scholarly journals Aerosol effects on clouds and precipitation during the 1997 smoke episode in Indonesia

2007 ◽  
Vol 7 (6) ◽  
pp. 17099-17116 ◽  
Author(s):  
H.-F. Graf ◽  
J. Yang ◽  
T. M. Wagner

Abstract. In 1997/98 a severe smoke episode due to extensive biomass burning, especially of peat, was observed over Indonesia. September 1997 was the month with the highest aerosol burden. This month was simulated using the limited area model REMOTE driven at its lateral boundaries by ERA40 reanalysis data. REMOTE was extended by a new convective cloud parameterization mimicking individual clouds competing for instability energy. This allows for the interaction of aerosols and convective clouds and precipitation. Results show that convective precipitation is diminished at all places with high aerosol loading, but at some areas with high background humidity precipitation from large-scale clouds may over-compensate the loss in convective rainfall. At individual time steps, very few cases were found when polluted convective clouds produced intensified rainfall via mixed phase microphysics. However, these cases are not unequivocal and opposite results were also simulated, indicating that other than aerosol-microphysics effects have important impact on the results. Overall, the introduction of the new cumulus parameterization and of aerosol-cloud interaction improved the simulation of precipitation patterns and total amount.

2009 ◽  
Vol 9 (2) ◽  
pp. 743-756 ◽  
Author(s):  
H.-F. Graf ◽  
J. Yang ◽  
T. M. Wagner

Abstract. In 1997/1998 a severe smoke episode due to extensive biomass burning, especially of peat, was observed over Indonesia. September 1997 was the month with the highest aerosol burden. This month was simulated using the limited area model REMOTE driven at its lateral boundaries by ERA40 reanalysis data. REMOTE was extended by a new convective cloud parameterization mimicking individual clouds competing for instability energy. This allows for the interaction of aerosols, convective clouds and precipitation. Results show that in the monthly mean convective precipitation is diminished at nearly all places with high aerosol loading, but at some areas with high background humidity precipitation from large-scale clouds may over-compensate the loss in convective rainfall. The simulations revealed that both large-scale and convective clouds' microphysics are influenced by aerosols. Since aerosols are washed and rained out by rainfall, high aerosol concentrations can only persist at low rainfall rates. Hence, aerosol concentrations are not independent of the rainfall amount and in the mean the maximum absolute effects on rainfall from large scale clouds are found at intermediate aerosol concentrations. The reason for this behavior is that at high aerosol concentrations rainfall rates are small and consequently also the anomalies are small. For large-scale as well as for convective rain negative and positive anomalies are found for all aerosol concentrations. Negative anomalies dominate and are highly statistically significant especially for convective rainfall since part of the precipitation loss from large-scale clouds is compensated by moisture detrained from the convective clouds. The mean precipitation from large-scale clouds is less reduced (however still statistically significant) than rain from convective clouds. This effect is due to detrainment of cloud water from the less strongly raining convective clouds and because of the generally lower absolute amounts of rainfall from large-scale clouds. With increasing aerosol load both, convective and large scale clouds produce less rain. At very few individual time steps cases were found when polluted convective clouds produced intensified rainfall via mixed phase microphysics. However, these cases are not unequivocal and opposite results were also simulated, indicating that other than aerosol-microphysics effects have important impact on the results. Overall, the introduction of the new cumulus parameterization and aerosol-cloud interaction reduced some of the original REMOTE biases of precipitation patterns and total amount.


2006 ◽  
Vol 6 (5) ◽  
pp. 10217-10246
Author(s):  
H.-F. Graf ◽  
J. Yang

Abstract. A convective cloud field model (CCFM) is substituted for a standard mass flux parameterisation of convective clouds in a limited area atmospheric model (REMO) and is tested for a whole annual cycle (July 1997 to June 1998) over the Maritime Continent. REMO with CCFM is run in 0.5-degree resolution and the model at the boundaries is forced 6-hourly by ECMWF reanalysis data. Simulated precipitation from runs with the standard convection parameterisation and with CCFM is compared against two sets of observations. The use of CCFM clearly improves the simulated precipitation patterns and total rainfall over the whole model domain. The distribution between large-scale and convective precipitation becomes more realistic. CCFM shows to be a useful concept to describe convective cloud spectra in atmospheric models, although there are still similar problems with occasionally extreme precipitation as in the original set-up of REMO.


2007 ◽  
Vol 7 (2) ◽  
pp. 409-421 ◽  
Author(s):  
H.-F. Graf ◽  
J. Yang

Abstract. A convective cloud field model (CCFM) is substituted for a standard mass flux parameterisation of convective clouds in a limited area atmospheric model (REMO) and is tested for a whole annual cycle (July 1997 to June 1998) over the West Pacific Maritime Continent. REMO with CCFM is run in 0.5-degree resolution and the model at the lateral boundaries is forced 6-hourly by ECMWF reanalysis data. Simulated precipitation from runs with the standard convection parameterisation and with CCFM is compared against two sets of observations. The use of CCFM clearly improves the simulated precipitation patterns and total rainfall over the whole model domain. The distribution between large-scale and convective precipitation becomes more realistic. CCFM shows to be a useful concept to describe convective cloud spectra in atmospheric models, although there are still similar problems with occasionally extreme precipitation as in the original set-up of REMO.


