scholarly journals Toward autonomous surface-based infrared remote sensing of polar clouds: cloud-height retrievals

2016 ◽  
Vol 9 (8) ◽  
pp. 3641-3659 ◽  
Author(s):  
Penny M. Rowe ◽  
Christopher J. Cox ◽  
Von P. Walden
Keyword(s):  
Polar Regions ◽  
Active Sensors ◽  
Polar Climate ◽  
Infrared Radiance ◽  
Cloud Height ◽  
Infrared Spectrometer ◽  
Instrument Noise ◽  
Atmospheric State ◽  
Polar Clouds ◽  
Different Sources

Abstract. Polar regions are characterized by their remoteness, making measurements challenging, but an improved knowledge of clouds and radiation is necessary to understand polar climate change. Infrared radiance spectrometers can operate continuously from the surface and have low power requirements relative to active sensors. Here we explore the feasibility of retrieving cloud height with an infrared spectrometer that would be designed for use in remote polar locations. Using a wide variety of simulated spectra of mixed-phase polar clouds at varying instrument resolutions, retrieval accuracy is explored using the CO2 slicing/sorting and the minimum local emissivity variance (MLEV) methods. In the absence of imposed errors and for clouds with optical depths greater than  ∼  0.3, cloud-height retrievals from simulated spectra using CO2 slicing/sorting and MLEV are found to have roughly equivalent high accuracies: at an instrument resolution of 0.5 cm−1, mean biases are found to be  ∼  0.2 km for clouds with bases below 2 and −0.2 km for higher clouds. Accuracy is found to decrease with coarsening resolution and become worse overall for MLEV than for CO2 slicing/sorting; however, the two methods have differing sensitivity to different sources of error, suggesting an approach that combines them. For expected errors in the atmospheric state as well as both instrument noise and bias of 0.2 mW/(m2 sr cm−1), at a resolution of 4 cm−1, average retrieval errors are found to be less than  ∼  0.5 km for cloud bases within 1 km of the surface, increasing to  ∼  1.5 km at 4 km. This sensitivity indicates that a portable, surface-based infrared radiance spectrometer could provide an important complement in remote locations to satellite-based measurements, for which retrievals of low-level cloud are challenging.

scholarly journals Toward autonomous surface-based infrared remote sensing of polar clouds: Cloud height retrievals

2016 ◽  
Author(s):  
Penny M. Rowe ◽  
Christopher J. Cox ◽  
Von P. Walden
Keyword(s):  
Single Layer ◽  
Polar Regions ◽  
Active Sensors ◽  
Retrieval Accuracy ◽  
Infrared Radiance ◽  
Low Clouds ◽  
Cloud Height ◽  
Polar Clouds ◽  
Signal Accuracy ◽  
High Clouds

Abstract. Polar regions are characterized by their remoteness, making measurements challenging, but an improved knowledge of clouds and radiation is necessary to understand polar climate change. Infrared radiance spectrometers can operate continuously from the surface and have low power requirements relative to active sensors. Here we explore the feasibility of retrieving cloud height with an infrared spectrometer that would be designed for use in remote locations, for single-layer, mixed-phase polar clouds, using the CO2 slicing/sorting and the Minimum Local Emissivity Variance (MLEV) methods. In the absence of imposed errors and for clouds with optical depths greater than ∼0.3, cloud height retrievals from simulated spectra using CO2 slicing/sorting and MLEV are found to have roughly equivalent, high accuracies: at an instrument resolution of 0.5 cm−1, mean biases are found to be ∼0.2 km for low clouds (bases below 2 km) and −0.2 km for medium-to-high clouds (hereafter “high clouds”). Accuracy is found to decrease with decreasing cloud signal and increasing cloud height (independent of signal). Accuracy also decreases with coarsening resolution and becomes worse overall for MLEV than for CO2 slicing/sorting; however, the two methods have differing sensitivity to different sources of error, suggesting an approach that combines them. In the presence of errors, the dependence of retrieval accuracy on resolution is weakened. Further, errors have a small effect on retrievals of low clouds but a large effect on high clouds. Expected errors in the atmospheric state indicate that at a resolution of 0.5 cm−1, instrument noise level and bias of 0.1 mW/(m2 sr cm−1) would permit a retrieval accuracy of −2 ± 2 km for high clouds and ∼0.2 ± 0.5 km for low clouds, for both methods. This study highlights the sensitivity of surface-based infrared spectrometers to low clouds prevalent in polar regions.

