Analysis of Relative Humidity Sensors at the WMO Radiosonde Intercomparison Experiment in Brazil

Sapucci, Luiz Fernando; Machado, Luiz A. T.; Silveira, Reinaldo; Fisch, Gilberto; Monico, João Francisco Galera

doi:10.1175/jtech1754.1

Cited by 27 publications

(20 citation statements)

References 10 publications

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“…This result is similar to ones obtained by other works, which reported that the RS80 appears to have a dry bias (Turner et al 2003;Revercomb et al 2003;Sapucci et al 2005). …”

Section: ) Analysis Of the Resultssupporting

confidence: 92%

“…Turner et al (2003), using a microwave radiometer, suggested that daytime RS80 is typically 3%-4% drier than nighttime. Sapucci et al (2005), in a WMO radiosonde intercomparison experiment in Brazil, reported drier diurnal behavior to the order of 5.9% (or 2.9 kg m…”

Section: ϫ2mentioning

confidence: 98%

“…This region is one of the most humid on the planet, where the integrated water vapor (IWV) average is of the order of 50 kg m Ϫ2 (Sapucci et al 2004). The impact of land use change on the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia and the interactions between Amazonia and the earth's system are currently being investigated.…”

Section: Introductionmentioning

confidence: 99%

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Intercomparison of Integrated Water Vapor Estimates from Multisensors in the Amazonian Region

Sapucci

Machado

Monico

et al. 2007

Journal of Atmospheric and Oceanic Technology

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Water vapor is an atmospheric component of major interest in atmospheric science because it affects the energy budget and plays a key role in several atmospheric processes. The Amazonian region is one of the most humid on the planet, and land use change is able to affect the hydrologic cycle in several areas and consequently to generate severe modifications in the global climate. Within this context, accessing the error associated with atmospheric humidity measurement and the validation of the integrated water vapor (IWV) quantification from different techniques is very important in this region. Using data collected during the Radiation, Cloud, and Climate Interactions in Amazonia during the Dry-to-Wet Transition Season (RACCI/DRY-TO-WET), an experiment carried out in southwestern Amazonia in 2002, this paper presents quality analysis of IWV measurements from RS80 radiosondes, a suite of GPS receivers, an Aerosol Robotic Network (AERONET) solar radiometer, and humidity sounding from the Humidity Sounder for Brazil (HSB) aboard the Aqua satellite. When compared to RS80 IWV values, the root-mean-square (RMS) from the AERONET and GPS results are of the order of 2.7 and 3.8 kg m Ϫ2, respectively. The difference generated between IWV from the GPS receiver and RS80 during the daytime was larger than that of the nighttime period because of the combination of the influence of high ionospheric activity during the RACCI experiment and a daytime drier bias from the RS80.

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“…This result is similar to ones obtained by other works, which reported that the RS80 appears to have a dry bias (Turner et al 2003;Revercomb et al 2003;Sapucci et al 2005). …”

Section: ) Analysis Of the Resultssupporting

confidence: 92%

Section: ϫ2mentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Intercomparison of Integrated Water Vapor Estimates from Multisensors in the Amazonian Region

Sapucci

Machado

Monico

et al. 2007

Journal of Atmospheric and Oceanic Technology

Self Cite

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“…However, the network has not been explicitly designed to cater for the taxing requirements of climate monitoring, and it is heavily affected by technological and processing changes that act to mask any small climate signals that may be present in the data (e.g., Elliott and Gaffen 1991;Elliott 1995;Soden and Lanzante 1996;Sapucci et al 2005). Individual station humidity records will contain changes in the measured humidity over time that result from changes in measurement technology (e.g., resistance, capacitive, or skin hygristors), instrument design (e.g., housing of the instruments or inclusion of multiple sensors), instrument response times, and on-site or other data processing (e.g., Wade 1994;Elliott et al 1998).…”

