Visible And Infrared Spin Scan Radiometer Research Articles

Comprehensive evaluation of the precipitable water vapor products of Fengyun satellites via GNSS data over mainland China

The Chinese meteorological satellites Fengyun (FY) have recently developed rapidly, resulting in a substantial wealth of precipitable water vapor (PWV) products. However, these latest operational PWV products still need to be systematically validated. In this paper, we focus on the PWV products derived from the FY-3D/Medium Resolution Spectral Imager II (MERSI-II), FY-2H/Visible and Infrared Spin Scan Radiometer (VISSR), and FY-4A/Advanced Geostationary Radiation Imager (AGRI), and test their performance by using the global navigation satellite system (GNSS) data. We find that FY-4A/AGRI performs best in various regions of China in 2021. Compared to GNSS-PWV, FY-4A/AGRI PWV has a correlation coefficient 0.95, a root mean square error (RMSE) of 4.67 mm, and a mean deviation (MB) of −0.73 mm, respectively. Significant discrepancies between FY-PWV and GNSS-PWV are observed in the Qinghai-Tibetan Plateau (MB: −4.86 mm for FY-2H/VISSR and − 5.12 mm for FY-4A/AGRI) and the Sichuan Basin (MB: 5.52 mm for FY-2H/VISSR, and 3.82 mm FY-4A/AGRI). All FY-PWVs exhibit season-dependent variations, and their discrepancies with GNSS-PWV during winter are smaller than in summer. Finally, we analyze the distribution and changes of water vapor in China from 2019 to 2022 using the preferred FY-4A/AGRI PWV. The results reveal a gradual decrease in the annual mean water vapor content, diminishing by approximately 0.33 mm during this period. Notably, this decrease occurs in southern China, and the water vapor content spikes in summer, culminating at 23.59 mm in 2022. Our findings strongly correlate with the precipitation changes documented in the China Climate Bulletin (2022).

Recalibration of over 35 Years of Infrared and Water Vapor Channel Radiances of the JMA Geostationary Satellites

Infrared sounding measurements of the Infrared Atmospheric Sounding Interferometer (IASI), Atmospheric Infrared Sounder (AIRS), and High-resolution Infrared Radiation Sounder/2 (HIRS/2) instruments are used to recalibrate infrared (IR; ~11 µm) channels and water vapor (WV; ~6 µm) channels of the Visible and Infrared Spin Scan Radiometer (VISSR), Japanese Advanced Meteorological Imager (JAMI), and IMAGER instruments onboard the historical geostationary satellites of the Japan Meteorological Agency (JMA). The recalibration was performed using a common recalibration method developed by European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), which can be applied to the historical geostationary satellites to produce Fundamental Climate Data Records (FCDR). Pseudo geostationary imager radiances were computed from the infrared sounding measurements and regressed against the radiances from the geostationary satellites. Recalibration factors were computed from these pseudo imager radiance pairs. This paper presents and evaluates the result of recalibration of longtime-series of IR (1978–2016) and WV (1995–2016) measurements from JMA’s historical geostationary satellites. For the IR data of the earlier satellites (Geostationary Metrological Satellite (GMS) to GMS-4) significant seasonal variations in radiometric biases were observed. This suggests that the sensors on GMS to GMS-4 were strongly affected by seasonal variations in solar illumination. The amplitudes of these seasonal variations range from 3 K for the earlier satellites to <0.4 K for the recent satellites (GMS-5, Geostationary Operational Environmental Satellite-9 (GOES-9), Multi-functional Transport Satellite-1R (MTSAT-1R) and MTSAT-2). For the WV data of GOES-9, MTSAT-1R and MTSAT-2, no seasonal variations in radiometric biases were observed. However, for GMS-5, the amplitude of seasonal variation in bias was about 0.5 K. Overall, the magnitude of the biases for GMS-5, MTSAT-1R and MTSAT-2 were smaller than 0.3 K. Finally, our analysis confirms the existence of errors due to atmospheric absorption contamination in the operational Spectral Response Function (SRF) of the WV channel of GMS-5. The method used in this study is based on the principles developed within Global Space-based Inter-calibration System (GSICS). Moreover, presented results contribute to the Inter-calibration of imager observations from time-series of geostationary satellites (IOGEO) project under the umbrella of the World Meteorological Organization (WMO) initiative Sustained and Coordinated Processing of Environmental Satellite data for Climate Monitoring (SCOPE-CM).

