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Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 27914

Special Issue Editors

Dr. Fuzhong Weng

E-Mail Website
Guest Editor
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Interests: radiative transfer; satellite remote sensing; data assimilation; satellite meteorology; microwave instrument cal/val; atmosphere remote sensing
Prof. Dr. Zhanqing Li

E-Mail Website
Guest Editor
Department of Atmospheric & Oceanic Science, University of Maryland, College Park, MD 20742, USA
Interests: satellite remote sensing; radiation budget; aerosol and climate effects
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Since 1999, a direct assimilation of satellite radiances in NWP models has been proven to be very effective in producing positive impacts on numerical weather prediction. Since radiances are not atmospheric state variables produced by forecast models, a relationship between the state variable and the satellite radiances is required, and this relationship is based on the radiative transfer model or observation operator. Thus, atmospheric and surface modeling of remote sensing has been heavily focused on developments of fast and accurate radiative transfer models. As the capability of these models has improved, the range of satellite data that can be successfully assimilated has increased. State-of-the art remote sensing algorithms also benefit from fast radiative transfer models.

This Special Issue calls for papers addressing the developments of the modeling components for observations sensitive not only to the atmosphere, which is often well represented by existing models, but other Earth system components (e.g., ocean, sea ice, snow, land, atmospheric composition). It also addresses shortcomings in the models that fast models are trained on, such as line-by-line transmittance models, and in the models that are used for computing particle scattering and absorption.

Suggested articles for submissions will consist of full-size papers documenting research pertaining to the following themes:

  1. Fast and accurate radiative transfer schemes;
  2. Atmospheric scattering and emission related to aerosols, clouds, and precipitation;
  3. Surface reflectivity and emissivity modeling;
  4. Applications of radiative transfer models in data assimilation and remote sensing.

Prof. Dr. Fuzhong Weng
Prof. Dr. Zhanqing Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Radiative transfer
  • Surface emissivity
  • Scattering and absorption
  • Gaseous absorption
  • Satellite data assimilation
  • Storm monitoring

Published Papers (15 papers)

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20 pages, 5846 KiB  
Article
Effect of Urban Built-Up Area Expansion on the Urban Heat Islands in Different Seasons in 34 Metropolitan Regions across China
by Wenchao Han, Zhuolin Tao, Zhanqing Li, Miaomiao Cheng, Hao Fan, Maureen Cribb and Qi Wang
Remote Sens. 2023, 15(1), 248; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15010248 - 31 Dec 2022
Cited by 4 | Viewed by 2102
Abstract
The urban heat island (UHI) refers to the land surface temperature (LST) difference between urban areas and their undeveloped or underdeveloped surroundings. It is a measure of the thermal influence of the urban built-up area expansion ( [...] Read more.
The urban heat island (UHI) refers to the land surface temperature (LST) difference between urban areas and their undeveloped or underdeveloped surroundings. It is a measure of the thermal influence of the urban built-up area expansion (UBAE), a topic that has been extensively studied. However, the impact of UBAE on the LST differences between urban areas and rural areas (UHIU−R) and between urban areas and emerging urban areas (UHIU−S) in different seasons has seldom been investigated. Here, the UHIU−S and UHIU−R in 34 major metropolitan regions across China, and their spatiotemporal variations based on long-term space-borne observations during the period 2001–2020 were analyzed. The UBAE quantified by the difference in landscape metrics of built-up areas between 2020 and 2000 and their impact on UHI was further analyzed. The UBAE is impacted by the level of economic development and topography. The UBAE of cities located in more developed regions was more significant than that in less developed regions. Coastal cities experienced the most obvious UBAE, followed by plain and hilly cities. The UBAE in mountainous regions was the weakest. On an annual basis, UHIU−R was larger than UHIU−S, decreasing more slowly with UBAE than UHIU−S. In different seasons, the UHIU−S and UHIU−R were larger, more clearly varying temporally with UBAE in summer than in winter, and their temporal variations were significantly correlated with UBAE in summer but not in winter. The seasonal difference in UHIU−R was larger than that of UHIU−S. Both the UHIU−S and UHIU−R in coastal cities were the lowest in summer, decreasing the fastest with UBAE, while those in mountain cities decreased the slowest. The change in the density of built-up lands was the primary driver affecting the temporal variations in UHIU−S and UHIU−R during UBAE, followed by changes in proportion and shape, while the impact of the speed of expansion was the smallest, all of which were more obvious in summer than in winter. The decreased density of built-up lands can reduce UHI. These findings provide a new perspective for a deeper understanding of the effect of urban expansion on LST in different seasons. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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21 pages, 4660 KiB  
Article
Influence of Scattered Sunlight for Wind Measurements with the O2(a1Δg) Dayglow
by Weiwei He, Xiangrui Hu, Houmao Wang, Daoqi Wang, Juan Li, Faquan Li and Kuijun Wu
Remote Sens. 2023, 15(1), 232; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15010232 - 31 Dec 2022
Cited by 1 | Viewed by 1312
Abstract
Observing the O2(a1Δg) dayglow with the limb-viewing DASH instrument enables remote sensing of neutral wind in near space. Many advantages are gained by using this new approach, but the influence factors on measurement accuracy have not been [...] Read more.
