A layer-averaged relative humidity profile retrieval for microwave observations: design and results for the Megha-Tropiques payload

Sivira, Ramses; Brogniez, Hélène; Mallet, Cécile; Oussar, Yacine

doi:10.5194/amt-8-1055-2015

Cited by 24 publications

(36 citation statements)

References 76 publications

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“…As in Sivira et al (2015), the simulation of SAPHIR BTs from the RS profile is performed using version 9.3 of the Radiative Transfer for the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (RT TOV) fast radiative transfer model (Matricardi et al 2004). The surface emissivity is either prescribed using the 10-yr emissivity atlas of Prigent et al (2006) for the continental cases or computed within RTTOV with the Fast Emissivity Model-3 (FASTEM-3; Deblonde and English 2000) and 10-m wind speed.…”

Section: ) the Synthetic Training Setmentioning

confidence: 93%

“…This study follows the work described in Sivira et al (2015) dedicated to the design of a layer-averaged RH profile algorithm. Therefore, the synthetic dataset is the same and has the same purpose of statistical training and validation.…”

Section: ) the Synthetic Training Setmentioning

confidence: 99%

“…Hence, in order to overcome the size issue of a training dataset made of Megha-Tropiques observations collocated in space and time with highquality RS profiles, we associated the thermodynamic profiles extracted from the Analyzed Radiosoundings Archive (ARSA; http://ara.abct.lmd.polytechnique.fr/ index.php?page5arsa) with a radiative transfer model used to provide the corresponding SAPHIR brightness temperatures (BTs). The various quality steps applied to the RS profiles of ARSA can be found in Sivira et al (2015).…”

Section: ) the Synthetic Training Setmentioning

confidence: 99%

“…Ice layers in the upper parts of clouds and convective rainfall have a clear signature in 183-GHz channels (Hakkarinen and Adler 1988;Burns et al 1997), and the detection schemes of such scenes have been developed for the Advanced Microwave Sounding Unit-B (AMSU-B; Greenwald and Christopher 2002;Hong et al 2005) and adapted for the slightly different channels of SAPHIR (Sivira et al 2015). In fact, because SAPHIR measurements are almost insensitive to the presence of nonscattering clouds (either from ice or from rainfall), the RH retrieval method is applied to all pixels, in an undifferentiated manner, as soon as the detection scheme mentioned above considers a pixel as nonconvective.…”

Section: Data a Saphir Observationsmentioning

confidence: 99%

“…Multivariate regression techniques (Rosenkranz et al 1982;Sivira et al a Current affiliation: Meteo Protect SAS, Paris, France. 2015), and in particular neural networking (CabreraMercader and Staelin 1995;Karbou et al 2005;Aires et al 2013), embed all the atmospheric characteristics in a statistical training base.…”

Section: Introductionmentioning

confidence: 99%

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Estimating Confidence Intervals around Relative Humidity Profiles from Satellite Observations: Application to the SAPHIR Sounder

Brogniez

Fallourd

Mallet

et al. 2016

Journal of Atmospheric and Oceanic Technology

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To cite this version:Hélène Brogniez, Renaud Fallourd, Cécile Mallet, Ramses Sivira, Christophe Dufour. Estimating confidence intervals around relative humidity profiles from satellite observations: Application to the SAPHIR sounder. Journal of Atmospheric and Oceanic Technology, American Meteorological Society, 2016, 33 (5) ABSTRACT A novel scheme for the estimation of layer-averaged relative humidity (RH) profiles from spaceborne observations in the 183.31-GHz line is presented. Named atmospheric relative humidity profiles including analysis of confidence intervals (ARPIA), it provides for each vector of observations the parameters of the distribution of the RH instead of its expectation, as is usually done by the current methods. The profiles are composed of six layers distributed between 100 and 950 hPa. The approach combines the six channels of the Sondeur Atmosphérique du Profil d'Humidité Intertropical par Radiométrie (SAPHIR) instrument on board the MeghaTropiques satellite and the generalized additive model for location, scale and shape (GAMLSS) method to infer the parametric distributions, assuming that they follow a Gaussian law. The knowledge of the conditional uncertainty is an asset in the evaluation using radiosounding profiles of RH with a dedicated Bayesian method. Taking the uncertainties into account in both the ARPIA estimates and the in situ measurements yields biases, root-mean-square, and correlation coefficients in the range of 20.56% to 9.79%, 1.58% to 13.32%, and 0.55 to 0.98, respectively, with the largest biases being obtained over the continent, in the midtropospheric layers.