An Operational Precipitable Water Vapor Retrieval Algorithm for Fengyun-2F/VLSSR Using a Modified Three-Band Physical Split-Window Method

The Visible and Infrared Spin-Scan Radiometer (VISSR) onboard the Fengyun-2 (FY-2) satellite can provide valuable thermal infrared observations to help create a precipitable water vapor (PWV) product with high spatial and temporal resolutions. The current FY-2/VISSR PWV product in operation is produced by using a traditional two-band physical split-window (PSW) method, which produces low quality results under dry atmospheric conditions. Based on the sensitivity characteristics of FY-2F/VISSR water vapor channel and two split-window channels to atmospheric water vapor, this study developed a new, robust operational PWV retrieval algorithm for FY-2F to improve the operational precision of the current PWV product. The algorithm uses a modified three-band PSW method, which adds a scale for the water vapor channel in the improved three-band PSW method. Integrated PWV products from the radiosonde data in 2016 are used here to validate the precision of the PWV retrieved by the modified three-band and traditional two-band PSW methods. The mean bias, root mean square error (RMSE), and correlation coefficient of the PWV retrieved by the modified three-band PSW method are 0.28 mm, 4.53 mm, and 0.969, respectively. The accuracy is much better than the PWV retrieved by the two-band method, whose mean bias, RMSE, and correlation coefficient are 12.67 mm, 29.35 mm, and 0.23. Especially, in mid- or high-latitude regions, the RMSE of the PWV is improved from 10 to 2 mm by changing the inversion in the two-band method to the modified three-band PSW method. Furthermore, the modified three-band PSW results show a better consistency with the radiosonde PWV at any zonal belt and season than the two-band PSW results. This new algorithm could significantly improve the quality of the current FY-2F/VISSR PWV product, especially at sites where the actual PWV are lower than 15 mm.

Fractional Snow Cover Mapping from FY-2 VISSR Imagery of China

Daily fractional snow cover (FSC) products derived from optical sensors onboard low Earth orbit (LEO) satellites are often discontinuous, primarily due to prevalent cloud cover. To map the daily cloud-reduced FSC over China, we utilized clear-sky multichannel observations from the first-generation Chinese geostationary orbit (GEO) satellites (namely, the FY-2 series) by taking advantage of their high temporal resolution. The method proposed in this study combines a newly developed binary snow cover detection algorithm designed for the Visible and Infrared Spin Scan Radiometer (VISSR) onboard FY-2F with a simple linear spectral mixture technique applied to the visible (VIS) band. This method relies upon full snow cover and snow-free end-members to estimate the daily FSC. The FY-2E/F VISSR FSC maps of China were compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) FSC data based on the multiple end-member spectral mixture analysis (MESMA), and with Landsat-8 Operational Land Imager (OLI) FSC maps based on the SNOWMAP approach. The FY-2E/F VISSR FSC maps, which demonstrate a lower cloud coverage, exhibit the root mean squared errors (RMSEs) of 0.20/0.19 compared with the MODIS FSC data. When validated against the Landsat-8 OLI FSC data, the FY-2E/F VISSR FSC maps, which display overall accuracies that can reach 0.92, have an RMSE of 0.18~0.29 with R2 values ranging from 0.46 to 0.80.

