A concept for a satellite mission to measure cloud ice water path, ice particle size, and cloud altitude

Buehler, Stefan; Jiménez, Carlos; Evans, K. Franklin; Eriksson, Patrick; Rydberg, Bengt; Heymsfield, Andrew J.; Stubenrauch, C.; Lohmann, Ulrike; Emde, Claudia; John, Viju O.; Sreerekha, T. R.; Davis, C.

doi:10.1002/qj.143

Cited by 114 publications

(123 citation statements)

References 38 publications

(44 reference statements)

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“…Note that when studying some specific issues, such as polarization or the impact of the receiver noise, the noise levels can be different from those given in the table. Also note that the noise figures in Table I for some channels deviate slightly from those given in Buehler et al (2007), which are based on a later performance estimate of the engineering team. The differences are small and do not affect the results significantly.…”

Section: Sensor Modelmentioning

confidence: 80%

“…However, aircraft instruments are useful for specific campaigns but cannot provide global coverage, while the limb-sounding geometry results in poor horizontal resolution. A satellite down-looking millimetre and submillimetre sensor can provide both global coverage and good horizontal resolution, and a mission concept for this type of instrument has been proposed by Buehler et al (2007). The suggested instrument is a conical scanning instrument placed in a sun-synchronous orbit at between 830 and 870 km, with an incident angle of around 53 degrees providing an instrument swath of around 1800 km, a footprint resolution of around 10 km, and nearly global coverage in about a day.…”

Section: Introductionmentioning

confidence: 99%

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Performance simulations for a submillimetre-wave satellite instrument to measure cloud ice

Jiménez

Buehler

Rydberg

et al. 2007

Q.J.R. Meteorol. Soc.

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ABSTRACT:The performance of a conically scanning satellite instrument for the measurement of cloud ice was studied. The instrument measures radiances in 12 channels placed around the 183, 325 and 448 GHz water vapour lines and the 243, 664 and 874 GHz window channels, and is designed to provide estimations of ice water path (IWP), the equivalent sphere diameter (DME), and the median ice mass height (ZME). Overall median relative errors of around 20% for IWP, 33 µm for DME, and 240 m for ZME for a midlatitude winter scenario, and 17% for IWP, 30 µm for DME, and 310 m for ZME for a tropical scenario were found. Detection limits (relative retrieval error reaching 100%) of around 2 gm −2 were estimated for both scenarios. The performance of a five-receiver instrument, where either the 664 or 874 GHz channel is dropped, was close, but with increased errors for very thin and high clouds. A trade-off between having the 874 GHz receiver or two infrared channels at 10.7 and 12 µm emerged, as very similar performance was found between the six-receiver instrument and the five-receiver instrument with the infrared channels. Another trade-off between receiver selection and noise was also apparent, with some of the four-receiver selections operating at half noise levels being able to compete with the standard six-receiver instrument. Dual-polarized measurements were also tested, but they did not significantly improve the retrievals of IWP or DME.

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Section: Sensor Modelmentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Performance simulations for a submillimetre-wave satellite instrument to measure cloud ice

Jiménez

Buehler

Rydberg

et al. 2007

Q.J.R. Meteorol. Soc.

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“…, whereas sensitivity to "cloud ice" particles requires shorter wavelengths. Accordingly, instruments dedicated to cloud ice mass retrieval that have channels above 200 GHz have been proposed (Evans et al, 1999;Buehler et al, 2007). Following these mission proposals the Ice Cloud Imager (ICI) is now considered as an instrument for the second series of Metop satellites.…”

Section: P Eriksson Et Al: Upper Tropospheric Water As Observed By mentioning

confidence: 99%

Overview and sample applications of SMILES and Odin-SMR retrievals of upper tropospheric humidity and cloud ice mass

Eriksson

Rydberg²,

Sagawa

et al. 2014

Atmos. Chem. Phys.

