scholarly journals Improving Satellite-Derived Sea Surface Temperature Accuracies Using Water Vapor Profile Data

2011 ◽  
Vol 28 (1) ◽  
pp. 85-93 ◽  
Author(s):  
Ian J. Barton
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Satellite Data ◽  
Sea Surface ◽  
Radiative Transfer Model ◽  
Clear Correlation ◽  
Transfer Model ◽  
The Difference

Abstract Analyses based on atmospheric infrared radiative transfer simulations and collocated ship and satellite data are used to investigate whether knowledge of vertical atmospheric water vapor distributions can improve the accuracy of sea surface temperature (SST) estimates from satellite data. Initially, a simulated set of satellite brightness temperatures generated by a radiative transfer model with a large maritime radiosonde database was obtained. Simple linear SST algorithms are derived from this dataset, and these are then reapplied to the data to give simulated SST estimates and errors. The concept of water vapor weights is introduced in which a weight is a measure of the layer contribution to the difference between the surface temperature and that measured by the satellite. The weight of each atmospheric layer is defined as the layer water vapor amount multiplied by the difference between the SST and the midlayer temperature. Satellite-derived SST errors are then plotted against the difference in the sum of weights above an altitude of 2.5 km and that below. For the simple two-channel (with typical wavelengths of 11 and 12 μm) analysis, a clear correlation between the weights differences and the SST errors is found. A second group of analyses using ship-released radiosondes and satellite data also show a correlation between the SST errors and the weights differences. The analyses suggest that, for an SST derived using a simple two-channel algorithm, the accuracy may be improved if account is taken of the vertical distribution of water vapor above the ocean surface. For SST estimates derived using algorithms that include data from a 3.7-μm channel, there is no such correlation found.

scholarly journals Effect of Out-of-Band Response in NOAA-16 AVHRR Channel 3b on Top-of-Atmosphere Radiances Calculated with the Community Radiative Transfer Model

2009 ◽  
Vol 26 (9) ◽  
pp. 1968-1972 ◽  
Author(s):  
Quanhua Liu ◽  
Xingming Liang ◽  
Yong Han ◽  
Paul van Delst ◽  
Yong Chen ◽  
...  
Keyword(s):  
High Resolution ◽  
Radiative Transfer ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Surface Wind ◽  
Sea Surface ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Absorption Bands ◽  
Clear Sky

Abstract The Community Radiative Transfer Model (CRTM) developed at the Joint Center for Satellite Data Assimilation (JCSDA) is used in conjunction with a daily sea surface temperature (SST) and the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) atmospheric data and surface wind to calculate clear-sky top-of-atmosphere (TOA) brightness temperatures (BTs) in three Advanced Very High Resolution Radiometer (AVHRR) thermal infrared channels over global oceans. CRTM calculations are routinely performed by the sea surface temperature team for four AVHRR instruments on board the National Oceanic and Atmospheric Administration (NOAA) satellites NOAA-16, NOAA-17, and NOAA-18 and the Meteorological Operation (MetOp) satellite MetOp-A, and they are compared with clear-sky TOA BTs produced by the operational AVHRR Clear-Sky Processor for Oceans (ACSPO). It was observed that the model minus observation (M−O) bias in the NOAA-16 AVHRR channel 3b (Ch3b) centered at 3.7 μm experienced a discontinuity of ∼0.3 K when a new CRTM version 1.1 (v.1.1) was implemented in ACSPO processing in September 2008. No anomalies occurred in any other AVHRR channel or for any other platform. This study shows that this discontinuity is caused by the out-of-band response in NOAA-16 AVHRR Ch3b and by using a single layer to the NCEP GFS temperature profiles above 10 hPa for the alpha version of CRTM. The problem has been solved in CRTM v.1.1, which uses one of the six standard atmospheres to fill in the missing data above the top pressure level in the input NCEP GFS data. It is found that, because of the out-of-band response, the NOAA-16 AVHRR Ch3b has sensitivity to atmospheric temperature at high altitudes. This analysis also helped to resolve another anomaly in the absorption bands of the High Resolution Infrared Radiation Sounder (HIRS) sensor, whose radiances and Jacobians were affected to a much greater extent by this CRTM inconsistency.

scholarly journals Estimating Infrared Radiometric Satellite Sea Surface Temperature Retrieval Cold Biases in the Tropics due to Unscreened Optically Thin Cirrus Clouds

2017 ◽  
Vol 34 (2) ◽  
pp. 355-373 ◽  
Author(s):  
Jared W. Marquis ◽  
Alec S. Bogdanoff ◽  
James R. Campbell ◽  
James A. Cummings ◽  
Douglas L. Westphal ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Radiative Transfer Model ◽  
Orthogonal Polarization ◽  
Cold Bias ◽  
Transfer Model ◽  
Single Observation ◽  
Cloud Optical Depth ◽  
Level 2

