A clear-sky radiance archive from Meteosat “water vapor” observations

Abstract This paper examines the controls on global precipitation that are evident in the transient experiments conducted using coupled climate models collected for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). The change in precipitation, water vapor, clouds, and radiative heating of the atmosphere evident in the 1% increase in carbon dioxide until doubled (1pctto2x) scenario is examined. As noted in other studies, the ensemble-mean changes in water vapor as carbon dioxide is doubled occur at a rate similar to that predicted by the Clausius–Clapeyron relationship. The ratio of global changes in precipitation to global changes in water vapor offers some insight on how readily increased water vapor is converted into precipitation in modeled climate change. This ratio ɛ is introduced in this paper as a gross indicator of the global precipitation efficiency under global warming. The main findings of this paper are threefold. First, increases in the global precipitation track increase atmospheric radiative energy loss and the ratio of precipitation sensitivity to water vapor sensitivity is primarily determined by changes to this atmospheric column energy loss. A reference limit to this ratio is introduced as the rate at which the emission of radiation from the clear-sky atmosphere increases as water vapor increases. It is shown that the derived efficiency based on the simple ratio of precipitation to water vapor sensitivities of models in fact closely matches the sensitivity derived from simple energy balance arguments involving changes to water vapor emission alone. Second, although the rate of increase of clear-sky emission is the dominant factor in the change to the energy balance of the atmosphere, there are two important and offsetting processes that contribute to ɛ in the model simulations studied: One involves a negative feedback through cloud radiative heating that acts to reduce the efficiency; the other is the global reduction in sensible heating that counteracts the effects of the cloud feedback and increases the efficiency. These counteracting feedbacks only apply on the global scale. Third, the negative cloud radiative heating feedback occurs through reductions of cloud amount in the middle troposphere, defined as the layer between 680 and 440 hPa, and by slight global cloud decreases in the lower troposphere. These changes act in a manner to expose the warmer atmosphere below to high clouds, thus resulting in a net warming of the atmospheric column by clouds and a negative feedback on the precipitation.

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

Journal of Climate ◽

10.1175/jcli-d-11-00552.1 ◽

2012 ◽

Vol 25 (17) ◽

pp. 5845-5863 ◽

Cited By ~ 6

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.

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Approximate model of clear-sky radiance distribution

10.1117/12.676652 ◽

2006 ◽

Author(s):

ChunPing Yang ◽

Jian Wu ◽

Rong Qiu ◽

XiaoDong Wang ◽

Miao Liu ◽

...

Keyword(s):

Approximate Model ◽

Clear Sky ◽

Sky Radiance ◽

Radiance Distribution

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Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-8-10755-2015 ◽

2015 ◽

Vol 8 (10) ◽

pp. 10755-10792

Author(s):

A. M. Dzambo ◽

D. D. Turner ◽

E. J. Mlawer

Keyword(s):

Water Vapor ◽

Statistical Significance ◽

Microwave Radiometer ◽

Precipitable Water ◽

Upper Troposphere ◽

Clear Sky ◽

Microwave Radiometers ◽

The Impact ◽

Dry Bias ◽

Better Than

Abstract. Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV), downwelling radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km MSL), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS). The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from ground-based microwave radiometers at tropical, mid-latitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the ground-based retrievals. The two closure activities – done for clear-sky scenes – use the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG- and MILO-corrected RH are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes. The cause of this statistical significance is likely explained by the fact the WANG correction also accounts for cloud cover – a condition not accounted for in the radiance closure experiments.

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Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms

Atmospheric Measurement Techniques ◽

10.5194/amt-9-1613-2016 ◽

2016 ◽

Vol 9 (4) ◽

pp. 1613-1626 ◽

Cited By ~ 9

Author(s):

Andrew M. Dzambo ◽

David D. Turner ◽

Eli J. Mlawer

Keyword(s):

Water Vapor ◽

Statistical Significance ◽

Microwave Radiometer ◽

Precipitable Water ◽

Upper Troposphere ◽

Clear Sky ◽

Microwave Radiometers ◽

The Impact ◽

Dry Bias ◽

Better Than

Abstract. Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV), downwelling radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km m.s.l.), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS). The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from ground-based microwave radiometers at tropical, midlatitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the ground-based retrievals. The two closure activities – done for clear-sky scenes – use the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG- and MILO-corrected RHs are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes. The cause of this statistical significance is likely explained by the fact the WANG correction also accounts for cloud cover – a condition not accounted for in the radiance closure experiments.