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Abstract. Retrievals of cloud ice mass and humidity from the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and the Odin-SMR (Sub-Millimetre Radiometer) limb sounder are presented and example applications of the data are given. SMILES data give an unprecedented view of the diurnal variation of cloud ice mass. Mean regional diurnal cycles are reported and compared to some global climate models. Some improvements in the models regarding diurnal timing and relative amplitude were noted, but the models' mean ice mass around 250 hPa is still low compared to the observations. The influence of the ENSO (El Niño-Southern Oscillation) state on the upper troposphere is demonstrated using 12 years of Odin-SMR data.The same retrieval scheme is applied for both sensors, and gives low systematic differences between the two data sets. A special feature of this Bayesian retrieval scheme, of Monte Carlo integration type, is that values are produced for all measurements but for some atmospheric states retrieved values only reflect a priori assumptions. However, this "allweather" capability allows a direct statistical comparison to model data, in contrast to many other satellite data sets. Another strength of the retrievals is the detailed treatment of "beam filling" that otherwise would cause large systematic biases for these passive cloud ice mass retrievals.The main retrieval inputs are spectra around 635/525 GHz from tangent altitudes below 8/9 km for SMILES/Odin-SMR, respectively. For both sensors, the data cover the upper troposphere between 30 • S and 30 • N. Humidity is reported as both relative humidity and volume mixing ratio. The vertical coverage of SMILES is restricted to a single layer, while Odin-SMR gives some profiling capability between 300 and 150 hPa. Ice mass is given as the partial ice water path above 260 hPa, but for Odin-SMR ice water content, estimates are also provided. Besides a smaller contrast between most dry and wet cases, the agreement with Aura MLS (Microwave Limb Sounder) humidity data is good. In terms of tropical mean humidity, all three data sets agree within 3.5 %RHi. Mean ice mass is about a factor of 2 lower compared to CloudSat. This deviation is caused by the fact that different particle size distributions are assumed, combined with saturation and a priori influences in the SMILES and Odin-SMR data.

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“…Profiles of pressure, temperature, relative humidity, cloud ice water content and cloud liquid water content were used to simulate AMSU-B radiances. (Incidentally, the same meteorological event was used in Buehler et al (2007) to illustrate the measurement of a proposed submillimeter-wave cloud sensor. )…”

Section: Case Studymentioning

confidence: 99%

A cloud filtering method for microwave upper tropospheric humidity measurements

et al. 2007

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Abstract. The paper presents a cloud filtering method for upper tropospheric humidity (UTH) measurements at 183.31±1.00 GHz. The method uses two criteria: a viewing angle dependent threshold on the brightness temperature at 183.31±1.00 GHz, and a threshold on the brightness temperature difference between another channel and 183.31±1.00 GHz. Two different alternatives, using 183.31±3.00 GHz or 183.31±7.00 GHz as the other channel, are studied. The robustness of this cloud filtering method is demonstrated by a mid-latitudes winter case study. The paper then studies different biases on UTH climatologies. Clouds are associated with high humidity, therefore the possible dry bias introduced by cloud filtering is discussed and compared to the wet biases introduced by the clouds radiative effect if no filtering is done. This is done by means of a case study, and by means of a stochastic cloud database with representative statistics for midlatitude conditions. Both studied filter alternatives perform nearly equally well, but the alternative using 183.31±3.00 GHz as other channel is preferable, because that channel is less likely to see the Earth's surface than the one at 183.31±7.00 GHz. The consistent result of all case studies and for both filter alternatives is that both cloud wet bias and cloud filtering dry bias are modest for microwave data. The recommended strategy is to use the cloud filtered data as an estimate for the true all-sky UTH value, but retain the unfiltered data to have an estimate of the cloud induced uncertainty. The focus of the paper is on midlatitude data, since atmospheric data to test the filter for that case were readily available. The filter is expected to be applicable also to subtropical and tropical data, but should be further validated with case studies similar to the one presented here for those cases.

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A concept for a satellite mission to measure cloud ice water path, ice particle size, and cloud altitude

Cited by 114 publications

References 38 publications

Performance simulations for a submillimetre-wave satellite instrument to measure cloud ice

Performance simulations for a submillimetre-wave satellite instrument to measure cloud ice

Overview and sample applications of SMILES and Odin-SMR retrievals of upper tropospheric humidity and cloud ice mass

A cloud filtering method for microwave upper tropospheric humidity measurements

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