Monitoring snow cover using Chinese meteorological satellite data over China

Snow cover plays an important role in hydrological processes and global climate change research. Geostationary satellites with high temporal resolution provide multiple observations in one day, which highlights their potential for monitoring real-time snow-cover information. In this paper, data from the Chinese meteorological satellites Fengyun-2D (FY-2D), Fengyun-2E (FY-2E) and Fengyun-3B (FY-3B) was used for snow-cover mapping over China. A new method of detecting snow-cover information is proposed, that combines the Visible and Infrared Spin Scan-Radiometer (VISSR) on board the geostationary satellites FY-2D and FY-2E and the Microwave Radiation Imager (MWRI) on board the polar orbiting satellite FY-3B. The snow cover estimated from Fengyun satellites was compared by the Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover products (MOD10A1 and MYD10A1), and Interactive Multisensor Snow and Ice Mapping System (IMS) snow-cover products. The Fengyun satellite snow-cover images and IMS snow-cover products were validated with meteorological station observations for the 2010–2011 and 2011–2012 winter seasons. The influence of elevation and land-cover types on the accuracy of snow retrievals was also analyzed. The results showed that the combined use of FY-2D and FY-2E VISSR data reduced cloud obscuration by 30.47% compared to the MODIS products. The validation demonstrated that the accuracy of the final multi-sensor snow-cover images was 91.28%, which is similar to that for IMS snow-cover products. This work indicates that combined data from geostationary satellites and passive microwave remote sensing monitored snow cover over China to a high level of accuracy.

A Kalman Filter-Based Method for Reconstructing GMS-5 Global Solar Radiation by Introduction of In Situ Data

Solar radiation is an important input for various land-surface energy balance models. Global solar radiation data retrieved from the Japanese Geostationary Meteorological Satellite 5 (GMS-5)/Visible and Infrared Spin Scan Radiometer (VISSR) has been widely used in recent years. However, due to the impact of clouds, aerosols, solar elevation angle and bidirectional reflection, spatial or temporal deficiencies often exist in solar radiation datasets that are derived from satellite remote sensing, which can seriously affect the accuracy of application models of land-surface energy balance. The goal of reconstructing radiation data is to simulate the seasonal variation patterns of solar radiation, using various statistical and numerical analysis methods to interpolate the missing observations and optimize the whole time-series dataset. In the current study, a reconstruction method based on data assimilation is proposed. Using a Kalman filter as the assimilation algorithm, the retrieved radiation values are corrected through the continuous introduction of local in-situ global solar radiation (GSR) provided by the China Meteorological Data Sharing Service System (Daily radiation dataset_Version 3) which were collected from 122 radiation data collection stations over China. A complete and optimal set of time-series data is ultimately obtained. This method is applied and verified in China’s northern agricultural areas (humid regions, semi-humid regions and semi-arid regions in a warm temperate zone). The results show that the mean value and standard deviation of the reconstructed solar radiation data series are significantly improved, with greater consistency with ground-based observations than the series before reconstruction. The method implemented in this study provides a new solution for the time-series reconstruction of surface energy parameters, which can provide more reliable data for scientific research and regional renewable-energy planning.

Cross-calibration of FY-2E/VISSR infrared window and water vapor channels with TERRA/MODIS

介绍了利用高精度的TERRA/MODIS观测资料对FY-2E红外窗区和水汽吸收通道进行绝对交叉定标的方法,并选用2010年5、7和12三个月的卫星数据进行了交叉定标计算。结果表明,交叉定标系数计算亮温与MODIS匹配点处实测结果非常接近,约90%的亮温偏差小于1K,其中高温区结果更稳定,偏差小于低温区,这主要是由于低温区杂散光影响显著造成的。总的说来,借助TERRA/MODIS可以实现对FY-2E/VISSR的高频次高精度的绝对定标,为FY-2E在轨替代定标提供重要的方法基础.