How do polar clouds and precipitation affect global warming?

2021 ◽  
Author(s):  
Jennifer Kay
Keyword(s):  
Global Warming ◽  
Climate Model ◽  
Research Problem ◽  
Cloud Feedback ◽  
Polar Regions ◽  
Unsolved Research Problem ◽  
Cloud Feedbacks ◽  
Surface Warming ◽  
Polar Clouds ◽  
Radiative Feedbacks

<p>Understanding the influence of clouds and precipitation on global warming remains an important unsolved research problem. This talk presents an overview of this topic, with a focus on recent observations, theory, and modeling results for polar clouds. After a general introduction, experiments that disable cloud radiative feedbacks or “lock the clouds” within a state‐of‐the‐art,  well‐documented, and observationally vetted climate model will be presented. Through comparison of idealized greenhouse warming experiments with and without cloud locking, the sign and magnitude cloud feedbacks can be quantified. Global cloud feedbacks increase both global and Arctic warming by around 25%. In contrast, disabling Arctic cloud feedbacks has a negligible influence on both Arctic and global surface warming. Do observations and theory support a positive global cloud feedback and a weak Arctic cloud feedback?  How does precipitation affect polar cloud feedbacks? What are the implications especially for climate change in polar regions?  </p>

scholarly journals Matching radiative transfer models and radiosonde data from the EPS/Metop Sodankylä campaign to IASI measurements

2011 ◽  
Vol 4 (6) ◽  
pp. 1177-1189 ◽  
Author(s):  
X. Calbet ◽  
R. Kivi ◽  
S. Tjemkes ◽  
F. Montagner ◽  
R. Stuhlmann
Keyword(s):  
Radiative Transfer ◽  
Water Vapour ◽  
Spectral Region ◽  
Radiosonde Data ◽  
Radiative Transfer Models ◽  
Frost Point ◽  
Instrument Noise ◽  
Atmospheric State ◽  
Dry Bias ◽  
Transfer Models

Abstract. Radiances observed from IASI are compared to calculated ones. Calculated radiances are obtained using several radiative transfer models (OSS, LBLRTM v11.3 and v11.6) on best estimates of the atmospheric state vectors. The atmospheric state vectors are derived from cryogenic frost point hygrometer and humidity dry bias corrected RS92 measurements flown on sondes launched 1 h and 5 min before IASI overpass time. The temperature and humidity best estimate profiles are obtained by interpolating or extrapolating these measurements to IASI overpass time. The IASI observed and calculated radiances match to within one sigma IASI instrument noise in the spectral region where water vapour is a strong absorber (wavenumber, ν, in the range of 1500 ≤ ν ≤ 1570 and 1615 ≤ ν ≤ 1800 cm−1).

I—Special Problems in Polar Regions

1951 ◽  
Vol 4 (02) ◽  
pp. 126-135
Author(s):  
J. D. D. Moore
Keyword(s):  
High Latitude ◽  
Polar Regions ◽  
Polar Climate ◽  
Definition Of

The three basic problems of navigation are determination of position, definition of direction, and steering the direction required. In polar regions, all these problems are affected either by the high latitude, or by the polar climate, or by both. In this paper the various problems which arise are reviewed, possible solutions are discussed, and it is indicated where further research and experiment might be desirable.

scholarly journals Matching radiative transfer models and radiosonde data from the EPS/MetOp Sodankylä campaign to IASI measurements

