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L. Cucurull

Abstract

As of May 2007, the National Centers for Environmental Prediction (NCEP) implemented a new Global Data Assimilation System. This system incorporated the assimilation of global positioning system (GPS) radio occultation (RO) profiles from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) mission, which was launched in April 2006. Since then, this new type of observation has been shown to provide additional information on the thermodynamic state of the atmosphere, resulting in a significant increase in the model skill.

Recent updates of the analysis and modeling codes have required a revision of the algorithm that assimilates GPS RO data. In addition, some modifications in the processing of the observations have further enhanced the need for a revisiting of the assimilation code. Better characterizations of the quality control procedures, observation error structure, and forward modeling for the GPS RO observations are described. The updated system significantly improves the data usage, in particular in the tropics. Different sets of the atmospheric refractive indices are also evaluated in this study. The model performance is proven to be quite sensitive to the chosen coefficients and a reevaluation of these constants is recommended within the GPS community.

The new assimilation configuration results in an improvement in the anomaly correlation scores for the Southern Hemisphere extratropics (∼4.5 h for the 500-mb geopotential heights at day 7) and a reduction of the high- and low-level tropical wind errors. Overall, the benefits of using COSMIC on top of all the other observations used in the operational system are still very significant. The loss in model skill when COSMIC is removed from the observing system is remarkable at day 4 (∼8 h) and steadily increases beyond 12 h with the extended forecast range.

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L. Cucurull and M. J. Mueller

Abstract

Observing system simulation experiments (OSSEs) were conducted to evaluate the potential impact of the six Global Navigation Satellite System (GNSS) radio occultation (RO) receiver satellites in equatorial orbit from the initially proposed Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) mission, known as COSMIC-2A. Furthermore, the added value of the high-inclination component of the proposed mission was investigated by considering a few alternative architecture designs, including the originally proposed polar constellation of six satellites (COSMIC-2B), a constellation with a reduced number of RO receiving satellites, and a constellation of six satellites but with fewer observations in the lower troposphere. The 2015 year version of the operational three-dimensional ensemble–variational data assimilation system of the National Centers for Environment Prediction (NCEP) was used to run the OSSEs. Observations were simulated and assimilated using the same methodology and their errors assumed uncorrelated. The largest benefit from the assimilation of COSMIC-2A, with denser equatorial coverage, was to improve tropical winds, and its impact was found to be overall neutral in the extratropics. When soundings from the high-inclination orbit were assimilated in addition to COSMIC-2A, positive benefits were found globally, confirming that a high-inclination orbit constellation of RO receiving satellites is necessary to improve weather forecast skill globally. The largest impact from reducing COSMIC-2B from six to four satellites was to slightly degrade weather forecast skill in the Northern Hemisphere extratropics. The impact of degrading COSMIC-2B to the COSMIC level of accuracy, in terms of penetration into the lower troposphere, was mostly neutral.

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L. Cucurull and M. J. Mueller

Abstract

Observing system simulation experiments (OSSEs) were conducted to evaluate the potential impact of the six Global Navigation Satellite System (GNSS) radio occultation (RO) receiver satellites in equatorial orbit from the initially proposed Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) mission, known as COSMIC-2A. Furthermore, the added value of the high-inclination component of the proposed mission was investigated by considering a few alternative architecture designs, including the originally proposed polar constellation of six satellites (COSMIC-2B), a constellation with a reduced number of RO receiving satellites, and a constellation of six satellites but with fewer observations in the lower troposphere. The 2015 year version of the operational three-dimensional ensemble–variational data assimilation system of the National Centers for Environment Prediction (NCEP) was used to run the OSSEs. Observations were simulated and assimilated using the same methodology and their errors assumed uncorrelated. The largest benefit from the assimilation of COSMIC-2A, with denser equatorial coverage, was to improve tropical winds, and its impact was found to be overall neutral in the extratropics. When soundings from the high-inclination orbit were assimilated in addition to COSMIC-2A, positive benefits were found globally, confirming that a high-inclination orbit constellation of RO receiving satellites is necessary to improve weather forecast skill globally. The largest impact from reducing COSMIC-2B from six to four satellites was to slightly degrade weather forecast skill in the Northern Hemisphere extratropics. The impact of degrading COSMIC-2B to the COSMIC level of accuracy, in terms of penetration into the lower troposphere, was mostly neutral.

