scholarly journals Assessment of cloud properties from the reanalysis with satellite observations over East Asia

2019 ◽  
Author(s):  
Bin Yao ◽  
Chao Liu ◽  
Yan Yin ◽  
Zhiquan Liu ◽  
Chunxiang Shi ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
East Asia ◽  
Deep Convection ◽  
Satellite Observation ◽  
Reanalysis Data ◽  
Satellite Observations ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
China Meteorological Administration ◽  
Cloud Properties

Abstract. Extensive observational and numerical investigations have been performed to better characterize cloud properties. However, due to the large variations of cloud spatiotemporal distributions and physical properties, quantitative depictions of clouds in different atmospheric reanalysis datasets are still highly uncertain, and cloud parameters in the models to produce those datasets remain largely unconstrained. A radiance-based evaluation approach is introduced and performed to assess the quality of cloud properties by directly comparing reanalysis-driven forward radiative transfer results with radiances from satellite observation. The newly developed China Meteorological Administration Reanalysis data (CRA), the ECMWF’s Fifth-generation Reanalysis (ERA5), and the Modern-Era Retrospective Analysis for Applications, Version 2 (MERRA-2) are considered in the present study. To avoid the unrealistic assumptions and uncertainties on satellite retrieval algorithms and products, the radiative transfer model (RTM) is used as a bridge to “translate” the reanalysis to corresponding satellite observations. The simulated reflectance and brightness temperatures (BTs) are directly compared with observations from the Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite in the region from 80° E to 160° W between 60° N and 60° S, especially for results over East Asia. Comparisons of the reflectance in the solar and BTs in the infrared (IR) window channels reveal that CRA reanalysis better represents the total cloud cover than the other two reanalysis datasets. The simulated BTs for CRA and ERA5 are close to each other in many pixels, whereas the vertical distributions of cloud properties are significantly different, and ERA5 depicts a better deep convection structure than CRA reanalysis. Comparisons of the BT differences (BTDs) between the simulations and observations suggest that the water clouds are generally overestimated in ERA5 and MERRA-2, whereas the ice cloud is responsible for the overestimation over the center of cyclones in ERA5. Overall, the cloud from CRA, ERA5, and MERRA-2 show their own advantages in different aspects. The ERA5 reanalysis is found the most capability in representing the cloudy atmosphere over East Asia, and the results in CRA are close to those in ERA5.

scholarly journals Evaluation of cloud properties from reanalyses over East Asia with a radiance-based approach

2020 ◽  
Vol 13 (3) ◽  
pp. 1033-1049 ◽  
Author(s):  
Bin Yao ◽  
Chao Liu ◽  
Yan Yin ◽  
Zhiquan Liu ◽  
Chunxiang Shi ◽  
...  
Keyword(s):  
East Asia ◽  
Deep Convection ◽  
China Meteorological Administration ◽  
Ice Clouds ◽  
Brightness Temperatures ◽  
Evaluation Approach ◽  
Cloud Properties ◽  
Fifth Generation ◽  
East Asia Region ◽  
Modern Era

Abstract. Extensive observational and numerical investigations have been performed to better characterize cloud properties. However, due to the large variations in cloud spatiotemporal distributions and physical properties, quantitative depictions of clouds in different atmospheric reanalysis datasets are still highly uncertain. A radiance-based evaluation approach is introduced and performed to evaluate the quality of cloud properties from reanalysis datasets. The China Meteorological Administration reanalysis (CRA); the ECMWF fifth-generation reanalysis (ERA5); and the Modern-Era Retrospective analysis for Applications, Version 2 (MERRA-2), i.e., those reanalyses providing sufficient cloud information, are considered. To avoid the influence of assumptions and uncertainties on satellite retrieval algorithms, forward radiative transfer simulations are used as a bridge to translate the reanalyses to corresponding radiances that are expected to be observed by satellites. The simulated reflectances and brightness temperatures (BTs) are directly compared with observations from the Advanced Himawari Imager onboard the Himawari-8 satellite in the East Asia region. We find that the simulated reflectances and BTs based on CRA and ERA5 are close to each other. CRA represents the total and midlayer cloud cover better than the other two datasets, and ERA5 depicts deep-convection structures more closely than CRA does. Comparisons of the simulated and observed BT differences suggest that water clouds are generally overestimated in ERA5 and MERRA-2, and MERRA-2 also overestimates the ice clouds over cyclone centers. Overall, clouds from CRA, ERA5, and MERRA-2 show their own advantages in different aspects. The ERA5 reanalysis has the best capability to represent the cloudy atmospheres over East Asia, and the CRA representations are close to those in ERA5.

