scholarly journals Water vapor isotopologues retrievals from high resolution GOSAT short-wave infrared spectra

2012 ◽  
Vol 5 (5) ◽  
pp. 6357-6386 ◽  
Author(s):  
C. Frankenberg ◽  
D. Wunch ◽  
G. Toon ◽  
C. Risi ◽  
R. Scheepmaker ◽  
...  
Keyword(s):  
Water Vapor ◽  
Hydrological Cycle ◽  
Time Frame ◽  
Short Wave ◽  
Global Scale ◽  
Total Carbon ◽  
High Spectral Resolution ◽  
Validation Dataset ◽  
Spatial Correlations ◽  
Vertical Column

Abstract. Remote sensing of the isotopic composition of water vapor can provide valuable information on the hydrological cycle. Here, we demonstrate feasibility of retrievals of the relative abundance of HDO (the HDO/H2O ratio) from the Japanese GOSAT satellite. For this purpose, we use high spectral resolution nadir radiances around 6400 cm−1 (1.56 μm) to retrieve vertical column amounts of H2O and HDO. Retrievals of H2O correlate well with ECMWF (European Centre for Medium-Range Weather Forecasts) integrated profiles (r2 = 0.96). Typical precision errors in the retrieved column averaged deuterium depletion (δD) are 20–40‰. We validate δD against a TCCON (Total Carbon Column Observing Network) ground-based station in Lamont, Oklahoma. Using retrievals in very dry areas over Antarctica, we detect a small systematic offset in retrieved H2O and HDO column amounts and take this into account for a bias-correction of δD. Monthly averages of δD in the June 2009 to September 2011 time-frame are well correlated with TCCON (r2 = 0.79) and exhibit a slope of 0.98 (1.23 if not bias corrected). We also compare seasonal averages on the global scale with results from the SCIAMACHY instrument in the 2003–2005 timeframe. Despite the lack of temporal overlap, seasonal averages in general agree well, with spatial correlations (r2) ranging from 0.62 in September through November to 0.83 in June through August. However, we observe higher variability in GOSAT δD, indicated by fitted slopes between 1.2 and 1.46. The discrepancies are likely related to differences in vertical sensitivities but warrant further validation of both GOSAT and SCIAMACHY and an extension of the validation dataset.

scholarly journals Water vapor isotopologue retrievals from high-resolution GOSAT shortwave infrared spectra

2013 ◽  
Vol 6 (2) ◽  
pp. 263-274 ◽  
Author(s):  
C. Frankenberg ◽  
D. Wunch ◽  
G. Toon ◽  
C. Risi ◽  
R. Scheepmaker ◽  
...  
Keyword(s):  
Water Vapor ◽  
Hydrological Cycle ◽  
Time Frame ◽  
Global Scale ◽  
Total Carbon ◽  
High Spectral Resolution ◽  
Validation Dataset ◽  
Spatial Correlations ◽  
Vertical Column ◽  
Shortwave Infrared

Abstract. Remote sensing of the isotopic composition of water vapor can provide valuable information on the hydrological cycle. Here, we demonstrate the feasibility of retrievals of the relative abundance of HDO (the HDO/H2O ratio) from the Japanese GOSAT satellite. For this purpose, we use high spectral resolution nadir radiances around 6400 cm−1 (1.56 μm) to retrieve vertical column amounts of H2O and HDO. Retrievals of H2O correlate well with ECMWF (European Centre for Medium-Range Weather Forecasts) integrated profiles (r2 = 0.96). Typical precision errors in the retrieved column-averaged deuterium depletion (δD) are 20–40‰. We compare δD against a TCCON (Total Carbon Column Observing Network) ground-based station in Lamont, Oklahoma. Using retrievals in very dry areas over Antarctica, we detect a small systematic offset in retrieved H2O and HDO column amounts and take this into account for a bias correction of δD. Monthly averages of δD in the June 2009 to September 2011 time frame are well correlated with TCCON (r2 = 0.79) and exhibit a slope of 0.98 (1.23 if not bias corrected). We also compare seasonal averages on the global scale with results from the SCIAMACHY instrument in the 2003–2005 time frame. Despite the lack of temporal overlap, seasonal averages in general agree well, with spatial correlations (r2) ranging from 0.62 in September through November to 0.83 in June through August. However, we observe higher variability in GOSAT δD, indicated by fitted slopes between 1.2 and 1.46. The discrepancies are likely related to differences in vertical sensitivities but warrant further validation of both GOSAT and SCIAMACHY and an extension of the validation dataset.

