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

2009 ◽  
Vol 48 (9) ◽  
pp. 1790-1802 ◽  
Author(s):  
David P. Duda ◽  
Patrick Minnis
Keyword(s):  
Relative Humidity ◽  
Wind Direction ◽  
Meteorological Data ◽  
Logistic Models ◽  
Satellite Observations ◽  
Lapse Rate ◽  
Prediction System ◽  
Advanced Regional Prediction System ◽  
Regional Prediction ◽  
Surface Models

Abstract A probabilistic forecast to accurately predict contrail formation over the conterminous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and the Rapid Update Cycle (RUC) combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The most common predictors selected for the SURFACE models tend to be related to temperature, relative humidity, and wind direction when the models are generated using RUC or ARPS analyses. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The most common predictors for the OUTBREAK models tend to be wind direction, atmospheric lapse rate, temperature, relative humidity, and the product of temperature and humidity.

scholarly journals Mean and Turbulent Flow Downstream of a Low-Intensity Fire: Influence of Canopy and Background Atmospheric Conditions

2015 ◽  
Vol 54 (1) ◽  
pp. 42-57 ◽  
Author(s):  
Michael T. Kiefer ◽  
Warren E. Heilman ◽  
Shiyuan Zhong ◽  
Joseph J. Charney ◽  
Xindi Bian
Keyword(s):  
Wind Speed ◽  
Turbulent Flow ◽  
Atmospheric Conditions ◽  
Advanced Regional Prediction System ◽  
Low Intensity ◽  
Regional Prediction ◽  
Vertical Heat Flux ◽  
Weak Wind ◽  
Canopy Model ◽  
Neutral Stratification

AbstractThis study examines the sensitivity of mean and turbulent flow in the planetary boundary layer and roughness sublayer to a low-intensity fire and evaluates whether the sensitivity is dependent on canopy and background atmospheric properties. The ARPS-CANOPY model, a modified version of the Advanced Regional Prediction System (ARPS) model with a canopy parameterization, is utilized for this purpose. A series of numerical experiments are conducted to evaluate whether the ability of the fire to alter downstream wind, temperature, turbulent kinetic energy (TKE), and vertical heat flux differs between forested and open areas, sparse and dense forests, weak and strong background flow, and neutral and convective background stability. Analysis of all experiments shows that, in general, mean and turbulent flow both prior to and during a low-intensity fire is damped in the presence of a canopy. Greater sensitivity to the fire is found in cases with strong ambient wind speed than in cases with quiescent or weak wind speed. Furthermore, sensitivity of downstream atmospheric conditions to the fire is shown to be strongest with a neutrally stratified background. An analysis of the TKE budget reveals that both buoyancy and wind shear contribute to TKE production during the period of time in which the fire conditions are applied to the model. On the basis of the results of the ARPS simulations, caution is advised when applying ARPS-simulation results to predictions of smoke transport and dispersion: smoke-model users should consider whether canopy impacts on the atmosphere are accounted for and whether neutral stratification is assumed.

scholarly journals Atmospheric turbulence affects wind turbine nacelle transfer functions

2017 ◽  
Vol 2 (1) ◽  
pp. 295-306 ◽  
Author(s):  
Clara M. St. Martin ◽  
Julie K. Lundquist ◽  
Andrew Clifton ◽  
Gregory S. Poulos ◽  
Scott J. Schreck
Keyword(s):  
Wind Speed ◽  
Energy Production ◽  
Transfer Functions ◽  
Meteorological Data ◽  
Atmospheric Stability ◽  
Production Optimization ◽  
Atmospheric Conditions ◽  
Power Performance ◽  
Complex Flows ◽  
Performance Validation

