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

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.

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High-Resolution Solar Climate Atlas for Greece under Climate Change Using the Weather Research and Forecasting (WRF) Model

Atmosphere ◽

10.3390/atmos11070761 ◽

2020 ◽

Vol 11 (7) ◽

pp. 761 ◽

Cited By ~ 1

Author(s):

Theodoros Katopodis ◽

Iason Markantonis ◽

Nadia Politi ◽

Diamando Vlachogiannis ◽

Athanasios Sfetsos

Keyword(s):

Climate Change ◽

High Resolution ◽

Energy Demand ◽

General Circulation ◽

Wrf Model ◽

General Circulation Models ◽

Weather Research And Forecasting ◽

Clear Sky ◽

The Future ◽

Weather Research

In the context of climate change and growing energy demand, solar technologies are considered promising solutions to mitigate Greenhouse Gas (GHG) emissions and support sustainable adaptation. In Greece, solar power is the second major renewable energy, constituting an increasingly important component of the future low-carbon energy portfolio. In this work, we propose the use of a high-resolution regional climate model (Weather Research and Forecasting model, WRF) to generate a solar climate atlas for the near-term climatological future under the Representative Concentration Pathway (RCPs) 4.5 and 8.5 scenarios. The model is set up with a 5 × 5 km2 spatial resolution, forced by the ERA-INTERIM for the historic (1980–2004) period and by the EC-EARTH General Circulation Models (GCM) for the future (2020–2044). Results reaffirm the high quality of solar energy potential in Greece and highlight the ability of the WRF model to produce a highly reliable future climate solar atlas. Projected changes between the annual historic and future RCPs scenarios indicate changes of the annual Global Horizontal Irradiance (GHI) in the range of ±5.0%. Seasonal analysis of the GHI values indicates percentage changes in the range of ±12% for both scenarios, with winter exhibiting the highest seasonal increases in the order of 10%, and autumn the largest decreases. Clear-sky fraction fclear projects increases in the range of ±4.0% in eastern and north continental Greece in the future, while most of the Greek marine areas might expect above 220 clear-sky days per year.

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Robustness of Tropospheric Temperature Trends from MSU Channels 2 and 4

Journal of Climate ◽

10.1175/jcli3866.1 ◽

2006 ◽

Vol 19 (17) ◽

pp. 4234-4242 ◽

Cited By ~ 22

Author(s):

Celeste M. Johanson ◽

Qiang Fu

Keyword(s):

Training Dataset ◽

Retrieval Algorithm ◽

Tropospheric Temperature ◽

Temperature Trends ◽

Combining Data ◽

Microwave Sounding Unit ◽

Microwave Sounding ◽

The Mean ◽

Stratospheric Cooling ◽

Global Mean

Abstract Tropospheric temperature trends based on Microwave Sounding Unit (MSU) channel 2 data are susceptible to contamination from strong stratospheric cooling. Recently, Fu et al. devised a method of removing the stratospheric contamination by linearly combining data from MSU channels 2 and 4. In this study the sensitivity of the weights of the two channels in the retrieval algorithm for the tropospheric temperatures to the choice of period of record used in the analysis and to the choice of training dataset is examined. The weights derived using monthly temperature anomalies are within about 10% of those obtained by Fu et al. irrespective of the choice of analysis period or training dataset. The trend errors in the retrieved global-mean tropospheric temperatures tested using two independent radiosonde datasets are less than about 0.01 K decade−1 for all time periods of 25 yr or longer with different starting and ending years during 1958–2004. It is found that the retrievals are more robust if they are interpreted in terms of the layer-mean temperature for the entire troposphere, rather than the mean of the 850–300-hPa layer. Because large spurious jumps remain in the reanalyses, especially prior to 1979, one should be cautious when using them as training datasets and in testing the trend errors.

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

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-10-05045.1 ◽

2011 ◽

Vol 28 (9) ◽

pp. 1104-1116 ◽

Cited By ~ 18

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.