scholarly journals Feasibility study of multi-pixel retrieval of optical thickness and droplet effective radius of inhomogeneous clouds using deep learning

2017 ◽  
Vol 10 (12) ◽  
pp. 4747-4759 ◽  
Author(s):  
Rintaro Okamura ◽  
Hironobu Iwabuchi ◽  
K. Sebastian Schmidt
Keyword(s):  
Deep Learning ◽  
Radiative Transfer ◽  
Optical Thickness ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Optical Remote Sensing ◽  
Transfer Effects ◽  
Cloud Properties

Abstract. Three-dimensional (3-D) radiative-transfer effects are a major source of retrieval errors in satellite-based optical remote sensing of clouds. The challenge is that 3-D effects manifest themselves across multiple satellite pixels, which traditional single-pixel approaches cannot capture. In this study, we present two multi-pixel retrieval approaches based on deep learning, a technique that is becoming increasingly successful for complex problems in engineering and other areas. Specifically, we use deep neural networks (DNNs) to obtain multi-pixel estimates of cloud optical thickness and column-mean cloud droplet effective radius from multispectral, multi-pixel radiances. The first DNN method corrects traditional bispectral retrievals based on the plane-parallel homogeneous cloud assumption using the reflectances at the same two wavelengths. The other DNN method uses so-called convolutional layers and retrieves cloud properties directly from the reflectances at four wavelengths. The DNN methods are trained and tested on cloud fields from large-eddy simulations used as input to a 3-D radiative-transfer model to simulate upward radiances. The second DNN-based retrieval, sidestepping the bispectral retrieval step through convolutional layers, is shown to be more accurate. It reduces 3-D radiative-transfer effects that would otherwise affect the radiance values and estimates cloud properties robustly even for optically thick clouds.

scholarly journals Sensitivity of satellite observations for freshly produced lightning NO<sub>x</sub>

2009 ◽  
Vol 9 (3) ◽  
pp. 1077-1094 ◽  
Author(s):  
S. Beirle ◽  
M. Salzmann ◽  
M. G. Lawrence ◽  
T. Wagner
Keyword(s):  
Radiative Transfer ◽  
Satellite Observations ◽  
Radiative Transfer Model ◽  
Visible Range ◽  
Transfer Model ◽  
Satellite Measurements ◽  
Vertical Column ◽  
Toga Coare ◽  
Photo Chemistry ◽  
Lightning Nox

Abstract. In this study, we analyse the sensitivity of nadir viewing satellite observations in the visible range to freshly produced lightning NOx. This is a particular challenge due to the complex and highly variable conditions of meteorology, (photo-) chemistry, and radiative transfer in and around cumulonimbus clouds. For the first time, such a study is performed accounting for photo-chemistry, dynamics, and radiative transfer in a consistent way: A one week episode in the TOGA COARE/CEPEX region (Pacific) in December 1992 is simulated with a 3-D cloud resolving chemistry model. The simulated hydrometeor mixing ratios are fed into a Monte Carlo radiative transfer model to calculate box-Air Mass Factors (box-AMFs) for NO2. From these box-AMFs, together with model NOx profiles, slant columns of NO2 (SNO2), i.e. synthetic satellite measurements, are calculated and set in relation to the actual model NOx vertical column (VNOx), yielding the "sensitivity" SNO2/VNOx. From this study, we find a mean sensitivity of 0.46. NOx below the cloud bottom is mostly present as NO2, but shielded from the satellites' view, whereas NOx at the cloud top or above is shifted to NO due to high photolysis and low temperature, and hence not detectable from space. However, a significant fraction of the lightning produced NOx in the middle part of the cloud is present as NO2 and has a good visibility from space. Due to the resulting total sensitivity being quite high, nadir viewing satellites provide a valuable additional platform to quantify NOx production by lightning; strong lightning events over "clean" regions should be clearly detectable in satellite observations. Since the observed enhancement of NO2 column densities over mesoscale convective systems are lower than expected for current estimates of NOx production per flash, satellite measurements can in particular constrain the upper bound of lightning NOx production estimates.

scholarly journals Evaluation of Cirrus Parameterizations for Radiative Flux Computations in Climate Models Using TOVS–ScaRaB Satellite Observations

2007 ◽  
Vol 20 (17) ◽  
pp. 4459-4475 ◽  
Author(s):  
C. J. Stubenrauch ◽  
F. Eddounia ◽  
J. M. Edwards ◽  
A. Macke
Keyword(s):  
Optical Properties ◽  
Radiative Transfer ◽  
Climate Models ◽  
Radiative Flux ◽  
Satellite Observations ◽  
Radiation Budget ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Ice Crystal ◽  
Infrared Observation