Observing the O2(a1Δg) dayglow with the limb-viewing DASH instrument enables remote sensing of neutral wind in near space. Many advantages are gained by using this new approach, but the influence factors on measurement accuracy have not been thoroughly investigated. This paper reports the quantitative evaluation of the wind error caused by scattered sunlight. The spectral concept of the O2(a1Δg) band and the measurement technique are briefly described. A comprehensive truth model simulation that is based on atmospheric limb radiance spectra and the instrument concept are used to obtain interferogram images. The algorithm, which uses these images to retrieve the interferogram containing information solely from the target altitude, is described. The self-absorption effect is taken into account in the unraveling of the line-of-sight integration. The influence of scattered sunlight on the limb-viewing weight and signal-to-noise ratio, two definitive factors for wind definitive factors, are also described. Representative wind precision profiles and their variation with surface albedo, aerosol loading, and cloud are presented. This indicates that the random error for Doppler wind is in the range of 2–3 m/s for the tangent height range from 45–80 km, and the wind precision under 45 km suffers significantly from scattered sunlight background. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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15 pages, 4435 KiB  
Article
A Comparison of Information Content at Microwave to Millimeter Wave Bands for Atmospheric Sounding
by Xianjun Xiao and Fuzhong Weng
Remote Sens. 2022, 14(23), 6124; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14236124 - 02 Dec 2022
Cited by 1 | Viewed by 1112
Abstract
The brightness temperatures and their Jacobians with respect to atmospheric temperature and humidity at the microwave to millimeter wave spectral bands from 23 GHz to 424 GHz are simulated with the ECMWF IFS-137 profiles as inputs to the Advanced Radiative transfer Modeling System [...] Read more.
The brightness temperatures and their Jacobians with respect to atmospheric temperature and humidity at the microwave to millimeter wave spectral bands from 23 GHz to 424 GHz are simulated with the ECMWF IFS-137 profiles as inputs to the Advanced Radiative transfer Modeling System (ARMS). The information content of temperature and humidity is then calculated individually through the Shannon entropy which is contributed by a-priori background information and observations. For a typical set of measurement uncertainties, a high information content for atmospheric temperature is mainly obtained from V band near 50–70 GHz, whereas that for water vapor comes from G band near 183 GHz and Y1 band near 380 GHz. The channels within the G band have a large temperature information content mainly for lower and middle layers of troposphere and the Y1 band has a relatively large humidity information content for the entire troposphere. A large measurement uncertainty can significantly reduce the information content of each band. Thus, to make a best use of the data from each band, it is important to reduce the instrument calibration noise and increase the accuracy in forward radiative transfer simulation. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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18 pages, 11144 KiB  
Article
Assimilation of Water Vapor Retrieved from Radar Reflectivity Data through the Bayesian Method
by Junjian Liu, Shuiyong Fan, Mamtimin Ali, Huoqing Li, Hailiang Zhang, Yu Wang and Ailiyaer Aihaiti
Remote Sens. 2022, 14(22), 5897; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14225897 - 21 Nov 2022
Viewed by 2135
Abstract
This work describes the implementation of an updated radar reflectivity assimilation scheme with the three-dimensional variational (3D-Var) system of Weather Research and Forecast (WRF). The updated scheme, instead of the original scheme assuming the relative humidity to a fixed value where radar reflectivity [...] Read more.