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Sudden Track Changes of Tropical Cyclones in Monsoon Gyres: Full-Physics, Idealized Numerical Experiments*

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-13-0393.1 ◽

2015 ◽

Vol 72 (4) ◽

pp. 1307-1322 ◽

Cited By ~ 19

Author(s):

Jia Liang ◽

Liguang Wu

Keyword(s):

Tropical Cyclones ◽

Numerical Experiments ◽

Large Scale ◽

Wrf Model ◽

Weather Research And Forecasting ◽

Coalescence Process ◽

The West ◽

Steering Flow ◽

Sharp Turn ◽

Wind Profiles

Abstract Tropical cyclones (TCs) in the eastern semicircle of large-scale monsoon gyres (MGs) were observed to take either a northward (sudden northward and northward without a sharp turn) or a westward TC turn, but only the northward turn was previously simulated in a barotropic model. To understand what controls TC track types in MGs, idealized numerical experiments are performed using the full-physics Weather Research and Forecasting (WRF) Model. These experiments indicate that TCs initially located in the eastern semicircle of MGs can generally take three types of tracks: a sudden northward track, a westward track, and a northward track without a sharp turn. The track types depend upon the TC movement relative to the MG center. In agreement with barotropic simulations, the WRF simulation confirms that approaching and being collocated with the MG center is crucial to the occurrence of sudden northward TC track changes and that sudden northward track changes can be generally accounted for by changes in the steering flow. TCs that take westward tracks and northward tracks without a sharp turn do not experience such a coalescence process. Westward TCs move faster than MGs and are then located to the west of the MG center, while TCs move more slowly than MGs and then take a northward track without a sharp turn. This study reveals that the specific TC track in the eastern semicircle of an MG is sensitive to the initial wind profiles of both MGs and TCs, suggesting that improvement in the observation of TC and MG structures is very important for predicting TC track types in MGs.

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A Features-Based Assessment of the Evolution of Warm Season Precipitation Forecasts from the HRRR Model over Three Years of Development

Weather and Forecasting ◽

10.1175/waf-d-17-0050.1 ◽

2017 ◽

Vol 32 (5) ◽

pp. 1841-1856 ◽

Cited By ~ 5

Author(s):

Janice L. Bytheway ◽

Christian D. Kummerow ◽

Curtis Alexander

Keyword(s):

Data Assimilation ◽

Model Development ◽

Wrf Model ◽

Warm Season ◽

Convective Precipitation ◽

Weather Research And Forecasting ◽

Central Plains ◽

Convective Initiation ◽

Precipitation Forecasting ◽

Data Assimilation System

Abstract The High Resolution Rapid Refresh (HRRR) model has been the National Weather Service’s (NWS) operational rapid update model since 2014. The HRRR has undergone continual development, including updates to the Weather Research and Forecasting (WRF) Model core, the data assimilation system, and the various physics packages in order to better represent atmospheric processes, with updated operational versions of the model being implemented approximately every spring. Given the model’s intent for use in convective precipitation forecasting, it is of interest to examine how forecasts of warm season precipitation have changed as a result of the continued model upgrades. A features-based assessment is performed on the first 6 h of HRRR quantitative precipitation forecasts (QPFs) from the 2013, 2014, and 2015 versions of the model over the U.S. central plains in an effort to understand how specific aspects of QPF performance have evolved as a result of continued model development. Significant bias changes were found with respect to precipitation intensity. Model upgrades that increased boundary layer stability and reduced the strength of the latent heating perturbations in the data assimilation were found to reduce southward biases in convective initiation, reduce the tendency for the model to overestimate heavy rainfall, and improve the representation of convective initiation.

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

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-11-00080.1 ◽

2012 ◽

Vol 29 (2) ◽

pp. 248-259 ◽

Cited By ~ 21

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

Monthly Weather Review ◽

10.1175/mwr-d-18-0228.1 ◽

2019 ◽

Vol 147 (7) ◽

pp. 2603-2620 ◽

Cited By ~ 4

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.

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Dynamics and Predictability of Hurricane Nadine (2012) Evaluated through Convection-Permitting Ensemble Analysis and Forecasts

Monthly Weather Review ◽

10.1175/mwr-d-14-00358.1 ◽

2015 ◽

Vol 143 (11) ◽

pp. 4514-4532 ◽

Cited By ~ 17

Author(s):

Erin B. Munsell ◽

Jason A. Sippel ◽

Scott A. Braun ◽

Yonghui Weng ◽

Fuqing Zhang

Keyword(s):

