Spectral Retrieval of Latent Heating Profiles from TRMM PR Data. Part IV: Comparisons of Lookup Tables from Two- and Three-Dimensional Cloud-Resolving Model Simulations

2009 ◽  
Vol 22 (20) ◽  
pp. 5577-5594 ◽  
Author(s):  
Shoichi Shige ◽  
Yukari N. Takayabu ◽  
Satoshi Kida ◽  
Wei-Kuo Tao ◽  
Xiping Zeng ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Latent Heating ◽  
3D Simulations ◽  
Toga Coare ◽  
Trmm Pr ◽  
Lookup Tables ◽  
Cloud Resolving Model ◽  
Heating Profiles ◽  
Maximum Heating ◽  
Melting Level

Abstract The spectral latent heating (SLH) algorithm was developed to estimate latent heating profiles for the Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR). The method uses TRMM PR information (precipitation-top height, precipitation rates at the surface and melting level, and rain type) to select heating profiles from lookup tables (LUTs). LUTs for the three rain types—convective, shallow stratiform, and anvil rain (deep stratiform with a melting level)—were derived from numerical simulations of tropical cloud systems from the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) using a cloud-resolving model (CRM). The two-dimensional (2D) CRM was used in previous studies. The availability of exponentially increasing computer capabilities has resulted in three-dimensional (3D) CRM simulations for multiday periods becoming increasingly prevalent. In this study, LUTs from the 2D and 3D simulations are compared. Using the LUTs from 3D simulations results in less agreement between the SLH-retrieved heating and sounding-based heating for the South China Sea Monsoon Experiment (SCSMEX). The level of SLH-estimated maximum heating is lower than that of the sounding-derived maximum heating. This is explained by the fact that using the 3D LUTs results in stronger convective heating and weaker stratiform heating above the melting level than is the case if using the 2D LUTs. More condensate is generated in and carried from the convective region in the 3D model than in the 2D model, and less condensate is produced by the stratiform region’s own upward motion.

Spectral Retrieval of Latent Heating Profiles from TRMM PR Data. Part II: Algorithm Improvement and Heating Estimates over Tropical Ocean Regions

2007 ◽  
Vol 46 (7) ◽  
pp. 1098-1124 ◽  
Author(s):  
Shoichi Shige ◽  
Yukari N. Takayabu ◽  
Wei-Kuo Tao ◽  
Chung-Lin Shie
Keyword(s):  
Convective Heating ◽  
Consistency Check ◽  
Tropical Ocean ◽  
Stratiform Region ◽  
Toga Coare ◽  
Trmm Pr ◽  
Lookup Tables ◽  
Upper Level ◽  
Heating Profiles ◽  
Melting Level

Abstract The spectral latent heating (SLH) algorithm was developed for the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) in Part I of this study. The method uses PR information [precipitation-top height (PTH), precipitation rates at the surface and melting level, and rain type] to select heating profiles from lookup tables. Heating-profile lookup tables for the three rain types—convective, shallow stratiform, and anvil rain (deep stratiform with a melting level)—were derived from numerical simulations of tropical cloud systems from the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) utilizing a cloud-resolving model (CRM). To assess its global application to TRMM PR data, the universality of the lookup tables from the TOGA COARE simulations is examined in this paper. Heating profiles are reconstructed from CRM-simulated parameters (i.e., PTH, precipitation rates at the surface and melting level, and rain type) and are compared with the true CRM-simulated heating profiles, which are computed directly by the model thermodynamic equation. CRM-simulated data from the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE), South China Sea Monsoon Experiment (SCSMEX), and Kwajalein Experiment (KWAJEX) are used as a consistency check. The consistency check reveals discrepancies between the SLH-reconstructed and Goddard Cumulus Ensemble (GCE)-simulated heating above the melting level in the convective region and at the melting level in the stratiform region that are attributable to the TOGA COARE table. Discrepancies in the convective region are due to differences in the vertical distribution of deep convective heating due to the relative importance of liquid and ice water processes, which varies from case to case. Discrepancies in the stratiform region are due to differences in the level separating upper-level heating and lower-level cooling. Based on these results, improvements were made to the SLH algorithm. Convective heating retrieval is now separated into upper-level heating due to ice processes and lower-level heating due to liquid water processes. In the stratiform region, the heating profile is shifted up or down by matching the melting level in the TOGA COARE lookup table with the observed one. Consistency checks indicate the revised SLH algorithm performs much better for both the convective and stratiform components than does the original one. The revised SLH algorithm was applied to PR data, and the results were compared with heating profiles derived diagnostically from SCSMEX sounding data. Key features of the vertical profiles agree well—in particular, the level of maximum heating. The revised SLH algorithm was also applied to PR data for February 1998 and February 1999. The results are compared with heating profiles derived by the convective–stratiform heating (CSH) algorithm. Because observed information on precipitation depth is used in addition to precipitation type and intensity, differences between shallow and deep convection are more distinct in the SLH algorithm in comparison with the CSH algorithm.

scholarly journals Spectral Retrieval of Latent Heating Profiles from TRMM PR Data. Part III: Estimating Apparent Moisture Sink Profiles over Tropical Oceans