Estimating photosynthetically available radiation at the ocean surface from ADEOS-II global imager data

A simple, yet efficient and fairly accurate algorithm is presented to estimate photosynthetically available radiation (PAR) at the ocean surface from Global Imager (GLI) data. The algorithm utilizes plane-parallel radiation-transfer theory and separates the effects of the clear atmosphere and clouds, i.e., the planetary atmosphere is modeled as a clear atmosphere positioned above a cloud layer. PAR is computed as the difference between the incident 400–700 nm solar flux at the top of the atmosphere (known) and the solar flux reflected back to space by the atmosphere and surface (derived from GLI radiance), taking atmospheric absorption into account. Knowledge of pixel composition is not required, eliminating the need for cloud screening and arbitrary assumptions about sub-pixel cloudiness. For each GLI pixel, clear or cloudy, a daily PAR estimate is obtained. Diurnal changes in cloudiness are taken into account statistically, using a regional diurnal albedo climatology based on 5 years of Earth Radiation Budget Satellite (ERBS) data. The algorithm results are verified against other satellite estimates of PAR, the National Centers for Environmental Prediction (NCEP) reanalysis product, and in-situ measurements from fixed buoys. Agreement is generally good between GLI and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) estimates, with root-mean-squared (rms) differences of 7.9 (22%), 4.6 (13%), and 2.7 (8%) Einstein/m2/day on daily, weekly, and monthly time scales, and a bias of only 0.8–0.9 (about 2%) Einstein/m2/day. The rms differences between GLI and Visible and Infrared Spin Scan Radiometer (VISSR) estimates and between GLI and NCEP estimates are smaller and larger, respectively, on monthly time scales, i.e., 3.0 (7%) and 5.0 (14%) Einstein/m2/day, and biases are 1.1 (2%) and −0.2 (−1%) Einstein/m2/day. The comparison with buoy data also shows good agreement, with rms inaccuracies of 10.2 (23%), 6.3 (14%), and 4.5 (10%) Einstein/m2/day on daily, weekly, and monthly time scales, and slightly higher GLI values by about 1.0 (2%) Einstein/m2/day. The good statistical performance makes the algorithm suitable for large-scale studies of aquatic photosynthesis.

Detection of eruption cloud with DTII derived from GMS-5 VLSSR data

On January 2, 1996 two eruption clouds from Karymsky volcano group in Kamchatka Peninsula were detected in the imageries of VISSR (Visible and Infrared Spin Scan Radiometer) aboard the fifth Japanese Geostationary Meteorological Satellite, GMS-5. The cloud drifting ENE was brighter than that drifting SSE in the imagery of visible channel. The ENE cloud was recognizable in the infrared imagery, while the SSE cloud was not. Although ash-bearing eruption cloud is generally discriminated in the imagery of DTII (Differential Thermal Infrared Imaging) made from the data of two infrared window channels of GMS-5 VISSR, the ENE cloud was not discriminated with DTII. The data of in situ and radio sounding observations revealed that the height of the ENE cloud was around 6.3 km above sea level and originated from the crater in the Karymskoe Lake side, containing abundant ice particles, while the height of the SSE cloud was around 2.7 km above sea level. This eruption cloud was from the crater near the summit of the volcano, containing abundant ash (silicate glass). The directions of the eruption clouds coincided with those of the prevailing winds at the cloud heights. It is considered that, although the ENE cloud contained abundant ash, the radiative characteristics of the ash was greatly reduced by ice coating on ash particles. The advantage of DTII is rather reduced in the cold area due to the low temperature of the Earth's surface.