2010 ◽  
Vol 3 (5) ◽  
pp. 4497-4530 ◽  
Author(s):  
X. Calbet ◽  
R. Kivi ◽  
S. Tjemkes ◽  
F. Montagner ◽  
R. Stuhlmann
Keyword(s):  
Radiative Transfer ◽  
Radiosonde Data ◽  
Radiative Transfer Models ◽  
Frost Point ◽  
Instrument Noise ◽  
Atmospheric State ◽  
Humidity Profiles ◽  
Dry Bias ◽  
Transfer Models ◽  
Best Estimates

Abstract. Radiances observed from IASI are compared to calculated ones. Calculated radiances are obtained using several radiative transfer models (OSS, LBLRTM v11.3 and v11.6) on best estimates of the atmospheric state vectors. The atmospheric state vectors are derived from cryogenic frost point hygrometer and humidity dry bias corrected RS92 measurements flown on sondes launched 1 h and 5 min before IASI overpass time. The temperature and humidity profiles are finally obtained by interpolating or extrapolating these measurements to IASI overpass time. The IASI observed and calculated radiances match to within one sigma IASI instrument noise in the wavenumber, ν, range of 1500 ≤ ν ≤ 1570 and 1615 ≤ ν ≤ 1800 cm−1 .

Investigating the dynamics of an Antarctic coastal polynya using a regional climate model

2020 ◽  
Author(s):  
Pierre-Vincent Huot ◽  
Thierry Fichefet ◽  
Christoph Kittel ◽  
Nicolas Jourdain ◽  
Xavier Fettweis
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
Coupled Model ◽  
Polar Regions ◽  
Coupled Models ◽  
Polar Climate ◽  
Coastal Polynya ◽  
The Impact ◽  
Regional Coupled Model

<p>Coastal polynyas of the Southern Ocean, such as the Mertz Glacier Polynya, are paramount features of the polar climate. They allow for exchanges of heat, momentum and moisture between the atmosphere and ocean where sea ice usually prevents such interactions. Polynyas are believed to have a profound impact on polar and global climate, thanks to their sustained sea ice production and the associated formation of Dense Shelf Waters. Less is known, however, about the impact of polynyas on the atmosphere. Changes in air properties and winds induced by heat and moisture flux could for instance affect precipitation regime over the ice sheet or sea ice. As the formation and evolution of coastal polynyas are tied to the state of the atmosphere, such changes can also induce important feedbacks to polynyas dynamics. Such processes have almost never been studied, whether on the field or with the help of coupled models. Here, we propose to describe the behavior of a coastal polynya and its relationship with the ocean and atmosphere. To do so, we developed a regional coupled model of the ocean, sea ice and atmosphere (including interactive basal melt of ice shelves) and applied it to the Adélie Land area, in East Antarctica. The dynamics of the Mertz Glacier Polynya is described, together with its impact on the atmosphere, sea ice growth, dense water production and ice shelf melt. To assess the importance of potential feedbacks, we compare the dynamics of the polynya from the coupled model to a forced ocean-sea ice model. We then use the regional coupled model to investigate the implications of the Mertz ice tongue calving in early 2010 which led to a drastic decrease of the Mertz Glacier Polynya extent. This experiment aims at investigating the sensitivity of the atmosphere to the activity of the polynya and to evaluate the impact of the calving on regional climate. This work improves the understanding of the Mertz Glacier Polynya dynamics, and of the impact of coastal polynyas on polar climate. It also constitutes an additional step in the modelling of the polar regions in Earth System Models.</p>

scholarly journals A simulation-experiment-based assessment of retrievals of above-cloud temperature and water vapor using a hyperspectral infrared sounder

2021 ◽  
Vol 14 (8) ◽  
pp. 5717-5734
Author(s):  
Jing Feng ◽  
Yi Huang ◽  
Zhipeng Qu
Keyword(s):  
Water Vapor ◽  
Prior Knowledge ◽  
Simulation Experiment ◽  
Effective Radius ◽  
Active Sensors ◽  
Convective Storms ◽  
Knowledge Based ◽  
Infrared Radiance ◽  
Ice Water Content ◽  
Ice Water

