Multi‐scale observations of atmospheric moisture variability in relation to heavy precipitating systems in the northwestern Mediterranean during HyMeX IOP12

Khodayar, S.; Czajka, Beata; Caldas-Álvarez, Alberto; Helgert, Sebastian; Flamant, Cyrille; Girolamo, Paolo Di; Bock, Olivier; Chazette, Patrick

doi:10.1002/qj.3402

Cited by 19 publications

(24 citation statements)

References 57 publications

(89 reference statements)

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“…Ground-based Global Positioning System (GPS) Integrated Water Vapour (IWV) observations have been used for some time as an independent validation source for global atmospheric reanalyses over limited regions and periods (Hagemann et al, 2003;Bock et al, 2005;Heise et al, 2009;Bock and Nuret, 2009;Bock et al, 2016) and moist atmospheric process studies (Bastin et al, 2007;Bock et al, 2008;Koulali Idrissi et al, 2012;Means, 2013;Adler et al, 2015;Khodayar et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Consistency and representativeness of integrated water vapour from ground-based GPS observations and ERA-Interim reanalysis

Bock¹,

Parracho²

2019

Preprint

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Abstract. This study examines the consistency and representativeness differences of daily IWV data from ERA-Interim reanalysis and GPS observations at 120 global sites over a 16-year period (1995&#8211;2010). Various comparison statistics are analysed as a function of geographic, topographic, and climatic features. A small (&#177;1&#8201;kg&#8201;m&#8722;2) bias is found in the reanalysis across latitudes (moist in northern and southern mid-latitudes and dry in the tropics). The standard deviation of daily IWV differences is generally below 2&#8201;kg&#8201;m&#8722;2 but peaks in the northern and southern storm-tracks regions. In general, the larger IWV differences are explained by increased representativeness errors, when GPS observations capture some small-scale variability that is not resolved by the reanalysis. A representativeness error statistic is proposed which measures the spatiotemporal variability in the vicinity of the GPS sites, based on reanalysis data at the four surrounding grid points. It allows to predict the standard deviation of daily IWV differences with a correlation of 0.73. In general, representativeness differences can be reduced by temporal averaging and spatial interpolation from the four surrounding grid points. A small number of outlying cases (15 sites) which don&#8217;t follow the general tendencies are further examined. It is found that their special topographic and climatic features strongly enhance the representativeness errors (e.g. steep topography and coast-lines, strong seasonal cycle in monsoon regions). Discarding these sites significantly improves the global ERA-Interim and GPS comparison results. The selection of site a priori, based on the representativeness error statistic, is able to detect 11 out of the 15 sites and improve the comparison results by 20 to 30&#8201;%.

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Section: Introductionmentioning

confidence: 99%

Consistency and representativeness of integrated water vapour from ground-based GPS observations and ERA-Interim reanalysis

Bock¹,

Parracho²

2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Ground-based Global Positioning System (GPS) integrated water vapour (IWV) observations have been used for some time as an independent validation source for global atmospheric reanalyses over limited regions and periods (Hagemann et al, 2003;Bock et al, 2005Bock et al, , 2016Heise et al, 2009;Bock and Nuret, 2009) and moist atmospheric process studies (Bastin et al, 2007;Bock et al, 2008;Koulali Idrissi et al, 2012;Means, 2013;Adler et al, 2016;Khodayar et al, 2018). More recently, the value of continuous long time series of GPS IWV data has been investigated for the purpose of studying global and regional climate variability and validating climate models (Nilsson and Elgered, 2008; O. Bock and A. C. Parracho: Consistency and representativeness of IWV Vey et al, 2009;Roman et al, 2012;Ning et al, 2013;Chen and Liu, 2016;Wang et al, 2016;Parracho, 2017;.…”

Section: Introductionmentioning

confidence: 99%

Consistency and representativeness of integrated water vapour from ground-based GPS observations and ERA-Interim reanalysis

Bock

Parracho

2019

Atmos. Chem. Phys.

