scholarly journals Developing a western Siberia reference site for tropospheric water vapour isotopologue observations obtained by different techniques (in situ and remote sensing)

2014 ◽  
Vol 14 (12) ◽  
pp. 5943-5957 ◽  
Author(s):  
K. Gribanov ◽  
J. Jouzel ◽  
V. Bastrikov ◽  
J.-L. Bonne ◽  
F.-M. Breon ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapour ◽  
General Circulation ◽  
Western Siberia ◽  
Water Cycle ◽  
General Circulation Models ◽  
Forest Site ◽  
Atmospheric Water ◽  
Local Measurements

Abstract. Water stable isotopologues provide integrated tracers of the atmospheric water cycle, affected by changes in air mass origin, non-convective and convective processes and continental recycling. Novel remote sensing and in situ measuring techniques have recently offered opportunities for monitoring atmospheric water vapour isotopic composition. Recently developed infrared laser spectrometers allow for continuous in situ measurements of surface water vapour δDv and δ18Ov. So far, very few intercomparisons of measurements conducted using different techniques have been achieved at a given location, due to difficulties intrinsic to the comparison of integrated with local measurements. Nudged simulations conducted with high-resolution isotopically enabled general circulation models (GCMs) provide a consistent framework for comparison with the different types of observations. Here, we compare simulations conducted with the ECHAM5-wiso model with two types of water vapour isotopic data obtained during summer 2012 at the forest site of Kourovka, western Siberia: hourly ground-based FTIR total atmospheric columnar δDv amounts, and in situ hourly Picarro δDv measurements. There is an excellent correlation between observed and predicted δDv at surface while the comparison between water column values derived from the model compares well with FTIR estimates.

scholarly journals ECHAM5-wiso water vapour isotopologues simulation and its comparison with WS-CRDS measurements and retrievals from GOSAT and ground-based FTIR spectra in the atmosphere of Western Siberia

2013 ◽  
Vol 13 (1) ◽  
pp. 2599-2640 ◽  
Author(s):  
K. Gribanov ◽  
J. Jouzel ◽  
V. Bastrikov ◽  
J.-L. Bonne ◽  
F.-M. Breon ◽  
...  
Keyword(s):  
Water Vapour ◽  
Western Siberia ◽  
Water Cycle ◽  
Forest Site ◽  
Atmospheric Water ◽  
Russian Government ◽  
Measuring Techniques ◽  
Local Measurements ◽  
Air Mass Origin

Abstract. Water stable isotopes provide integrated tracers of the atmospheric water cycle, affected by changes in air mass origin, non-convective and convective processes and continental recycling. Novel remote sensing and in situ measuring techniques have recently offered opportunities for monitoring atmospheric water vapour isotopic composition. Recently developed infrared laser spectrometers allow for continuous in situ measurements of surface water vapour δDv and δ18Ov. So far, very few intercomparison of measurements conducted using different techniques have been achieved at a given location, due to difficulties intrinsic to the comparison of integrated with local measurements. Nudged simulations conducted with high resolution isotopically enabled GCMs provide a consistent framework for comparison with the different types of observations. Here, we compare simulations conducted with the ECHAM5-wiso model with three types of water vapour isotopic data obtained during summer 2012 at the forest site of Kourovka, Western Siberia: daily mean GOSAT δDv soundings, hourly ground-based FTIR total atmospheric columnar δDv amounts, and in situ hourly Picarro δDv measurements. There is an excellent correlation between observed and predicted δDv at surface while the comparison between water column values derived from the model compares well with FTIR and GOSAT estimates. This research was supported by the grant of Russian government under the contract 11.G34.31.0064.

scholarly journals Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

2016 ◽  
Vol 113 (21) ◽  
pp. 5781-5790 ◽  
Author(s):  
John H. Seinfeld ◽  
Christopher Bretherton ◽  
Kenneth S. Carslaw ◽  
Hugh Coe ◽  
Paul J. DeMott ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Forcing ◽  
General Circulation ◽  
Climate Models ◽  
Large Range ◽  
General Circulation Models ◽  
Radiative Properties ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

scholarly journals Ground-based remote sensing of tropospheric water vapour isotopologues within the project MUSICA

