Influence of the underlying surface on the accuracy of satellite differential radiometric measurements of water vapor profile in the lower troposphere

2017 ◽  
Vol 14 (5) ◽  
pp. 268-277 ◽  
Author(s):  
V.V. Sterlyadkin ◽  
◽  
E.V. Pashinov ◽  
А.V. Kuzmin ◽  
E.A. Sharkov ◽  
...  
Keyword(s):  
Water Vapor ◽  
Lower Troposphere ◽  
Underlying Surface ◽  
Radiometric Measurements

scholarly journals A comparison between the GNSS tomography technique and the WRF model in retrieving 3D wet refractivity field in Hong Kong

2018 ◽  
Author(s):  
Zhaohui Xiong ◽  
Bao Zhang ◽  
Yibin Yao
Keyword(s):  
Hong Kong ◽  
Water Vapor ◽  
Weather Prediction ◽  
Wrf Model ◽  
Vertical Direction ◽  
Lower Troposphere ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Rainy Period ◽  
Lower Accuracy

Abstract. Water vapor plays an important role in various scales of weather processes. However, there are limited means to monitor its 3-dimensional (3D) dynamical changes. The Numerical Weather Prediction (NWP) model and the Global Navigation Satellite System (GNSS) tomography technique are two of the limited means. Here, we conduct an interesting comparison between the GNSS tomography technique and the Weather Research and Forecasting (WRF) model (a representative of the NWP models) in retrieving Wet Refractivity (WR) in Hong Kong area during a rainy period and a rainless period. The GNSS tomography technique is used to retrieve WR from the GNSS slant wet delay. The WRF Data Assimilation (WRFDA) model is used to assimilate GNSS Zenith Tropospheric Delay (ZTD) to improve the background data. The WRF model is used to generate reanalysis data using the WRFDA output as the initial values. The radiosonde data are used to validate the WR derived from the GNSS tomography and the reanalysis data. The Root Mean Square (RMS) of the tomographic WR, the reanalysis WR that assimilate GNSS ZTD, and the reanalysis WR that without assimilating GNSS ZTD are 6.50 mm/km, 4.31 mm/km and 4.15 mm/km in the rainy period. The RMS becomes 7.02 mm/km, 7.26 mm/km and 6.35 mm/km in the rainless period. The lower accuracy in the rainless period is mainy due to the sharp variation of WR in the vertical direction. The results also show that assimilating GNSS ZTD into the WRFDA model only slightly improves the accuracy of the reanalysis WR and that the reanalysis WR is better than the tomographic WR in most cases. However, in a special experimental period when the water vapor is highly concentrated in the lower troposphere, the tomographic WR outperforms the reanalysis WR in the lower troposphere. When we assimilate the tomographic WR in the lower troposphere into the WRFDA model, the reanalysis WR is improved.

scholarly journals The Effect of Clouds on Water Vapor Profiling from the Millimeter-Wave Radiometric Measurements

1997 ◽  
Vol 36 (9) ◽  
pp. 1232-1244 ◽  
Author(s):  
J. R. Wang ◽  
J. D. Spinhirne ◽  
P. Racette ◽  
L. A. Chang ◽  
W. Hart
Keyword(s):  
Water Vapor ◽  
Millimeter Wave ◽  
Radiometric Measurements

Robustness of Dynamical Feedbacks from Radiative Forcing: 2% Solar versus 2 × CO2 Experiments in an Idealized GCM

2012 ◽  
Vol 69 (7) ◽  
pp. 2256-2271 ◽  
Author(s):  
Ming Cai ◽  
Ka-Kit Tung
Keyword(s):  
Water Vapor ◽  
Radiative Forcing ◽  
Lower Troposphere ◽  
Radiative Heating ◽  
Climate Feedback ◽  
Response Analysis ◽  
High Latitudes ◽  
Water Vapor Feedback ◽  
The Tropics ◽  
Heating Profile