Abstract. Measuring atmospheric conditions above convective storms using spaceborne instruments is challenging. The operational retrieval framework of current hyperspectral infrared sounders adopts a cloud-clearing scheme that is unreliable in overcast conditions. To overcome this issue, previous studies have developed an optimal estimation method that retrieves the temperature and humidity above high thick clouds by assuming a slab of cloud. In this study, we find that variations in the effective radius and density of cloud ice near the tops of convective clouds lead to non-negligible spectral uncertainties in simulated infrared radiance spectra. These uncertainties cannot be fully eliminated by the slab-cloud assumption. To address this problem, a synergistic retrieval method is developed here. This method retrieves temperature, water vapor, and cloud properties simultaneously by incorporating observations from active sensors in synergy with infrared radiance spectra. A simulation experiment is conducted to evaluate the performance of different retrieval strategies using synthetic radiance data from the Atmospheric Infrared Sounder (AIRS) and cloud data from CloudSat/CALIPSO. In this experiment, we simulate infrared radiance spectra from convective storms through a combination of a numerical weather prediction model and a radiative transfer model. The simulation experiment shows that the synergistic method is advantageous, as it shows high retrieval sensitivity to the temperature and ice water content near the cloud top. The synergistic method more than halves the root-mean-square errors in temperature and column integrated water vapor compared to prior knowledge based on the climatology. It can also improve the quantification of the ice water content and effective radius compared to prior knowledge based on retrievals from active sensors. Our results suggest that existing infrared hyperspectral sounders can detect the spatial distributions of temperature and humidity anomalies above convective storms.

scholarly journals Evaluations of the Climatologies of Three Latest Cloud Satellite Products Based on Passive Sensors (ISCCP-H, Two CERES) against the CALIPSO-GOCCP

2021 ◽  
Vol 13 (24) ◽  
pp. 5150
Author(s):  
Faisal S. Boudala ◽  
Jason A. Milbrandt
Keyword(s):  
Pacific Islands ◽  
Polar Regions ◽  
Active Sensors ◽  
Tropical Regions ◽  
Satellite Retrieval ◽  
The Pacific ◽  
Summer Hemisphere ◽  
Passive Sensors ◽  
Winter Hemisphere ◽  
Global Mean

In this study, the climatologies of three different satellite cloud products, all based on passive sensors (CERES Edition 4.1 [EBAF4.1 and SYN4.1] and ISCCP–H), were evaluated against the CALIPSO-GOCCP (GOCCP) data, which are based on active sensors and, hence, were treated as the reference. Based on monthly averaged data (ocean + land), the passive sensors underestimated the total cloud cover (TCC) at lower (TCC < 50%), but, overall, they correlated well with the GOCCP data (r = 0.97). Over land, the passive sensors underestimated the TCC, with a mean difference (MD) of −2.6%, followed by the EBAF4.1 and ISCCP-H data with a MD of −2.0%. Over the ocean, the CERES-based products overestimated the TCC, but the SYN4.1 agreed better with the GOCCP data. The ISCCP-H data on average underestimated the TCC both over oceanic and continental regions. The annual mean TCC distribution over the globe revealed that the passive sensors generally underestimated the TCC over continental dry regions in northern Africa and southeastern South America as compared to the GOCCP, particularly over the summer hemisphere. The CERES datasets overestimated the TCC over the Pacific Islands between the Indian and eastern Pacific Oceans, particularly during the winter hemisphere. The ISCCP-H data also underestimated the TCC, particularly over the southern hemisphere near 60° S where the other datasets showed a significantly enhanced TCC. The ISCCP data also showed less TCC when compared against the GOCCP data over the tropical regions, particularly over the southern Pacific and Atlantic Oceans near the equator and also over the polar regions where the satellite retrieval using the passive sensors was generally much more challenging. The calculated global mean root meant square deviation value for the ISCCP-H data was 6%, a factor of 2 higher than the CERES datasets. Based on these results, overall, the EBAF4.1 agreed better with the GOCCP data.

scholarly journals The QME AERI LBLRTM: A Closure Experiment for Downwelling High Spectral Resolution Infrared Radiance