Abstract. Despite their potential as a valuable source of individual turbine power performance and turbine array energy production optimization information, nacelle-mounted anemometers have often been neglected because complex flows around the blades and nacelle interfere with their measurements. This work quantitatively explores the accuracy of and potential corrections to nacelle anemometer measurements to determine the degree to which they may be useful when corrected for these complex flows, particularly for calculating annual energy production (AEP) in the absence of other meteorological data. Using upwind meteorological tower measurements along with nacelle-based measurements from a General Electric (GE) 1.5sle model, we calculate empirical nacelle transfer functions (NTFs) and explore how they are impacted by different atmospheric and turbulence parameters. This work provides guidelines for the use of NTFs for deriving useful wind measurements from nacelle-mounted anemometers. Corrections to the nacelle anemometer wind speed measurements can be made with NTFs and used to calculate an AEP that comes within 1 % of an AEP calculated with upwind measurements. We also calculate unique NTFs for different atmospheric conditions defined by temperature stratification as well as turbulence intensity, turbulence kinetic energy, and wind shear. During periods of low stability as defined by the Bulk Richardson number (RB), the nacelle-mounted anemometer underestimates the upwind wind speed more than during periods of high stability at some wind speed bins below rated speed, leading to a steeper NTF during periods of low stability. Similarly, during periods of high turbulence, the nacelle-mounted anemometer underestimates the upwind wind speed more than during periods of low turbulence at most wind bins between cut-in and rated wind speed. Based on these results, we suggest different NTFs be calculated for different regimes of atmospheric stability and turbulence for power performance validation purposes.

scholarly journals Atmospheric turbulence affects wind turbine nacelle transfer functions

2016 ◽  
Author(s):  
Clara M. St. Martin ◽  
Julie K. Lundquist ◽  
Andrew Clifton ◽  
Gregory S. Poulos ◽  
Scott J. Schreck
Keyword(s):  
Wind Speed ◽  
Energy Production ◽  
Transfer Functions ◽  
Meteorological Data ◽  
Atmospheric Stability ◽  
Production Optimization ◽  
Atmospheric Conditions ◽  
Power Performance ◽  
Complex Flows ◽  
Performance Validation

Abstract. Despite their potential as a valuable source of individual turbine power performance and turbine array energy production optimization information, nacelle-mounted anemometers have often been neglected because complex flows around the blades and nacelle interfere with their measurements. This work quantitatively explores the accuracy of and potential corrections to nacelle anemometer measurements to determine the degree to which they may be useful when corrected for these complex flows, particularly for calculating annual energy production (AEP) in the absence of other meteorological data. Using upwind meteorological tower measurements along with nacelle-based measurements from a General Electric (GE) 1.5sle model, we calculate empirical nacelle transfer functions (NTFs) and explore how they are impacted by different atmospheric and turbulence parameters. This work provides guidelines for the use of NTFs for deriving useful wind measurements from nacelle-mounted anemometers. Corrections to the nacelle anemometer wind speed measurements can be made with NTFs and used to calculate an AEP that comes within 1 % of an AEP calculated with upwind measurements. We also calculate unique NTFs for different atmospheric conditions defined by temperature stratification as well as turbulence intensity, turbulence kinetic energy, and wind shear. During periods of low stability as defined by the Bulk Richardson number (RB), the nacelle-mounted anemometer underestimates the upwind wind speed more than during periods of high stability at some wind speed bins below rated speed, leading to a more steep NTF during periods of low stability. Similarly, during periods of high turbulence, the nacelle-mounted anemometer underestimates the upwind wind speed more than during periods of low turbulence at most wind bins between cut-in and rated wind speed. Based on these results, we suggest different NTFs be calculated for different regimes of atmospheric stability and turbulence for power performance validation purposes.