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L. Cucurull and R. A. Anthes

Abstract

A comparison of the impact of infrared (IR), microwave (MW), and radio occultation (RO) observations on NCEP’s operational global forecast model over the month of March 2013 is presented. Analyses and forecasts with only IR, MW, and RO observations are compared with analyses and forecasts with no satellite data and with each other. Overall, the patterns of the impact of the different satellite systems are similar, with the MW observations producing the largest impact on the analyses and RO producing the smallest. Without RO observations, satellite radiances are over– or under–bias corrected and RO acts as an anchor observation, reducing the forecast biases globally. Positive correlation coefficients of temperature impacts are generally found between the different satellite observation analyses, indicating that the three satellite systems are affecting the global temperatures in a similar way. However, the correlation in the lower troposphere among all three systems is surprisingly small. Correlations for the moisture field tend to be small in the lower troposphere between the different satellite analyses. The impact of the satellite observations on the 500-hPa geopotential height forecasts is much different in the Northern and Southern Hemispheres. In the Northern Hemisphere, all the satellite observations together make a small positive impact compared to the base (no satellite) forecasts. The IR and MW, but not the RO, make a small positive impact when assimilated alone. The situation is considerably different in the Southern Hemisphere, where all the satellite observations together make a much larger positive impact, and all three observation types (IR, MW, and RO) make similar and significant impacts.

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L. Cucurull and J. C. Derber

Abstract

The next generation of NCEP’s Global Data Assimilation System became operational on 1 May 2007. This system incorporates the assimilation of global positioning system (GPS) radio occultation (RO) profiles from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) mission launched in April 2006. Roughly 1 yr after the launch of COSMIC, NCEP has begun operational use of this new dataset.

A preliminary assessment of this observation type was performed with an earlier version of NCEP’s analysis at a lower resolution. These experiments showed positive impact when GPS RO soundings from the Challenging Minisatellite Payload (CHAMP) mission were assimilated into the system in non–real time. In these earlier studies, two different forward operators for the GPS RO profiles were evaluated: one for refractivity and another one for bending angle.

In this paper, the data assimilation experiments with COSMIC observations that led NOAA/NCEP to assimilate COSMIC data into operations are described. The experiments were conducted with the current operational version of the code and at full operational resolution. Based on the results of the experiments analyzed here, profiles of refractivity were selected as the type of GPS RO observation to be assimilated. Further enhancement to the assimilation of bending angles is currently being evaluated at NCEP.

The results show a significant improvement of the anomaly correlation skill and a global reduction of the NCEP model bias and root-mean-square errors when COSMIC observations are assimilated into the system. The improvement is found for the temperature, geopotential heights, and moisture variables. Larger benefits are found in the Southern Hemisphere extratropics, although a significant positive impact is also found in the Northern Hemisphere extratropics and the tropics. Even if GPS RO observations cannot produce direct impact on the wind field through the adjoint of the forward operator, a slight benefit is found in the wind components.

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L. Cucurull and S. P. F. Casey

Abstract

As global data assimilation systems continue to evolve, observing system simulation experiments (OSSEs) need to be updated to accurately quantify the impact of proposed observing technologies in weather forecasting. Earlier OSSEs with radio occultation (RO) observations have been updated, and the impact of the originally proposed Constellation Observing System for Meteorology, Ionosphere and Climate-2 (COSMIC-2) mission, with high-inclination and low-inclination components, has been investigated by using the operational data assimilation system at NOAA and a one-dimensional bending-angle RO forward operator. It is found that the impact of the low-inclination component of the originally planned COSMIC-2 mission (now officially named COSMIC-2) has significantly increased as compared with earlier studies, and significant positive impact is now found globally in terms of mass and wind fields. These are encouraging results as COSMIC-2 was successfully launched in June 2019 and data have been recently released to operational weather centers. Earlier findings remain valid indicating that globally distributed RO observations are more important to improve weather prediction globally than a denser sampling of the tropical latitudes. Overall, the benefits reported here from assimilating RO soundings are much more significant than the impacts found in previous OSSEs. This is largely attributed to changes in the data assimilation and forecast system and less to the more advanced one-dimensional forward operator chosen for the assimilation of RO observations.