Abstract Combined simultaneous satellite observations are used to evaluate the performance of parameterizations of the microphysical and optical properties of cirrus clouds used for radiative flux computations in climate models. Atmospheric and cirrus properties retrieved from Television and Infrared Observation Satellite (TIROS-N) Operational Vertical Sounder (TOVS) observations are given as input to the radiative transfer model developed for the Met Office climate model to simulate radiative fluxes at the top of the atmosphere (TOA). Simulated cirrus shortwave (SW) albedos are then compared to those retrieved from collocated Scanner for Radiation Budget (ScaRaB) observations. For the retrieval, special care has been given to angular direction models. Three parameterizations of cirrus ice crystal optical properties are represented in the Met Office radiative transfer model. These parameterizations are based on different physical approximations and different hypotheses on crystal habit. One parameterization assumes pristine ice crystals and two ice crystal aggregates. By relating the cirrus ice water path (IWP) retrieved from the effective infrared emissivity to the cirrus SW albedo, differences between the parameterizations are amplified. This study shows that pristine crystals seem to be plausible only for cirrus with IWP less than 30 g m−2. For larger IWP, ice crystal aggregates lead to cirrus SW albedos in better agreement with the observations. The data also indicate that climate models should allow the cirrus effective ice crystal diameter (De) to increase with IWP, especially in the range up to 30 g m−2. For cirrus with IWP less than 20 g m−2, this would lead to SW albedos that are about 0.02 higher than the ones of a constant De of 55 μm.

scholarly journals Retrieval of Ice Cloud Properties from AIRS and MODIS Observations Based on a Fast High-Spectral-Resolution Radiative Transfer Model

2013 ◽  
Vol 52 (3) ◽  
pp. 710-726 ◽  
Author(s):  
Chenxi Wang ◽  
Ping Yang ◽  
Steven Platnick ◽  
Andrew K. Heidinger ◽  
Bryan A. Baum ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Spectral Resolution ◽  
Spectral Response ◽  
Thermal Infrared ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Retrieval Method ◽  
Ice Cloud ◽  
Cloud Properties

AbstractA computationally efficient high-spectral-resolution cloudy-sky radiative transfer model (HRTM) in the thermal infrared region (700–1300 cm−1, 0.1 cm−1 spectral resolution) is advanced for simulating the upwelling radiance at the top of atmosphere and for retrieving cloud properties. A precomputed transmittance database is generated for simulating the absorption contributed by up to seven major atmospheric absorptive gases (H2O, CO2, O3, O2, CH4, CO, and N2O) by using a rigorous line-by-line radiative transfer model (LBLRTM). Both the line absorption of individual gases and continuum absorption are included in the database. A high-spectral-resolution ice particle bulk scattering properties database is employed to simulate the radiation transfer within a vertically nonisothermal ice cloud layer. Inherent to HRTM are sensor spectral response functions that couple with high-spectral-resolution measurements in the thermal infrared regions from instruments such as the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer. When compared with the LBLRTM and the discrete ordinates radiative transfer model (DISORT), the root-mean-square error of HRTM-simulated single-layer cloud brightness temperatures in the thermal infrared window region is generally smaller than 0.2 K. An ice cloud optical property retrieval scheme is developed using collocated AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) data. A retrieval method is proposed to take advantage of the high-spectral-resolution instrument. On the basis of the forward model and retrieval method, a case study is presented for the simultaneous retrieval of ice cloud optical thickness τ and effective particle size Deff that includes a cloud-top-altitude self-adjustment approach to improve consistency with simulations.

scholarly journals Performance of the Line-By-Line Radiative Transfer Model (LBLRTM) for temperature, water vapor, and trace gas retrievals: recent updates evaluated with IASI case studies

2013 ◽  
Vol 13 (14) ◽  
pp. 6687-6711 ◽  
Author(s):  
M. J. Alvarado ◽  
V. H. Payne ◽  
E. J. Mlawer ◽  
G. Uymin ◽  
M. W. Shephard ◽  
...  
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Fixed Ratio ◽  
Satellite Observations ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Temperature Profiles ◽  
A Posteriori ◽  
The Impact ◽  
Temperature Water

