scholarly journals Assimilation of Satellite Microwave Observations over the Rainbands of Tropical Cyclones

2020 ◽  
Vol 148 (12) ◽  
pp. 4729-4745
Author(s):  
Isaac Moradi ◽  
K. Franklin Evans ◽  
Will McCarty ◽  
Marangelly Cordero-Fuentes ◽  
Ronald Gelaro ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Microwave Radiometer ◽  
Monte Carlo Integration ◽  
Advanced Technology ◽  
Radiative Transfer Model ◽  
Small Scale ◽  
Transfer Model ◽  
Uncertainty Estimates ◽  
Satellite Microwave ◽  
The Impact

AbstractA novel Bayesian Monte Carlo integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from the Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar-Orbiting Partnership (Suomi NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small-scale variability of precipitation and clouds when compared with the instrument footprint and also the nonlinear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model is discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include 1) the resolution of the model (about 25 km), which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast, and 2) the data assimilation system not being able to consider vertically correlated observation errors.

scholarly journals NOAA Operational Microwave Sounding Radiometer Data Quality Monitoring and Anomaly Assessment Using COSMIC GNSS Radio-Occultation Soundings

2020 ◽  
Vol 12 (5) ◽  
pp. 828
Author(s):  
Robbie Iacovazzi ◽  
Lin Lin ◽  
Ninghai Sun ◽  
Quanhua Liu
Keyword(s):  
Data Quality ◽  
Radio Occultation ◽  
Weather Prediction ◽  
Microwave Radiometer ◽  
Advanced Technology ◽  
Quality Monitoring ◽  
Radiative Transfer Model ◽  
Double Difference ◽  
Transfer Model ◽  
Microwave Sounding

National Oceanic and Atmospheric Administration (NOAA) operational Advanced Technology Microwave Sounder (ATMS) and Advanced Microwave Sounding Unit-A (AMSU-A) data used in numerical weather prediction and climate analysis are essential to protect life and property and maintain safe and efficient commerce. Routine data quality monitoring and anomaly assessment is important to sustain data effectiveness. One valuable parameter used to monitor microwave sounder data quality is the antenna temperature (Ta) difference (O-B) computed between direct instrument Ta measurements and forward radiative transfer model (RTM) brightness temperature (Tb) simulations. This requires microwave radiometer data to be collocated with atmospheric temperature and moisture sounding profiles, so that representative boundary conditions are used to produce the RTM-simulated Tb values. In this study, Constellation Observing System for Meteorology, Ionosphere, and Climate/Formosa Satellite Mission 3 (COSMIC) Global Navigation Satellite System (GNSS) Radio Occultation (RO) soundings over the ocean and equatorward of 60° latitude are used as input to the Community RTM (CRTM) to generate simulated NOAA-18, NOAA-19, Metop-A, and Metop-B AMSU-A and S-NPP and NOAA-20 ATMS Tb values. These simulated Tb values, together with observed Ta values that are nearly simultaneous in space and time, are used to compute Ta O-B statistics on monthly time scales for each instrument. In addition, the CRTM-simulated Tb values based on the COSMIC GNSS RO soundings can be used as a transfer standard to inter-compare Ta values from different microwave radiometer makes and models that have the same bands. For example, monthly Ta O-B statistics for NOAA-18 AMSU-A Channels 4–12 and NOAA-20 ATMS Channels 5–13 can be differenced to estimate the “double-difference” Ta biases between these two instruments for the corresponding frequency bands. This study reveals that the GNSS RO soundings are critical to monitoring and trending individual instrument O-B Ta biases and inter-instrument “double-difference” Ta biases and also to estimate impacts of some sensor anomalies on instrument Ta values.

scholarly journals The impact of residential combustion emissions on atmospheric aerosol, human health, and climate

2016 ◽  
Vol 16 (2) ◽  
pp. 873-905 ◽  
Author(s):  
E. W. Butt ◽  
A. Rap ◽  
A. Schmidt ◽  
C. E. Scott ◽  
K. J. Pringle ◽  
...  
Keyword(s):  
Eastern Europe ◽  
Human Health ◽  
Atmospheric Aerosol ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
So2 Emissions ◽  
Residential Sector ◽  
Residential Combustion ◽  
Combustion Emissions ◽  
The Impact