This work describes the implementation of an updated radar reflectivity assimilation scheme with the three-dimensional variational (3D-Var) system of Weather Research and Forecast (WRF). The updated scheme, instead of the original scheme assuming the relative humidity to a fixed value where radar reflectivity is higher than a threshold, assimilates pseudo water vapor retrieved by the Bayesian method, which would be consistent with clouds/precipitations provided by the model in theory. To verify the effect of the updated scheme to the improvement of precipitation simulation, a convective case in Wenquan County and the continuous monthly simulation with contrasting experiments in Xinjiang were performed. The test of single reflectivity observation demonstrates that the water vapor retrieved by the Bayesian method is consistent with the meteorological situation around. In the convective case, both the updated and original scheme results show that the assimilation of pseudo water vapor can adjust to the environmental conditions of water vapor and temperature. This can improve the hourly precipitation forecast skill more than the contrasting experiment, which was designed to only assimilate conventional observations and radar radial velocity data. In the continuous monthly experiments, the updated scheme reveals that the analysis of water vapor is more reasonable, and obtains a better precipitation forecast skill for 6 h accumulated precipitation than the contrasting experiments. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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19 pages, 7372 KiB  
Article
An All-Sky Scattering Index Derived from Microwave Sounding Data at Dual Oxygen Absorption Bands
by Wanlin Kan, Hao Hu and Fuzhong Weng
Remote Sens. 2022, 14(21), 5332; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14215332 - 25 Oct 2022
Viewed by 1711
Abstract
Combining the temperature sounding channels near 118 GHz onboard Fengyun-3D (FY-3D) with channels near 50 GHz makes it possible to obtain the spatial and vertical distributions of the clouds through a cloud emission and scattering index (CESI). Previous research has shown its advantages [...] Read more.
Combining the temperature sounding channels near 118 GHz onboard Fengyun-3D (FY-3D) with channels near 50 GHz makes it possible to obtain the spatial and vertical distributions of the clouds through a cloud emission and scattering index (CESI). Previous research has shown its advantages in cloud detection over oceans. In this study, the CESI method is expanded and validated under different surface conditions, and angular corrections are conducted to remove the effect of viewing angles. The landfall process of Typhoon MANGKHUT and a case over special terrain are chosen to investigate its sensitivities to different surface types. It is found that the cloud spatial distribution is well demonstrated in both of the cases. Moreover, the CESI vertical distributions are compared with the Global Precipitation Measurement (GPM) hydrometeor profiles. The results show that CESIs are highly related to the GPM hydrometeor profiles in all of the conditions, and the correlations with the sea surface vary with the weighting functions of the matched channels, while the phenomenon is not obvious for the land surface. In addition, the validation results show that the new threshold combination for different surface types at different heights can be more effective for cloud identification. The probability density distribution for most of the channels of the screened-out clear sky data approximates a Gaussian distribution well, and these radiances can be well assimilated into the numerical weather prediction models. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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21 pages, 7276 KiB  
Article
Impact of Fengyun-3E Microwave Temperature and Humidity Sounder Data on CMA Global Medium Range Weather Forecasts
by Wanlin Kan, Peiming Dong, Fuzhong Weng, Hao Hu and Changjiao Dong
Remote Sens. 2022, 14(19), 5014; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14195014 - 09 Oct 2022
Viewed by 1326
Abstract
In this study, the polarization characteristics of the newly launched Fengyun-3E (FY-3E) microwave sounding instruments are discussed, and its data quality is also assessed using one month of observation by the double-difference method. By comparison with the equivalent channels onboard Fengyun-3D (FY-3D) and [...] Read more.