2008 ◽  
Vol 47 (2) ◽  
pp. 620-640 ◽  
Author(s):  
Shoichi Shige ◽  
Yukari N. Takayabu ◽  
Wei-Kuo Tao
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Latent Heating ◽  
Tropical Ocean ◽  
Tropical Oceans ◽  
Cloud Resolving Model ◽  
Trmm Precipitation ◽  
Low Levels ◽  
Heating Profiles ◽  
The Western Pacific ◽  
Good Agreement

Abstract The spectral latent heating (SLH) algorithm was developed to estimate apparent heat source (Q1) profiles for the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) in Parts I and II of this study. In this paper, the SLH algorithm is used to estimate apparent moisture sink (Q2) profiles. The procedure of Q2 retrieval is the same as that of heating retrieval except for using the Q2 profile lookup tables derived from numerical simulations of tropical cloud systems from the Tropical Ocean and Global Atmosphere (TOGA) Coupled Ocean–Atmosphere Response Experiment (COARE) utilizing a cloud-resolving model (CRM). The Q2 profiles were reconstructed from CRM-simulated parameters with the COARE table and then compared with CRM-simulated “true” Q2 profiles, which were computed directly from the water vapor equation in the model. The consistency check indicates that discrepancies between the SLH-reconstructed and CRM-simulated profiles for Q2, especially at low levels, are larger than those for Q1 and are attributable to moistening for the nonprecipitating region that SLH cannot reconstruct. Nevertheless, the SLH-reconstructed total Q2 profiles are in good agreement with the CRM-simulated ones. The SLH algorithm was applied to PR data, and the results were compared with Q2 profiles derived from the budget study. Although discrepancies between the SLH-retrieved and sounding-based profiles for Q2 for the South China Sea Monsoon Experiment (SCSMEX) are larger than those for heating, key features of the vertical profiles agree well. The SLH algorithm can also estimate differences of Q2 between the western Pacific Ocean and the Atlantic Ocean, consistent with the results from the budget study.

scholarly journals Assessing the Vertical Latent Heating Structure of the East Pacific ITCZ Using the CloudSat CPR and TRMM PR

2018 ◽  
Vol 31 (7) ◽  
pp. 2563-2577 ◽  
Author(s):  
L. Huaman ◽  
C. Schumacher
Keyword(s):  
Meridional Circulation ◽  
Deep Convection ◽  
Tropical Rainfall Measuring Mission ◽  
Hadley Cell ◽  
Convective Precipitation ◽  
Latent Heating ◽  
Shallow Convection ◽  
East Pacific ◽  
Trmm Pr ◽  
Heating Profiles

In the east Pacific (EP) intertropical convergence zone (ITCZ), Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) latent heating retrievals suggest a top-heavy structure; however, light precipitation and its associated low-level heating are underestimated by the PR. This study uses stratiform and deep convective precipitation from the TRMM PR and shallow precipitation from the more sensitive CloudSat radar to assess the seasonal latent heating structure in the EP ITCZ (130°–90°W) for 1998–2014. This study also uses reanalyses (MERRA-2, ERA-Interim, and NCEP–NCAR) to analyze the meridional circulation linked to variations in ITCZ heating. The TRMM/ CloudSat heating profiles suggest a distinct seasonality. During DJF, latent heating peaks at 800 hPa because of the predominance of shallow convection and rises to 700 hPa during MAM as the contribution from deep convective rain increases. During JJA and SON, stratiform precipitation increases and the latent heating has a double peak at 700 and 400 hPa. Additionally, the EP ITCZ heating has a meridional slope throughout most of the year as a result of the prevalence of shallow (deep) convection in the southern (northern) part of the ITCZ. While the reanalyses agree that the most bottom-heavy heating occurs in DJF and the most top-heavy heating occurs in JJA, they underestimate heating aloft compared to the satellite retrievals throughout the year and show varying ability in representing the shallow meridional circulation and deeper Hadley cell overturning.

scholarly journals Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part II: Evaluation of Estimates Using Independent Data

2006 ◽  
Vol 45 (5) ◽  
pp. 721-739 ◽  
Author(s):  
Song Yang ◽  
William S. Olson ◽  
Jian-Jian Wang ◽  
Thomas L. Bell ◽  
Eric A. Smith ◽  
...  
Keyword(s):  
Rain Rate ◽  
Sampling Error ◽  
Contextual Information ◽  
Total Error ◽  
Bias Reduction ◽  
Passive Microwave ◽  
Latent Heating ◽  
Cloud Resolving Model ◽  
Surface Rain Rate ◽  
Heating Profiles