UTCI as the NWP model ALADIN (CHMI) output – first experiences

2021 ◽  
Vol 94 (2) ◽  
pp. 237-249
Author(s):  
Martin Novák
Keyword(s):  
Numerical Weather Prediction ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Climate Index ◽  
Basic Information ◽  
Universal Thermal Climate Index ◽  
Numerical Weather ◽  
Weather Forecasters ◽  
Thermal Climate ◽  
Nwp Model

The article includes a summary of basic information about the Universal Thermal Climate Index (UTCI) calculation by the numerical weather prediction (NWP) model ALADIN of the Czech Hydrometeorological Institute (CHMI). Examples of operational outputs for weather forecasters in the CHMI are shown in the first part of this work. The second part includes results of a comparison of computed UTCI values by ALADIN for selected place with UTCI values computed from real measured meteorological data from the same place.

scholarly journals Little Ice Age (Neoglacial) Paleoenvironmental Conditions At Siple Station, Antarctica

1990 ◽  
Vol 14 ◽  
pp. 199-204 ◽  
Author(s):  
Ellen Mosley-Thompson ◽  
Lonnie G. Thompson ◽  
Pieter M. Grootes ◽  
N. Gundestrup
Keyword(s):  
Little Ice Age ◽  
Regional Differences ◽  
Meteorological Data ◽  
Ice Core ◽  
Observational Evidence ◽  
Ice Age ◽  
Temperature Pattern ◽  
South Pole ◽  
Atmospheric Conditions ◽  
Spatially Distributed

The 550-year records of δ18O and dust concentrations from Siple Station, Antarctica suggest warmer and less dusty atmospheric conditions from 1600 to 1830 A.D. which encompasses much of the northern hemisphere Little Ice Age (LIA). Dust and δ18O data from South Pole Station indicate that the opposite conditions (e.g. cooler and more dusty) were prevalent there during the LIA. Meteorological data from 1945–85 show that the LIA temperature opposition between Amundsen-Scott and Siple, inferred from δ18O, is consistent with the present spatial distribution of surface temperature. There is some observational evidence suggesting that under present conditions stronger zonal westerlies produce a temperature pattern similar to that of the LIA. These regional differences demonstrate that a suite of spatially distributed, high resolution ice-core records will be necessary to characterize the LIA in Antarctica

scholarly journals Explicit Prediction of Hail in a Long-Lasting Multicellular Convective System in Eastern China Using Multimoment Microphysics Schemes

2018 ◽  
Vol 75 (9) ◽  
pp. 3115-3137 ◽  
Author(s):  
Liping Luo ◽  
Ming Xue ◽  
Kefeng Zhu ◽  
Bowen Zhou
Keyword(s):  
Eastern China ◽  
Convective System ◽  
Distribution Characteristics ◽  
Grid Spacing ◽  
Particle Size Distributions ◽  
Growth Processes ◽  
Microphysics Scheme ◽  
Advanced Regional Prediction System ◽  
Regional Prediction ◽  
Size Sorting

Abstract During the afternoon of 28 April 2015, a multicellular convective system swept southward through much of Jiangsu Province, China, over about 7 h, producing egg-sized hailstones on the ground. The hailstorm event is simulated using the Advanced Regional Prediction System (ARPS) at 1-km grid spacing. Different configurations of the Milbrandt–Yau microphysics scheme are used, predicting one, two, and three moments of the hydrometeor particle size distributions (PSDs). Simulated reflectivity and maximum estimated size of hail (MESH) derived from the simulations are verified against reflectivity observed by operational S-band Doppler radars and radar-derived MESH, respectively. Comparisons suggest that the general evolution of the hailstorm is better predicted by the three-moment scheme, and neighborhood-based MESH evaluation further confirms the advantage of the three-moment scheme in hail size prediction. Surface accumulated hail mass, number, and hail distribution characteristics within simulated storms are examined across sensitivity experiments. Results suggest that multimoment schemes produce more realistic hail distribution characteristics, with the three-moment scheme performing the best. Size sorting is found to play a significant role in determining hail distribution within the storms. Detailed microphysical budget analyses are conducted for each experiment, and results indicate that the differences in hail growth processes among the experiments can be mainly ascribed to the different treatments of the shape parameter within different microphysics schemes. Both the differences in size sorting and hail growth processes contribute to the simulated hail distribution differences within storms and at the surface.

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