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

2019 ◽  
Vol 11 (10) ◽  
pp. 1189 ◽  
Author(s):  
Tasuku Tabata ◽  
Viju O. John ◽  
Rob A. Roebeling ◽  
Tim Hewison ◽  
Jörg Schulz
Keyword(s):  
Water Vapor ◽  
Seasonal Variations ◽  
Spectral Response ◽  
Japan Meteorological Agency ◽  
Climate Data ◽  
Atmospheric Infrared Sounder ◽  
European Organization ◽  
Geostationary Satellites ◽  
Global Space ◽  
Atmospheric Sounding

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).

Intercalibration of Broadband Geostationary Imagers Using AIRS

2009 ◽  
Vol 26 (4) ◽  
pp. 746-758 ◽  
Author(s):  
Mathew M. Gunshor ◽  
Timothy J. Schmit ◽  
W. Paul Menzel ◽  
David C. Tobin
Keyword(s):  
Spectral Resolution ◽  
Spectral Response ◽  
High Spectral Resolution ◽  
Spectral Gaps ◽  
Atmospheric Infrared Sounder ◽  
Earth Observing System ◽  
First Approximation ◽  
Atmospheric Sounding ◽  
Calibration Accuracy ◽  
Polar Orbiting Satellite

Abstract Geostationary simultaneous nadir observations (GSNOs) are collected for Earth Observing System (EOS) Atmospheric Infrared Sounder (AIRS) on board Aqua and a global array of geostationary imagers. The imagers compared in this study are on (Geostationary Operational Environmental Satellites) GOES-10, GOES-11, GOES-12, (Meteorological Satellites) Meteosat-8, Meteosat-9, Multifunctional Transport Satellite-IR (MTSAT-IR), and Fenguyun-2C (FY-2C). It has been shown that a single polar-orbiting satellite can be used to intercalibrate any number of geostationary imagers. Using a high-spectral-resolution infrared sensor, in this case AIRS, brings this method closer to an absolute reckoning of imager calibration accuracy based on laboratory measurements of the instrument’s spectral response. An intercalibration method is presented here, including a method of compensating for AIRS’ spectral gaps, along with results for approximately 22 months of comparisons. The method appears to work very well for most bands, but there are still unresolved issues with bands that are not spectrally covered well by AIRS (such as the water vapor bands and the 8.7-μm band on Meteosat). To the first approximation, most of the bands on the world’s geostationary imagers are reasonably well calibrated—that is, they compare to within 1 K of a standard reference (AIRS). The next step in the evolution of geostationary intercalibration is to use Infrared Atmospheric Sounding Interferometer (IASI) data. IASI is a high-spectral-resolution instrument similar to AIRS but without significant spectral gaps.

scholarly journals Land Surface Albedo Derived on a Ten Daily Basis from Meteosat Second Generation Observations: The NRT and Climate Data Record Collections from the EUMETSAT LSA SAF

2018 ◽  
Vol 10 (8) ◽  
pp. 1262 ◽  
Author(s):  
Dominique Carrer ◽  
Suman Moparthy ◽  
Gabriel Lellouch ◽  
Xavier Ceamanos ◽  
Florian Pinault ◽  
...  
Keyword(s):  
Land Surface ◽  
Surface Albedo ◽  
Second Generation ◽  
Weather Prediction ◽  
Retrieval Algorithm ◽  
Climate Data ◽  
European Organization ◽  
Geostationary Satellites ◽  
Data Record ◽  
Climate Data Record

Land surface albedo determines the splitting of downwelling solar radiation into components which are either reflected back to the atmosphere or absorbed by the surface. Land surface albedo is an important variable for the climate community, and therefore was defined by the Global Climate Observing System (GCOS) as an Essential Climate Variable (ECV). Within the scope of the Satellite Application Facility for Land Surface Analysis (LSA SAF) of EUMETSAT (European Organization for the Exploitation of Meteorological Satellites), a near-real time (NRT) daily albedo product was developed in the last decade from observations provided by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary satellites of the Meteosat Second Generation (MSG) series. In this study we present a new collection of albedo satellite products based on the same satellite data. The MSG Ten-day Albedo (MTAL) product incorporates MSG observations over 31 days with a frequency of NRT production of 10 days. The MTAL collection is more dedicated to climate analysis studies compared to the daily albedo that was initially designed for the weather prediction community. For this reason, a homogeneous reprocessing of MTAL was done in 2018 to generate a climate data record (CDR). The resulting product is called MTAL-R and has been made available to the community in addition to the NRT version of the MTAL product which has been available for several years. The retrieval algorithm behind the MTAL products comprises three distinct modules: One for atmospheric correction, one for daily inversion of a semi-empirical model of the bidirectional reflectance distribution function, and one for monthly composition, that also determines surface albedo values. In this study the MTAL-R CDR is compared to ground surface measurements and concomitant albedo products collected by sensors on-board polar-orbiting satellites (SPOT-VGT and MODIS). We show that MTAL-R meets the quality requirements if MODIS or SPOT-VGT are considered as reference. This work leads to 14 years of production of geostationary land surface albedo products with a guaranteed continuity in the LSA SAF for the future years with the forthcoming third generation of European geostationary satellites.