2012 ◽  
Vol 5 (12) ◽  
pp. 3007-3027 ◽  
Author(s):  
M. Schneider ◽  
S. Barthlott ◽  
F. Hase ◽  
Y. González ◽  
K. Yoshimura ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapour ◽  
General Circulation ◽  
Lower Troposphere ◽  
Circulation Model ◽  
Complex Nature ◽  
Atmospheric Water ◽  
Mid Infrared ◽  
The Cross

Abstract. Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water), long-term tropospheric water vapour isotopologue data records are provided for ten globally distributed ground-based mid-infrared remote sensing stations of the NDACC (Network for the Detection of Atmospheric Composition Change). We present a new method allowing for an extensive and straightforward characterisation of the complex nature of such isotopologue remote sensing datasets. We demonstrate that the MUSICA humidity profiles are representative for most of the troposphere with a vertical resolution ranging from about 2 km (in the lower troposphere) to 8 km (in the upper troposphere) and with an estimated precision of better than 10%. We find that the sensitivity with respect to the isotopologue composition is limited to the lower and middle troposphere, whereby we estimate a precision of about 30‰ for the ratio between the two isotopologues HD16O and H216O. The measurement noise, the applied atmospheric temperature profiles, the uncertainty in the spectral baseline, and the cross-dependence on humidity are the leading error sources. We introduce an a posteriori correction method of the cross-dependence on humidity, and we recommend applying it to isotopologue ratio remote sensing datasets in general. In addition, we present mid-infrared CO2 retrievals and use them for demonstrating the MUSICA network-wide data consistency. In order to indicate the potential of long-term isotopologue remote sensing data if provided with a well-documented quality, we present a climatology and compare it to simulations of an isotope incorporated AGCM (Atmospheric General Circulation Model). We identify differences in the multi-year mean and seasonal cycles that significantly exceed the estimated errors, thereby indicating deficits in the modeled atmospheric water cycle.

scholarly journals Atmospheric water vapour tracers and the significance of the vertical dimension

2012 ◽  
Vol 12 (11) ◽  
pp. 30119-30176 ◽  
Author(s):  
H. F. Goessling ◽  
C. H. Reick
Keyword(s):  
Water Vapour ◽  
General Circulation ◽  
Degrees Of Freedom ◽  
General Circulation Models ◽  
Significant Degree ◽  
Reanalysis Data ◽  
Vertical Dimension ◽  
Atmospheric Water ◽  
Atmospheric Water Vapour ◽  
Source Sink

Abstract. Atmospheric water vapour tracers (WVTs) are an elegant tool to determine source-sink relations of moisture "online" in atmospheric general circulation models (AGCMs). However, it is sometimes desireable to establish such relations "offline" based on already existing atmospheric data (e.g. reanalysis data). One simple and frequently applied offline method is 2-D moisture tracing. It makes use of the "well-mixed" assumption, which allows to treat the vertical dimension integratively. Here we scrutinise the "well-mixed" assumption and 2-D moisture tracing by means of analytical considerations in combination with AGCM-WVT simulations. We find that vertically well-mixed conditions are seldomly met. Due to the presence of vertical inhomogeneities, 2-D moisture tracing (I) neglects a significant degree of fast-recycling, and (II) results in erroneous advection where the direction of the horizontal winds varies vertically. The latter is not so much the case in the extratropics, but in the tropics this can lead to large errors. For example, computed by 2-D moisture tracing, the fraction of precipitation in the Western Sahel that originates from beyond the Sahara is ~40%, whereas the fraction that originates from the tropical and Southern Atlantic is only ~4%. Full (i.e. 3-D) moisture tracing however shows that both regions contribute roughly equally, which reveals the results of an earlier study as spurious. Moreover, we point out that there are subtle degrees of freedom associated with the implementation of WVTs into AGCMs because the strength of mixing between precipitation and the ambient water vapour is not completely provided by such models. We compute an upper bound for the resulting uncertainty and show that this uncertainty is smaller than the errors associated with 2-D moisture tracing.

