Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales

The article “Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales”, written by Yunji ZHANG, Eugene E. CLOTHIAUX, and David J. STENSRUD was originally published electronically on the publisher’s internet portal on 30 of April 2021 without open access. With the author(s)’ decision to opt for Open Choice, the copyright of the article changed on 26 of October 2021 to © The Author(s), 2021 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0.The original article has been corrected.

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Far-Infrared Brightness Temperatures of the Planets

The Astrophysical Journal ◽

10.1086/181090 ◽

1972 ◽

Vol 178 ◽

pp. L89 ◽

Cited By ~ 40

Author(s):

K. R. Armstrong ◽

D. A., Jr. Harper ◽

F. J. Low

Keyword(s):

Far Infrared ◽

Brightness Temperatures ◽

Infrared Brightness

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How microphysical choices affect simulated infrared brightness temperatures

Atmospheric Research ◽

10.1016/j.atmosres.2014.12.010 ◽

2015 ◽

Vol 156 ◽

pp. 67-79 ◽

Cited By ~ 12

Author(s):

S. Eikenberg ◽

C. Köhler ◽

A. Seifert ◽

S. Crewell

Keyword(s):

Brightness Temperatures ◽

Infrared Brightness

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Assessing the Accuracy of the Cloud and Water Vapor Fields in the Hurricane WRF (HWRF) Model Using Satellite Infrared Brightness Temperatures

Monthly Weather Review ◽

10.1175/mwr-d-16-0354.1 ◽

2017 ◽

Vol 145 (5) ◽

pp. 2027-2046 ◽

Cited By ~ 7

Author(s):

Jason A. Otkin ◽

William E. Lewis ◽

Allen J. Lenzen ◽

Brian D. McNoldy ◽

Sharanya J. Majumdar

Keyword(s):

Forecast Accuracy ◽

Cloud Microphysics ◽

Cumulus Parameterization ◽

Upper Troposphere ◽

Wind Speeds ◽

Parameterization Schemes ◽

Brightness Temperatures ◽

Cumulus Parameterization Schemes ◽

Hwrf Model ◽

Infrared Brightness

Abstract In this study, cycled forecast experiments were performed to assess the ability of different cloud microphysics and cumulus parameterization schemes in the Hurricane Weather Research and Forecasting (HWRF) Model to accurately simulate the evolution of the cloud and moisture fields during the entire life cycle of Hurricane Edouard (2014). The forecast accuracy for each model configuration was evaluated through comparison of observed and simulated Geostationary Operational Environmental Satellite-13 (GOES-13) infrared brightness temperatures and satellite-derived tropical cyclone intensity estimates computed using the advanced Dvorak technique (ADT). Overall, the analysis revealed a large moist bias in the mid- and upper troposphere during the entire forecast period that was at least partially due to a moist bias in the initialization datasets but was also affected by the microphysics and cumulus parameterization schemes. Large differences occurred in the azimuthal brightness temperature distributions, with two of the microphysics schemes producing hurricane eyes that were much larger and clearer than observed, especially for later forecast hours. Comparisons to the forecast 10-m wind speeds showed reasonable agreement (correlations between 0.58 and 0.74) between the surface-based intensities and the ADT intensity estimates inferred via cloud patterns in the upper troposphere. It was also found that model configurations that had the smallest differences between the ADT and surface-based intensities had the most accurate track and intensity forecasts. Last, the cloud microphysics schemes had the largest impact on the forecast accuracy.

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Assessing the Influence of Upper-Tropospheric Troughs on Tropical Cyclone Intensification Rates after Genesis

Monthly Weather Review ◽

10.1175/mwr-d-16-0275.1 ◽

2017 ◽

Vol 145 (4) ◽

pp. 1295-1313 ◽

Cited By ~ 18

Author(s):

Michael S. Fischer ◽

Brian H. Tang ◽

Kristen L. Corbosiero

Keyword(s):

