scholarly journals Expansion of the All-Sky Radiance Assimilation to ATMS at NCEP

2019 ◽  
Vol 147 (7) ◽  
pp. 2603-2620 ◽  
Author(s):  
Yanqiu Zhu ◽  
George Gayno ◽  
R. James Purser ◽  
Xiujuan Su ◽  
Runhua Yang
Keyword(s):  
Quality Control ◽  
Advanced Technology ◽  
Observation Error ◽  
Clear Sky ◽  
Radiance Assimilation ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
Control Procedures ◽  
Sky Radiance ◽  
Analysis System

Abstract Since the implementation of all-sky radiance assimilation of the Advanced Microwave Sounding Unit-A (AMSU-A) in the operational hybrid 4D ensemble–variational Global Forecast System at NCEP in 2016, the all-sky approach has been tested to expand to the radiances of Advanced Technology Microwave Sounder (ATMS) in the Gridpoint Statistical Interpolation analysis system (GSI). Following the all-sky framework implemented for the AMSU-A radiances, ATMS radiance assimilation adopts similar procedures in quality control, bias correction, and model of observation error. Efforts have been focused on special considerations that are necessary because of the unique features of the ATMS radiances and water vapor channels, including surface properties based on fields of view size and shape, and taking care of large departures from the first guess (OmF) along coastlines and radiances affected by strong scattering. More importantly, it is shown that this work makes microwave radiance OmFs become more consistent among different sensors, and provides indications of the deficiencies in quality control procedures of the original ATMS and Microwave Humidity Sounder (MHS) clear-sky radiance assimilation. While the generalized tracer effect is noticed, the overall impact on the forecast skill is neutral. This work is included in the upcoming operational implementation in 2019.

scholarly journals All-Sky Microwave Radiance Assimilation in NCEP’s GSI Analysis System

2016 ◽  
Vol 144 (12) ◽  
pp. 4709-4735 ◽  
Author(s):  
Yanqiu Zhu ◽  
Emily Liu ◽  
Rahul Mahajan ◽  
Catherine Thomas ◽  
David Groff ◽  
...  
Keyword(s):  
Quality Control ◽  
Bias Correction ◽  
Microwave Radiometer ◽  
Cloud Water ◽  
Development Effort ◽  
Observation Error ◽  
Background Error ◽  
Radiance Assimilation ◽  
Analysis System ◽  
Sky Conditions

Abstract The capability of all-sky microwave radiance assimilation in the Gridpoint Statistical Interpolation (GSI) analysis system has been developed at the National Centers for Environmental Prediction (NCEP). This development effort required the adaptation of quality control, observation error assignment, bias correction, and background error covariance to all-sky conditions within the ensemble–variational (EnVar) framework. The assimilation of cloudy radiances from the Advanced Microwave Sounding Unit-A (AMSU-A) microwave radiometer for ocean fields of view (FOVs) is the primary emphasis of this study. In the original operational hybrid 3D EnVar Global Forecast System (GFS), the clear-sky approach for radiance data assimilation is applied. Changes to data thinning and quality control have allowed all-sky satellite radiances to be assimilated in the GSI. Along with the symmetric observation error assignment, additional situation-dependent observation error inflation is employed for all-sky conditions. Moreover, in addition to the current radiance bias correction, a new bias correction strategy has been applied to all-sky radiances. In this work, the static background error variance and the ensemble spread of cloud water are examined, and the levels of cloud variability from the ensemble forecast in single- and dual-resolution configurations are discussed. Overall, the all-sky approach provides more realistic simulated brightness temperatures and cloud water analysis increments, and improves analysis off the west coasts of the continents by reducing a known bias in stratus. An approximate 10% increase in the use of AMSU-A channels 1–5 and a 12% increase for channel 15 are also observed. The all-sky AMSU-A radiance assimilation became operational in the 4D EnVar GFS system upgrade of 12 May 2016.

scholarly journals All-Sky Radiance Assimilation of ATMS in HWRF: A Demonstration Study

2018 ◽  
Vol 147 (1) ◽  
pp. 85-106 ◽  
Author(s):  
Ting-Chi Wu ◽  
Milija Zupanski ◽  
Lewis D. Grasso ◽  
Christian D. Kummerow ◽  
Sid-Ahmed Boukabara
Keyword(s):  
Single Case ◽  
Control Variable ◽  
Data Availability ◽  
Advanced Technology ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
State Variables ◽  
Initial State ◽  
Clear Sky ◽  
Analysis System

