scholarly journals Climate Model–Simulated Diurnal Cycles in HIRS Clear-Sky Brightness Temperatures

2012 ◽  
Vol 25 (17) ◽  
pp. 5845-5863 ◽  
Author(s):  
Ian A. MacKenzie ◽  
Simon F. B. Tett ◽  
Anders V. Lindfors
Keyword(s):  
Water Vapor ◽  
Brightness Temperature ◽  
Climate Models ◽  
Tropospheric Temperature ◽  
Diurnal Variability ◽  
Diurnal Cycles ◽  
Clear Sky ◽  
Recent Climate ◽  
Diurnal Behavior ◽  
Sky Brightness

Abstract Clear-sky brightness temperature measurements from the High-Resolution Infrared Radiation Sounder (HIRS) are simulated with two climate models via a radiative transfer code. The models are sampled along the HIRS orbit paths to derive diurnal climatologies of simulated brightness temperature analogous to an existing climatology based on HIRS observations. Simulated and observed climatologies are compared to assess model performance and the robustness of the observed climatology. Over land, there is good agreement between simulations and observations, with particularly high consistency for the tropospheric temperature channels. Diurnal cycles in the middle- and upper-tropospheric water vapor channels are weak in both simulations and observations, but the simulated diurnal brightness temperature ranges are smaller than are observed with different phase and there are also intermodel differences. Over sea, the absence of diurnal variability in the models’ sea surface temperatures causes an underestimate of the small diurnal cycles measured in the troposphere. The simulated and observed climatologies imply similar diurnal sampling biases in the HIRS record for the tropospheric temperature channels, but for the upper-tropospheric water vapor channel, differences in the contributions of the 24- and 12-hourly diurnal harmonics lead to differences in the implied bias. Comparison of diurnal cycles derived from HIRS-like and full model sampling suggests that the HIRS measurements are sufficient to fully constrain the diurnal behavior. Overall, the results suggest that recent climate models well represent the major processes driving the diurnal behavior of clear-sky brightness temperature in the HIRS channels. This encourages further studies of observed and simulated climate trends over the HIRS era.

scholarly journals Testing Climate Models Using Thermal Infrared Spectra

2008 ◽  
Vol 21 (9) ◽  
pp. 1863-1875 ◽  
Author(s):  
Stephen Leroy ◽  
James Anderson ◽  
John Dykema ◽  
Richard Goody
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Climate Models ◽  
Tropospheric Temperature ◽  
Strong Constraint ◽  
Detection Techniques ◽  
Clear Sky ◽  
Stratospheric Temperature ◽  
Occultation Data ◽  
The Tropics

Abstract An approach to test climate models with observations is presented. In this approach, it is possible to directly observe the longwave feedbacks of the climate system in time series of annual average outgoing longwave spectra. Tropospheric temperature, stratospheric temperature, water vapor, and carbon dioxide have clear and distinctive signatures in the infrared spectrum, and it is possible to detect trends of these signals unambiguously from trends in the outgoing longwave spectrum by optimal detection techniques. This approach is applied to clear-sky data in the tropics simulated from the output of an ensemble of climate models. Estimates of the water vapor–longwave feedback by this approach agree to within estimated errors with truth, and it is likely that an uncertainty of 50% can be obtained in 20 yr of a continuous time series. The correlation of tropospheric temperature and water vapor anomalies can provide a constraint on the water vapor–longwave feedback to 5% uncertainty in 20 yr, or 7% in 10 yr. Thus, it should be possible to place a strong constraint on climate models, which currently show a range of 30% in the water vapor–longwave feedback, in just 10 yr. These results may not hold in the presence of clouds, however, and so it may be necessary to supplement time series of outgoing longwave spectra with GPS radio occultation data, which are insensitive to clouds.

scholarly journals Climatological Diurnal Cycles in Clear-Sky Brightness Temperatures from the High-Resolution Infrared Radiation Sounder (HIRS)

2011 ◽  
Vol 28 (10) ◽  
pp. 1199-1205 ◽  
Author(s):  
Anders V. Lindfors ◽  
Ian A. Mackenzie ◽  
Simon F. B. Tett ◽  
Lei Shi
Keyword(s):  
Monte Carlo ◽  
Fourier Series ◽  
High Resolution ◽  
Infrared Radiation ◽  
Lower Troposphere ◽  
Sampling Bias ◽  
Diurnal Cycles ◽  
Clear Sky ◽  
Brightness Temperatures ◽  
Sky Brightness