Abstract. Modern data assimilation algorithms depend on accurate infrared spectroscopy in order to make use of the information related to temperature, water vapor (H2O), and other trace gases provided by satellite observations. Reducing the uncertainties in our knowledge of spectroscopic line parameters and continuum absorption is thus important to improve the application of satellite data to weather forecasting. Here we present the results of a rigorous validation of spectroscopic updates to an advanced radiative transfer model, the Line-By-Line Radiative Transfer Model (LBLRTM), against a global dataset of 120 near-nadir, over-ocean, nighttime spectra from the Infrared Atmospheric Sounding Interferometer (IASI). We compare calculations from the latest version of LBLRTM (v12.1) to those from a previous version (v9.4+) to determine the impact of spectroscopic updates to the model on spectral residuals as well as retrieved temperature and H2O profiles. We show that the spectroscopy in the CO2 ν2 and ν3 bands is significantly improved in LBLRTM v12.1 relative to v9.4+, and that these spectroscopic updates lead to mean changes of ~0.5 K in the retrieved vertical temperature profiles between the surface and 10 hPa, with the sign of the change and the variability among cases depending on altitude. We also find that temperature retrievals using each of these two CO2 bands are remarkably consistent in LBLRTM v12.1, potentially allowing these bands to be used to retrieve atmospheric temperature simultaneously. The updated H2O spectroscopy in LBLRTM v12.1 substantially improves the a posteriori residuals in the P-branch of the H2O ν2 band, while the improvements in the R-branch are more modest. The H2O amounts retrieved with LBLRTM v12.1 are on average 14% lower between 100 and 200 hPa, 42% higher near 562 hPa, and 31% higher near the surface compared to the amounts retrieved with v9.4+ due to a combination of the different retrieved temperature profiles and the updated H2O spectroscopy. We also find that the use of a fixed ratio of HDO to H2O in LBLRTM may be responsible for a significant fraction of the remaining bias in the P-branch relative to the R-branch of the H2O ν2 band. There were no changes to O3 spectroscopy between the two model versions, and so both versions give positive a posteriori residuals of ~ 0.3 K in the R-branch of the O3 ν3 band. While the updates to the H2O self-continuum employed by LBLRTM v12.1 have clearly improved the match with observations near the CO2 ν3 band head, we find that these updates have significantly degraded the match with observations in the fundamental band of CO. Finally, significant systematic a posteriori residuals remain in the ν4 band of CH4, but the magnitude of the positive bias in the retrieved mixing ratios is reduced in LBLRTM v12.1, suggesting that the updated spectroscopy could improve retrievals of CH4 from satellite observations.

scholarly journals Sensitivity of satellite observations for freshly produced lightning NO<sub>x</sub>

2008 ◽  
Vol 8 (5) ◽  
pp. 18111-18153
Author(s):  
S. Beirle ◽  
M. Salzmann ◽  
M. G. Lawrence ◽  
T. Wagner
Keyword(s):  
Radiative Transfer ◽  
Middle Part ◽  
Satellite Observations ◽  
Radiative Transfer Model ◽  
Visible Range ◽  
Transfer Model ◽  
Satellite Measurements ◽  
Vertical Column ◽  
Toga Coare ◽  
Lightning Nox

Abstract. In this study, we analyse the sensitivity of nadir viewing satellite observations in the visible range to freshly produced lightning NOx, i.e. for meteorological and (photo-) chemical conditions found in and around cumulonimbus clouds. For the first time, such a study is performed accounting for photo-chemistry, dynamics, and radiative transfer in a consistent way: A one week episode in the TOGA COARE/CEPEX region (Pacific) in December 1992 is simulated with a 3-D cloud resolving chemistry model. The simulated hydrometeor mixing ratios are fed into a Monte Carlo radiative transfer model to calculate box-Air Mass Factors (box-AMFs) for NO2. From these box-AMFs, together with model NOx profiles, slant columns of NO2 (SNO2), i.e. synthetic satellite measurements, are calculated and set in relation to the actual model NOx vertical column (VNOx), yielding the "sensitivity" SNO2/VNOx. From this study, we find a mean sensitivity of 0.46. NOx below the cloud bottom is mostly present as NO2, but shielded from the satellites' view, whereas NOx at the cloud top or above is shifted to NO due to high photolysis and low temperature, and hence not detectable from space. But a significant fraction of the lightning produced NOx in the middle part of the cloud is present as NO2 and has a good visibility from space. Due to the resulting total sensitivity being quite high, nadir viewing satellites provide a valuable additional platform to quantify NOx production by lightning; strong lightning events over "clean" regions should be clearly detectable in satellite observations. Since the observed enhancement of NO2 column densities over mesoscale convective systems are lower than expected for current estimates of NOx production per flash, satellite measurements can in particular constrain the upper bound of lightning NOx production estimates.

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