Abstract Satellite all-sky radiances from the Advanced Technology Microwave Sounder (ATMS) are assimilated into the Hurricane Weather Research and Forecasting (HWRF) Model using the hybrid Gridpoint Statistical Interpolation analysis system (GSI). To extend the all-sky capability recently developed for global applications to HWRF, some modifications in HWRF and GSI are facilitated. In particular, total condensate is added as a control variable, and six distinct hydrometeor habits are added as state variables in hybrid GSI within HWRF. That is, clear-sky together with cloudy and precipitation-affected satellite pixels are assimilated using the Community Radiative Transfer Model (CRTM) as a forward operator that includes hydrometeor information and Jacobians with respect to hydrometeor variables. A single case study with the 2014 Atlantic storm Hurricane Cristobal is used to demonstrate the methodology of extending the global all-sky capability to HWRF due to ATMS data availability. Two data assimilation experiments are carried out. One experiment uses the operational configuration and assimilates ATMS radiances under the clear-sky condition, and the other experiment uses the modified HWRF system and assimilates ATMS radiances under the all-sky condition with the inclusion of total condensate update and cycling. Observed and synthetic Geostationary Operational Environmental Satellite (GOES)-13 data along with Global Precipitation Measurement Mission (GPM) Microwave Imager (GMI) data from the two experiments are used to show that the experiment with all-sky ATMS radiances assimilation has cloud signatures that are supported by observations. In contrast, there is lack of clouds in the initial state that led to a noticeable lag of cloud development in the experiment that assimilates clear-sky radiances.

scholarly journals Connecting the Time Series of Microwave Sounding Observations from AMSU to ATMS for Long-Term Monitoring of Climate

2014 ◽  
Vol 31 (10) ◽  
pp. 2206-2222 ◽  
Author(s):  
Xiaolei Zou ◽  
Fuzhong Weng ◽  
H. Yang
Keyword(s):  
Time Series ◽  
Atmospheric Temperature ◽  
Advanced Technology ◽  
Central Frequency ◽  
Brightness Temperatures ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
Cross Calibration ◽  
Term Monitoring

Abstract The measurements from the Microwave Sounding Unit (MSU) and the Advanced Microwave Sounding Unit-A (AMSU-A) on board NOAA polar-orbiting satellites have been extensively utilized for detecting atmospheric temperature trend during the last several decades. After the launch of the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite on 28 October 2011, MSU and AMSU-A time series will be overlapping with the Advanced Technology Microwave Sounder (ATMS) measurements. While ATMS inherited the central frequency and bandpass from most of AMSU-A sounding channels, its spatial resolution and noise features are, however, distinctly different from those of AMSU. In this study, the Backus–Gilbert method is used to optimally resample the ATMS data to AMSU-A fields of view (FOVs). The differences between the original and resampled ATMS data are demonstrated. By using the simultaneous nadir overpass (SNO) method, ATMS-resampled observations are collocated in space and time with AMSU-A data. The intersensor biases are then derived for each pair of ATMS–AMSU-A channels. It is shown that the brightness temperatures from ATMS now fall well within the AMSU data family after resampling and SNO cross calibration. Thus, the MSU–AMSU time series can be extended into future decades for more climate applications.

scholarly journals Using MetOp-A AVHRR Clear-Sky Measurements to Cloud-Clear MetOp-A IASI Column Radiances

2011 ◽  
Vol 28 (9) ◽  
pp. 1104-1116 ◽  
Author(s):  
Eric S. Maddy ◽  
Thomas S. King ◽  
Haibing Sun ◽  
Walter W. Wolf ◽  
Christopher D. Barnet ◽  
...  
Keyword(s):  
High Spatial Resolution ◽  
Zero Bias ◽  
Clear Sky ◽  
Microwave Sounding Unit ◽  
Atmospheric Sounding ◽  
Microwave Sounding ◽  
Ecmwf Model ◽  
Skin Temperatures ◽  
Very High ◽  
Better Than

