Water vapor column abundance retrievals during FIFE

Bruegge, Carol J.; Conel, J. E.; Green, Robert O.; Margolis, J. S.; Holm, Ronald G.; Toon, G. C.

doi:10.1029/92jd01050

Cited by 144 publications

(117 citation statements)

References 14 publications

Supporting

Mentioning

111

Contrasting

Unclassified

Order By: Relevance

“…Using a power law parameterisation, a conversion of the slant optical depth to the slant IWV can be obtained (e.g. Bruegge et al, 1992;Schmid et al, 2001). Uncertainties in this parameterisation and the Langley plot regression (due to variable atmospheric water vapour amounts) as well as deficits in the filter characterisation are the leading error sources.…”

Section: Cimel Sun Photometermentioning

confidence: 99%

A multi-site intercomparison of integrated water vapour observations for climate change analysis

et al. 2014

View full text Add to dashboard Cite

Abstract. Water vapour plays a dominant role in the climate change debate. However, observing water vapour over a climatological time period in a consistent and homogeneous manner is challenging. On one hand, networks of groundbased instruments able to retrieve homogeneous integrated water vapour (IWV) data sets are being set up. Typical examples are Global Navigation Satellite System (GNSS) observation networks such as the International GNSS Service (IGS), with continuous GPS (Global Positioning System) observations spanning over the last 15+ years, and the AErosol RObotic NETwork (AERONET), providing long-term observations performed with standardized and well-calibrated sun photometers. On the other hand, satellite-based measurements of IWV already have a time span of over 10 years (e.g. AIRS) or are being merged to create long-term time series (e.g. GOME, SCIAMACHY, and GOME-2).This study performs an intercomparison of IWV measurements from satellite devices (in the visible, GOME/SCIAMACHY/GOME-2, and in the thermal infrared, AIRS), in situ measurements (radiosondes) and ground-based instruments (GPS, sun photometer), to assess their use in water vapour trends analysis. To this end, we selected 28 sites world-wide for which GPS observations can directly be compared with coincident satellite IWV observations, together with sun photometer and/or radiosonde measurements. The mean biases of the different techniques compared to the GPS estimates vary only between −0.3 to 0.5 mm of IWV. Nevertheless these small biases are accompanied by large standard deviations (SD), especially for the satellite instruments. In particular, we analysed the impact of clouds on the IWV agreement. The influence of specific issues for each instrument on the intercomparison is also investigated (e.g. the distance between the satellite ground pixel centre and the co-located ground-based station, the satellite scan angle, daytime/nighttime differences). Furthermore, we checked if the properties of the IWV scatter plots between these different instruments are dependent on the geography and/or altitude of the station. For all considered instruments, the only dependency clearly detected is with latitude: the SD of the IWV observations with respect to the GPS IWV retrievals decreases with increasing latitude and decreasing mean IWV.

show abstract

Section: Cimel Sun Photometermentioning

confidence: 99%

A multi-site intercomparison of integrated water vapour observations for climate change analysis

et al. 2014

View full text Add to dashboard Cite

show abstract

“…They found that the mixing ratio mean values for clear-sky days in the 1989 rainy season vary 30% during 9:00 -12:00 local time, and 40% in 12:00 -15:00. Bruegge et al (1992) reported that water vapor column abundances retrieved from the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data during the First ISLSCP Field Experiment (FIFE) over the Konza Prairie, Kansas, on August 31, 1990, indicated that the spatial variability over scales associated with surface topography and the underlying vegetation may be greater than 10%.…”

Section: Heritage For Lst Remote Sensingmentioning

confidence: 99%

Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data

Wan¹,

Zhang²,

Zhang³

et al. 2002

Remote Sensing of Environment

771

488

View full text Add to dashboard Cite

“…At Izaña, we determine the water vapour columns by the modified Langley plot method. Therefore, the relation between the slant optical depth and the water vapour slant column amounts is approximated by a power law parameterisation (e.g., Bruegge et al, 1992;Schmid et al, 2001). Uncertainties in this parameterisation and the Langley regression (due to variable atmospheric water vapour amounts) as well as deficits in the filter characterisation are the leading error sources.…”

Section: Cimel Sunphotometermentioning

confidence: 99%

Continuous quality assessment of atmospheric water vapour measurement techniques: FTIR, Cimel, MFRSR, GPS, and Vaisala RS92

et al. 2010

View full text Add to dashboard Cite

Abstract. At the Izaña Observatory, water vapour amounts have been measured routinely by different techniques for many years. We intercompare the total precipitable water vapour (PWV) amounts measured between 2005 and 2009 by a Fourier Transform Infrared (FTIR) spectrometer, a Multifilter Rotating Shadow-band Radiometer (MFRSR), a Cimel sunphotometer, a Global Positioning System (GPS) receiver, and daily radiosondes (Vaisala RS92). The long-term characteristics of our study allows a reliable and extensive empirical quality assessment of long-term validity, which is an important prerequisite when applying the data to climate research. We estimate a PWV precision of 1% for the FTIR, about 10% for the MFRSR, Cimel, and GPS (when excluding rather dry conditions), and significantly better than 15% for the RS92 (the detection of different airmasses avoids a better constrained estimation). We show that the MFRSR, Cimel and GPS data quality depends on the atmospheric conditions (humid or dry) and that the restriction to clear-sky observations introduces a significant dry bias in the FTIR and Cimel data. In addition, we intercompare the water vapour profiles measured by the FTIR and the Vaisala RS92, which allows the conclusion that both experiments are able to detect lower to upper tropospheric water vapour mixing ratios with a precision of better than 15%.

show abstract

Water vapor column abundance retrievals during FIFE

Cited by 144 publications

References 14 publications

A multi-site intercomparison of integrated water vapour observations for climate change analysis

A multi-site intercomparison of integrated water vapour observations for climate change analysis

Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data

Continuous quality assessment of atmospheric water vapour measurement techniques: FTIR, Cimel, MFRSR, GPS, and Vaisala RS92

Contact Info

Product

Resources

About