Estimates of Cn2 from Numerical Weather Prediction Model Output and Comparison with Thermosonde Data

2010 ◽  
Vol 49 (8) ◽  
pp. 1742-1755 ◽  
Author(s):  
Rod Frehlich ◽  
Robert Sharman ◽  
Francois Vandenberghe ◽  
Wei Yu ◽  
Yubao Liu ◽  
...  
Keyword(s):  
Spatial Structure ◽  
Structure Function ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
The United States ◽  
Spatial Filter ◽  
Structure Functions ◽  
Model Output ◽  
Numerical Weather ◽  
Nwp Model

Abstract Area-averaged estimates of Cn2 from high-resolution numerical weather prediction (NWP) model output are produced from local estimates of the spatial structure functions of refractive index with corrections for the inherent smoothing and filtering effects of the underlying NWP model. The key assumptions are the existence of a universal statistical description of small-scale turbulence and a locally universal spatial filter for the NWP model variables. Under these assumptions, spatial structure functions of the NWP model variables can be related to the structure functions of the atmospheric variables and extended to the smaller underresolved scales. The shape of the universal spatial filter is determined by comparisons of model structure functions with the climatological spatial structure function determined from an archive of aircraft data collected in the upper troposphere and lower stratosphere. This method of computing Cn2 has an important advantage over more traditional methods that are based on vertical differences because the structure function–based estimates avoid reference to the turbulence outer length scale. To evaluate the technique, NWP model–derived structure-function estimates of Cn2 are compared with nighttime profiles of Cn2 derived from temperature structure-function sensors attached to a rawinsonde (thermosonde) near Holloman Air Force Base in the United States.

The Use of Structure Functions and Spectra from Numerical Model Output to Determine Effective Model Resolution

2008 ◽  
Vol 136 (4) ◽  
pp. 1537-1553 ◽  
Author(s):  
Rod Frehlich ◽  
Robert Sharman
Keyword(s):  
Spatial Structure ◽  
Spatial Statistics ◽  
Weather Prediction ◽  
Structure Functions ◽  
Effective Model ◽  
Model Output ◽  
Model Resolution ◽  
Nwp Model ◽  
Spatial Spectra ◽  
Aircraft Data

Abstract The effective model resolution of three numerical weather prediction (NWP) models is determined from analyses of spatial structure functions and spatial spectra. In this paper, the effective resolution is defined as the dimensions of the rectangular spatial filter that describes the net effect of all of the NWP model’s numerical filtering and smoothing effects. These effects are determined by comparison of spatial statistics of the NWP model output with statistical climatologies derived from aircraft data for the upper troposphere and lower stratosphere. The comparisons are based on both spatial structure functions and spatial spectra. The structure function approach has fewer assumptions and fewer numerical artifacts. Accurate estimates of NWP effective model resolution require a robust climatology of the spatial statistics, which are a function of latitude and location, such as over mountainous regions. An artifact in the climatology of the velocity statistics resulting from mountain waves is identified from NWP model output and corroborated with research aircraft data, which has not been previously observed in global statistical climatologies.

scholarly journals The National Earth System Prediction Capability: Coordinating the Giant

2017 ◽  
Vol 98 (2) ◽  
pp. 239-252 ◽  
Author(s):  
Jessie C. Carman ◽  
Daniel P. Eleuterio ◽  
Timothy C. Gallaudet ◽  
Gerald L. Geernaert ◽  
Patrick A. Harr ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
The United States ◽  
Department Of Energy ◽  
Earth System ◽  
Numerical Weather ◽  
Interagency Coordination ◽  
Research Technology ◽  
Prediction Capability ◽  
The U.S

Abstract The United States has had three operational numerical weather prediction centers since the Joint Numerical Weather Prediction Unit was closed in 1958. This led to separate paths for U.S. numerical weather prediction, research, technology, and operations, resulting in multiple community calls for better coordination. Since 2006, the three operational organizations—the U.S. Air Force, the U.S. Navy, and the National Weather Service—and, more recently, the Department of Energy, the National Aeronautics and Space Administration, the National Science Foundation, and the National Oceanic and Atmospheric Administration/Office of Oceanic and Atmospheric Research, have been working to increase coordination. This increasingly successful effort has resulted in the establishment of a National Earth System Prediction Capability (National ESPC) office with responsibility to further interagency coordination and collaboration. It has also resulted in sharing of data through an operational global ensemble, common software standards, and model components among the agencies. This article discusses the drivers, the progress, and the future of interagency collaboration.

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.