Abstract High spatial resolution measurements from the Advanced Very High Resolution Radiometer (AVHRR) on the Meteorological Operation (MetOp)-A satellite that are collocated to the footprints from the Infrared Atmospheric Sounding Interferometer (IASI) on the satellite are exploited to improve and quality control cloud-cleared radiances obtained from the IASI. For a partial set of mostly ocean MetOp-A orbits collected on 3 October 2010 for latitudes between 70°S and 75°N, these cloud-cleared radiances and clear-sky subpixel AVHRR measurements within the IASI footprint agree to better than 0.25-K root-mean-squared difference for AVHRR window channels with almost zero bias. For the same dataset, surface skin temperatures retrieved using the combined AVHRR, IASI, and Advanced Microwave Sounding Unit (AMSU) cloud-clearing algorithm match well with ECMWF model surface skin temperatures over ocean, yielding total uncertainties ≤1.2 K for scenes with up to 97% cloudiness.

scholarly journals Contribuição de diversos sistemas de observação na previsão de tempo no CPTEC/INPE

2008 ◽  
Vol 23 (2) ◽  
pp. 219-238 ◽  
Author(s):  
Rita V. Andreoli ◽  
Sérgio Henrique S. Ferreira ◽  
Luiz F. Sapucci ◽  
Rodrigo Augusto F. de Souza ◽  
Renata Weissmann B. Mendonça ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Physical Space ◽  
Total Precipitation ◽  
Atmospheric Infrared Sounder ◽  
Statistical Analysis System ◽  
Microwave Sounding Unit ◽  
Precipitation Water ◽  
Microwave Sounding ◽  
Advanced Microwave Sounding Unit ◽  
Analysis System

Experimentos utilizando sistemas de observação global, foram realizados excluindo um ou mais tipos de observação do esquema global de assimilação de dados/previsão de tempo do Centro de Previsão de Tempo e Estudos Climáticos do Instituto Nacional de Pesquisas Espaciais - CPTEC/INPE (Global Physical-space Statistical Analysis System - GPSAS). Estes experimentos indicam como efetivamente as observações são usadas no GPSAS. Os sistemas de observação testados foram o conjunto de dados convencionais, que incluem informações de superfície (estações em superfície, bóias, navios e plataformas oceânicas) e de ar superior (radiossondagem, aeronaves e balões piloto), os sistemas de sondagem Advanced TIROS-N/NOAA Operational Vertical Sounder (ATOVS) e AQUA, composto pelos sensores Atmospheric Infrared Sounder e Advanced Microwave Sounding Unit (AIRS/AMSU), dados de vento de satélite, estimados a partir do deslocamento de nuvens (Cloud Track Wind), dados de vento em superfície sobre o oceano (QuikScat) e água precipitável (Total Precipitation water - TPW). Todos os sistemas testados mostram um impacto positivo na qualidade da previsão. Os dados convencionais têm um maior impacto na região do Hemisfério Norte devido à maior disponibilidade dessas informações sobre esta região. Por outro lado, as sondagens AIRS/AMSU são fundamentais para uma boa previsão sobre o Hemisfério Sul. Sobre a América do Sul, os perfis inferidos pelo sistema de sondagem AQUA contribuem com a mesma ordem de grandeza dos dados convencionais e apresentam um impacto positivo para todos os períodos de previsões analisados. Dados de vento e água precipitável estimados por satélites têm maior impacto nas regiões tropical e da América do Sul, nas primeiras horas de previsão (1-3 dias). Todavia, a utilização de um conjunto completo de observações é crucial para se obter, operacionalmente, uma boa condição inicial do estado atmosférico para ser utilizada nos modelos de previsão numérica de tempo do CPTEC/INPE.

Quality Assurance of Energy Dispersive Spectrometry Systems

1998 ◽  
Vol 4 (S2) ◽  
pp. 214-215
Author(s):  
E. B. Steel ◽  
R. B. Marinenko
Keyword(s):  
Quality Control ◽  
Energy Dispersive Spectrometry ◽  
Standard Procedure ◽  
Energy Dispersive ◽  
X Ray ◽  
Standard Procedures ◽  
Reliability Sensitivity ◽  
Control Procedures ◽  
Analysis System ◽  
Quality Instruments

Monitoring the performance and capabilities of energy dispersive X-ray spectrometers (EDS) and related x-ray analysis electronics and software is important for maintaining and improving the reliability, sensitivity, and accuracy of the x-ray analysis system. There is growing demand for quality systems through laboratory accreditation, ISO 9000, ISO Guide 25 and related programs that require set quality control procedures for analytical instrumentation. In such cases it is frequently more useful to have one national/international standard. This approach is not only more efficient than having each analyst devise their own system, but the use of the same standard procedures among labs would allow direct intercomparison of results. This intercomparison can help labs and manufacturers determine what are normal versus abnormal results and lead to higher quality instruments and analyses.We are designing a standard procedure to maximize the efficiency of each quality control (QC) measurement so that we spend as little time monitoring the analysis system as is possible.