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L. Cucurull, R. Li, and T. R. Peevey

Abstract

The mainstay of the global radio occultation (RO) system, the COSMIC constellation of six satellites launched in April 2006, is already past the end of its nominal lifetime and the number of soundings is rapidly declining because the constellation is degrading. For about the last decade, COSMIC profiles have been collected and their retrievals assimilated in numerical weather prediction systems to improve operational weather forecasts. The success of RO in increasing forecast skill and COSMIC’s aging constellation have motivated planning for the COSMIC-2 mission, a 12-satellite constellation to be deployed in two launches. The first six satellites (COSMIC-2A) are expected to be deployed in December 2017 in a low-inclination orbit for dense equatorial coverage, while the second six (COSMIC-2B) are expected to be launched later in a high-inclination orbit for global coverage. To evaluate the potential benefits from COSMIC-2, an earlier version of the NCEP’s operational forecast model and data assimilation system is used to conduct a series of observing system simulation experiments with simulated soundings from the COSMIC-2 mission. In agreement with earlier studies using real RO observations, the benefits from assimilating COSMIC-2 observations are found to be most significant in the Southern Hemisphere. No or very little gain in forecast skill is found by adding COSMIC-2A to COSMIC-2B, making the launch of COSMIC-2B more important for terrestrial global weather forecasting than that of COSMIC-2A. Furthermore, results suggest that further improvement in forecast skill might better be obtained with the addition of more RO observations with global coverage and other types of observations.

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A. C. Kren, L. Cucurull, and H. Wang

Abstract

A preliminary investigation into the impact of dropsonde observations from the Global Hawk (GH) on tropical and extratropical forecasts is performed using the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS). Experiments are performed during high-impact weather events that were sampled as part of the NOAA Unmanned Aerial Systems (UAS) Sensing Hazards with Operational Unmanned Technology (SHOUT) field campaigns in 2016: 1) three extratropical systems in February 2016 and 2) Hurricanes Matthew and Nicole in the western Atlantic. For these events, the benefits of GH observations under a satellite data gap scenario are also investigated. It is found that the assimilation of GH dropsondes reduces the track error for both Matthew and Nicole; the improvements are as high as 20% beyond 60 h. Additionally, the localized dropsondes reduce global forecast track error for four tropical cyclones by up to 9%. Results are mixed under a satellite gap scenario, where only Hurricane Matthew is improved from assimilated dropsondes. The improved storm track is attributed to a better representation of the steering flow and atmospheric midlevel pattern. For all cases, dropsondes reduce the root-mean-square error in temperature, relative humidity, wind, and sea level pressure by 3%–8% out to 96 h. Additional benefits from GH dropsondes are obtained for precipitation, with higher skill scores over the southeastern United States versus control forecasts of up to 8%, as well as for low-level parameters important for severe weather prediction. The findings from this study are preliminary and, therefore, more cases are needed for statistical significance.

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L. Cucurull, R. A. Anthes, and L.-L. Tsao

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.

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L. Cucurull, F. Vandenberghe, D. Barker, E. Vilaclara, and A. Rius

Abstract

The impact of GPS zenith total delay (ZTD) measurements on mesoscale weather forecasts is studied. GPS observations from a permanent European network are assimilated into the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) using its three-dimensional variational data assimilation (3DVAR) system. The case study focuses on a snow storm that occurred during the period of 14–15 December 2001 over the western Mediterranean Sea.

The experiments show that the most significant improvement in forecast is obtained when GPS ZTD data are assimilated together with local surface meteorological observations into the model within a cycling assimilation framework. In this case, the root-mean-square (rms) differences between forecasted and observed values are reduced by 1.7% in the wind component, 4.1% in the temperature variable, and 17.8% in the specific humidity field. This suggests the deployment of GPS receivers at surface stations to better initialize numerical weather prediction models during strong storm mesoscale events.

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