Tropical Cyclones ◽

North Atlantic ◽

Temporal Evolution ◽

Tropical Cyclogenesis ◽

Brightness Temperatures ◽

The North ◽

The North Atlantic ◽

Upper Level ◽

Infrared Brightness

Abstract The role of upper-tropospheric troughs on the intensification rate of newly formed tropical cyclones (TCs) is analyzed. This study focuses on TCs forming in the presence of upper-tropospheric troughs in the North Atlantic basin between 1980 and 2014. TCs were binned into three groups based upon the 24-h intensification rate starting at the time of genesis: rapid TC genesis (RTCG), slow TC genesis (STCG), and neutral TC genesis (NTCG). Composite analysis shows RTCG events are characterized by amplified upper-tropospheric flow with the largest upshear displacement between the TC and trough of the three groups. RTCG events are associated with greater quasigeostrophic (QG) ascent in upshear quadrants of the TC, forced by differential vorticity advection by the thermal wind, especially around the time of genesis. This pattern of QG ascent closely matches the RTCG composite of infrared brightness temperatures. Conversely, NTCG events are associated with an upper-tropospheric trough that is closest to the TC center. The distribution of QG ascent in NTCG events becomes increasingly asymmetric around the time of genesis, with a maximum that shifts downshear of the TC center, consistent with infrared brightness temperatures. It is hypothesized that the TC intensification rate after tropical cyclogenesis, in environments of upper-tropospheric troughs, is closely linked to the structure and temporal evolution of the upper-level trough. The TC–trough configurations that provide greater QG ascent to the left of, and upshear of, the TC center feature more symmetric convection and faster TC intensification rates.

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Climatology of Tropical Overshooting Tops in North Atlantic Tropical Cyclones

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-16-0413.1 ◽

2017 ◽

Vol 56 (6) ◽

pp. 1783-1796 ◽

Cited By ~ 3

Author(s):

Sarah M. Griffin

Keyword(s):

Tropical Cyclones ◽

North Atlantic ◽

North Atlantic Ocean ◽

Vertical Wind Shear ◽

Detection Algorithm ◽

Exponential Relationship ◽

Brightness Temperatures ◽

Study Results ◽

Infrared Brightness

AbstractOrganized tropical convection, often characterized by overshooting tops, is a distinguishing quality of tropical cyclones (TCs). In this study, the climatology of tropical overshooting tops (TOTs) in North Atlantic Ocean TCs from 2004 to 2015 is examined. Previous studies have investigated the distribution of convection in TCs based on lightning data. The purpose of this study is to examine the distribution of TC convection from geostationary satellites using an objective TOT detection algorithm based on infrared brightness temperatures and empirically dependent thresholds. It will be shown that TOTs can provide an additional metric for identifying the characteristics of TC convection. Based on the 12-yr (2004–15) climatology, a distinct semidiurnal cycle in TOT activity is detected within 500 km of the TC center. In agreement with lightning data from previous studies, a predawn maximum (local to the TC) in TOTs is observed within 300 km of the TC center. A second predusk maximum is associated with TOTs between 300 and 500 km of the TC center. TC intensity and intensity trend along with environmental factors can affect the number and distribution of TOTs. For example, an exponential relationship exists between the number of TOTs and increasing sea surface temperatures. Conversely, increasing vertical wind shear magnitude decreases the density of TOTs, with a higher percentage of TOTs observed downshear of the wind direction. Generally, within 100 km (100–300 km) of the TC center, the preferred quadrant for TOTs is downshear left (downshear right), and increased TOT activity is observed right of TC motion. The findings corroborate previous lightning study results while providing additional insights into TC convection.

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PAMTRA 1.0: A Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere

10.5194/gmd-2019-356 ◽

2020 ◽

Cited By ~ 1

Author(s):

Mario Mech ◽

Maximilian Maahn ◽

Stefan Kneifel ◽

Davide Ori ◽

Emiliano Orlandi ◽

...

Keyword(s):

Radiative Transfer ◽

Forward Model ◽

Doppler Spectrum ◽

Brightness Temperatures ◽

Cloudy Atmosphere ◽

Radar Measurements ◽

Self Similar ◽

Atmospheric State ◽

Simulation Results

Abstract. Forward models are a key tool to generate synthetic observations given the knowledge of the atmospheric state. In this way they are an integral part of inversion algorithms that aim to retrieve geophysical variables from observations or in data assimilation. Their application for the exploitation of the full information content of remote sensing observations becomes increasingly important when these are used to evaluate the performance of cloud resolving models (CRMs). Herein, CRMs profiles or fields provide the input to the forward model whose simulation results are subsequently compared to the observations. This paper introduces the freely available comprehensive microwave forward model PAMTRA (Passive and Active Microwave TRAnsfer), demonstrates its capabilities to simulate passive and active measurements across the microwave spectral region for up- and downward looking geometries, and illustrates how the forward simulations can be used to evaluate CRMs and to interpret measurements to improve our understanding of cloud processes. PAMTRA is unique as it treats passive and active radiative transfer (RT) in a consistent way with the passive forward model providing up- and down-welling polarized brightness temperatures and radiances for arbitrary observation angles. The active part is capable of simulating the full radar Doppler spectrum and its moments. PAMTRA is designed to be flexible with respect to instrument specifications, interfaces to many different formats of in- and output type, especially CRMs, spanning the range from bin-resolved microphysical output to one- and two-moment schemes, and to in situ measured hydrometeor properties. A specific highlight is the incorporation of the self-similar Rayleigh--Gans Approximation (SSRGA) both for active and passive applications which becomes especially important for the investigation of frozen hydrometeors.