Abstract. Combustion of fuels in the residential sector for cooking and heating results in the emission of aerosol and aerosol precursors impacting air quality, human health, and climate. Residential emissions are dominated by the combustion of solid fuels. We use a global aerosol microphysics model to simulate the impact of residential fuel combustion on atmospheric aerosol for the year 2000. The model underestimates black carbon (BC) and organic carbon (OC) mass concentrations observed over Asia, Eastern Europe, and Africa, with better prediction when carbonaceous emissions from the residential sector are doubled. Observed seasonal variability of BC and OC concentrations are better simulated when residential emissions include a seasonal cycle. The largest contributions of residential emissions to annual surface mean particulate matter (PM2.5) concentrations are simulated for East Asia, South Asia, and Eastern Europe. We use a concentration response function to estimate the human health impact due to long-term exposure to ambient PM2.5 from residential emissions. We estimate global annual excess adult (>  30 years of age) premature mortality (due to both cardiopulmonary disease and lung cancer) to be 308 000 (113 300–497 000, 5th to 95th percentile uncertainty range) for monthly varying residential emissions and 517 000 (192 000–827 000) when residential carbonaceous emissions are doubled. Mortality due to residential emissions is greatest in Asia, with China and India accounting for 50 % of simulated global excess mortality. Using an offline radiative transfer model we estimate that residential emissions exert a global annual mean direct radiative effect between −66 and +21 mW m−2, with sensitivity to the residential emission flux and the assumed ratio of BC, OC, and SO2 emissions. Residential emissions exert a global annual mean first aerosol indirect effect of between −52 and −16 mW m−2, which is sensitive to the assumed size distribution of carbonaceous emissions. Overall, our results demonstrate that reducing residential combustion emissions would have substantial benefits for human health through reductions in ambient PM2.5 concentrations.

scholarly journals Analysis of actinic flux profiles measured from an ozonesonde balloon

2015 ◽  
Vol 15 (8) ◽  
pp. 4131-4144 ◽  
Author(s):  
P. Wang ◽  
M. Allaart ◽  
W. H. Knap ◽  
P. Stammes
Keyword(s):  
Atmospheric Chemistry ◽  
Low Cost ◽  
Green Light ◽  
Single Layer ◽  
Radiative Transfer Model ◽  
Cloud Base ◽  
Transfer Model ◽  
Actinic Flux ◽  
Clear Sky ◽  
The Impact

Abstract. A green light sensor has been developed at KNMI to measure actinic flux profiles using an ozonesonde balloon. In total, 63 launches with ascending and descending profiles were performed between 2006 and 2010. The measured uncalibrated actinic flux profiles are analysed using the Doubling–Adding KNMI (DAK) radiative transfer model. Values of the cloud optical thickness (COT) along the flight track were taken from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Cloud Physical Properties (CPP) product. The impact of clouds on the actinic flux profile is evaluated on the basis of the cloud modification factor (CMF) at the cloud top and cloud base, which is the ratio between the actinic fluxes for cloudy and clear-sky scenes. The impact of clouds on the actinic flux is clearly detected: the largest enhancement occurs at the cloud top due to multiple scattering. The actinic flux decreases almost linearly from cloud top to cloud base. Above the cloud top the actinic flux also increases compared to clear-sky scenes. We find that clouds can increase the actinic flux to 2.3 times the clear-sky value at cloud top and decrease it to about 0.05 at cloud base. The relationship between CMF and COT agrees well with DAK simulations, except for a few outliers. Good agreement is found between the DAK-simulated actinic flux profiles and the observations for single-layer clouds in fully overcast scenes. The instrument is suitable for operational balloon measurements because of its simplicity and low cost. It is worth further developing the instrument and launching it together with atmospheric chemistry composition sensors.

INFLUENCE OF REGULARITY OF SATELLITE MICROWAVE RADIOMETER MEASUREMENTS ON THE ACCURACY OF BRIGHTNESS TEMPERATURE REPRODUCTION IN AREAS OF THE TROPICAL CYCLONES

2021 ◽  
pp. 78-85
Author(s):  
А. G. Grankov ◽  
◽  
А. А. Milshin ◽  
Keyword(s):  
Brightness Temperature ◽  
Tropical Cyclones ◽  
Microwave Radiometer ◽  
Measurement Data ◽  
Hurricane Wilma ◽  
Brightness Temperatures ◽  
Atmosphere System ◽  
Ocean Atmosphere ◽  
The Caribbean ◽  
Satellite Microwave

An accuracy of reproduction of daily variations in the ocean–atmosphere system brightness temperature in the areas of development and movement of tropical hurricanes in the Caribbean Sea and Gulf of Mexico is analyzed. The analysis is based on the data of single and group satellite microwave radiometer measurements. The results are obtained using archival measurement data of SSM/I radiometers from the F11, F13, F14, and F15 DMSP satellites during the period of existence of tropical hurricanes Bret and Wilma. An example is given to demonstrate the use of daily brightness temperatures obtained from DMSP satellites for monitoring the development and propagation of hurricane Wilma.

scholarly journals Data-Driven Localization Mappings in Filtering the Monsoon–Hadley Multicloud Convective Flows