Abstract Despite the differences in the spatial patterns of the external forcing associated with a doubling CO2 and with a 2% solar variability, the final responses in the troposphere and at the surface in a three-dimensional general circulation model appear remarkably similar. Various feedback processes are diagnosed and compared using the climate feedback–response analysis method (CFRAM) to understand the mechanisms responsible. At the surface, solar radiative forcing is stronger in the tropics than at the high latitudes, whereas greenhouse radiative forcing is stronger at high latitudes compared with the tropics. Also solar forcing is positive everywhere in the troposphere and greenhouse radiative forcing is positive mainly in the lower troposphere. The water vapor feedback strengthens the upward-decreasing radiative heating profile in the tropics and the poleward-decreasing radiative heating profile in the lower troposphere. The “evaporative” and convective feedbacks play an important role only in the tropics where they act to reduce the warming at the surface and lower troposphere in favor of upper-troposphere warming. Both water vapor feedback and enhancement of convection in the tropics further strengthen the initial poleward-decreasing profile of energy flux convergence perturbations throughout the troposphere. As a result, the large-scale dynamical poleward energy transport, which acts on the negative temperature gradient, is enhanced in both cases, contributing to a polar amplification of warming aloft and a warming reduction in the tropics. The dynamical amplification of polar atmospheric warming also contributes additional warming to the surface below via downward thermal radiation.

scholarly journals Retrieval of temperature and water vapor profiles from radio occultation refractivity and bending angle measurements using an Optimal Estimation approach: a simulation study

2005 ◽  
Vol 5 (6) ◽  
pp. 1665-1677 ◽  
Author(s):  
A. von Engeln ◽  
G. Nedoluha
Keyword(s):  
Water Vapor ◽  
Radio Occultation ◽  
A Priori ◽  
Estimation Method ◽  
Lower Troposphere ◽  
Optimal Estimation ◽  
Pronounced Difference ◽  
Bending Angle ◽  
Advantages And Disadvantages ◽  
The Impact

Abstract. The Optimal Estimation Method is used to retrieve temperature and water vapor profiles from simulated radio occultation measurements in order to assess how different retrieval schemes may affect the assimilation of this data. High resolution ECMWF global fields are used by a state-of-the-art radio occultation simulator to provide quasi-realistic bending angle and refractivity profiles. Both types of profiles are used in the retrieval process to assess their advantages and disadvantages. The impact of the GPS measurement is expressed as an improvement over the a priori knowledge (taken from a 24h old analysis). Large improvements are found for temperature in the upper troposphere and lower stratosphere. Only very small improvements are found in the lower troposphere, where water vapor is present. Water vapor improvements are only significant between about 1 km to 7 km. No pronounced difference is found between retrievals based upon bending angles or refractivity. Results are compared to idealized retrievals, where the atmosphere is spherically symmetric and instrument noise is not included. Comparing idealized to quasi-realistic calculations shows that the main impact of a ray tracing algorithm can be expected for low latitude water vapor, where the horizontal variability is high. We also address the effect of altitude correlations in the temperature and water vapor. Overall, we find that water vapor and temperature retrievals using bending angle profiles are more CPU intensive than refractivity profiles, but that they do not provide significantly better results.

scholarly journals Aircraft validation of Aura Tropospheric Emission Spectrometer retrievals of HDO / H<sub>2</sub>O

2014 ◽  
Vol 7 (9) ◽  
pp. 3127-3138 ◽  
Author(s):  
R. L. Herman ◽  
J. E. Cherry ◽  
J. Young ◽  
J. M. Welker ◽  
D. Noone ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Standard Deviation ◽  
Lower Troposphere ◽  
Temporal Variations ◽  
Observation Error ◽  
Free Troposphere ◽  
Data Set ◽  
Airborne Measurements

