scholarly journals Space and ground segment performance of the FORMOSAT-3/COSMIC mission: four years in orbit

2011 ◽  
Vol 4 (1) ◽  
pp. 599-638 ◽  
Author(s):  
C.-J. Fong ◽  
D. Whiteley ◽  
E. Yang ◽  
K. Cook ◽  
V. Chu ◽  
...  
Keyword(s):  
Real Time ◽  
Numerical Weather Prediction ◽  
Radio Occultation ◽  
Prediction Models ◽  
Positive Impact ◽  
Weather Prediction ◽  
Low Earth Orbit ◽  
Lessons Learned ◽  
Numerical Weather ◽  
Ground System

Abstract. The FORMOSAT-3/COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) mission consisting of six Low-Earth-Orbit (LEO) satellites is the world's first demonstration constellation using radio occultation signals from Global Positioning System (GPS) satellites. The radio occultation signals are retrieved in near real-time for global weather/climate monitoring, numerical weather prediction, and space weather research. The mission has processed on average 1400 to 1800 high-quality atmospheric sounding profiles per day. The atmospheric radio occultation soundings data are assimilated into operational numerical weather prediction models for global weather prediction, including typhoon/hurricane/cyclone forecasts. The radio occultation data has shown a positive impact on weather predictions at many national weather forecast centers. A proposed follow-on mission transitions the program from the current experimental research system to a significantly improved real-time operational system, which will reliably provide 8000 radio occultation soundings per day. The follow-on mission as planned will consist of 12 satellites with a data latency of 45 min, which will provide greatly enhanced opportunities for operational forecasts and scientific research. This paper will address the FORMOSAT-3/COSMIC system and mission overview, the spacecraft and ground system performance after four years in orbit, the lessons learned from the encountered technical challenges and observations, and the expected design improvements for the new spacecraft and ground system.

scholarly journals Space and ground segment performance and lessons learned of the FORMOSAT-3/COSMIC mission: four years in orbit

2011 ◽  
Vol 4 (6) ◽  
pp. 1115-1132 ◽  
Author(s):  
C.-J. Fong ◽  
D. Whiteley ◽  
E. Yang ◽  
K. Cook ◽  
V. Chu ◽  
...  
Keyword(s):  
Real Time ◽  
Numerical Weather Prediction ◽  
Radio Occultation ◽  
Weather Prediction ◽  
Lessons Learned ◽  
Numerical Weather ◽  
Leo Satellites ◽  
Ground System ◽  
Occultation Data ◽  
Radio Occultation Data

Abstract. The FORMOSAT-3/COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) Mission consisting of six Low-Earth-Orbit (LEO) satellites is the world's first demonstration constellation using radio occultation signals from Global Positioning System (GPS) satellites. The atmospheric profiles derived by processing radio occultation signals are retrieved in near real-time for global weather/climate monitoring, numerical weather prediction, and space weather research. The mission has processed, on average, 1400 to 1800 high-quality atmospheric sounding profiles per day. The atmospheric radio occultation data are assimilated into operational numerical weather prediction models for global weather prediction, including typhoon/hurricane/cyclone forecasts. The radio occultation data has shown a positive impact on weather predictions at many national weather forecast centers. A follow-on mission was proposed that transitions the current experimental research mission into a significantly improved real-time operational mission, which will reliably provide 8000 radio occultation soundings per day. The follow-on mission, as planned, will consist of 12 LEO satellites (compared to 6 satellites for the current mission) with data latency requirement of 45 min (compared to 3 h for the current mission), which will provide greatly enhanced opportunities for operational forecasts and scientific research. This paper will address the FORMOSAT-3/COSMIC system and mission overview, the spacecraft and ground system performance after four years in orbit, the lessons learned from the encountered technical challenges and observations, and the expected design improvements for the spacecraft and ground system for FORMOSAT-7/COSMIC-2.

scholarly journals Radio Occultation Observations as Anchor Observations in Numerical Weather Prediction Models and Associated Reduction of Bias Corrections in Microwave and Infrared Satellite Observations

2014 ◽  
Vol 31 (1) ◽  
pp. 20-32 ◽  
Author(s):  
L. Cucurull ◽  
R. A. Anthes ◽  
L.-L. Tsao
Keyword(s):  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Radio Occultation ◽  
Prediction Models ◽  
Positive Impact ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Operational Environment ◽  
Numerical Weather ◽  
Bias Corrections