scholarly journals First data set of H<sub>2</sub>O/HDO columns from the Tropospheric Monitoring Instrument (TROPOMI)

2020 ◽  
Vol 13 (1) ◽  
pp. 85-100 ◽  
Author(s):  
Andreas Schneider ◽  
Tobias Borsdorff ◽  
Joost aan de Brugh ◽  
Franziska Aemisegger ◽  
Dietrich G. Feist ◽  
...  
Keyword(s):  
Water Vapour ◽  
Hydrological Cycle ◽  
Short Wave ◽  
Total Carbon ◽  
Atmospheric Water ◽  
Vertical Column ◽  
Data Set ◽  
Monitoring Instrument ◽  
Global Circulation Models ◽  
Blocking Anticyclone

Abstract. Global measurements of atmospheric water vapour isotopologues aid to better understand the hydrological cycle and improve global circulation models. This paper presents a new data set of vertical column densities of H2O and HDO retrieved from short-wave infrared (2.3 µm) reflectance measurements by the Tropospheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite. TROPOMI features daily global coverage with a spatial resolution of up to 7 km×7 km. The retrieval utilises a profile-scaling approach. The forward model neglects scattering, and strict cloud filtering is therefore necessary. For validation, recent ground-based water vapour isotopologue measurements by the Total Carbon Column Observing Network (TCCON) are employed. A comparison of TCCON δD with ground-based measurements by the Multi-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) project for data prior to 2014 (where MUSICA data are available) shows a bias in TCCON δD estimates. As TCCON HDO is currently not validated, an overall correction of recent TCCON HDO data is derived based on this finding. The agreement between the corrected TCCON measurements and co-located TROPOMI observations is good with an average bias of (-0.2±3)×1021 molec cm−2 ((1.1±7.2) %) in H2O and (-2±7)×1017 molec cm−2 ((-1.1±7.3) %) in HDO, which corresponds to a mean bias of (-14±17) ‰ in a posteriori δD. The bias is lower at low- and mid-latitude stations and higher at high-latitude stations. The use of the data set is demonstrated with a case study of a blocking anticyclone in northwestern Europe in July 2018 using single-overpass data.

scholarly journals First data set of H<sub>2</sub>O/HDO columns from TROPOMI

2019 ◽  
Author(s):  
Andreas Schneider ◽  
Tobias Borsdorff ◽  
Joost aan de Brugh ◽  
Franziska Aemisegger ◽  
Dietrich G. Feist ◽  
...  
Keyword(s):  
Water Vapour ◽  
Short Wave ◽  
Total Carbon ◽  
A Posteriori ◽  
Vertical Column ◽  
Data Set ◽  
Blocking Anticyclone ◽  
Global Coverage ◽  
Reflectance Measurements

Abstract. This paper presents a new data set of vertical column densities of the water vapour isotopologues H2O and HDO retrieved from short-wave infrared (2.3 μm) reflectance measurements by the Tropospheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor satellite. TROPOMI features daily global coverage with a spatial resolution of up to 7 km × 7 km. The retrieval utilises a profile-scaling approach. The forward model neglects scattering, thus strict cloud filtering is necessary. For validation, recent ground-based water vapour isotopologue measurements by the Total Carbon Column Observing Network (TCCON) are employed. A comparison of TCCON δD with measurements by the project Multi-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) for data prior to 2014 (where MUSICA data is available) shows a bias in TCCON δD estimates. As TCCON HDO is currently not validated, an overall correction of recent TCCON HDO data is derived based on this finding. The agreement between the corrected TCCON measurements and collocated TROPOMI observations is good with an average bias of (0.02 ± 2) · 1021 molec cm−2 in H2O and (−0.3 ± 7) · 1017 molec cm−2 in HDO, which corresponds to a bias of (−12 ± 17) ‰ in a posteriori δD. The use of the data set is demonstrated with a case study of a blocking anticyclone in northwestern Europe in July 2018 using single overpass data.