The Global Space-Based Inter-Calibration System

2011 ◽  
Vol 92 (4) ◽  
pp. 467-475 ◽  
Author(s):  
M. Goldberg ◽  
G. Ohring ◽  
J. Butler ◽  
C. Cao ◽  
R. Datla ◽  
...  
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Reference Standards ◽  
Japan Meteorological Agency ◽  
Observation System ◽  
Climate Data ◽  
Calibration System ◽  
China Meteorological Administration ◽  
Common Reference ◽  
Global Space

The Global Space-based Inter-Calibration System (GSICS) is a new international program to assure the comparability of satellite measurements taken at different times and locations by different instruments operated by different satellite agencies. Sponsored by the World Meteorological Organization and the Coordination Group for Meteorological Satellites, GSICS will intercalibrate the instruments of the international constellation of operational low-earth-orbiting (LEO) and geostationary earth-orbiting (GEO) environmental satellites and tie these to common reference standards. The intercomparability of the observations will result in more accurate measurements for assimilation in numerical weather prediction models, construction of more reliable climate data records, and progress toward achieving the societal goals of the Global Earth Observation System of Systems. GSICS includes globally coordinated activities for prelaunch instrument characterization, onboard routine calibration, sensor intercomparison of near-simultaneous observations of individual scenes or overlapping time series, vicarious calibration using Earth-based or celestial references, and field campaigns. An initial strategy uses high-accuracy satellite instruments, such as the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)'s Centre National d'Études Spatiales (CNES) Infrared Atmospheric Sounding Interferometer (IASI), as space-based reference standards for intercalibrating the operational satellite sensors. Examples of initial intercalibration results and future plans are presented. Agencies participating in the program include the Centre National d'Études Spatiales, China Meteorological Administration, EUMETSAT, Japan Meteorological Agency, Korea Meteorological Administration, NASA, National Institute of Standards and Technology, and NOAA.

scholarly journals A Global Climatology of Temperature and Water Vapor Variance Scaling from the Atmospheric Infrared Sounder

2009 ◽  
Vol 22 (20) ◽  
pp. 5558-5576 ◽  
Author(s):  
Brian H. Kahn ◽  
João Teixeira
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Seasonal Variations ◽  
Atmospheric Infrared Sounder ◽  
Upper Troposphere ◽  
Clear Sky ◽  
Power Law Exponent ◽  
Large Length ◽  
The Tropics ◽  
Scale Break

Abstract A global climatology of height-resolved variance scaling within the troposphere is presented using derived temperature (T) and water vapor (q) profiles from the Atmospheric Infrared Sounder (AIRS). The power-law exponent of T variance scaling approaches 1.0 outside of the tropics at scales &gt;500–800 km, but it is closer to 0.3 at scales &lt;500 km, similar to exponents obtained from aircraft campaigns, numerical modeling, and theoretical studies. The T exponents in the tropics at all scales become less than 0.3, with a similar pattern observed within the boundary layer in some extratropical regions. For q, the variance scaling differs substantially from T with exponents near 0.5–0.6 in parts of the tropics and subtropics with little to no scale break, showing some consistency with a very limited set of aircraft and satellite studies. Scaling differences as a function of land and ocean, altitude, and cloudy- and clear-sky scenes are quantified. Both T and q exponents indicate peak magnitudes in the midtroposphere and reductions are observed near the boundary layer and upper troposphere. Seasonal variations of T and q scaling reveal a stronger seasonal cycle over land than ocean, especially for T at large length scales. While the zonal variations of T and q exponents vary significantly for scales &lt;500 km, the seasonal variations are much smaller in magnitude. The exponents derived from AIRS could eventually be extrapolated to smaller scales in the absence of additional scale breaks &lt;150 km to provide useful information for constraining subgrid-scale cloud parameterizations.

Comparison of upper tropospheric water vapor from GOES, Raman lidar, and cross-chain loran atmospheric sounding system measurements

1994 ◽  
Vol 99 (D10) ◽  
pp. 21005 ◽  
Author(s):  
B. J. Soden ◽  
S. A. Ackerman ◽  
D. O'C. Starr ◽  
S. H. Melfi ◽  
R. A. Ferrare
Keyword(s):  
Water Vapor ◽  
Raman Lidar ◽  
Atmospheric Sounding

scholarly journals Retrieval of water vapor using SSM/I and its relation with the onset of monsoon

2004 ◽  
Vol 22 (8) ◽  
pp. 3079-3083 ◽  
Author(s):  
R. P. Singh ◽  
S. Dey ◽  
A. K. Sahoo ◽  
M. Kafatos
Keyword(s):  
Water Vapor ◽  
Interannual Variability ◽  
Seasonal Variations ◽  
Indian Monsoon ◽  
Precipitable Water ◽  
Climatic Conditions ◽  
Satellite Monitoring ◽  
Onset Date ◽  
Microwave Imager ◽  
Onset Of Monsoon