An estimation of degradation of VISSR visible sensors aboard GMS-3, GMS-4, and GMS-5

The rates of degradation of VISSR (Visible and Infrared Spin Scan Radiometer) visible radiometers on three GMS-series satellites, GMS-3, GMS-4 and GMS-5, were estimated from 1987 to 2000 by a simple method in which the long-term behaviour of the higher end of brightness was used as a calibration target. The sensitivity of GMS-3/VIS was found to have decreased by about 3.5% per year during March 1987 through to December 1989. GMS-4/VIS appeared to have deteriorated steadily at a similar rate as GMS-3/VIS except in the first five months when quicker degradation is thought to have occurred. The degradation rate of GMS-5/VIS was estimated to be about 1.1% per year, which is nearly one-third of the preceding two satellites. The results are compared with the vicarious calibration by ISCCP (International Satellite Cloud Climatology Project). Both results agree in general degrading tendency for GMS-3 and GMS-4 visible channels, but the deterioration was likely more constant than ISCCP shows. The most distinct difference is that GMS-5/VIS seems to have also been degraded in the present investigation though ISCCP shows an increase of sensitivity.

An Assessment of the Accuracy of Land Surface Temperature Determination from the GMS-5 VISSR

The Japanese Geostationary Meterological Satellite 5 (GMS-5) carries the Visible and Infrared Spin Scan Radiometer (VISSR), which has two thermal infrared channels within the “so-called” atmospheric window. These channels are similar to the split-window channels of the AVHRR-2 and are potentially useful for determining surface temperatures. The purpose of the present work is to determine the accuracy of land surface temperatures derived from the GMS-5 VISSR. For a period of 10 clear days during March 1997 hourly digital data from the GMS-5 VISSR are analyzed over two ground-truth sites in Australia. The satellite and ground-truth data are used to test the efficacy of a variety of published land surface temperature (LST) algorithms. NOAA AVHRR-2 data are also used to compare and contrast the accuracies of the LST estimates from these instruments. The results show that LST can be determined from the GMS-5 VISSR to root-mean-squared accuracy of 2–3°C with little bias. Two land surface temperature algorithms are validated and presented for use with the GMS-5 VISSR split-window radiances.

Estimation of BRDF from AVHRR Short-Wave Channels: Tests over Semiarid Australian Sites

Correction of time series of Advanced Very High Resolution Radiometer (AVHRR) short-wave reflectances for directional effects is investigated for four semiarid Australian sites. Two contrasting models for the bidirectional reflectance distribution function (BRDF), which satisfy the reciprocity condition, are fitted to all cloud-free observations within a sliding window centered on the current time. The window length is adaptive, but typically is between 10 and 20 days, corresponding to one or two repeat cycles of the polar orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA). Observations within the window include satellite elevations ranging from one horizon to the other, so that the parameters of the BRDF models are well determined. In cloudy conditions the algorithm allows the time window to be extended in small steps up to an upper limit in order to secure sufficient data to fix the parameters of the model. For the test sites examined, the algorithm appears to be robust. Once the BRDF has been estimated, times series of reflectances at the top of the atmosphere are calculated for an observer at zenith and the Sun at fixed elevation. The corrected time series of reflectances are consistent and reveal structure not apparent in the raw data. In particular, times series of normalized difference vegetation index (NDVI) computed from the BRDF-corrected reflectances show the rapid response to rain expected for semiarid test sites. The accuracy of the fitted BRDF is validated for one of the test sites by comparing reflectances observed by the visible channel of the Visible and Infrared Spin-Scan Radiometer (VISSR) on the Japanese Geostationary Meteorological Satellite (GMS) against reflectances predicted by the BRDF model. The correlation between the two sets of reflectances is excellent. Because GMS samples regions of the angular domain not seen by AVHRR, the high correlation confirms that the BRDF is well represented by the model based on AVHRR data, even for geometries unsampled by AVHRR.

Retrieval of Geophysical Parameters from GOES: Evaluation of a Split-Window Technique

Abstract The performance of a physical split-window retrieval algorithm used to retrieve skin temperature (ST) and precipitable water (PW) from Geostationary Operational Environmental Satellites’ (GOES) infrared measurements is evaluated. The evaluation assesses the potential of using GOES measurements to provide accurate retrieval products for climate research studies. Several algorithm performance issues are addressed, including the time of retrieval (diurnal effects), sensitivity to the first-guess field, and an evaluation of performance differences associated with the split-window channel characteristics of the GOES-7 VISSR (Visible and Infrared Spin Scan Radiometer) Atmospheric Sounder (VAS) and the GOES-8 imager and sounder. The investigation used a mesoscale model, initialized by radiosonde data, to generate a simulated atmosphere representative of a case study characterized by summertime conditions over the east-central United States. Synthetic GOES channel radiances were developed from the surrog...