Section: Strategymentioning

confidence: 99%

An Analysis of Tropospheric Humidity Trends from Radiosondes

2009

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A new analysis of historical radiosonde humidity observations is described. An assessment of both known and unknown instrument and observing practice changes has been conducted to assess their impact on bias and uncertainty in long-term trends. The processing of the data includes interpolation of data to address known sampling bias from missing dry day and cold temperature events, a first-guess adjustment for known radiosonde model changes, and a more sophisticated ensemble of estimates based on 100 neighbor-based homogenizations. At each stage the impact and uncertainty of the process has been quantified. The adjustments remove an apparent drying over Europe and parts of Asia and introduce greater consistency between temperature and specific humidity trends from day and night observations. Interannual variability and trends at the surface are shown to be in good agreement with independent in situ datasets, although some steplike discrepancies are apparent between the time series of relative humidity at the surface.Adjusted trends, accounting for documented and undocumented break points and their uncertainty, across the extratropical Northern Hemisphere lower and midtroposphere show warming of 0.1-0.4 K decade 21 and moistening on the order of 1%-5% decade 21 since 1970. There is little or no change in the observed relative humidity in the same period, consistent with climate model expectation of a positive water vapor feedback in the extratropics with near-constant relative humidity.

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“…Unlike radiosonde temperature records, whose discontinuities primarily result from sensor-dependent biases, the discontinuities in monthly humidity time series result not only from hygrometer-dependent biases (measurement bias) (Wang et al 2003;Sapucci et al 2005;Wang and Zhang 2008) but also from changes in sampling (sampling bias). For example, as radiosonde hygrometers have been improved over time to have shorter response time and smaller errors under cold conditions, there has been increased sampling-reporting of cold and dry conditions at a given pressure level.…”

Section: Introductionmentioning

confidence: 99%

A New Approach to Homogenize Daily Radiosonde Humidity Data

et al. 2011

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Radiosonde humidity records represent the only in situ observations of tropospheric water vapor content with multidecadal length and quasi-global coverage. However, their use has been hampered by ubiquitous and large discontinuities resulting from changes to instrumentation and observing practices. Here a new approach is developed to homogenize historical records of tropospheric (up to 100 hPa) dewpoint depression (DPD), the archived radiosonde humidity parameter. Two statistical tests are used to detect changepoints, which are most apparent in histograms and occurrence frequencies of the daily DPD: a variant of the Kolmogorov-Smirnov (K-S) test for changes in distributions and the penalized maximal F test (PMFred) for mean shifts in the occurrence frequency for different bins of DPD. These tests capture most of the apparent discontinuities in the daily DPD data, with an average of 8.6 changepoints (;1 changepoint per 5 yr) in each of the analyzed radiosonde records, which begin as early as the 1950s and ended in March 2009. Before applying breakpoint adjustments, artificial sampling effects are first adjusted by estimating missing DPD reports for cold (T , 2308C) and dry (DPD artificially set to 308C) conditions using empirical relationships at each station between the anomalies of air temperature and vapor pressure derived from recent observations when DPD reports are available under these conditions. Next, the samplingadjusted DPD is detrended separately for each of the 4-10 quantile categories and then adjusted using a quantile-matching algorithm so that the earlier segments have histograms comparable to that of the latest segment. Neither the changepoint detection nor the adjustment uses a reference series given the stability of the DPD series.Using this new approach, a homogenized global, twice-daily DPD dataset (available online at www.cgd.ucar.edu/cas/catalog/) is created for climate and other applications based on the Integrated Global Radiosonde Archive (IGRA) and two other data sources. The adjusted-daily DPD has much smaller and spatially more coherent trends during 1973-2008 than the raw data. It implies only small changes in relative humidity in the lower and middle troposphere. When combined with homogenized radiosonde temperature, other atmospheric humidity variables can be calculated, and these exhibit spatially more coherent trends than without the DPD homogenization. The DPD adjustment yields a different pattern of change in humidity parameters compared to the apparent trends from the raw data. The adjusted estimates show an increase in tropospheric water vapor globally.

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Analysis of Relative Humidity Sensors at the WMO Radiosonde Intercomparison Experiment in Brazil

Cited by 27 publications

References 10 publications

Intercomparison of Integrated Water Vapor Estimates from Multisensors in the Amazonian Region

Intercomparison of Integrated Water Vapor Estimates from Multisensors in the Amazonian Region

An Analysis of Tropospheric Humidity Trends from Radiosondes

A New Approach to Homogenize Daily Radiosonde Humidity Data

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