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Section: ) the Synthetic Training Setmentioning

confidence: 93%

Section: ) the Synthetic Training Setmentioning

confidence: 99%

Section: ) the Synthetic Training Setmentioning

confidence: 99%

Section: Data a Saphir Observationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimating Confidence Intervals around Relative Humidity Profiles from Satellite Observations: Application to the SAPHIR Sounder

Brogniez

Fallourd

Mallet

et al. 2016

Journal of Atmospheric and Oceanic Technology

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Quantifying the contribution of the Megha‐Tropiques mission to the estimation of daily accumulated rainfall in the Tropics

Roca

Taburet

Lorant

et al. 2018

Quart J Royal Meteoro Soc

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Satellite estimation of accumulated precipitation is an important facet of the study of the tropical water cycle. An advanced data merging approach using infrared geostationary imagery and microwave constellation based instantaneous rain rate estimates has been implemented in the framework of the Megha‐Tropiques and Global Precipitation Measurements missions. The Tropical Amount of Rainfall with Estimation of ERors (TAPEER) algorithm has been tailored to account for the loss of the MADRAS conical scanning radiometer by using the SAPHIR sounder rainfall detection capability, thanks to a novel two‐constellation implementation of the algorithm. A new bias correction module based on the TRMM PR observations is also presented. The performances of this new version of the product are reviewed with emphasis on West Africa. In particular, using data‐denial experiments, the contribution of SAPHIR data to the rainfall daily accumulation is quantified for various configurations of the microwave constellation and various algorithmic parameter selections. The results show that the daily accumulation statistics are well improved when SAPHIR is taken into the constellation. The improvements can be quantified using bulk statistics but are more evident following a frequency analysis. The pattern of the impact is a complex convolution of rainfall occurrence and of the Megha‐Tropiques mission original sampling. Over the 20°N–20°S belt, in zonal mean, the inclusion of SAPHIR data alters the daily accumulation substantially (more than 50% of the daily accumulation) more than 10% of the time and more than 20% when conditioned upon rainfall. Under both metrics, the improvement is majored in the 12°–17° latitude band where the Megha‐Tropiques mission sampling is at its maximum.

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Using Megha‐Tropiques satellite data to constrain humidity in regional convective simulations: A northern Australian test case

Prasad

Sherwood

Brogniez

2020

Quart J Royal Meteoro Soc

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Convective initiation and growth are sensitive to atmospheric conditions, especially humidity, in ways that need to be understood and quantified. It is not clear, however, how well current observations and modelling systems can serve to test this understanding. We simulate multiple cases of convergent cloud lines observed during January 2016 over northeastern Australia using the Weather Research and Forecasting (WRF) model (version 3.7.1), initialized by and nudged to reanalysis data. Overall, WRF appears to skilfully simulate the convergence lines. However, the associated convective clouds as seen by satellite were not properly captured by the model. The model humidity was tested against the current version (V3‐00) of the Megha‐Tropiques satellite, which although up to 30% too moist in the lowest retrieved layer over the dry continental interior compared to radiosondes, is usually accurate to within ±10% near the cloud lines. Unperturbed WRF simulations were found to be 10–20% too dry in this region. Compensating for this humidity bias via the model initialization produced more realistic simulations of clouds and convection, and this had a comparable or larger impact than changing model physics. This result highlights the importance of observations of water vapour that are accurate and have good spatial coverage, especially in the lower troposphere, for properly constraining simulations of convective environments and for model evaluation of moist processes.

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A layer-averaged relative humidity profile retrieval for microwave observations: design and results for the Megha-Tropiques payload

Cited by 24 publications

References 76 publications

Estimating Confidence Intervals around Relative Humidity Profiles from Satellite Observations: Application to the SAPHIR Sounder

Estimating Confidence Intervals around Relative Humidity Profiles from Satellite Observations: Application to the SAPHIR Sounder

Quantifying the contribution of the Megha‐Tropiques mission to the estimation of daily accumulated rainfall in the Tropics

Using Megha‐Tropiques satellite data to constrain humidity in regional convective simulations: A northern Australian test case

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