Abstract Satellite radiance measurements are used daily at numerical weather prediction (NWP) centers around the world, providing a significant positive impact on weather forecast skill. Owing to the existence of systematic errors, either in the observations, instruments, and/or forward models, which can be larger than the signal, the use of infrared or microwave radiances in data assimilation systems requires significant bias corrections. As most bias-correction schemes do not correct for biases that exist in the model forecasts, the model needs to be grounded by an unbiased observing system. These reference measurements, also known as “anchor observations,” prevent a drift of the model to its own climatology and associated biases, thus avoiding a spurious drift of the observation bias corrections. This paper shows that the assimilation of global positioning system (GPS) radio occultation (RO) observations over a 3-month period in an operational NWP system results in smaller, more accurate bias corrections in infrared and microwave observations, resulting in an overall more effective use of satellite radiances and a larger number of radiance observations that pass quality control. A full version of the NCEP data assimilation system is used to evaluate the results on the bias corrections for the High Resolution Infrared Radiation Sounder-3 (HIRS-3) on NOAA-17 and the Advanced Microwave Sounding Unit-A (AMSU-A) on NOAA-15 in an operational environment.

A Real-Time MODIS Vegetation Product for Land Surface and Numerical Weather Prediction Models

2014 ◽  
Vol 52 (3) ◽  
pp. 1772-1786 ◽  
Author(s):  
Jonathan L. Case ◽  
Frank J. LaFontaine ◽  
Jordan R. Bell ◽  
Gary J. Jedlovec ◽  
Sujay V. Kumar ◽  
...  
Keyword(s):  
Real Time ◽  
Numerical Weather Prediction ◽  
Land Surface ◽  
Prediction Models ◽  
Weather Prediction ◽  
Numerical Weather ◽  
Numerical Weather Prediction Models

A new vertical coordinate formulation to improve forecasts of fog and low stratus in high-resolution numerical weather prediction models

2021 ◽  
Author(s):  
Stephanie Westerhuis ◽  
Oliver Fuhrer
Keyword(s):  
High Resolution ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Positive Impact ◽  
Weather Prediction ◽  
Vertical Coordinate ◽  
Electrical Grid ◽  
Numerical Weather ◽  
Terrain Following ◽  
Numerical Weather Prediction Models

<p>Fog and low stratus pose a major challenge for numerical weather prediction (NWP) models. Despite high resolution in the horizontal (~1 km) and vertical (~20 m), operational NWP models often fail to accurately predict fog and low stratus. This is a major issue at airports which require visibility predictions, or for energy agencies estimating day-ahead input into the electrical grid from photovoltaic power.</p><p>Most studies dedicated to fog and low stratus forecasts have focused on the physical parameterisations or grid resolutions. We illustrate how horizontal advection at the cloud top of fog and low stratus in a grid with sloping vertical coordinates leads to spurious numerical diffusion and subsequent erroneous dissipation of the clouds. This cannot be prevented by employing a higher-order advection scheme. After all, the formulation of the terrain-following vertical coordinate plays a crucial role in regions which do not exhibit perfectly flat orography. We suggest a new vertical coordinate formulation which allows for a faster decay of the orographic signal with altitude and present its positive impact on fog and low stratus forecasts. Our experiments indicate that smoothing of the vertical coordinates at low altitudes is a crucial measure to prevent premature dissipation of fog and low stratus in high-resolution NWP models.</p>

scholarly journals Parametrizations of Liquid and Ice Clouds’ Optical Properties in Operational Numerical Weather Prediction Models

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 89
Author(s):  
Harel. B. Muskatel ◽  
Ulrich Blahak ◽  
Pavel Khain ◽  
Yoav Levi ◽  
Qiang Fu
Keyword(s):  
Optical Properties ◽  
Numerical Weather Prediction ◽  
Radiation Transfer ◽  
Prediction Models ◽  
Weather Prediction ◽  
Effective Size ◽  
Asymmetry Factor ◽  
Numerical Weather ◽  
Numerical Weather Prediction Models ◽  
Spectral Averaging