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Abstract. This study examines the consistency and representativeness differences of daily integrated water vapour (IWV) data from ERA-Interim reanalysis and GPS observations at 120 global sites over a 16-year period (1995–2010). Various comparison statistics are analysed as a function of geographic, topographic, and climatic features. A small (±1 kg m−2) bias is found in the reanalysis across latitudes (moist in northern and southern midlatitudes and dry in the tropics). The standard deviation of daily IWV differences is generally below 2 kg m−2 but peaks in the northern and southern storm-track regions. In general, the larger IWV differences are explained by increased representativeness errors, when GPS observations capture some small-scale variability that is not resolved by the reanalysis. A representativeness error statistic is proposed which measures the spatiotemporal variability in the vicinity of the GPS sites, based on reanalysis data at the four surrounding grid points. It allows to predict the standard deviation of daily IWV differences with a correlation of 0.73. In general, representativeness differences can be reduced by temporal averaging and spatial interpolation from the four surrounding grid points. A small number of outlying cases (15 sites) which do not follow the general tendencies are further examined. It is found that their special topographic and climatic features strongly enhance the representativeness errors (e.g. steep topography, coastlines, and strong seasonal cycle in monsoon regions). Discarding these sites significantly improves the global ERA-Interim and GPS comparison results. The selection of sites a priori, based on the representativeness error statistic, is able to detect 11 out of the 15 sites and improve the comparison results by 20 % to 30 %.

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“…Several authors have highlighted the important role of mid-level moisture in aiding the transition from shallow to deep moist convection (Lintner et al, 2011;Neelin et al, 2009;Bernstein et al, 2016;Zhuang et al, 2018;Khodayar et al, 2018), as a sufficiently moist LFT prevents excessive entrainment (Honda et al, 2015), helps convection penetrate possible intrusions and maintains the buoyancy of the rising parcels.…”

Section: Introductionmentioning

confidence: 99%

The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6

Caldas-Álvarez¹,

Khodayar²,

Knippertz³

2021

Preprint

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Abstract. Heavy precipitation is one of the most devastating weather extremes in the western Mediterranean region. Our capacity to prevent negative impacts from such extreme events requires advancements in numerical weather prediction, data assimilation and new observation techniques. In this paper we investigate the impact of two state-of-the-art data sets with very high resolution, Global Positioning System-Zenith Total Delays (GPS-ZTD) with a 10 min temporal resolution and radiosondes with ~700 levels, on the representation of convective precipitation in nudging experiments. Specifically, we investigate whether the high temporal resolution, quality, and coverage of GPS-ZTDs can outweigh their lack of vertical information or if radiosonde profiles are more valuable despite their scarce coverage and low temporal resolution (24 h to 6 h). The study focuses on the Intensive Observation Period 6 (IOP6) of the Hydrological Cycle in the Mediterranean eXperiment (HyMeX; 24 September 2012). This event is selected due to its severity (100 mm/12 h), the availability of observations for nudging and validation, and the large observation impact found in preliminary sensitivity experiments. We systematically compare simulations performed with the COnsortium for Small scale MOdelling (COSMO) model assimilating GPS, high- and low vertical resolution radiosoundings in model resolutions of 7 km, 2.8 km and 500 m. The results show that the additional GPS and radiosonde observations cannot compensate errors in the model dynamics and physics. In this regard the reference COSMO runs have an atmospheric moisture wet bias prior to precipitation onset but a negative bias in rainfall, indicative of deficiencies in the numerics and physics, unable to convert the moisture excess into sufficient precipitation. Nudging GPS and high-resolution soundings corrects atmospheric humidity, but even further reduces total precipitation. This case study also demonstrates the potential impact of individual observations in highly unstable environments. We show that assimilating a low-resolution sounding from Nimes (southern France) while precipitation is taking place induces a 40 % increase in precipitation during the subsequent three hours. This precipitation increase is brought about by the moistening of the 700 hPa level (7.5 g kg−1) upstream of the main precipitating systems, reducing the entrainment of dry air above the boundary layer. The moist layer was missed by GPS observations and high-resolution soundings alike, pointing to the importance of profile information and timing. However, assimilating GPS was beneficial for simulating the temporal evolution of precipitation. Finally, regarding the scale dependency, no resolution is particularly sensitive to a specific observation type, however the 2.8 km run has overall better scores, possibly as this is the optimally tuned operational version of COSMO. In follow-up experiments the Icosahedral Nonhydrostatic Model (ICON) will be investigated for this case study to assert whether its numerical and physics updates, compared to its predecessor COSMO, are able to improve the quality of the simulations.

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Multi‐scale observations of atmospheric moisture variability in relation to heavy precipitating systems in the northwestern Mediterranean during HyMeX IOP12

Cited by 19 publications

References 57 publications

Consistency and representativeness of integrated water vapour from ground-based GPS observations and ERA-Interim reanalysis

Consistency and representativeness of integrated water vapour from ground-based GPS observations and ERA-Interim reanalysis

Consistency and representativeness of integrated water vapour from ground-based GPS observations and ERA-Interim reanalysis

The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6

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