A Comparison of the First-Guess Dependence of Precipitable Water Estimates from Three Techniques Using GOES Data

Abstract This paper evaluates and intercompares three existing algorithms for calculating precipitable water (PW) using infrared radiances from the GOES-7 VISSR (Visible and Infrared Spin Scan Radiometer) Atmospheric Sounder (VAS). The study exclusively uses simulated, rather than observed, VAS radiances in all retrievals. The National Environmental Satellite, Data, and Information Service simultaneous physical algorithm utilizes data from all 12 VAS channels and produces a vertical profile of temperature and dewpoint from which PW can be calculated. The Chesters technique and Jedlovec’s physical split-window technique retrieve PW from radiances in the two split window channels without first computing a dewpoint profile. All three algorithms also can be used with GOES-8 and GOES-9 data. These algorithms have not been intercompared previously. Each is applied on case days having wide variations in temperature and moisture. The algorithms are supplied with first-guess information of varying accuracy to asse...

A satellite‐based estimate of evapotranspiration over Amazonia

Abstract If rainfall, storage and flux divergence are known, evapotranspiration can be estimated as the residual in a budget of atmospheric moisture. We describe a new approach to moisture‐budget estimates of Amazon evapotranspiration. Synoptic observations (and numerical model analyses from the U.S. National Meteorological Center) are combined with wind, humidity and rain information retrieved from radiances measured by the Geostationary Operational Environmental Satellite (GOES). Rainfall is inferred from the thermal infrared channel of the Visible and Infrared Spin Scan Radiometer (VISSR). Humidity is retrieved from the VISSR Atmospheric Sounder (VAS). Winds are inferred from both VISSR and VAS images, using visible, thermal infrared and water vapor bands. Satellite and station or model information is merged by means of a recursive filter. The GOES‐budget approach was tested over a three‐day period from May 1987. Our estimate of evapotranspiration over the basin, 9 mm/d, is unrealistically large. A sen...

Comparison of Nimbus-7 SMMR and GOES-1 VISSR Atmospheric Liquid Water Content

Abstract Vertically integrated atmospheric liquid water content derived from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) brightness temperatures and from GOES-1 Visible and Infrared Spin-Scan Radiometer (VISSR) radiances in the visible are compared over the Indian Ocean during MONEX (monsoon experiment). In the retrieval procedure, Wilheit and Chang&apos algorithm and Stephens' parameterization schemes are applied to the SMMR and VISSR data, respectively. The results indicate that in the 0–100 mg cm−2 range of liquid water content considered, the correlation coefficient between the two types of estimates is 0.83 (0.81– 0.85 at the 99 percent confidence level). The Wilheit and Chang algorithm, however, yields values lower than those obtained with Stephens's schemes by 24.5 mg cm−2 on the average, and occasionally the SMMR-based values are negative. Alternative algorithms are proposed for use with SMMR data, which eliminate the bias, augment the correlation coefficient, and reduce the rms dif...

Environmental Conditions Associated with the Dallas Microburst Storm Determined from Satellite Soundings

Abstract The thermodynamic structure of the troposphere in the vicinity of the microburst storm at Dallas-Ft. Worth Airport (DFW), Texas on 2 August 1985 is described. The analysis was based principally on a set of vertical soundings from the Visible and Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) onboard the Geostationary Operational Environmental Satellite (GOES), valid about 1 h before the occurrence of peak surface winds. Convection in the DFW area developed in a gradient of stability on the west side of a tongue of low lifted index and high precipitable water. The lapse rates in the 850 mb-700 mb layer were large (8°–9°C km−1). Vertical profiles of VAS data showed that DFW was in a transition zone in which conditions became drier at all levels and slightly warmer near 500 mb to the south and southwest. The midlevel warming reduced the buoyant energy available above cloud base, thus acting as a capping mechanism for the unstable, northward- moving low-level air. The potential insta...