scholarly journals Ground-based remote sensing of tropospheric water vapour isotopologues within the project MUSICA

2012 ◽  
Vol 5 (4) ◽  
pp. 5357-5418 ◽  
Author(s):  
M. Schneider ◽  
S. Barthlott ◽  
F. Hase ◽  
Y. González ◽  
K. Yoshimura ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapour ◽  
General Circulation ◽  
Lower Troposphere ◽  
Circulation Model ◽  
Atmospheric Composition ◽  
Complex Nature ◽  
Atmospheric Water ◽  
Mid Infrared

Abstract. Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water), long-term tropospheric water vapour isotopologues data records are provided for ten globally distributed ground-based mid-infrared remote sensing stations of the NDACC (Network for the Detection of Atmospheric Composition Change). We present a new method allowing for an extensive and straightforward characterisation of the complex nature of such isotopologue remote sensing datasets. We demonstrate that the MUSICA humidity profiles are representative for most of the troposphere with a vertical resolution ranging from about 2 km (in the lower troposphere) to 8 km (in the upper troposphere) and with an estimated precision of better than 10%. We find that the sensitivity with respect to the isotopologue composition is limited to the lower and middle troposphere, whereby we estimate a precision of about 30‰ for the ratio between the two isotopologues HD16O and H216O. The measurement noise, the applied atmospheric temperature profiles, the uncertainty in the spectral baseline, and interferences from humidity are the leading error sources. We introduce an a posteriori correction method of the humidity interference error and we recommend applying it for isotopologue ratio remote sensing datasets in general. In addition, we present mid-infrared CO2 retrievals and use them for demonstrating the MUSICA network-wide data consistency. In order to indicate the potential of long-term isotopologue remote sensing data if provided with a well-documented quality, we present a climatology and compare it to simulations of an isotope incorporated AGCM (Atmospheric General Circulation Model). We identify differences in the multi-year mean and seasonal cycles that significantly exceed the estimated errors, thereby indicating deficits in the modeled atmospheric water cycle.

scholarly journals Quality assessment of water cycle parameters in REMO by Radar-Lidar synergy

2007 ◽  
Vol 7 (3) ◽  
pp. 8455-8524
Author(s):  
B. Hennemuth ◽  
A. Weiss ◽  
J. Bösenberg ◽  
D. Jacob ◽  
H. Linné ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Soil Moisture ◽  
Water Content ◽  
Water Vapour ◽  
Water Cycle ◽  
Sensible Heat Flux ◽  
Regional Model ◽  
Cloud Base ◽  
Cloud Radar

Abstract. A comparison study of water cycle parameters derived from ground-based remote-sensing instruments and from the regional model REMO is presented. Observational data sets were collected during three measuring campaigns in summer/autumn 2003 and 2004 at Richard Aßmann Observatory, Lindenberg, Germany. The remote sensing instruments which were used are differential absorption lidar, Doppler lidar, ceilometer, cloud radar, and micro rain radar for the derivation of humidity profiles, ABL height, water vapour flux profiles, cloud parameters, and rain rate. Additionally, surface latent and sensible heat flux and soil moisture were measured. Error ranges and representativity of the data are discussed. For comparisons the regional model REMO was run for all measuring periods with a horizontal resolution of 18 km and 33 vertical levels. Parameter output was every hour. The measured data were transformed to the vertical model grid and averaged in time in order to better fit with gridbox model values. The comparisons show that the atmospheric boundary layer is not adequately simulated, on most days it is too shallow and too moist. This is found to be caused by a wrong partitioning of energy at the surface, particularly a too large latent heat flux. The reason is obviously an overestimation of soil moisture during drying periods by the one-layer scheme in the model. The profiles of water vapour transport within the ABL appear to be realistically simulated. The comparison of cloud cover reveals an underestimation of low-level and mid-level clouds by the model, whereas the comparison of high-level clouds is hampered by the inability of the cloud radar to see cirrus clouds above 10 km. Simulated ABL clouds apparently have a too low cloud base, and the vertical extent is underestimated. The ice water content of clouds agree in model and observation whereas the liquid water content is unsufficiently derived from cloud radar reflectivity in the present study. Rain rates are similar, but the representativeness of both observations and grid box values is low.