Abstract A climatology of the diurnal cycles of HIRS clear-sky brightness temperatures was developed based on measurements over the period 2002–07. This was done by fitting a Fourier series to monthly gridded brightness temperatures of HIRS channels 1–12. The results show a strong land–sea contrast with stronger diurnal cycles over land, and extending from the surface up to HIRS channel 6 or 5, with regional maxima over the subtropics. Over seas, the diurnal cycles are generally small and therefore challenging to detect. A Monte Carlo uncertainty analysis showed that more robust results are reached by aggregating the data zonally before applying the fit. The zonal fits indicate that small diurnal cycles do exist over sea. The results imply that for a long-lived satellite such as NOAA-14, drift in the overpass time can cause a diurnal sampling bias of more than 5 K for channel 8 (surface and lower troposphere).

scholarly journals Carbon monoxide mixing ratios over Oklahoma between 2002 and 2009 retrieved from Atmospheric Emitted Radiance Interferometer spectra

2010 ◽  
Vol 3 (5) ◽  
pp. 1319-1331 ◽  
Author(s):  
L. Yurganov ◽  
W. McMillan ◽  
C. Wilson ◽  
M. Fischer ◽  
S. Biraud ◽  
...  
Keyword(s):  
Water Vapor ◽  
Great Plains ◽  
Microwave Radiometer ◽  
Precipitable Water ◽  
Retrieval Algorithm ◽  
Southern Great Plains ◽  
Diurnal Cycles ◽  
Mixing Ratios ◽  
Clear Sky ◽  
The Tropics

Abstract. CO mixing ratios for the lowermost 2-km atmospheric layer were retrieved from downwelling infrared (IR) radiance spectra of the clear sky measured between 2002 and 2009 by a zenith-viewing Atmospheric Emitted Radiance Interferometer (AERI) deployed at the Southern Great Plains (SGP) observatory of the Atmospheric Radiation Measurements (ARM) Program near Lamont, Oklahoma. A version of a published earlier retrieval algorithm was improved and validated. Archived temperature and water vapor profiles retrieved from the same AERI spectra through automated ARM processing were used as input data for the CO retrievals. We found the archived water vapor profiles required additional constraint using SGP Microwave Radiometer retrievals of total precipitable water vapor. A correction for scattered solar light was developed as well. The retrieved CO was validated using simultaneous independently measured CO profiles from an aircraft. These tropospheric CO profiles were measured from the surface to altitudes of 4572 m a.s.l. once or twice a week between March 2006 and December 2008. The aircraft measurements were supplemented with ground-based CO measurements using a non-dispersive infrared gas correlation instrument at the SGP and retrievals from the Atmospheric IR Sounder (AIRS) above 5 km to create full tropospheric CO profiles. Comparison of the profiles convolved with averaging kernels to the AERI CO retrievals found a squared correlation coefficient of 0.57, a standard deviation of ±11.7 ppbv, a bias of -16 ppbv, and a slope of 0.92. Averaged seasonal and diurnal cycles measured by the AERI are compared with those measured continuously in situ at the SGP in the boundary layer. Monthly mean CO values measured by the AERI between 2002 and 2009 are compared with those measured by the AIRS over North America, the Northern Hemisphere mid-latitudes, and over the tropics.

scholarly journals Assimilation of GOES-13 Imager Clear-Sky Water Vapor (6.5 μm) Radiances into a Warn-on-Forecast System

2018 ◽  
Vol 146 (4) ◽  
pp. 1077-1107 ◽  
Author(s):  
Thomas A. Jones ◽  
Xuguang Wang ◽  
Patrick Skinner ◽  
Aaron Johnson ◽  
Yongming Wang
Keyword(s):  
Water Vapor ◽  
High Resolution ◽  
Data Assimilation ◽  
Initial Conditions ◽  
Positive Impact ◽  
Horizontal Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Tropospheric Temperature ◽  
Clear Sky

A prototype convection-allowing system using the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model and employing an ensemble Kalman filter (EnKF) data assimilation technique has been developed and used during the spring 2016 and 2017 Hazardous Weather Testbeds. This system assimilates WSR-88D reflectivity and radial velocity, geostationary satellite cloud water path (CWP) retrievals, and available surface observations over a regional domain with a 3-km horizontal resolution at 15-min intervals, with 3-km initial conditions provided by an experimental High-Resolution Rapid Refresh ensemble (HRRR-e). However, no information on upper-level thermodynamic conditions in cloud-free regions is currently assimilated, as few timely observations exist. One potential solution is to also assimilate clear-sky satellite radiances, which provide information on mid- and upper-tropospheric temperature and moisture conditions. This research assimilates GOES-13 imager water vapor band (6.5 μm) radiances using the GSI-EnKF system to take advantage of the Community Radiative Transfer Model (CRTM) integration. Results using four cases from May 2016 showed that assimilating radiances generally had a neutral-to-positive impact on the model analysis, reducing humidity bias and/or errors at the appropriate model levels where verification observations were present. The effects on high-impact weather forecasts, as verified against forecast reflectivity and updraft helicity, were mixed. Three cases (9, 22, and 24 May) showed some improvement in skill, while the other (25 May) performed worse, despite the improved environment. This research represents the first step in designing a high-resolution ensemble data assimilation system to use GOES-16 Advanced Baseline Imager data, which provides additional water vapor bands and increased spatial and temporal resolution.