Parametrization of radiation transfer through clouds is an important factor in the ability of Numerical Weather Prediction models to correctly describe the weather evolution. Here we present a practical parameterization of both liquid droplets and ice optical properties in the longwave and shortwave radiation. An advanced spectral averaging method is used to calculate the extinction coefficient, single scattering albedo, forward scattered fraction and asymmetry factor (bext, v, f, g), taking into account the nonlinear effects of light attenuation in the spectral averaging. An ensemble of particle size distributions was used for the ice optical properties calculations, which enables the effective size range to be extended up to 570 μm and thus be applicable for larger hydrometeor categories such as snow, graupel, and rain. The new parameterization was applied both in the COSMO limited-area model and in ICON global model and was evaluated by using the COSMO model to simulate stratiform ice and water clouds. Numerical weather prediction models usually determine the asymmetry factor as a function of effective size. For the first time in an operational numerical weather prediction (NWP) model, the asymmetry factor is parametrized as a function of aspect ratio. The method is generalized and is available on-line to be readily applied to any optical properties dataset and spectral intervals of a wide range of radiation transfer models and applications.

Impact of Consistent Semi-Lagrangian Trajectory Calculations on Numerical Weather Prediction Performance

2017 ◽  
Vol 145 (10) ◽  
pp. 4127-4150 ◽  
Author(s):  
Syed Zahid Husain ◽  
Claude Girard
Keyword(s):  
Numerical Weather Prediction ◽  
Numerical Experiments ◽  
Prediction Models ◽  
Weather Prediction ◽  
Forecast Accuracy ◽  
Multiscale Model ◽  
Dynamical Equations ◽  
Numerical Weather ◽  
Trajectory Calculation ◽  
Trajectory Calculations

Inconsistencies may arise in numerical weather prediction models—that are based on semi-Lagrangian advection—when the governing dynamical and the kinematic trajectory equations are discretized in a dissimilar manner. This study presents consistent trajectory calculation approaches, both in the presence and absence of off-centering in the discretized dynamical equations. Both uniform and differential off-centering in the discretized dynamical equations have been considered. The proposed consistent trajectory calculations are evaluated using numerical experiments involving a nonhydrostatic two-dimensional theoretical mountain case and hydrostatic global forecasts. The experiments are carried out using the Global Environmental Multiscale model. Both the choice of the averaging method for approximating the velocity integral in the discretized trajectory equations and the interpolation scheme for calculating the departure positions are found to be important for consistent trajectory calculations. Results from the numerical experiments confirm that the proposed consistent trajectory calculation approaches not only improve numerical consistency, but also improve forecast accuracy.

scholarly journals EMPOL 1.0: a new parameterization of pollen emission in numerical weather prediction models

2013 ◽  
Vol 6 (6) ◽  
pp. 1961-1975 ◽  
Author(s):  
K. Zink ◽  
A. Pauling ◽  
M. W. Rotach ◽  
H. Vogel ◽  
P. Kaufmann ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Birch Pollen ◽  
Small Scale ◽  
Pollen Emission ◽  
Numerical Weather ◽  
Pollen Concentrations ◽  
Scale Modelling ◽  
Reactive Trace Gases

Abstract. Simulating pollen concentrations with numerical weather prediction (NWP) systems requires a parameterization for pollen emission. We have developed a parameterization that is adaptable for different plant species. Both biological and physical processes of pollen emission are taken into account by parameterizing emission as a two-step process: (1) the release of the pollen from the flowers, and (2) their entrainment into the atmosphere. Key factors influencing emission are temperature, relative humidity, the turbulent kinetic energy and precipitation. We have simulated the birch pollen season of 2012 using the NWP system COSMO-ART (Consortium for Small-scale Modelling – Aerosols and Reactive Trace Gases), both with a parameterization already present in the model and with our new parameterization EMPOL. The statistical results show that the performance of the model can be enhanced by using EMPOL.

Forecasting wave height probabilities with numerical weather prediction models

2005 ◽  
Vol 32 (14-15) ◽  
pp. 1841-1863 ◽  
Author(s):  
Mark S. Roulston ◽  
Jerome Ellepola ◽  
Jost von Hardenberg ◽  
Leonard A. Smith
Keyword(s):  
Wave Height ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Numerical Weather ◽  
Numerical Weather Prediction Models
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