scholarly journals Evaluation of the hydrological cycle of MATCH driven by NCEP reanalysis data: comparison with GOME water vapor measurements

2005 ◽  
Vol 5 (4) ◽  
pp. 887-908 ◽  
Author(s):  
R. Lang ◽  
M. G. Lawrence
Keyword(s):  
Water Vapor ◽  
Regional Differences ◽  
Hydrological Cycle ◽  
Transport Model ◽  
Global Precipitation Climatology Project ◽  
Global Scale ◽  
Reanalysis Data ◽  
Model Parameters ◽  
Ncep Reanalysis ◽  
Inter Tropical Convergence Zone

Abstract. This study examines two key parameters of the hydrological cycle, water vapor (WV) and precipitation rates (PR), as modelled by the chemistry transport model MATCH (Model of Atmospheric Transport and Chemistry) driven by National Centers for Environmental Prediction (NCEP) reanalysis data (NRA). For model output evaluation we primarily employ WV total column data from the Global Ozone Monitoring Experiment (GOME) on ERS-2, which is the only instrument capable measuring WV on a global scale and over all surface types with a substantial data record from 1995 to the present. We find that MATCH and NRA WV and PR distributions are closely related, but that significant regional differences in both parameters exist in magnitude and distribution patterns when compared to the observations. We also find that WV residual patterns between model and observations show remarkable similarities to residuals observed in the PR when comparing MATCH and NRA output to observations comprised by the Global Precipitation Climatology Project (GPCP). We conclude that deficiencies in model parameters shared by MATCH and NRA, like in the surface evaporation rates and regional transport patterns, are likely to lead to the observed differences. Monthly average regional differences between MATCH modelled WV columns and the observations can be as large as 2 cm, based on the analysis of three years. Differences in the global mean WV values are, however, below 0.1 cm. Regional differences in the PR between MATCH and GPCP can be above 0.5 cm per day and MATCH computes on average a higher PR than what has been observed. The lower water vapor content of MATCH is related to shorter model WV residence times by up to 1 day as compared to the observations. We find that MATCH has problems in modelling the WV content in regions of strong upward convection like, for example, along the Inter Tropical Convergence Zone, where it appears to be generally too dry as compared to the observations. We discuss possible causes for this bias and demonstrate the value of the GOME WV record for model evaluation.

scholarly journals 8-Day and Daily Maximum and Minimum Air Temperature Estimation via Machine Learning Method on a Climate Zone to Global Scale

2021 ◽  
Vol 13 (12) ◽  
pp. 2355
Author(s):  
Linglin Zeng ◽  
Yuchao Hu ◽  
Rui Wang ◽  
Xiang Zhang ◽  
Guozhang Peng ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Air Temperature ◽  
Spatial Scales ◽  
Model Performance ◽  
Global Scale ◽  
Scale Model ◽  
Validation Dataset ◽  
Daily Maximum ◽  
Climate Zone ◽  
Temporal And Spatial

Air temperature (Ta) is a required input in a wide range of applications, e.g., agriculture. Land Surface Temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) are widely used to estimate Ta. Previous studies of these products in Ta estimation, however, were generally applied in small areas and with a small number of meteorological stations. This study designed both temporal and spatial experiments to estimate 8-day and daily maximum and minimum Ta (Tmax and Tmin) on three spatial scales: climate zone, continental and global scales from 2009 to 2018, using the Random Forest (RF) method based on MODIS LST products and other auxiliary data. Factors contributing to the relation between LST and Ta were determined based on physical models and equations. Temporal and spatial experiments were defined by the rules of dividing the training and validation datasets for the RF method, in which the stations selected in the training dataset were all included or not in the validation dataset. The RF model was first trained and validated on each spatial scale, respectively. On a global scale, model accuracy with a determination coefficient (R2) > 0.96 and root mean square error (RMSE) < 1.96 °C and R2 > 0.95 and RMSE < 2.55 °C was achieved for 8-day and daily Ta estimations, respectively, in both temporal and spatial experiments. Then the model was trained and cross-validated on each spatial scale. The results showed that the data size and station distribution of the study area were the main factors influencing the model performance at different spatial scales. Finally, the spatial patterns of the model performance and variable importance were analyzed. Both daytime and nighttime LST had a significant contribution in the 8-day Tmax estimation on all the three spatial scales; while their contribution in daily Tmax estimation varied over different continents or climate zones. This study was expected to improve our understanding of Ta estimation in terms of accuracy variations and influencing variables on different spatial and temporal scales. The future work mainly includes identifying underlying mechanisms of estimation errors and the uncertainty sources of Ta estimation from a local to a global scale.