Ensemble Kalman Filter ◽

Regional Scale ◽

Wrf Model ◽

Heat Fluxes ◽

Sensitivity Analyses ◽

Weather Research And Forecasting ◽

Sensitivity Experiment ◽

Steering Flow ◽

General Success ◽

Initial Intensity

Abstract The governing dynamics and uncertainties of an ensemble simulation of Hurricane Nadine (2012) are assessed through the use of a regional-scale convection-permitting analysis and forecast system based on the Weather Research and Forecasting (WRF) Model and an ensemble Kalman filter (EnKF). For this case, the data that are utilized were collected during the 2012 phase of the National Aeronautics and Space Administration’s (NASA) Hurricane and Severe Storm Sentinel (HS3) experiment. The majority of the tracks of this ensemble were successful, correctly predicting Nadine’s turn toward the southwest ahead of an approaching midlatitude trough, though 10 members forecasted Nadine to be carried eastward by the trough. Ensemble composite and sensitivity analyses reveal the track divergence to be caused by differences in the environmental steering flow that resulted from uncertainties associated with the position and subsequent strength of a midlatitude trough. Despite the general success of the ensemble track forecasts, the intensity forecasts indicated that Nadine would strengthen, which did not happen. A sensitivity experiment performed with the inclusion of sea surface temperature (SST) updates significantly reduced the intensity errors associated with the simulation. This weakening occurred as a result of cooling of the SST field in the vicinity of Nadine, which led to weaker surface sensible and latent heat fluxes at the air–sea interface. A comparison of environmental variables, including relative humidity, temperature, and shear yielded no obvious differences between the WRF-EnKF simulations and the HS3 observations. However, an initial intensity bias in which the WRF-EnKF vortices are stronger than the observed vortex appears to be the most likely cause of the final intensity errors.

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A Land and Ocean Microwave Cloud Classification Algorithm Derived from AMSU-A and -B, Trained Using MSG-SEVIRI Infrared and Visible Observations

Monthly Weather Review ◽

10.1175/mwr-d-10-05012.1 ◽

2011 ◽

Vol 139 (8) ◽

pp. 2347-2366 ◽

Cited By ~ 15

Author(s):

Filipe Aires ◽

Francis Marquisseau ◽

Catherine Prigent ◽

Geneviève Sèze

Keyword(s):

Classification Algorithm ◽

Satellite Observations ◽

Significant Information ◽

Clear Sky ◽

Cloud Classification ◽

Infrared Imager ◽

Microwave Sounding Unit ◽

Microwave Sounding ◽

Cloud Mask ◽

High Clouds

AbstractA statistical cloud classification and cloud mask algorithm is developed based on Advanced Microwave Sounding Unit (AMSU-A and -B) microwave (MW) observations. The visible and infrared data from the Meteosat Third Generation-Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) are used to train the microwave classifier. The goal of the MW algorithms is not to fully reproduce this MSG-SEVIRI cloud classification, as the MW observations do not have enough information on clouds to reach this level of precision. The objective is instead to obtain a stand-alone MW cloud mask and classification algorithm that can be used efficiently in forthcoming retrieval schemes of surface or atmospheric parameters from microwave satellite observations. This is an important tool over both ocean and land since the assimilation of the MW observations in the operational centers is independent from the other satellite observations.Clear sky and low, medium, and opaque–high clouds can be retrieved over ocean and land at a confidence level of more than 80%. An information content analysis shows that AMSU-B provides significant information over both land and ocean, especially for the classification of medium and high clouds, whereas AMSU-A is more efficient over ocean when discriminating clear situations and low clouds.

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Methodology for Deriving Deep-Layer Mean Temperatures from Combined Satellite Infrared and Microwave Observations

Journal of Climate ◽

10.1175/1520-0442-12.1.5 ◽

1999 ◽

Vol 12 (1) ◽

pp. 5-20 ◽

Cited By ~ 1

Author(s):

Mitchell D. Goldberg ◽

Larry M. McMillin

Keyword(s):

Deep Layer ◽

Horizontal Resolution ◽

Infrared Observations ◽

Infrared Radiance ◽

Stratospheric Temperature ◽

Preliminary Validation ◽

Microwave Sounding Unit ◽

Microwave Sounding ◽

The Mean ◽

The Relationship

Abstract Deep-layer mean temperatures from Microwave Sounding Unit (MSU) observations have been used by scientists to study trends and interannual variations of tropospheric and lower-stratospheric temperature. The spatial resolution of MSU deep-layer mean temperatures is rather poor for studying trends in localized regions. A method is developed in which infrared observations from the High-resolution InfraRed Sounder (HIRS) is used in combination with MSU to derive deep-layer mean temperatures with improved vertical and horizontal resolution. Even though the relationship between infrared radiance and temperature is not linear, the layer associated with the mean temperature is shown to be well defined with a small airmass dependency that is similar to MSU’s airmass dependency. Preliminary validation of HIRS–MSU-derived layer mean temperatures with radiosonde layer mean temperatures show similar precision when compared to MSU-only derived temperatures.

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