2018 ◽  
Vol 146 (4) ◽  
pp. 1197-1218
Author(s):  
Michèle De La Chevrotière ◽  
John Harlim
Keyword(s):  
Learning Algorithm ◽  
Data Driven ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Model Errors ◽  
Accurate Analysis ◽  
Perfect Model ◽  
Nonlinear Stochastic Model ◽  
Correlation Statistics ◽  
The Impact

This paper demonstrates the efficacy of data-driven localization mappings for assimilating satellite-like observations in a dynamical system of intermediate complexity. In particular, a sparse network of synthetic brightness temperature measurements is simulated using an idealized radiative transfer model and assimilated to the monsoon–Hadley multicloud model, a nonlinear stochastic model containing several thousands of model coordinates. A serial ensemble Kalman filter is implemented in which the empirical correlation statistics are improved using localization maps obtained from a supervised learning algorithm. The impact of the localization mappings is assessed in perfect-model observing system simulation experiments (OSSEs) as well as in the presence of model errors resulting from the misspecification of key convective closure parameters. In perfect-model OSSEs, the localization mappings that use adjacent correlations to improve the correlation estimated from small ensemble sizes produce robust accurate analysis estimates. In the presence of model error, the filter skills of the localization maps trained on perfect- and imperfect-model data are comparable.

scholarly journals All-Sky Radiance Assimilation of ATMS in HWRF: A Demonstration Study

2018 ◽  
Vol 147 (1) ◽  
pp. 85-106 ◽  
Author(s):  
Ting-Chi Wu ◽  
Milija Zupanski ◽  
Lewis D. Grasso ◽  
Christian D. Kummerow ◽  
Sid-Ahmed Boukabara
Keyword(s):  
Single Case ◽  
Control Variable ◽  
Data Availability ◽  
Advanced Technology ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
State Variables ◽  
Initial State ◽  
Clear Sky ◽  
Analysis System

Abstract Satellite all-sky radiances from the Advanced Technology Microwave Sounder (ATMS) are assimilated into the Hurricane Weather Research and Forecasting (HWRF) Model using the hybrid Gridpoint Statistical Interpolation analysis system (GSI). To extend the all-sky capability recently developed for global applications to HWRF, some modifications in HWRF and GSI are facilitated. In particular, total condensate is added as a control variable, and six distinct hydrometeor habits are added as state variables in hybrid GSI within HWRF. That is, clear-sky together with cloudy and precipitation-affected satellite pixels are assimilated using the Community Radiative Transfer Model (CRTM) as a forward operator that includes hydrometeor information and Jacobians with respect to hydrometeor variables. A single case study with the 2014 Atlantic storm Hurricane Cristobal is used to demonstrate the methodology of extending the global all-sky capability to HWRF due to ATMS data availability. Two data assimilation experiments are carried out. One experiment uses the operational configuration and assimilates ATMS radiances under the clear-sky condition, and the other experiment uses the modified HWRF system and assimilates ATMS radiances under the all-sky condition with the inclusion of total condensate update and cycling. Observed and synthetic Geostationary Operational Environmental Satellite (GOES)-13 data along with Global Precipitation Measurement Mission (GPM) Microwave Imager (GMI) data from the two experiments are used to show that the experiment with all-sky ATMS radiances assimilation has cloud signatures that are supported by observations. In contrast, there is lack of clouds in the initial state that led to a noticeable lag of cloud development in the experiment that assimilates clear-sky radiances.

scholarly journals Influence of spatial heterogeneity of local surface albedo on the area-averaged surface albedo retrieved from airborne irradiance measurements

2013 ◽  
Vol 6 (3) ◽  
pp. 527-537 ◽  
Author(s):  
E. Jäkel ◽  
M. Wendisch ◽  
B. Mayer
Keyword(s):  
Optical Depth ◽  
Surface Albedo ◽  
Radiative Transfer Model ◽  
Small Scale ◽  
Mean Deviation ◽  
Transfer Model ◽  
Horizontal Distance ◽  
Local Surface ◽  
Atmospheric Scattering ◽  
The Mean

Abstract. Spectral airborne upward and downward irradiance measurements are used to derive the area-averaged surface albedo. Real surfaces are not homogeneous in their reflectivity. Therefore, this work studies the effects of the heterogeneity of surface reflectivity on the area-averaged surface albedo to quantify how well aircraft measurements can resolve the small-scale variability of the local surface albedo. For that purpose spatially heterogeneous surface albedo maps were input into a 3-dimensional (3-D) Monte Carlo radiative transfer model to simulate 3-D irradiance fields. The calculated up- and downward irradiances in altitudes between 0.1 and 5 km are used to derive the area-averaged surface albedo using an iterative retrieval method that removes the effects due to atmospheric scattering and absorption within the layer beneath the considered level. For the case of adjacent land and sea surfaces, parametrizations are presented which quantify the horizontal distance from the coastline that is required to reduce surface heterogeneity effects on the area-averaged surface albedo to a given limit. The parametrization which is a function of altitude, aerosol optical depth, single scattering albedo, and the ratio of local land and sea albedo was applied for airborne spectral measurements. In addition, the deviation between area-averaged and local surface albedo is determined for more complex surface albedo maps. For moderate aerosol conditions (optical depth less than 0.4) and a wavelength range between 400 and 1000 nm, the altitude and the heterogeneity of the surface albedo are the dominant factors determining the mean deviation between local and area-averaged surface albedo. A parametrization of the mean deviation is applied to an albedo map that was derived from a Landsat image of an area in East Anglia (UK). Parametrization and direct comparison of local and area-averaged surface albedo show similar mean deviations (20% vs. 25%) over land.