scholarly journals Review on Applications of 17O in Hydrological Cycle

Molecules ◽  
2021 ◽  
Vol 26 (15) ◽  
pp. 4468
Author(s):  
Yalalt Nyamgerel ◽  
Yeongcheol Han ◽  
Minji Kim ◽  
Dongchan Koh ◽  
Jeonghoon Lee
Keyword(s):  
Water Vapor ◽  
General Circulation ◽  
Hydrological Cycle ◽  
General Circulation Models ◽  
Convective Precipitation ◽  
Subsurface Water ◽  
Polar Regions ◽  
Sea Ice Concentration ◽  
Moisture Source ◽  
Depositional Processes

The triple oxygen isotopes (16O, 17O, and 18O) are very useful in hydrological and climatological studies because of their sensitivity to environmental conditions. This review presents an overview of the published literature on the potential applications of 17O in hydrological studies. Dual-inlet isotope ratio mass spectrometry and laser absorption spectroscopy have been used to measure 17O, which provides information on atmospheric conditions at the moisture source and isotopic fractionations during transport and deposition processes. The variations of δ17O from the developed global meteoric water line, with a slope of 0.528, indicate the importance of regional or local effects on the 17O distribution. In polar regions, factors such as the supersaturation effect, intrusion of stratospheric vapor, post-depositional processes (local moisture recycling through sublimation), regional circulation patterns, sea ice concentration and local meteorological conditions determine the distribution of 17O-excess. Numerous studies have used these isotopes to detect the changes in the moisture source, mixing of different water vapor, evaporative loss in dry regions, re-evaporation of rain drops during warm precipitation and convective storms in low and mid-latitude waters. Owing to the large variation of the spatial scale of hydrological processes with their extent (i.e., whether the processes are local or regional), more studies based on isotopic composition of surface and subsurface water, convective precipitation, and water vapor, are required. In particular, in situ measurements are important for accurate simulations of atmospheric hydrological cycles by isotope-enabled general circulation models.

scholarly journals Ensemble Sensitivity Analysis for Mesoscale Forecasts of Dryline Convection Initiation

2016 ◽  
Vol 144 (11) ◽  
pp. 4161-4182 ◽  
Author(s):  
Aaron J. Hill ◽  
Christopher C. Weiss ◽  
Brian C. Ancell
Keyword(s):  
Sensitivity Analysis ◽  
Time Frame ◽  
Short Wave ◽  
Ensemble Member ◽  
Cold Pool ◽  
Dynamic Features ◽  
Wave Trough ◽  
Antecedent Precipitation ◽  
Non Gaussian ◽  
Convection Initiation

Abstract Two cases of dryline convection initiation (CI) over north Texas have been simulated (3 April 2012 and 15 May 2013) from a 50-member WRF-DART ensemble adjustment Kalman filter (EAKF) ensemble. In this study, ensemble sensitivity analysis (ESA) is applied to a convective forecast metric, maximum composite reflectivity (referred to as the response function), as a simple proxy for CI to analyze dynamic mesoscale sensitivities at the surface and aloft. Analysis reveals positional and magnitude sensitivities related to the strength and placement of important dynamic features. Convection initiation is sensitive to the evolving temperature and dewpoint fields upstream of the forecast response region in the near-CI time frame (0–12 h), prior to initiation. The sensitivity to thermodynamics is also manifest in the magnitude of dewpoint gradients along the dryline that triggers the convection. ESA additionally highlights the importance of antecedent precipitation and cold pool generation that modifies the pre-CI environment. Aloft, sensitivity of CI to a weak short-wave trough and capping inversion-level temperature is coherent, consistent, and traceable through the entire forecast period. Notwithstanding the (often) non-Gaussian distribution of ensemble member forecasts of convection, which violate the underpinnings of ESA theory, ESA is demonstrated to sufficiently identify regions that influence dryline CI. These results indicate an application of ESA for severe storm forecasting at operational centers and forecast offices as well as other mesoscale forecasting applications.