In this study, the polarization characteristics of the newly launched Fengyun-3E (FY-3E) microwave sounding instruments are discussed, and its data quality is also assessed using one month of observation by the double-difference method. By comparison with the equivalent channels onboard Fengyun-3D (FY-3D) and advanced technology microwave sounder (ATMS), the data quality of FY-3E Microwave Humidity Sounder-II (MWHS-II) is improved and comparable to ATMS, while the data of FY-3E Microwave Temperature Sounder-III (MWTS-III) are slightly worse than data of FY-3D. The data of FY-3E MWTS-III are more susceptible to the early-morning orbit than the data of MWHS-II. In addition, striping noise is still present in channels 5–10 of MWTS-III. After the assessments, FY-3E microwave data are preprocessed and assimilated in the global forecast system for the Chinese Meteorology Administration (CMA-GFS). A total of six individual experiments over the period from 16 July to 15 August 2021 were conducted and the impact was evaluated with the composite score used in operation. It is shown that not only the forecasts for the southern hemisphere and tropics are improved significantly, but also the predictions for the northern hemisphere show some improvements in an overall neutral change from adding FY-3E microwave sounding instruments. The impact of FY-3E microwave radiance is equivalent to ATMS as they are assimilated individually. Furthermore, we note that the forecast impact is affected by the cloud detection scheme to a large extent. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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20 pages, 3732 KiB  
Article
Improving Clear-Sky Solar Power Prediction over China by Assimilating Himawari-8 Aerosol Optical Depth with WRF-Chem-Solar
by Su Wang, Tie Dai, Cuina Li, Yueming Cheng, Gang Huang and Guangyu Shi
Remote Sens. 2022, 14(19), 4990; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14194990 - 07 Oct 2022
Cited by 1 | Viewed by 2322
Abstract
Although the Weather Research and Forecasting model with solar extensions (WRF-Solar) is tailed for solar energy applications, its official version lacks the consideration of the online aerosol-radiation process. To overcome this limitation, we have coupled the aerosol module online with the radiation module, [...] Read more.
Although the Weather Research and Forecasting model with solar extensions (WRF-Solar) is tailed for solar energy applications, its official version lacks the consideration of the online aerosol-radiation process. To overcome this limitation, we have coupled the aerosol module online with the radiation module, then assimilated the high-resolution aerosol optical depth (AOD) from the Himawari-8 next-generation geostationary satellite using a three-dimensional variational (3DVAR) AOD data assimilation system to optimize the irradiance predictions with the better aerosol–radiation interaction. The results show that data assimilation can significantly eliminate the AOD underestimations and reasonably reproduce the AOD temporal distributions, improving 51.63% for biases and 61.29% for correlation coefficients. Compared with the original WRF-Solar version, coupled online with an advanced aerosol module minifies the bias value of global horizontal irradiance (GHI) up to 44.52%, and AOD data assimilation contributes to a further reduction of 17.43%. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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17 pages, 12070 KiB  
Article
Monitoring Asian Dust Storms from NOAA-20 CrIS Double CO2 Band Observations
by Chenggege Fang, Yang Han and Fuzhong Weng
Remote Sens. 2022, 14(18), 4659; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14184659 - 18 Sep 2022
Cited by 2 | Viewed by 1872
Abstract
Sand and dust storms (SDSs) are common environmental hazards in spring in Asian continent and have significant impacts on human health, weather, and climate. While many technologies have been developed to monitor SDSs, this study investigates the spectral characteristics of SDSs in satellite [...] Read more.