2004 ◽  
Vol 61 (22) ◽  
pp. 2657-2675 ◽  
Author(s):  
D. D. Turner ◽  
D. C. Tobin ◽  
S. A. Clough ◽  
P. D. Brown ◽  
R. G. Ellingson ◽  
...  
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Continuum Absorption ◽  
Clear Sky ◽  
Infrared Radiance ◽  
Wide Range ◽  
Atmospheric State

Abstract Research funded by the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program has led to significant improvements in longwave radiative transfer modeling over the last decade. These improvements, which have generally come in small incremental changes, were made primarily in the water vapor self- and foreign-broadened continuum and the water vapor absorption line parameters. These changes, when taken as a whole, result in up to a 6 W m−2 improvement in the modeled clear-sky downwelling longwave radiative flux at the surface and significantly better agreement with spectral observations. This paper provides an overview of the history of ARM with regard to clear-sky longwave radiative transfer, and analyzes remaining related uncertainties in the ARM state-of-the-art Line-by-Line Radiative Transfer Model (LBLRTM). A quality measurement experiment (QME) for the downwelling infrared radiance at the ARM Southern Great Plains site has been ongoing since 1994. This experiment has three objectives: 1) to validate and improve the absorption models and spectral line parameters used in line-by-line radiative transfer models, 2) to assess the ability to define the atmospheric state, and 3) to assess the quality of the radiance observations that serve as ground truth for the model. Analysis of data from 1994 to 1997 made significant contributions to optimizing the QME, but is limited by small but significant uncertainties and deficiencies in the atmospheric state and radiance observations. This paper concentrates on the analysis of QME data from 1998 to 2001, wherein the data have been carefully selected to address the uncertainties in the 1994–97 dataset. Analysis of this newer dataset suggests that the representation of self-broadened water vapor continuum absorption is 3%–8% too strong in the 750–1000 cm−1 region. The dataset also provides information on the accuracy of the self- and foreign-broadened continuum absorption in the 1100–1300 cm−1 region. After accounting for these changes, remaining differences in modeled and observed downwelling clear-sky fluxes are less than 1.5 W m−2 over a wide range of atmospheric states.

scholarly journals Intersatellite Radiance Biases for the High-Resolution Infrared Radiation Sounders (HIRS) on board NOAA-15, -16, and -17 from Simultaneous Nadir Observations

2005 ◽  
Vol 22 (4) ◽  
pp. 381-395 ◽  
Author(s):  
Changyong Cao ◽  
Hui Xu ◽  
Jerry Sullivan ◽  
Larry McMillin ◽  
Pubu Ciren ◽  
...  
Keyword(s):  
High Resolution ◽  
Infrared Radiation ◽  
Spectral Response ◽  
Lapse Rate ◽  
Polar Regions ◽  
Spatial Uniformity ◽  
Accuracy And Precision ◽  
Instrument Noise ◽  
Highly Correlated

Abstract Intersatellite radiance comparisons for the 19 infrared channels of the High-Resolution Infrared Radiation Sounders (HIRS) on board NOAA-15, -16, and -17 are performed with simultaneous nadir observations at the orbital intersections of the satellites in the polar regions, where each pair of the HIRS views the same earth target within a few seconds. Analysis of such datasets from 2000 to 2003 reveals unambiguous intersatellite radiance differences as well as calibration anomalies. The results show that in general, the intersatellite relative biases are less than 0.5 K for most HIRS channels. The large biases in different channels differ in both magnitude and sign, and are likely to be caused by the differences and measurement uncertainties in the HIRS spectral response functions. The seasonal bias variation in the stratosphere channels is found to be highly correlated with the lapse rate factor approximated by the channel radiance differences. The method presented in this study works particularly well for channels sensing the stratosphere because of the relative spatial uniformity and stability of the stratosphere, for which the intercalibration accuracy and precision are mostly limited by the instrument noise. This method is simple and robust, and the results are highly repeatable and unambiguous. Intersatellite radiance calibration with this method is very useful for the on-orbit verification and monitoring of instrument performance, and is potentially useful for constructing long-term time series for climate studies.

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