AbstractPassive longwave infrared radiometric satellite–based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically thin cirrus (OTC) clouds [cloud optical depth (COD) ≤ 0.3]. Level 2 nonlinear SST (NLSST) retrievals over tropical oceans (30°S–30°N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. OTC clouds are present in approximately 25% of tropical quality-assured (QA) Aqua-MODIS Level 2 data, representing over 99% of all contaminating cirrus found. Cold-biased NLSST (MODIS, AVHRR, and VIIRS) and triple-window (AVHRR and VIIRS only) SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5-km-thick OTC cloud placed incrementally from 10.0 to 18.0 km above mean sea level for cloud optical depths between 0.0 and 0.3. Corresponding cold bias estimates for each sensor are estimated using relative Aqua-MODIS cloud contamination frequencies as a function of cloud-top height and COD (assuming they are consistent across each platform) integrated within each corresponding modeled cold bias matrix. NLSST relative OTC cold biases, for any single observation, range from 0.33° to 0.55°C for the three sensors, with an absolute (bulk mean) bias between 0.09° and 0.14°C. Triple-window retrievals are more resilient, ranging from 0.08° to 0.14°C relative and from 0.02° to 0.04°C absolute. Cold biases are constant across the Pacific and Indian Oceans. Absolute bias is lower over the Atlantic but relative bias is higher, indicating that this issue persists globally.

scholarly journals Removing Solar Radiative Effect from the VIIRS M12 Band at 3.7 μm for Daytime Sea Surface Temperature Retrievals

2014 ◽  
Vol 31 (11) ◽  
pp. 2522-2529
Author(s):  
Quanhua Liu ◽  
Alexander Ignatov ◽  
Fuzhong Weng ◽  
XingMing Liang
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Atmospheric Aerosols ◽  
Infrared Imaging ◽  
Research Work ◽  
Sea Surface ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Infrared Band ◽  
Cloud Mask

AbstractOperational sea surface temperature (SST) retrieval algorithms are stratified into nighttime and daytime. The nighttime algorithm uses two split-window Visible Infrared Imaging Radiometer Suite (VIIRS) bands—M15 and M16, centered at ~11 and ~12 m, respectively—and a shortwave infrared band—M12, centered at ~3.7 m. The M12 is most transparent and critical for accurate SST retrievals. However, it is not used during the daytime because of contamination by solar radiation, which is reflected by the ocean surface and scattered by atmospheric aerosols. As a result, daytime VIIRS SST and cloud mask products and applications are degraded and inconsistent with their nighttime counterparts. This study proposes a method to remove the solar contamination from the VIIRS M12 based on theoretical radiative transfer model analyses. The method uses either of the two VIIRS shortwave bands, centered at 1.6 m (M10) or 2.25 m (M11), to correct for the effect of solar reflectance in M12. Subsequently, the corrected daytime brightness temperature in M12 can be used as input into nighttime cloud mask and SST algorithms. Preliminary comparisons with the European Centre for Medium-Range Weather Forecasts (ECMWF) SST analysis suggest that the daytime SST products can be improved and potentially reconciled with the nighttime SST product. However, more substantial case studies and assessments using different SST products are required before the transition of this research work into operational products.

scholarly journals Long-Term Observations of Microwave Brightness Temperatures over a Metropolitan Area: Comparison of Radiometric Data and Spectra Simulated with the Use of Radiosonde Measurements

2021 ◽  
Vol 13 (11) ◽  
pp. 2061
Author(s):  
Mikhail V. Belikovich ◽  
Mikhail Yu. Kulikov ◽  
Dmitry S. Makarov ◽  
Natalya K. Skalyga ◽  
Vitaly G. Ryskin ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Elevation Angle ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Systematic Bias ◽  
Tropospheric Temperature ◽  
Absorption Model ◽  
60 Ghz ◽  
Error Budget ◽  
The Difference

Ground-based microwave radiometers are increasingly used in operational meteorology and nowcasting. These instruments continuously measure the spectra of downwelling atmospheric radiation in the range 20–60 GHz used for the retrieval of tropospheric temperature and water vapor profiles. Spectroscopic uncertainty is an important part of the retrieval error budget, as it leads to systematic bias. In this study, we analyze the difference between observed and simulated microwave spectra obtained from more than four years of microwave and radiosonde observations over Nizhny Novgorod (56.2° N, 44° E). We focus on zenith-measured and elevation-scanning data in clear-sky conditions. The simulated spectra are calculated by a radiative transfer model with the use of radiosonde profiles and different absorption models, corresponding to the latest spectroscopy research. In the case of zenith-measurements, we found a systematic bias (up to ~2 K) of simulated spectra at 51–54 GHz. The sign of bias depends on the absorption model. A thorough investigation of the error budget points to a spectroscopic nature of the observed differences. The dependence of the results on the elevation angle and absorption model can be explained by the basic properties of radiative transfer and by cloud contamination at elevation angles.