Sand and dust storms (SDSs) are common environmental hazards in spring in Asian continent and have significant impacts on human health, weather, and climate. While many technologies have been developed to monitor SDSs, this study investigates the spectral characteristics of SDSs in satellite hyperspectral infrared observations and propose a new methodology to monitor the storms. An SDS emission and scattering index (SESI) is based on the differential responses of infrared CO2 shortwave and longwave IR bands to the scattering and emission of sand and dust particles. For a severe dust storm process during 14–17 March 2021, the SESI calculated by the Cross-track Infrared Sounder (CrIS) observations shows very negative values in the dusty region and is consistent with the spatial distribution of dust identified from the true-color RGB imagery and the dust RGB imagery of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the NOAA-20 Satellite. The use of the SESI index in the near-surface layer allows for monitoring of the dust storm process and enables an effective classification between surface variations and dust weather events. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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20 pages, 6582 KiB  
Article
The Computational Optimization of the Invariant Imbedding T Matrix Method for the Particles with N-Fold Symmetry
by Jiaqi Zhao, Shuai Hu, Xichuan Liu and Shulei Li
Remote Sens. 2022, 14(16), 4061; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14164061 - 19 Aug 2022
Cited by 1 | Viewed by 1046
Abstract
The invariant imbedding T-matrix (IIM T-matrix) model is regarded as one of the most promising models for calculating the scattering parameters of non-spherical particles. However, the IIM T-matrix model needs to be iterated along the radial direction when calculating the T-matrix, which involves [...] Read more.
The invariant imbedding T-matrix (IIM T-matrix) model is regarded as one of the most promising models for calculating the scattering parameters of non-spherical particles. However, the IIM T-matrix model needs to be iterated along the radial direction when calculating the T-matrix, which involves complex calculations such as matrix inversion and multiplication. Therefore, how to improve its computational efficiency is an important problem to be solved. Focused on particles with N-fold symmetric geometry, this paper deduced the symmetry in the calculation process of the IIM T-matrix model, derived the block iteration scheme of the T-matrix, and contracted the IIM T-matrix program for particles with N-fold symmetric geometry. Discrete Dipole Approximation (DDA) and Geometrical Optics Approximation (IGOA) were employed to verify the accuracy of the improved IIM T-matrix model. The results show that the six phase matrix elements (P11, P12/P11, P22/P11, P33/P11, P34/P11 and P44/P11) calculated by our model are in good agreement with other models. The computational efficiency of the improved IIM T-matrix model was further investigated. As demonstrated by the results, the computational efficiency for the particles with N-fold symmetry improved by nearly 70% with the improvement of the symmetry of U matrix and T matrix. In conclusion, the improved model can remarkably reduce the calculation time while maintaining high accuracy. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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14 pages, 6962 KiB  
Article
Monitoring Land Vegetation from Geostationary Satellite Advanced Himawari Imager (AHI)
by Shengqi Li, Xiuzhen Han and Fuzhong Weng
Remote Sens. 2022, 14(15), 3817; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14153817 - 08 Aug 2022
Cited by 3 | Viewed by 1645
Abstract
For many years, the Advanced Very High-Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments have been widely used to monitor the condition of surface vegetation. Since the polar-orbiting satellite provides limited daily samples on surface, a completed spatial coverage of land [...] Read more.
For many years, the Advanced Very High-Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments have been widely used to monitor the condition of surface vegetation. Since the polar-orbiting satellite provides limited daily samples on surface, a completed spatial coverage of land vegetation is often relied on over multiple days of observations. In this study, observations from the Japanese geostationary satellite imager Advanced Himawari Imagers (AHI) are used to derive the surface vegetation index. The AHI reflectance at visible and near-infrared bands are first corrected to the surface reflectance by using the 6S radiative transfer model. The AHI surface reflectance from various viewing angles and solar geometry is further normalized to form an angular-independent reflectance by using a BRDF model. Finally, the surface vegetation index is calculated and synthesized from the daytime AHI data. It is found that the high-frequency AHI observations can significantly reduce the impact of clouds on compositing land NDVI and require a shorter time for a complete coverage of surface conditions. Also, a single NDVI image from AHI exhibits spatial distribution similar to that from 16 days of MODIS data. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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17 pages, 7271 KiB  
Article
Development and Evaluation of AMSU-A Cloud Detection over the Tibetan Plateau
by Jiawen Wu, Zhengkun Qin, Juan Li and Zhiwen Wu
Remote Sens. 2022, 14(9), 2116; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14092116 - 28 Apr 2022
Cited by 1 | Viewed by 1835
Abstract
Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS) data have been widely assimilated in operational forecasting systems. However, effective distinction between cloudy and clear-sky data is still an essential prerequisite for the assimilation of microwave observations. Cloud detection over the Tibetan [...] Read more.
Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS) data have been widely assimilated in operational forecasting systems. However, effective distinction between cloudy and clear-sky data is still an essential prerequisite for the assimilation of microwave observations. Cloud detection over the Tibetan Plateau has long been a challenge owing to the influence of low temperatures, terrain height, surface vegetation, and inaccurate background fields. Based on the variations in the response characteristics of different channels of AMSU-A to clouds, five AMSU-A window and low-peaking channels (channels 1–4 and 15) are chosen to establish a cloud detection index. Combined with the existing MHS cloud detection index, a cloud detection scheme over the Tibetan Plateau is proposed. Referring to VISSR-II (Stretched Visible and Infrared Spin Scan Radiometer-II) and CALIPSO (The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) cloud classification products, the detection rate of cloudy data and the rejection rate of clear-sky data under different cloud index thresholds are evaluated. Results show that the new cloud detection scheme can identify more than 80% of cloudy data on average, but this decreases to 72% for area with terrain higher than 5 km, and the false deletion rate remains stable at 45%. The detection rates of mixed clouds and cumulonimbus are higher than 90%, but it is lower than 50% for altostratus with an altitude of about 7–8 km. Comparative analysis shows that the new method is more suitable for areas with terrain higher than 700 m. Based on the cloud detection results, the effects of terrain height on the characteristics of observation error and bias are also discussed for AMSU-A channels 5 and 6. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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16 pages, 7026 KiB  
Article
Assessments of Cloud Liquid Water and Total Precipitable Water Derived from FY-3E MWTS-III and NOAA-20 ATMS
by Changjiao Dong, Fuzhong Weng and Jun Yang
Remote Sens. 2022, 14(8), 1853; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14081853 - 12 Apr 2022
Cited by 4 | Viewed by 2282
Abstract
Cloud liquid water (CLW) and total precipitable water (TPW) are two important parameters for weather and climate applications. Typically, microwave temperature sounding instruments onboard satellites are designed with two low-frequency channels at 23.8 and 31.4 GHz and can be used for retrieving CLW [...] Read more.
Cloud liquid water (CLW) and total precipitable water (TPW) are two important parameters for weather and climate applications. Typically, microwave temperature sounding instruments onboard satellites are designed with two low-frequency channels at 23.8 and 31.4 GHz and can be used for retrieving CLW and TPW over global oceans. Since MWTS-III polarization at above two frequencies is uncertain, we must first determine their polarization involved in retrieval algorithms. Through radiative transfer simulation, we found that uses of the quasi-horizontal polarization for MWTS-III can produce smaller biases between observations and simulations and the scan-angle dependence of the biases is also in a general frown pattern, which is similar to ATMS pitch-maneuver observations. After the characterization of MWTS-III polarization, CLW and TPW are derived from Microwave Temperature Sounder (MWTS-III) and are compared with those from ATMS. It is found that CLW and TPW derived from two instruments exhibit a high consistency in terms of their spatial distributions and magnitudes. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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18 pages, 6891 KiB  
Article
Influences of 1DVAR Background Covariances and Observation Operators on Retrieving Tropical Cyclone Thermal Structures
by Hao Hu and Fuzhong Weng
Remote Sens. 2022, 14(5), 1078; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14051078 - 22 Feb 2022
Cited by 4 | Viewed by 2088
Abstract
Spaceborne passive microwave sounding instruments are important for monitoring tropical cyclones (TCs) over oceans. However, previous studies have found large retrieval errors at TCs’ inner region at the lower troposphere where heavy precipitation occurs. In this study, the background error covariance matrix used [...] Read more.