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Clear-Sky Surface Solar Radiation and the Radiative Effect of Aerosol and Water Vapor Based on Simulations and Satellite Observations over Northern China

Remote Sensing ◽

10.3390/rs12121931 ◽

2020 ◽

Vol 12 (12) ◽

pp. 1931

Author(s):

Guang Zhang ◽

Yingying Ma

Keyword(s):

Water Vapor ◽

Solar Radiation ◽

Inner Mongolia ◽

Northern China ◽

Satellite Observations ◽

Radiative Effect ◽

Surface Solar Radiation ◽

Clear Sky ◽

South Central ◽

West Central

The distribution and trend of clear-sky surface solar radiation (SSR) and the quantitative effects of aerosol and water vapor are investigated in northern China during 2001–2015 using radiation simulations and satellite observations. Clear-sky SSR in northern China is high in summer and low in winter, which is dominated by astronomical factors and strongly modulated by the seasonal variations of radiative effects of aerosol (ARE) and water vapor (WVRE). The larger variation of WVRE than ARE indicates that water vapor plays a more important role in moderating the seasonal variation of clear-sky SSR. Clear-sky SSR shows an overall decreasing trend of –0.12 W/m2 per year, with decrease more strongly than –0.60 W/m2 per year in west-central Shandong and increase (about 0.40 W/m2) in south-central Inner Mongolia. The consistency of spatial distribution and high correlation between clear-sky SSR and ARE trend indicate that the clear-sky SSR trend is mainly determined by aerosol variation. Dust mass concentration decreases about 16% in south-central Inner Mongolia from 2001 to 2015, resulting in the increase in clear-sky SSR. In contrast, sulfate aerosol increases about 92% in west-central Shandong, leading to the decreasing trend of clear-sky SSR.

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A Model for the Angular Distribution of Sky Radiance

Journal of Solar Energy Engineering ◽

10.1115/1.3266154 ◽

1980 ◽

Vol 102 (3) ◽

pp. 196-202 ◽

Cited By ~ 34

Author(s):

F. C. Hooper ◽

A. P. Brunger

Keyword(s):

Continuous Distribution ◽

Total Solar Radiation ◽

Diffuse Component ◽

Clear Sky ◽

Solar Radiation Incident ◽

The Mean ◽

Rms Error ◽

Sky Radiance ◽

Sky Conditions ◽

Overcast Sky

A flexible mathematical model is introduced which describes the radiance of the dome of the sky under various conditions. This three-component continuous distribution (TCCD) model is compounded by the superposition of three separate terms, isotropic, circumsolar and horizon-brightening factors, each representing the contribution of a distinguishable sky characteristic. In use, a particular sky condition is characterized by the values of the coefficients of each of these three terms, defining the distribution of the total diffuse component. The TCCD model has been demonstrated to fit both the normalized clear sky data and the normalized overcast sky data with an RMS error of about ten percent of the mean overall sky radiance. By extension the model could describe variable or partly clouded sky conditions. The model will permit improvement in the prediction of the total solar radiation incident upon a surface of given tilt and orientation, such as that of a solar collector.

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A Clear Sky Model of Diffuse Sky Radiance

Journal of Solar Energy Engineering ◽

10.1115/1.3268184 ◽

1987 ◽

Vol 109 (1) ◽

pp. 9-14 ◽

Cited By ~ 17

Author(s):

F. C. Hooper ◽

A. P. Brunger ◽

C. S. Chan

Keyword(s):

Direct Determination ◽

Field Of View ◽

Mean Bias Error ◽

Bias Error ◽

Mean Square ◽

Clear Sky ◽

Expected Values ◽

Sky Radiance ◽

Made In

A model, previously proposed, describing the sky radiance as a continuous function, has been calibrated from 11,000 individual measurements made in scans taken across springtime skies in Toronto using a narrow field of view radiometer. The model reproduces the measured sky radiance with a mean bias error under five percent and a root mean square error only slightly larger than the standard deviation of the measurements. The model is applied to the calculation of the ratio of the clear sky diffuse irradiance on a slope to that on a horizontal surface. Charts are presented for the direct determination of the expected values of these ratios for surfaces at three tilts and at any azimuth.

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