Correcting infrared satellite estimates of sea surface temperature for atmospheric water vapor attenuation

1994 ◽  
Vol 99 (C3) ◽  
pp. 5219 ◽  
Author(s):  
William J. Emery ◽  
Yunyue Yu ◽  
Gary A. Wick ◽  
Peter Schluessel ◽  
Richard W. Reynolds
Keyword(s):  
Water Vapor ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Atmospheric Water Vapor ◽  
Atmospheric Water

scholarly journals Can an Earth System Model simulate better climate change at mid-Holocene than an AOGCM? A comparison study of MIROC-ESM and MIROC3

2013 ◽  
Vol 9 (4) ◽  
pp. 1519-1542 ◽  
Author(s):  
R. Ohgaito ◽  
T. Sueyoshi ◽  
A. Abe-Ouchi ◽  
T. Hajima ◽  
S. Watanabe ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Earth System Model ◽  
Sea Surface ◽  
System Model ◽  
Earth System ◽  
Intercomparison Project ◽  
The Difference ◽  
Precipitation Enhancement

Abstract. The importance of evaluating models through paleoclimate simulations is becoming more recognized in efforts to improve climate projection. To evaluate an integrated Earth System Model, MIROC-ESM, we performed simulations in time-slice experiments for the mid-Holocene (6000 yr before present, 6 ka) and preindustrial (1850 AD, 0 ka) periods under the protocol of the Coupled Model Intercomparison Project 5/Paleoclimate Modelling Intercomparison Project 3. We first give an overview of the simulated global climates by comparing with simulations using a previous version of the MIROC model (MIROC3), which is an atmosphere–ocean coupled general circulation model. We then comprehensively discuss various aspects of climate change with 6 ka forcing and how the differences in the models can affect the results. We also discuss the representation of the precipitation enhancement at 6 ka over northern Africa. The precipitation enhancement at 6 ka over northern Africa according to MIROC-ESM does not differ greatly from that obtained with MIROC3, which means that newly developed components such as dynamic vegetation and improvements in the atmospheric processes do not have significant impacts on the representation of the 6 ka monsoon change suggested by proxy records. Although there is no drastic difference between the African monsoon representations of the two models, there are small but significant differences in the precipitation enhancement over the Sahara in early summer, which can be related to the representation of the sea surface temperature rather than the vegetation coupling in MIROC-ESM. Because the oceanic parts of the two models are identical, the difference in the sea surface temperature change is ultimately attributed to the difference in the atmospheric and/or land modules, and possibly the difference in the representation of low-level clouds.

scholarly journals Performance of the line-by-line radiative transfer model (LBLRTM) for temperature and species retrievals: IASI case studies from JAIVEx

2009 ◽  
Vol 9 (19) ◽  
pp. 7397-7417 ◽  
Author(s):  
M. W. Shephard ◽  
S. A. Clough ◽  
V. H. Payne ◽  
W. L. Smith ◽  
S. Kireev ◽  
...  
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Line Intensities ◽  
Remote Sounding ◽  
Instrument Noise ◽  
Large Peak ◽  
Line Coupling

Abstract. Presented here are comparisons between the Infrared Atmospheric Sounding instrument (IASI) and the "Line-By-Line Radiative Transfer Model" (LBLRTM). Spectral residuals from radiance closure studies during the IASI JAIVEx validation campaign provide insight into a number of spectroscopy issues relevant to remote sounding of temperature, water vapor and trace gases from IASI. In order to perform quality IASI trace gas retrievals, the temperature and water vapor fields must be retrieved as accurately as possible. In general, the residuals in the CO2 ν2 region are of the order of the IASI instrument noise. However, outstanding issues with the CO2 spectral regions remain. There is a large residual ~−1.7 K in the 667 cm−1 Q-branch, and residuals in the CO2 ν2 and N2O/CO2 ν3 spectral regions that sample the troposphere are inconsistent, with the N2O/CO2 ν3 region being too negative (warmer) by ~0.7 K. Residuals on this lower wavenumber side of the CO2 ν3 band will be improved by line parameter updates, while future efforts to reduce the residuals reaching ~−0.5 K on the higher wavenumber side of the CO2 ν3 band will focus on addressing limitations in the modeling of the CO2 line shape (line coupling and duration of collision) effects. Brightness temperature residuals from the radiance closure studies in the ν2 water vapor band have standard deviations of ~0.2–0.3 K with some large peak residuals reaching ±0.5–1.0 K. These are larger than the instrument noise indicating that systematic errors still remain. New H2O line intensities and positions have a significant impact on the retrieved water vapor, particularly in the upper troposphere where the water vapor retrievals are 10% drier when using line intensities compared with HITRAN 2004. In addition to O3, CH4, and CO, of the IASI instrument combined with an accurate forward model allows for the detection of minor species with weak atmospheric signatures in the nadir radiances, such as HNO3 and OCS.

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