The impact of time-dependent stellar activity on the atmospheric chemistry and observability of exoplanets

2021 ◽  
Author(s):  
Amy Louca ◽  
Yamila Miguel ◽  
Shang-Min Tsai
Keyword(s):  
Atmospheric Chemistry ◽  
Emission Spectra ◽  
Time Dependent ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Stellar Spectrum ◽  
Stellar Spectra ◽  
Chemical Tracers ◽  
Atmospheric Escape ◽  
The Impact

<p class="p1">Observations of exoplanets used to characterize the chemistry and dynamics of atmospheres have developed considerably throughout the years. Nonetheless, it remains a difficult task to give a full and detailed description using solely observations. With future space missions such as JWST and ARIEL, both expected to be launched within this decade, it becomes even more crucial to be able to fully explain and predict the underlying chemistry and physics involved. In this research, we focus on modeling star-planet interactions by using synthetic flare spectra to predict chemical tracers for future missions. We make use of a chemical kinetics code that includes synthetic time-dependent stellar spectra and thermal atmospheric escape to simulate the atmospheres of known exoplanets. Using a radiative transfer model we then retrieve emission spectra. This ongoing study is focused on various known planetary systems of which the stellar spectrum has been obtained by the (mega-)MUSCLES collaboration. Preliminary results on these systems show that stellar flares and thermal escape can have a significant effect on the chemistry in atmospheres. </p>

scholarly journals Characterization of aerosol hygroscopicity using Raman lidar measurements at the EARLINET station of Payerne

2019 ◽  
Vol 19 (18) ◽  
pp. 11651-11668 ◽  
Author(s):  
Francisco Navas-Guzmán ◽  
Giovanni Martucci ◽  
Martine Collaud Coen ◽  
María José Granados-Muñoz ◽  
Maxime Hervo ◽  
...  
Keyword(s):  
Lower Troposphere ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Raman Lidar ◽  
Hygroscopic Growth ◽  
Backscatter Coefficient ◽  
Radiative Balance ◽  
First Case ◽  
The Impact ◽  
Aerosol Hygroscopicity

Abstract. This study focuses on the analysis of aerosol hygroscopicity using remote sensing techniques. Continuous observations of aerosol backscatter coefficient (βaer), temperature (T) and water vapor mixing ratio (r) have been performed by means of a Raman lidar system at the aerological station of MeteoSwiss at Payerne (Switzerland) since 2008. These measurements allow us to monitor in a continuous way any change in aerosol properties as a function of the relative humidity (RH). These changes can be observed either in time at a constant altitude or in altitude at a constant time. The accuracy and precision of RH measurements from the lidar have been evaluated using the radiosonde (RS) technique as a reference. A total of 172 RS profiles were used in this intercomparison, which revealed a bias smaller than 4 % RH and a standard deviation smaller than 10 % RH between both techniques in the whole (in lower) troposphere at nighttime (at daytime), indicating the good performance of the lidar for characterizing RH. A methodology to identify situations favorable to studying aerosol hygroscopicity has been established, and the aerosol hygroscopicity has been characterized by means of the backscatter enhancement factor (fβ). Two case studies, corresponding to different types of aerosol, are used to illustrate the potential of this methodology. The first case corresponds to a mixture of rural aerosol and smoke particles (smoke mixture), which showed a higher hygroscopicity (fβ355=2.8 and fβ1064=1.8 in the RH range 73 %–97 %) than the second case, in which mineral dust was present (fβ355=1.2 and fβ1064=1.1 in the RH range 68 %–84 %). The higher sensitivity of the shortest wavelength to hygroscopic growth was qualitatively reproduced using Mie simulations. In addition, a good agreement was found between the hygroscopic analysis done in the vertical and in time for Case I, where the latter also allowed us to observe the hydration and dehydration of the smoke mixture. Finally, the impact of aerosol hygroscopicity on the Earth's radiative balance has been evaluated using the GAME (Global Atmospheric Model) radiative transfer model. The model showed an impact with an increase in absolute value of 2.4 W m−2 at the surface with respect to the dry conditions for the hygroscopic layer of Case I (smoke mixture).

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