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Assessing the Impact of Stochastic Perturbations in Cloud Microphysics using GOES-16 Infrared Brightness Temperatures

Monthly Weather Review ◽

10.1175/mwr-d-20-0078.1 ◽

2020 ◽

Vol 148 (8) ◽

pp. 3111-3137 ◽

Cited By ~ 1

Author(s):

Sarah M. Griffin ◽

Jason A. Otkin ◽

Gregory Thompson ◽

Maria Frediani ◽

Judith Berner ◽

...

Keyword(s):

Potential Temperature ◽

Control Object ◽

Cloud Microphysics ◽

Temperature Fields ◽

Microphysics Scheme ◽

Stochastic Perturbations ◽

Brightness Temperatures ◽

Object Based ◽

The Impact ◽

Infrared Brightness

Abstract In this study, infrared brightness temperatures (BTs) are used to examine how applying stochastic perturbed parameter (SPP) methodology to the widely used Thompson–Eidhammer cloud microphysics scheme impacts the cloud field in high-resolution forecasts. Modifications are made to add stochastic perturbations to three parameters controlling cloud generation and dissipation processes. Two five-member ensembles are generated, one using the microphysics parameter perturbations (SPP-MP) and another where white noise perturbations were added to potential temperature fields at initialization time (Control). The impact of the SPP method was assessed using simulated and observed GOES-16 BTs. This analysis uses pixel-based and object-based methods to assess the impact on the cloud field. Pixel-based methods revealed that the SPP-MP BTs are slightly more accurate than the Control BTs. However, too few pixels with a BT lower than 270 K result in a positive bias compared to the observations. A negative bias compared to the observations is observed when only analyzing lower BTs. The spread of the ensemble BTs was analyzed using the continuous ranked probability score differences, with the SPP-MP ensemble BTs having less (more) spread during May (January) compared to the Control. Object-based analysis using the Method for Object-Based Diagnostic Evaluation revealed the upper-level cloud objects are smaller in the SPP-MP ensemble than the Control but a lower bias exists in the SPP-MP BTs compared to the Control BTs when overlapping matching objects. However, there is no clear distinction between the SPP-MP and Control ensemble members during the evolution of objects, Overall, the SPP-MP perturbations result in lower BTs compared to the Control ensemble and more cloudy pixels.

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PAMTRA 1.0: the Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere

Geoscientific Model Development ◽

10.5194/gmd-13-4229-2020 ◽

2020 ◽

Vol 13 (9) ◽

pp. 4229-4251 ◽

Cited By ~ 3

Author(s):

Mario Mech ◽

Maximilian Maahn ◽

Stefan Kneifel ◽

Davide Ori ◽

Emiliano Orlandi ◽

...

Keyword(s):

Radiative Transfer ◽

Forward Model ◽

Doppler Spectrum ◽

Brightness Temperatures ◽

Input And Output ◽

Cloudy Atmosphere ◽

Radar Measurements ◽

Self Similar ◽

Atmospheric State

Abstract. Forward models are a key tool to generate synthetic observations given knowledge of the atmospheric state. In this way, they are an integral part of inversion algorithms that aim to retrieve geophysical variables from observations or in data assimilation. Their application for the exploitation of the full information content of remote sensing observations becomes increasingly important when these are used to evaluate the performance of cloud-resolving models (CRMs). Herein, CRM profiles or fields provide the input to the forward model whose simulation results are subsequently compared to the observations. This paper introduces the freely available comprehensive microwave forward model PAMTRA (Passive and Active Microwave TRAnsfer), demonstrates its capabilities to simulate passive and active measurements across the microwave spectral region for upward- and downward-looking geometries, and illustrates how the forward simulations can be used to evaluate CRMs and to interpret measurements to improve our understanding of cloud processes. PAMTRA is unique as it treats passive and active radiative transfer (RT) in a consistent way with the passive forward model providing upwelling and downwelling polarized brightness temperatures and radiances for arbitrary observation angles. The active part is capable of simulating the full radar Doppler spectrum and its moments. PAMTRA is designed to be flexible with respect to instrument specifications and interfaces to many different formats of input and output, especially CRMs, spanning the range from bin-resolved microphysical output to one- and two-moment schemes, and to in situ measured hydrometeor properties. A specific highlight is the incorporation of the self-similar Rayleigh–Gans approximation (SSRGA) for both active and passive applications, which becomes especially important for the investigation of frozen hydrometeors.

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