Abstract. The EOS (Earth Observing System) Aura Tropospheric Emission Spectrometer (TES) retrieves the atmospheric HDO / H2O ratio in the mid-to-lower troposphere as well as the planetary boundary layer. TES observations of water vapor and the HDO isotopologue have been compared with nearly coincident in situ airborne measurements for direct validation of the TES products. The field measurements were made with a commercially available Picarro L1115-i isotopic water analyzer on aircraft over the Alaskan interior boreal forest during the three summers of 2011 to 2013. TES special observations were utilized in these comparisons. The TES averaging kernels and a priori constraints have been applied to the in situ data, using version 5 (V005) of the TES data. TES calculated errors are compared with the standard deviation (1σ) of scan-to-scan variability to check consistency with the TES observation error. Spatial and temporal variations are assessed from the in situ aircraft measurements. It is found that the standard deviation of scan-to-scan variability of TES δD is ±34.1‰ in the boundary layer and ± 26.5‰ in the free troposphere. This scan-to-scan variability is consistent with the TES estimated error (observation error) of 10–18‰ after accounting for the atmospheric variations along the TES track of ±16‰ in the boundary layer, increasing to ±30‰ in the free troposphere observed by the aircraft in situ measurements. We estimate that TES V005 δD is biased high by an amount that decreases with pressure: approximately +123‰ at 1000 hPa, +98‰ in the boundary layer and +37‰ in the free troposphere. The uncertainty in this bias estimate is ±20‰. A correction for this bias has been applied to the TES HDO Lite Product data set. After bias correction, we show that TES has accurate sensitivity to water vapor isotopologues in the boundary layer.

Retrievals of column water vapor using millimeter-wave radiometric measurements

2002 ◽  
Vol 40 (6) ◽  
pp. 1220-1229 ◽  
Author(s):  
J.R. Wang ◽  
P. Racette ◽  
M.E. Tiesky ◽  
W. Manning
Keyword(s):  
Water Vapor ◽  
Millimeter Wave ◽  
Radiometric Measurements

scholarly journals Differential absorption lidar for water vapor isotopologues in the 1.98 µm spectral region: sensitivity analysis with respect to regional atmospheric variability

2021 ◽  
Vol 14 (10) ◽  
pp. 6675-6693
Author(s):  
Jonas Hamperl ◽  
Clément Capitaine ◽  
Jean-Baptiste Dherbecourt ◽  
Myriam Raybaut ◽  
Patrick Chazette ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Water Vapor ◽  
Spectral Region ◽  
Hydrological Cycle ◽  
Numerical Study ◽  
Lower Troposphere ◽  
Differential Absorption ◽  
Differential Absorption Lidar ◽  
Relative Precision ◽  
Mixing Ratios

Abstract. Laser active remote sensing of tropospheric water vapor is a promising technology to complement passive observational means in order to enhance our understanding of processes governing the global hydrological cycle. In such a context, we investigate the potential of monitoring both water vapor H216O and its isotopologue HD16O using a differential absorption lidar (DIAL) allowing for ground-based remote measurements at high spatio-temporal resolution (150 m and 10 min) in the lower troposphere. This paper presents a sensitivity analysis and an error budget for a DIAL system under development which will operate in the 2 µm spectral region. Using a performance simulator, the sensitivity of the DIAL-retrieved mixing ratios to instrument-specific and environmental parameters is investigated. This numerical study uses different atmospheric conditions ranging from tropical to polar latitudes with realistic aerosol loads. Our simulations show that the measurement of the main isotopologue H216O is possible over the first 1.5 km of atmosphere with a relative precision in the water vapor mixing ratio of <1 % in a mid-latitude or tropical environment. For the measurement of HD16O mixing ratios under the same conditions, relative precision is found to be slightly lower but still sufficient for the retrieval of range-resolved isotopic ratios with precisions in δD of a few per mil. We also show that expected precisions vary by an order of magnitude between tropical and polar conditions, the latter giving rise to poorer sensitivity due to low water vapor content and low aerosol load. Such values have been obtained for a commercial InGaAs PIN photodiode, as well as for temporal and line-of-sight resolutions of 10 min and 150 m, respectively. Additionally, using vertical isotopologue profiles derived from a previous field campaign, precision estimates for the HD16O isotopic abundance are provided for that specific case.

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