scholarly journals Impact of Assimilating Advanced Himawari Imager Channel 16 Data on Precipitation Prediction over the Haihe River Basin

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1253
Author(s):  
Hongxiang Ouyang ◽  
Zhengkun Qin ◽  
Juan Li
Keyword(s):  
Water Vapor ◽  
Brightness Temperature ◽  
River Basin ◽  
Geostationary Satellite ◽  
Haihe River Basin ◽  
Tropospheric Temperature ◽  
Haihe River ◽  
Precipitation Forecasting ◽  
Precipitation Prediction ◽  
The Haihe River Basin

Assimilation of high-resolution geostationary satellite data is of great value for precise precipitation prediction in regional basins. The operational geostationary satellite imager carried by the Himawari-8 satellite, Advanced Himawari Imager (AHI), has two additional water vapor channels and four other channels compared with its predecessor, MTSAT-2. However, due to the uncertainty in surface parameters, AHI surface-sensitive channels are usually not assimilated over land, except for the three water vapor channels. Previous research showed that the brightness temperature of AHI channel 16 is much more sensitive to the lower-tropospheric temperature than to surface emissivity, which is similar to the three water vapor channels 8–10. As a follow-up work, this paper evaluates the effectiveness of assimilating brightness temperature observations over land from both the three AHI water vapor channels and channel 16 to improve watershed precipitation forecasting through both case analysis (in the Haihe River basin, China) and batch tests. It is found that assimilating AHI channel 16 can improve the upstream near-surface atmospheric temperature forecast, which in turn affects the development of downstream weather systems. The precipitation forecasting test results indicate that adding the terrestrial observations of channel 16 to the assimilation of AHI data can improve short-term precipitation forecasting in the basin.

Intercomparison of Radiation Codes in Climate Models (ICRCCM): Longwave Clear-Sky Results—A Workshop Summary

1988 ◽  
Vol 69 (1) ◽  
pp. 40-48 ◽  
Author(s):  
Frederick M. Luther ◽  
Robert G. Ellingson ◽  
Yves Fouquart ◽  
Stephen Fels ◽  
Noelle A. Scott ◽  
...  
Keyword(s):  
Water Vapor ◽  
Climate Models ◽  
Model Performance ◽  
Continuum Absorption ◽  
Line Model ◽  
Clear Sky ◽  
Radiative Processes ◽  
Workshop Summary ◽  
Change Mechanisms

An international program of intercomparison of radiation models has been initiated because of the central role of radiative processes in many proposed climate change mechanisms. Models ranging from the most detailed (line-by-line) to the most-highly parameterized have been compared with each other and with selected aircraft observations. Although line-by-line-model fluxes tend to agree with each other to within one percent (if the water-vapor–continuum absorption is ignored), the less-detailed models show a spread of 10–20 percent. The spread is even larger (30–40 percent) for the sensitivities of the models to changes in important radiation variables, such as carbon dioxide amounts and water-vapor amounts. These spreads are disturbingly large. Lacking highly accurate flux observations from within the atmosphere, it has been customary to regard line-by-line–model results as “the truth.” However, uncertainties in the physics of line wings and in the proper treatment of the water-vapor continuum make it impossible for the line-by-line models to provide an absolute reference for evaluating less-detailed models. Therefore, a dedicated surface-based field measurement program is recommended in order to properly evaluate model performance; the goal would be to use sophisticated spectrometers to measure accurately spectral radiances rather than integrated fluxes.

scholarly journals Evaluating the Diurnal Cycle of Upper-Tropospheric Ice Clouds in Climate Models Using SMILES Observations

2015 ◽  
Vol 72 (3) ◽  
pp. 1022-1044 ◽  
Author(s):  
Jonathan H. Jiang ◽  
Hui Su ◽  
Chengxing Zhai ◽  
T. Janice Shen ◽  
Tongwen Wu ◽  
...  
Keyword(s):  
Diurnal Cycle ◽  
Climate Models ◽  
Space Station ◽  
Temporal Patterns ◽  
Spatial And Temporal Patterns ◽  
Ice Clouds ◽  
Diurnal Variability ◽  
Diurnal Cycles ◽  
Ice Cloud ◽  
The Tropics

