| 1. |
|
|
| 2. |
|
|
| 3. |
|
|
| 4. |
- Buehler, Stefan A., et al.
(author)
-
An upper tropospheric humidity data set from operational satellite microwave data
- 2008
-
In: Journal of Geophysical Research. - 0148-0227 .- 2156-2202. ; 113:14, s. D14110-
-
Journal article (peer-reviewed)abstract
- 183.31 GHz observations from the Advanced Microwave Sounding Unit B (AMSUB) instruments onboard the NOAA 15, 16, and 17 satellites were used to derive a new data set of Upper Tropospheric Humidity (UTH). The data set consist of monthly median and mean data on a 1.5 degrees latitude-longitude grid between 60 degrees S and 60 degrees N, and covers the time period of January 2000 to February 2007. The data from all three instruments are very consistent, with relative difference biases of less than 4% and relative difference standard deviations of 7%. Radiometric contributions by high ice clouds and by the Earth's surface affect the measurements in certain areas. The uncertainty due to clouds is estimated to be up to approximately 10%RH in areas with deep convection. The uncertainty associated with contamination from surface emission can exceed 10%RH in midlatitude winter, where the data therefore should be regarded with caution. Otherwise the surface influence appears negligible. The paper also discusses the UTH median climatology and seasonal cycle, which are found to be broadly consistent with UTH climatologies from other sensors. Finally, the paper presents an initial validation of the new data set against IR satellite data and radiosonde data. The observed biases of up to 9%RH (wet bias relative to HIRS) were found to be broadly consistent with expectations based on earlier studies. The observed standard deviations against all other data sets were below 6%RH. The UTH data are available to the scientific community on http://www.sat.ltu.se.
|
|
| 5. |
- Buehler, Stefan A., et al.
(author)
-
ARTS, the atmospheric radiative transfer simulator
- 2005
-
In: Journal of Quantitative Spectroscopy and Radiative Transfer. - : Elsevier BV. - 0022-4073 .- 1879-1352. ; 91:1, s. 65-93
-
Journal article (peer-reviewed)abstract
- RTS is a modular program that simulates atmospheric radiative transfer. The paper describes ARTS version 1.0, which is applicable in the absence of scattering. An overview over all major parts of the model is given: calculation of absorption coefficients, the radiative transfer itself, and the calculation of Jacobians. ARTS can be freely used under a GNU general public license. Unique features of the program are its scalability and modularity, the ability to work with different sources of spectroscopic parameters, the availability of several self-consistent water continuum and line absorption models, and the analytical calculation of Jacobians.
|
|
| 6. |
- Buehler, Stefan, et al.
(author)
-
A cloud filtering method for microwave upper tropospheric humidity measurements
- 2007
-
In: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 7:21, s. 5531-5542
-
Journal article (peer-reviewed)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.
|
|
| 7. |
- Buehler, Stefan, et al.
(author)
-
A concept for a satellite mission to measure cloud ice water path, ice particle size, and cloud altitude
- 2007
-
In: Quarterly Journal of the Royal Meteorological Society. - : Wiley. - 0035-9009 .- 1477-870X. ; 133:S2, s. 109-128
-
Journal article (peer-reviewed)abstract
- A passive satellite radiometer operating at submillimetre wavelengths can measure cloud ice water path (IWP), ice particle size, and cloud altitude. The paper first discusses the scientific background for such measurements. Formal scientific mission requirements are derived, based on this background and earlier assessments. The paper then presents a comprehensive prototype instrument and mission concept, and demonstrates that it meets the requirements. The instrument is a conically scanning 12-channel radiometer with channels between 183 and 664 GHz, proposed to fly in tandem with one of the Metop satellites. It can measure IWP with a relative accuracy of approximately 20% and a detection threshold of approximately 2 g m−2. The median mass equivalent sphere diameter of the ice particles can be measured with an accuracy of approximately 30 µm, and the median IWP cloud altitude can be measured with an accuracy of approximately 300 m. All the above accuracies are median absolute error values; root mean square error values are approximately twice as high, due to rare outliers.
|
|
| 8. |
- Buehler, Stefan, et al.
(author)
-
A simple method to relate microwave radiances to upper tropospheric humidity
- 2005
-
In: Journal of Geophysical Research. - 0148-0227 .- 2156-2202. ; 110:2, s. D02110-
-
Journal article (peer-reviewed)abstract
- A brightness temperature (BT) transformation method can be applied to microwave data to retrieve Jacobian weighted upper tropospheric relative humidity (UTH) in a broad layer centered roughly between 6 and 8 km altitude. The UTH bias is below 4% RH, and the relative UTH bias below 20%. The UTH standard deviation is between 2 and 6.5% RH in absolute numbers, or between 10 and 27% in relative numbers. The standard deviation is dominated by the regression noise, resulting from vertical structure not accounted for by the simple transformation relation. The UTH standard deviation due to radiometric noise alone has a relative standard deviation of approximately 7% for a radiometric noise level of 1 K. The retrieval performance was shown to be of almost constant quality for all viewing angles and latitudes, except for problems at high latitudes due to surface effects. A validation of AMSU UTH against radiosonde UTH shows reasonable agreement if known systematic differences between AMSU and radiosonde are taken into account. When the method is applied to supersaturation studies, regression noise and radiometric noise could lead to an apparent supersaturation even if there were no supersaturation. For a radiometer noise level of 1 K the drop-off slope of the apparent supersaturation is 0.17% RH−1, for a noise level of 2 K the slope is 0.12% RH−1. The main conclusion from this study is that the BT transformation method is very well suited for microwave data. Its particular strength is in climatological applications where the simplicity and the a priori independence are key advantages.
|
|
| 9. |
|
|
| 10. |
|
|