Spaceborne passive microwave sounding instruments are important for monitoring tropical cyclones (TCs) over oceans. However, previous studies have found large retrieval errors at TCs’ inner region at the lower troposphere where heavy precipitation occurs. In this study, the background error covariance matrix used in the variational retrieval algorithm is designed to vary with atmospheric conditions. It is found that the errors of retrieved temperature and humidity profiles are significantly reduced under the TC conditions, when they are compared with those from using a static covariance matrix. The retrieval errors of temperature and humidity are about 1.5 K and 10–20%, respectively, in the troposphere. Moreover, the influence of different observation operators on the retrievals are also investigated. It is shown that ARMS (Advanced Radiative Transfer Modeling System) used as an observation operator can produce a higher retrieval accuracy, compared to CRTM (Community Radiative Transfer Model). For the relative humidity profile, the error can be reduced by up to 5% from ARMS. The reason may be attributed to the more comprehensive handling of the scattering from various hydrometeors in ARMS, which results in a higher retrieval accuracy under cloudy conditions. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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13 pages, 42008 KiB  
Technical Note
Analysis of the Optical Turbulence Model Using Meteorological Data
by Manman Xu, Shiyong Shao, Ningquan Weng and Qing Liu
Remote Sens. 2022, 14(13), 3085; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14133085 - 27 Jun 2022
Cited by 6 | Viewed by 1525
Abstract
The model of atmosphere optical turbulence is important in the research field of laser atmospheric transmission, and plays a key role in astronomical site selection. In this paper, the single and overall statistical analysis between different outer scale models (HMNSP99 and the Dewan [...] Read more.
The model of atmosphere optical turbulence is important in the research field of laser atmospheric transmission, and plays a key role in astronomical site selection. In this paper, the single and overall statistical analysis between different outer scale models (HMNSP99 and the Dewan model) were conducted and the results show that the HMNSP99 model has better performance with the lowest bias, root mean square error, and center root mean square error. The results of the statistical analysis of three turbulence parameters revealed that there is a correlation between turbulence parameters and statistical operators, where statistical operators increase significantly when wind shear and temperature gradient respectively exceed 0.016 s−1, 0 K/m, and the outer scale is within 2.5 m. Furthermore, a new statistical outer-scale model, the WSTG model, is proposed and the results of statistical analysis present that the WSTG model is more reliable than the HMNSP99 model in reconstructing optical turbulence strength. These results acquired from this paper add substantially to our understanding of atmosphere optical turbulence and the conclusions can be applied to improve the performance of an adaptive optics system and astronomical site selection. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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15 pages, 8024 KiB  
Technical Note
Preliminary Evaluation of FY-3E Microwave Temperature Sounder Performance Based on Observation Minus Simulation
by Xiaoli Qian, Zhengkun Qin, Juan Li, Yang Han and Guiqing Liu
Remote Sens. 2022, 14(9), 2250; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14092250 - 07 May 2022
Cited by 8 | Viewed by 1959
Abstract
The FY-3E satellite was successfully launched on 5 July 2021 and carries on board the Microwave Temperature Sounder-III (MWTS-III). In this study, the biases of MWTS-III data with respect to simulations are analyzed according to the instrument field of view and location latitude [...] Read more.
The FY-3E satellite was successfully launched on 5 July 2021 and carries on board the Microwave Temperature Sounder-III (MWTS-III). In this study, the biases of MWTS-III data with respect to simulations are analyzed according to the instrument field of view and location latitude over the Pacific region. The cloud liquid water path (CLWP) over oceans is retrieved from two new window channels at 23.8 and 31.4 GHz and is used for detecting the clouds-affected microwave sounding data. The absolute bias between the observed and simulated brightness temperature (O–B) under the clear sky point is, in general, less than 2.0 K, depending on the MWTS-III channel. The standard deviations of O-B in most channels are less 1.0 K, but they are 1–1.5 K in channels 1–4 and 17. The average and the standard deviation of O−B from the channels 1–10 shows an obvious symmetrical variation with FOV. The evaluation results all indicate good prospects for the assimilation application of FY-3E microwave sounding data. Full article
(This article belongs to the Special Issue Atmospheric and Surface Modeling, Data Assimilation, and Forecasting of Remote Sensing)
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