scholarly journals Impact of Assimilating FY-3D MWTS-2 Upper Air Sounding Data on Forecasting Typhoon Lekima (2019)

2021 ◽  
Vol 13 (9) ◽  
pp. 1841
Author(s):  
Zeyi Niu ◽  
Lei Zhang ◽  
Peiming Dong ◽  
Fuzhong Weng ◽  
Wei Huang
Keyword(s):  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Forecast Performance ◽  
Clear Sky ◽  
Steering Flow ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
The Mean ◽  
Data Assimilation System ◽  
Statistical Interpolation

In this study, the Fengyun-3D (FY-3D) clear-sky microwave temperature sounder-2 (MWTS-2) radiances were directly assimilated in the regional mesoscale Weather Research and Forecasting (WRF) model using the Gridpoint Statistical Interpolation (GSI) data assimilation system. The assimilation experiments were conducted to compare the track errors of typhoon Lekima from uses of the Advanced Microwave Sounding Unit-A (AMSU-A) radiances (EXP_AD) with those from FY-3D MWTS-2 upper-air sounding data at channels 5–7 (EXP_AMD). The clear-sky mean bias-corrected observation-minus-background (O-B) values of FY-3D MWTS-2 channels 5, 6, and 7 are 0.27, 0.10 and 0.57 K, respectively, which are smaller than those without bias corrections. Compared with the control experiment, which was the forecast of the WRF model without use of satellite data, the assimilation of satellite radiances can improve the forecast performance and reduce the mean track error by 8.7% (~18.4 km) and 30% (~58.6 km) beyond 36 h through the EXP_AD and EXP_AMD, respectively. The direction of simulated steering flow changed from southwest in the EXP_AD to southeast in the EXP_AMD, which can be pivotal to forecasting the landfall of typhoon Lekima (2019) three days in advance. Assimilation of MWTS-2 upper-troposphere channels 5–7 has great potential to improve the track forecasts for typhoon Lekima.

scholarly journals On the Importance of Vaisala RS92 Radiosonde Humidity Corrections for a Better Agreement between Measured and Modeled Satellite Radiances

2012 ◽  
Vol 29 (2) ◽  
pp. 248-259 ◽  
Author(s):  
Ajil Kottayil ◽  
Stefan A. Buehler ◽  
Viju O. John ◽  
Larry M. Miloshevich ◽  
M. Milz ◽  
...  
Keyword(s):  
Bias Reduction ◽  
Satellite Measurements ◽  
Clear Sky ◽  
Empirical Correction ◽  
Microwave Sounding Unit ◽  
Upper Tropospheric Humidity ◽  
Microwave Sounding ◽  
Atmospheric Radiation Measurement ◽  
Atmospheric Radiative Transfer ◽  
Sky Conditions

Abstract A study has been carried out to assess the importance of radiosonde corrections in improving the agreement between satellite and radiosonde measurements of upper-tropospheric humidity. Infrared [High Resolution Infrared Radiation Sounder (HIRS)-12] and microwave [Advanced Microwave Sounding Unit (AMSU)-18] measurements from the NOAA-17 satellite were used for this purpose. The agreement was assessed by comparing the satellite measurements against simulated measurements using collocated radiosonde profiles of the Atmospheric Radiation Measurement (ARM) Program undertaken at tropical and midlatitude sites. The Atmospheric Radiative Transfer Simulator (ARTS) was used to simulate the satellite radiances. The comparisons have been done under clear-sky conditions, separately for daytime and nighttime soundings. Only Vaisala RS92 radiosonde sensors were used and an empirical correction (EC) was applied to the radiosonde measurements. The EC includes correction for mean calibration bias and for solar radiation error, and it removes radiosonde bias relative to three instruments of known accuracy. For the nighttime dataset, the EC significantly reduces the bias from 0.63 to −0.10 K in AMSU-18 and from 1.26 to 0.35 K in HIRS-12. The EC has an even greater impact on the daytime dataset with a bias reduction from 2.38 to 0.28 K in AMSU-18 and from 2.51 to 0.59 K in HIRS-12. The present study promises a more accurate approach in future radiosonde-based studies in the upper troposphere.

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