Abstract Upper-tropospheric ice cloud measurements from the Superconducting Submillimeter Limb Emission Sounder (SMILES) on the International Space Station (ISS) are used to study the diurnal cycle of upper-tropospheric ice cloud in the tropics and midlatitudes (40°S–40°N) and to quantitatively evaluate ice cloud diurnal variability simulated by 10 climate models. Over land, the SMILES-observed diurnal cycle has a maximum around 1800 local solar time (LST), while the model-simulated diurnal cycles have phases differing from the observed cycle by −4 to 12 h. Over ocean, the observations show much smaller diurnal cycle amplitudes than over land with a peak at 1200 LST, while the modeled diurnal cycle phases are widely distributed throughout the 24-h period. Most models show smaller diurnal cycle amplitudes over ocean than over land, which is in agreement with the observations. However, there is a large spread of modeled diurnal cycle amplitudes ranging from 20% to more than 300% of the observed over both land and ocean. Empirical orthogonal function (EOF) analysis on the observed and model-simulated variations of ice clouds finds that the first EOF modes over land from both observation and model simulations explain more than 70% of the ice cloud diurnal variations and they have similar spatial and temporal patterns. Over ocean, the first EOF from observation explains 26.4% of the variance, while the first EOF from most models explains more than 70%. The modeled spatial and temporal patterns of the leading EOFs over ocean show large differences from observations, indicating that the physical mechanisms governing the diurnal cycle of oceanic ice clouds are more complicated and not well simulated by the current climate models.

scholarly journals HIRS channel 12 brightness temperature dataset and its correlations with major climate indices

2013 ◽  
Vol 13 (14) ◽  
pp. 6907-6920 ◽  
Author(s):  
L. Shi ◽  
C. J. Schreck III ◽  
V. O. John
Keyword(s):  
Water Vapor ◽  
Brightness Temperature ◽  
Regional Climate ◽  
Climate Indices ◽  
Teleconnection Patterns ◽  
Clear Sky ◽  
Vapor Channel ◽  
Brightness Temperatures ◽  
Spatial Coverage ◽  
The Tropics

Abstract. A new version of the High-Resolution Infrared Radiation Sounder (HIRS) upper tropospheric water vapor channel (channel 12) brightness temperature dataset is developed using intersatellite calibrated data. In this dataset, only those pixels affected by upper tropospheric clouds are discarded. Compared to the previous version that was based on column-clear-sky data, the new version has much better daily spatial coverage. The HIRS observation patterns are compared to microwave sounder measurements. The differences between the two types of sounders vary with respect to brightness temperature with larger differences for higher (dry) values. Correlations between the HIRS upper tropospheric water vapor channel brightness temperatures and several major climate indices show strong signals during cold seasons. The selected climate indices track climate variation signals covering regions from the tropics to the poles. Qualitatively, moist signals are correlated with troughs and ascending branches of the circulation, while dry signals occur with ridges and descent. These correlations show the potential of using the upper tropospheric water vapor channel brightness temperature dataset together with a suite of many atmospheric variables to monitor regional climate changes and locate global teleconnection patterns.

scholarly journals Assimilation of INSAT-3D imager water vapour clear sky brightness temperature in the NCMRWF’s assimilation and forecast system

2019 ◽  
Vol 128 (7) ◽  
Author(s):  
S Indira Rani ◽  
Ruth Taylor ◽  
Priti Sharma ◽  
M T Bushair ◽  
Buddhi Prakash Jangid ◽  
...  
Keyword(s):  
Brightness Temperature ◽  
Water Vapour ◽  
Forecast System ◽  
Clear Sky ◽  
Sky Brightness

scholarly journals A Novel Approach for Selective Reconstruction of Cloud-Contaminated Satellite Images

2011 ◽  
Vol 28 (8) ◽  
pp. 1028-1035 ◽  
Author(s):  
Bipasha Paul Shukla ◽  
P. K. Pal ◽  
P. C. Joshi
Keyword(s):  
High Resolution ◽  
Brightness Temperature ◽  
Satellite Imagery ◽  
Satellite Images ◽  
Weather Prediction ◽  
Climate Research ◽  
Clear Sky ◽  
Novel Approach ◽  
Sky Brightness ◽  
Very High

Abstract The paper presents a robust technique for cloud clearing of satellite imagery. The proposed algorithm combines mathematical morphological techniques with a conventional cloud clearing scheme to restore clear sky values. The derived equivalent clear sky brightness temperature plays a very important role in numerical weather prediction, climate research, and monitoring. The developed methodology uses distinct approaches for reconstruction of partially clouded domains and overcast regions. It is found that the algorithm is especially suitable for pre- or postmonsoon months, where there is a high percentage of partially cloudy and small overcast cloudy regions. The algorithm is tested for the Kalpana Very High Resolution Radiometer (VHRR) thermal infrared (TIR) band data acquired over the oceanic region adjoining India throughout the month of May 2009. It is found that the algorithm is able to clear 25% of cloudy pixels with an RMSE of 1.2 K for brightness temperature.

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