Simulations of the GOES visible sensor to changing surface and atmospheric conditions

Numerical experiments have been conducted to simulate the GOES Visible and Infrared Spin Scan Radiometer (VISSR) visible sensor's response under varying surface and atmospheric conditions, as a function of solar zenith angle. The possible bias in the information obtained with this limited spectral response sensor was assessed by comparing the narrow‐band filtered clear‐sky planetary albedo, as observable with the VISSR, with the broadband (0.3–2.5 μm) unfiltered planetary albedo under the same environmental conditions. Four cases of wavelength‐dependent surface albedo (snow, meadow, dry sand, and water) and three atmospheric conditions have been simulated. It was demonstrated that the relationship between the filtered and the broadband planetary albedo depends primarily on the assumptions made about the magnitude and wavelength dependence of the surface albedo and, to a lesser extent, on the atmospheric conditions. Under certain circumstances (e.g., dry sand, water), the two were found to be in close agreement. For snow the filtered albedo exceeds the broadband albedo for all zenith angles; for meadow the broadband albedo will exceed the filtered albedo. Regression equations were derived to transform the VISSR filtered albedo to unfiltered broadband albedo for each surface type.

Integration of satellite data with other data for nowcasting

The Program for Regional Observing and Forecasting Services (PROFS) operates its own Geostationary Operational Environmental Satellite (GOES) mode AA and mode A groundstations and generates both VISSR (Visible and Infrared Spin-Scan Radiometer) and VAS (VISSR Atmospheric Sounder) image products for its advanced meteorological workstation in real time. Derived VAS temperature soundings are received daily from the University of Wisconsin-Madison. PROFS has been improving its real-time workstation since 1981 and has used it to study mesoscale nowcasting. The workstation provides efficient access, display, and loop control of satellite products and other conventional and advanced meteorological data. Data are integrated by displaying products on standard map projections so that imagery and graphics can be combined at the workstation, by using data from a variety of sources to compute image products, and through machine analysis and modeling. The workstation's capabilities have been assessed during PROFS real-time nowcasting experiments. Nowcasts are made with the workstation, and chase teams track and observe severe weather to evaluate these nowcasts. Five-minute rapid scan visible imagery was found to be quite useful in conjunction with Doppler radar data for nowcasting. In contrast, 30-minute infrared (IR) and VAS data were beneficial for short-range forecasts. Loops of VAS water vapor imagery along with conventional IR imagery at national and regional scales showed the greatest overall utility of the satellite imagery studied. Processed sounding data showed some success depicting unstable regions prior to convection.

Optimized retrievals of precipitable water fields from combinations of VAS satellite and conventional surface observations

VISSR (visible and infrared spin‐scan radiometer) atmospheric sounder (VAS) radiances and conventional surface temperature and dewpoint data are used in several combinations within a regression approach to determine the optimum resolution and accuracy of precipitable water (PW) fields retrieved from satellite observations. Point retrievals at radiosonde stations are used to determine the numerical accuracy of each retrieval technique, and image sequences of the retrieved PW fields are used to determine the temporal stability and spatial coherence of mesoscale PW features. VAS channels 5, 6, 7, and 8 (at 13, 4.5, 12, and 11 μm) and the surface dewpoint contribute the most information to regression‐based retrievals of PW. The most accurate PW retrievals are obtained when radiances are averaged to a resolution of 15 to 60 km. A physical “split‐window” approach provides better PW estimates than regression when only the 11‐ and 12‐μm VAS channels are available (as when the satellite operates in a multispectral image mode) or when radiosonde‐based training is limited to only one time period.