Abstract Rainfall rate estimates from spaceborne microwave radiometers are generally accepted as reliable by a majority of the atmospheric science community. One of the Tropical Rainfall Measuring Mission (TRMM) facility rain-rate algorithms is based upon passive microwave observations from the TRMM Microwave Imager (TMI). In Part I of this series, improvements of the TMI algorithm that are required to introduce latent heating as an additional algorithm product are described. Here, estimates of surface rain rate, convective proportion, and latent heating are evaluated using independent ground-based estimates and satellite products. Instantaneous, 0.5°-resolution estimates of surface rain rate over ocean from the improved TMI algorithm are well correlated with independent radar estimates (r ∼0.88 over the Tropics), but bias reduction is the most significant improvement over earlier algorithms. The bias reduction is attributed to the greater breadth of cloud-resolving model simulations that support the improved algorithm and the more consistent and specific convective/stratiform rain separation method utilized. The bias of monthly 2.5°-resolution estimates is similarly reduced, with comparable correlations to radar estimates. Although the amount of independent latent heating data is limited, TMI-estimated latent heating profiles compare favorably with instantaneous estimates based upon dual-Doppler radar observations, and time series of surface rain-rate and heating profiles are generally consistent with those derived from rawinsonde analyses. Still, some biases in profile shape are evident, and these may be resolved with (a) additional contextual information brought to the estimation problem and/or (b) physically consistent and representative databases supporting the algorithm. A model of the random error in instantaneous 0.5°-resolution rain-rate estimates appears to be consistent with the levels of error determined from TMI comparisons with collocated radar. Error model modifications for nonraining situations will be required, however. Sampling error represents only a portion of the total error in monthly 2.5°-resolution TMI estimates; the remaining error is attributed to random and systematic algorithm errors arising from the physical inconsistency and/or nonrepresentativeness of cloud-resolving-model-simulated profiles that support the algorithm.

scholarly journals Spectral Retrieval of Latent Heating Profiles from TRMM PR Data. Part I: Development of a Model-Based Algorithm

2004 ◽  
Vol 43 (8) ◽  
pp. 1095-1113 ◽  
Author(s):  
Shoichi Shige ◽  
Yukari N. Takayabu ◽  
Wei-Kuo Tao ◽  
Daniel E. Johnson
Keyword(s):  
Latent Heating ◽  
Model Based ◽  
Trmm Pr ◽  
Heating Profiles

3D simulations of warm and hot Jupiter atmospheres: the role of 3D mixing in shaping CH4-to-CO conversion pathways

2021 ◽  
Author(s):  
Maria Zamyatina ◽  
Eric Hebrard ◽  
Nathan Mayne ◽  
Benjamin Drummond
Keyword(s):  
Chemical Structure ◽  
Three Dimensional ◽  
Chemical Species ◽  
Radiation Chemistry ◽  
3D Simulations ◽  
Horizontal Advection ◽  
Co Conversion ◽  
Area Of Influence ◽  
Different Parts

<p>We present results from a set of cloud-free simulations of exoplanet atmospheres using a coupled three-dimensional (3D) hydrodynamics-radiation-chemistry model. We report in particular our investigation of the thermodynamic and chemical structure of the atmospheres of HAT-P-11b and WASP-17b and their comparison with the results for the atmospheres of HD 189733b and HD 209458b presented in Drummond et al. (2020). We found that the abundances of chemical species from simulations with interactive chemistry depart from their respective abundances computed at local chemical equilibrium, especially at higher latitudes. To understand this departure, we analysed the CH<sub>4</sub>-to-CO conversion pathways within the Venot et al. (2019) reduced chemical network used in our model using a chemical network analysis. We found that at steady state nine CH<sub>4</sub>-to-CO conversion pathways manifest in our 3D simulations with interactive chemistry, with different pathways dominating different parts of the atmosphere and their area of influence being determined by the vertical and horizontal advection and shifting between planets.</p>

scholarly journals tobac 1.2: towards a flexible framework for tracking and analysis of clouds in diverse datasets

2019 ◽  
Vol 12 (11) ◽  
pp. 4551-4570 ◽  
Author(s):  
Max Heikenfeld ◽  
Peter J. Marinescu ◽  
Matthew Christensen ◽  
Duncan Watson-Parris ◽  
Fabian Senf ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Longwave Radiation ◽  
Geostationary Satellite ◽  
Model Assessment ◽  
Model Simulations ◽  
Cloud Properties ◽  
Level Data ◽  
Different Types ◽  
Cloud Resolving Model ◽  
High Level

Abstract. We introduce tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing individual clouds in different types of datasets, such as cloud-resolving model simulations and geostationary satellite retrievals. The software has been designed to be used flexibly with any two- or three-dimensional time-varying input. The application of high-level data formats, such as Iris cubes or xarray arrays, for input and output allows for convenient use of metadata in the tracking analysis and visualisation. Comprehensive analysis routines are provided to derive properties like cloud lifetimes or statistics of cloud properties along with tools to visualise the results in a convenient way. The application of tobac is presented in two examples. We first track and analyse scattered deep convective cells based on maximum vertical velocity and the three-dimensional condensate mixing ratio field in cloud-resolving model simulations. We also investigate the performance of the tracking algorithm for different choices of time resolution of the model output. In the second application, we show how the framework can be used to effectively combine information from two different types of datasets by simultaneously tracking convective clouds in model simulations and in geostationary satellite images based on outgoing longwave radiation. The tobac framework provides a flexible new way to include the evolution of the characteristics of individual clouds in a range of important analyses like model intercomparison studies or model assessment based on observational data.

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