50th Anniversary of Operational Numerical Weather Prediction

2007 ◽  
Vol 88 (5) ◽  
pp. 639-650 ◽  
Author(s):  
Kristine Harper ◽  
Louis W. Uccellini ◽  
Eugenia Kalnay ◽  
Kenneth Carey ◽  
Lauren Morone
Keyword(s):  
Air Force ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
50Th Anniversary ◽  
Well Being ◽  
The United States ◽  
Numerical Weather ◽  
American Meteorological Society ◽  
College Park ◽  
The U.S

The National Centers for Environmental Prediction (NCEP), Air Force Weather Agency (AFWA), Fleet Numerical Meteorology and Oceanography Center (FNMOC), National Weather Association, and American Meteorological Society (AMS) cosponsored a “Symposium on the 50th Anniversary of Operational Numerical Weather Prediction,” on 14–17 June 2004 at the University of Maryland, College Park in College Park, Maryland. Operational numerical weather prediction (NWP) in the United States started with the Joint Numerical Weather Prediction Unit (JNWPU) on 1 July 1954, staffed by members of the U.S. Weather Bureau, the U.S. Air Force and the U.S. Navy. The origins of NCEP, AFWA, and FNMOC can all be traced to the JNWPU. The symposium celebrated the pioneering developments in NWP and the remarkable improvements in forecast skill and support of the nation's economy, well being, and national defense achieved over the last 50 years. This essay was inspired by the presentations from that symposium.

scholarly journals The Use of a Numerical Weather Prediction Model to Simulate Near-Field Volcanic Plumes

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 594
Author(s):  
Ralph R. Burton ◽  
Mark J. Woodhouse ◽  
Alan M. Gadian ◽  
Stephen D. Mobbs
Keyword(s):  
Numerical Weather Prediction ◽  
Near Field ◽  
Weather Prediction ◽  
Wrf Model ◽  
Integral Model ◽  
Eruption Column ◽  
Volcanic Plumes ◽  
Numerical Weather ◽  
Essential Components ◽  
Nwp Model

In this paper, a state-of the art numerical weather prediction (NWP) model is used to simulate the near-field plume of a Plinian-type volcanic eruption. The NWP model is run at very high resolution (of the order of 100 m) and includes a representation of physical processes, including turbulence and buoyancy, that are essential components of eruption column dynamics. Results are shown that illustrate buoyant gas plume dynamics in an atmosphere at rest and in an atmosphere with background wind, and we show that these results agree well with those from theoretical models in the quiescent atmosphere. For wind-blown plumes, we show that features observed in experimental and natural settings are reproduced in our model. However, when comparing with predictions from an integral model using existing entrainment closures there are marked differences. We speculate that these are signatures of a difference in turbulent mixing for uniform and shear flow profiles in a stratified atmosphere. A more complex implementation is given to show that the model may also be used to examine the dispersion of heavy volcanic gases such as sulphur dioxide. Starting from the standard version of the weather research and forecasting (WRF) model, we show that minimal modifications are needed in order to model volcanic plumes. This suggests that the modified NWP model can be used in the forecasting of plume evolution during future volcanic events, in addition to providing a virtual laboratory for the testing of hypotheses regarding plume behaviour.

scholarly journals An Evaluation of Radiative Transfer Simulations of Cloudy Scenes from a Numerical Weather Prediction Model at Sub-Millimetre Frequencies Using Airborne Observations

2020 ◽  
Vol 12 (17) ◽  
pp. 2758
Author(s):  
Stuart Fox
Keyword(s):  
Optical Properties ◽  
Radiative Transfer ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Full Range ◽  
Numerical Weather Prediction Model ◽  
Atmospheric Measurements ◽  
Numerical Weather ◽  
Nwp Model ◽  
Cloud Ice

The Ice Cloud Imager (ICI) will be launched on the next generation of EUMETSAT polar-orbiting weather satellites and make passive observations between 183 and 664 GHz which are sensitive to scattering from cloud ice. These observations have the potential to improve weather forecasts through direct assimilation using "all-sky" methods which have been successfully applied to microwave observations up to 200 GHz in current operational systems. This requires sufficiently accurate representations of cloud ice in both numerical weather prediction (NWP) and radiative transfer models. In this study, atmospheric fields from a high-resolution NWP model are used to drive radiative transfer simulations using the Atmospheric Radiative Transfer Simulator (ARTS) and a recently released database of cloud ice optical properties. The simulations are evaluated using measurements between 89 and 874 GHz from five case studies of ice and mixed-phase clouds observed by the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 research aircraft. The simulations are strongly sensitive to the assumed cloud ice optical properties, but by choosing an appropriate ice crystal model it is possible to simulate realistic brightness temperatures over the full range of sub-millimetre frequencies. This suggests that sub-millimetre observations have the potential to be assimilated into NWP models using the all-sky method.

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