Abstract. The seasonal variations and interannual variability of total precipitable water (TPW) deduced from the Special Sensor Microwave Imager (SSM/I) satellite over oceanic regions of the Indian sub-continent during the years between 1988 to 1998 show characteristic behavior. The weekly patterns of TPW are found to be closely related to the dynamics of the climatic conditions and the onset date of monsoon. The present results show that the satellite monitoring of TPW may prove as a good and reliable indicator in forecasting Indian monsoon.

scholarly journals Climate Data Records from Meteosat First Generation Part I: Simulation of Accurate Top-of-Atmosphere Spectral Radiance over Pseudo-Invariant Calibration Sites for the Retrieval of the In-Flight Visible Spectral Response

2018 ◽  
Vol 10 (12) ◽  
pp. 1959 ◽  
Author(s):  
Yves Govaerts ◽  
Frank Rüthrich ◽  
Viju John ◽  
Ralf Quast
Keyword(s):  
Spectral Function ◽  
First Generation ◽  
Spectral Response ◽  
Radiative Properties ◽  
Spectral Radiance ◽  
Climate Data ◽  
Recovery Method ◽  
Infrared Imager ◽  
Data Record ◽  
Climate Data Record

Meteosat First-Generation satellites have acquired more than 30 years of observations that could potentially be used for the generation of a Climate Data Record. The availability of harmonized and accurate a Fundamental Climate Data Record is a prerequisite to such generation. Meteosat Visible and Infrared Imager radiometers suffer from inaccurate pre-launch spectral function characterization and spectral ageing constitutes a serious limitation to achieve such prerequisite. A new method was developed for the retrieval of the pre-launch instrument spectral function and its ageing. This recovery method relies on accurately simulated top-of-atmosphere spectral radiances matching observed digital count values. This paper describes how these spectral radiances are simulated over pseudo-invariant targets such as open ocean, deep convective clouds and bright desert surface. The radiative properties of these targets are described with a limited number of parameters of known uncertainty. Typically, a single top-of-atmosphere radiance spectrum can be simulated with an estimated uncertainty of about 5%. The independent evaluation of the simulated radiance accuracy is also addressed in this paper. It includes two aspects: the comparison with narrow-band well-calibrated radiometers and a spectral consistency analysis using SEVIRI/HRVIS band on board Meteosat Second Generation which was accurately characterized pre-launch. On average, the accuracy of these simulated spectral radiances is estimated to be about ±2%.

Homogenized Water Vapor Absorption Band Radiances From International Geostationary Satellites

2019 ◽  
Vol 46 (17-18) ◽  
pp. 10599-10608 ◽  
Author(s):  
Zhenglong Li ◽  
Jun Li ◽  
Mathew Gunshor ◽  
Szu‐Chia Moeller ◽  
Timothy J. Schmit ◽  
...  
Keyword(s):  
Water Vapor ◽  
Absorption Band ◽  
Water Vapor Absorption ◽  
Geostationary Satellites ◽  
Vapor Absorption

scholarly journals Cloud-Resolving 4D-Var Assimilation of Doppler Wind Lidar Data on a Meso-Gamma-Scale Convective System

2014 ◽  
Vol 142 (12) ◽  
pp. 4484-4498 ◽  
Author(s):  
Takuya Kawabata ◽  
Hironori Iwai ◽  
Hiromu Seko ◽  
Yoshinori Shoji ◽  
Kazuo Saito ◽  
...  
Keyword(s):  
Water Vapor ◽  
Radial Velocity ◽  
Inversion Layer ◽  
Rainfall Event ◽  
Japan Meteorological Agency ◽  
Heavy Rainfall Event ◽  
Convective System ◽  
Vapor Flux ◽  
Wind Lidar ◽  
Doppler Wind Lidar

Abstract The authors evaluated the effects of assimilating three-dimensional Doppler wind lidar (DWL) data on the forecast of the heavy rainfall event of 5 July 2010 in Japan, produced by an isolated mesoscale convective system (MCS) at a meso-gamma scale in a system consisting of only warm rain clouds. Several impact experiments using the nonhydrostatic four-dimensional variational data assimilation system (NHM-4DVAR) and the Japan Meteorological Agency nonhydrostatic model with a 2-km horizontal grid spacing were conducted in which 1) no observations were assimilated (NODA), 2) radar reflectivity and radial velocity determined by Doppler radar and precipitable water vapor determined by GPS satellite observations were assimilated (CTL), and 3) radial velocity determined by DWL were added to the CTL experiment (LDR) and five data denial and two observational error sensitivity experiments. Although both NODA and CTL simulated an MCS, only LDR captured the intensity, location, and horizontal scale of the observed MCS. Assimilating DWL data improved the wind direction and speed of low-level airflows, thus improving the accuracy of the simulated water vapor flux. The examination of the impacts of specific assimilations and assigned observation errors showed that assimilation of all data types is important for forecasting intense MCSs. The investigation of the MCS structure showed that large amounts of water vapor were supplied to the rainfall event by southerly flow. A midlevel inversion layer led to the production of exclusively liquid water particles in the MCS, and in combination with the humid airflow into the MCS, this inversion layer may be another important factor in its development.

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