scholarly journals An evaluation of the importance of spatial resolution in a global climate and hydrological model based on the Rhine and Mississippi basin

2017 ◽  
Author(s):  
Imme Benedict ◽  
Chiel C. van Heerwaarden ◽  
Albrecht H. Weerts ◽  
Wilco Hazeleger
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Large Scale ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Scale ◽  
Global Climate Models ◽  
Convective Processes ◽  
Parameter Values

Abstract. The hydrological cycle of river basins can be simulated by combining global climate models (GCMs) and global hydrological models (GHMs). The spatial resolution of these models is restricted by computational resources and therefore limits the processes and level of detail that can be resolved. To further improve simulations of precipitation and river-runoff on a global scale, we assess and compare the benefits of an increased resolution for a GCM and a GHM. We focus on the Rhine and Mississippi basin. Increasing the resolution of a GCM (1.125° to 0.25°) results in more realistic large-scale circulation patterns over the Rhine and an improved precipitation budget. These improvements with increased resolution are not found for the Mississippi basin, most likely because precipitation is strongly dependent on the representation of still unresolved convective processes. Increasing the resolution of vegetation and orography in the high resolution GHM (from 0.5° to 0.05°) shows no significant differences in discharge for both basins, because the hydrological processes depend highly on other parameter values that are not readily available at high resolution. Therefore, increasing the resolution of the GCM provides the most straightforward route to better results. This route works best for basins driven by large-scale precipitation, such as the Rhine basin. For basins driven by convective processes, such as the Mississippi basin, improvements are expected with even higher resolution convection permitting models.

scholarly journals Differential absorption lidar measurements of water vapor by the High Altitude Lidar Observatory (HALO): Retrieval framework and validation

2021 ◽  
Author(s):  
Brian J. Carroll ◽  
Amin R. Nehrir ◽  
Susan Kooi ◽  
James Collins ◽  
Rory A. Barton-Grimley ◽  
...  
Keyword(s):  
Water Vapor ◽  
High Altitude ◽  
Dynamic Range ◽  
Precipitable Water ◽  
Spatiotemporal Variability ◽  
High Spectral Resolution ◽  
Atmospheric Conditions ◽  
Differential Absorption ◽  
Differential Absorption Lidar ◽  
Wide Range

Abstract. Airborne differential absorption lidar (DIAL) offers a uniquely capable solution to the problem of measuring water vapor (WV) with high precision, accuracy, and resolution throughout the troposphere and lower stratosphere. The High Altitude Lidar Observatory (HALO) airborne WV DIAL was recently developed at NASA Langley Research Center and was first deployed in 2019. It uses four wavelengths at 935 nm to achieve sensitivity over a wide dynamic range, and simultaneously employs 1064 nm backscatter and 532 nm high spectral resolution lidar (HSRL) measurements for aerosol and cloud profiling. A key component of the WV retrieval framework is flexibly trading resolution for precision to achieve optimal data sets for scientific objectives across scales. A technique for retrieving WV in the lowest few hundred meters of the atmosphere using the strong surface return signal is also presented. The five maiden flights of the HALO WV DIAL spanned the tropics through midlatitudes with a wide range of atmospheric conditions, but opportunities for validation were sparse. Comparisons to dropsonde WV profiles were qualitatively in good agreement, though statistical analysis was impossible due to systematic error in the dropsonde measurements. Comparison of HALO to in situ WV measurements onboard the aircraft showed no substantial bias across three orders of magnitude, despite variance (R2 = 0.66) that may be largely attributed to spatiotemporal variability. Precipitable water vapor measurements from the spaceborne sounders AIRS and IASI compared very well to HALO with R2 > 0.96 over ocean and R2 = 0.86 over land.

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