scholarly journals Diagnostic study of errors in the simulation of tropical continental precipitation in general circulation models

2003 ◽  
Vol 21 (5) ◽  
pp. 1197-1207 ◽  
Author(s):  
J. Srinivasan
Keyword(s):  
Water Vapour ◽  
General Circulation ◽  
Nonlinear Function ◽  
General Circulation Models ◽  
Atmospheric Model ◽  
Large Error ◽  
Tropical Meteorology ◽  
Diagnostic Model ◽  
Diagnostic Study ◽  
Integrated Water Vapour

Abstract. A simple diagnostic model has been used to identify the parameters that induce large errors in the simulation of tropical precipitation in atmospheric General Circulation models (GCM). The GCM that have been considered are those developed by the National Center for Environmental Prediction (NCEP), the National Center for Atmospheric Research (NCAR) and the Japanese Meteorological Agency (JMA). These models participated in the phase II of the Atmospheric Model Inter-comparison Project (AMIP II) and simulated the climate for the period 1979 to 1995. The root mean-square error in the simulation of precipitation in tropical continents was larger in NCEP and NCAR simulations than in the JMA simulation. The large error in the simulation of precipitation in NCEP was due to errors in the vertical profile of water vapour. The large error in precipitation in NCAR in North Africa was due to an error in net radiation (at the top of the atmosphere). The simple diagnostic model predicts that the moisture converge is a nonlinear function of integrated water vapour. The large error in the interannual variance of rainfall in NCEP over India has been shown to be due to this nonlinearity.Key words. Meteorology and atmospheric dynamics (precipitation; tropical meteorology; convective processes)

Estimation of fine-scale relative humidity profiles: an issue for understanding the atmospheric water cycle

2020 ◽  
Author(s):  
Veronique Michot ◽  
Helene Brogniez ◽  
Mathieu Vrac ◽  
Soulivanh Thao ◽  
Helene Chepfer ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Quantile Regression ◽  
Water Vapour ◽  
Climate Models ◽  
Water Cycle ◽  
Skill Score ◽  
Horizontal Resolution ◽  
Atmospheric Water ◽  
Global Knowledge ◽  
Humidity Profiles

<p>The multi-scale interactions at the origin of the links between clouds and water vapour are essential for the Earth's energy balance and thus the climate, from local to global. Knowledge of the distribution and variability of water vapour in the troposphere is indeed a major issue for the understanding of the atmospheric water cycle. At present, these interactions are poorly known at regional and local scales, i.e. within 100km, and are therefore poorly represented in numerical climate models. This is why we have sought to predict cloud scale relative humidity profiles in the intertropical zone, using a non-parametric statistical downscaling method called quantile regression forest. The procedure includes co-located data from 3 satellites: CALIPSO lidar and CloudSat radar, used as predictors and providing cloud properties at 90m and 1.4km horizontal resolution respectively; SAPHIR data used as a predictor and providing relative humidity at an initial horizontal resolution of 10km. Quantile regression forests were used to predict relative humidity profiles at the CALIPSO and CloudSat scales. These predictions are able to reproduce a relative humidity variability consistent with the cloud profiles and are confirmed by values of coefficients of determination greater than 0.7, relative to observed relative humidity, and Continuous Rank Probability Skill Score between 0 and 1, relative to climatology. Lidar measurements from the NARVAL 1&2 campaigns and radiosondes from the EUREC4A campaigns were also used to compare Relative Humidity profiles at the SAPHIR scale and at the scale of forest regression prediction by quantile regression.</p>

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