2019 ◽  
Author(s):  
Zak Kipling ◽  
Laurent Labbouz ◽  
Philip Stier

Abstract. The interactions between aerosols and convective clouds represent some of the greatest uncertainties in the climate impact of aerosols in the atmosphere. A wide variety of mechanisms have been proposed by which aerosols may invigorate, suppress, or change the properties of individual convective clouds, some of which can be reproduced in high-resolution limited-area models. However, there may also be mesoscale, regional or global adjustments which modulate or dampen such impacts which cannot be captured in the limited domain of such models. The Convective Cloud Field Model (CCFM) provides a mechanism to explicitly simulate a population of convective clouds within each grid column at resolutions used for global climate modelling, so that a representation of the microphysical aerosol response within each parameterised cloud type is possible. Using CCFM within the global aerosol–climate model ECHAM–HAM, we demonstrate how the parameterised cloud field responds to the present-day anthropogenic aerosol perturbation in different regions. In particular, we show that in regions with strongly-forced deep convection and/or significant aerosol effects via large-scale processes, the changes in the convective cloud field due to microphysical effects is rather small; however in a more weakly-forced regime such as the Caribbean, where large-scale aerosol effects are small, a signature of convective invigoration does become apparent.


2020 ◽  
Vol 20 (7) ◽  
pp. 4445-4460
Author(s):  
Zak Kipling ◽  
Laurent Labbouz ◽  
Philip Stier

Abstract. The interactions between aerosols and convective clouds represent some of the greatest uncertainties in the climate impact of aerosols in the atmosphere. A wide variety of mechanisms have been proposed by which aerosols may invigorate, suppress or change the properties of individual convective clouds, some of which can be reproduced in high-resolution limited-area models. However, there may also be mesoscale, regional or global adjustments which modulate or dampen such impacts which cannot be captured in the limited domain of such models. The Convective Cloud Field Model (CCFM) provides a mechanism to simulate a population of convective clouds, complete with microphysics and interactions between clouds, within each grid column at resolutions used for global climate modelling, so that a representation of the microphysical aerosol response within each parameterised cloud type is possible. Using CCFM within the global aerosol–climate model ECHAM–HAM, we demonstrate how the parameterised cloud field responds to the present-day anthropogenic aerosol perturbation in different regions. In particular, we show that in regions with strongly forced deep convection and/or significant aerosol effects via large-scale processes, the changes in the convective cloud field due to microphysical effects are rather small; however in a more weakly forced regime such as the Caribbean, where large-scale aerosol effects are small, a signature of convective invigoration does become apparent.


2017 ◽  
Vol 7 (2) ◽  
pp. 58 ◽  
Author(s):  
Shailendra Kumar

Tropical Rainfall Measuring Mission Precipitation Radar (TRMM-PR) based vertical structure in intense convective precipitation is presented here for Indian and Austral summer monsoon seasons. TRMM 2A23 data is used to identify the convective echoes in PR data. Two types of cloud cells are constructed here, namely intense convective cloud (ICC) and most intense convective cloud (MICC). ICC consists of PR radar beams having Ze>=40 dBZ above 1.5 km in convective precipitation area, whereas MICC, consists of maximum reflectivity at each altitude in convective precipitation area, with at least one radar pixel must be higher than 40 dBZ or more above 1.5 km within the selected areas. We have selected 20 locations across the tropics to see the regional differences in the vertical structure of convective clouds. One of the important findings of the present study is identical behavior in the average vertical profiles in intense convective precipitation in lower troposphere across the different areas. MICCs show the higher regional differences compared to ICCs between 5-12 km altitude. Land dominated areas show higher regional differences and Southeast south America (SESA) has the strongest vertical profile (higher Ze at higher altitude) followed by Indo-Gangetic plain (IGP), Africa, north Latin America whereas weakest vertical profile occurs over Australia. Overall SESA (41%) and IGP (36%) consist higher fraction of deep convective clouds (>10 km), whereas, among the tropical oceanic areas, Western (Eastern) equatorial Indian ocean consists higher fraction of low (high) level of convective clouds. Nearly identical average vertical profiles over the tropical oceanic areas, indicate the similarity in the development of intense convective clouds and useful while considering them in model studies.


2018 ◽  
Vol 75 (5) ◽  
pp. 1509-1524 ◽  
Author(s):  
Laurent Labbouz ◽  
Zak Kipling ◽  
Philip Stier ◽  
Alain Protat

Current climate models cannot resolve individual convective clouds, and hence parameterizations are needed. The primary goal of convective parameterization is to represent the bulk impact of convection on the gridbox-scale variables. Spectral convective parameterizations also aim to represent the key features of the subgrid-scale convective cloud field such as cloud-top-height distribution and in-cloud vertical velocities in addition to precipitation rates. Ground-based radar retrievals of these quantities have been made available at Darwin, Australia, permitting direct comparisons of internal parameterization variables and providing new observational references for further model development. A spectral convective parameterization [the convective cloud field model (CCFM)] is discussed, and its internal equation of motion is improved. Results from the ECHAM–HAM model in single-column mode using the CCFM and the bulk mass flux Tiedtke–Nordeng scheme are compared with the radar retrievals at Darwin. The CCFM is found to outperform the Tiedtke–Nordeng scheme for cloud-top-height and precipitation-rate distributions. Radar observations are further used to propose a modified CCFM configuration with an aerodynamic drag and reduced entrainment parameter, further improving both the convective cloud-top-height distribution (important for large-scale impact of convection) and the in-cloud vertical velocities (important for aerosol activation). This study provides a new development in the CCFM, improving the representation of convective cloud spectrum characteristics observed in Darwin. This is a step toward an improved representation of convection and ultimately of aerosol effects on convection. It also shows how long-term radar observations of convective cloud properties can help constrain parameters of convective parameterization schemes.


2008 ◽  
Vol 65 (6) ◽  
pp. 1773-1794 ◽  
Author(s):  
Zachary A. Eitzen ◽  
Kuan-Man Xu

Abstract A two-dimensional cloud-resolving model (CRM) is used to perform five sets of simulations of 68 deep convective cloud objects identified with Clouds and the Earth’s Radiant Energy System (CERES) data to examine their sensitivity to changes in thermodynamic and dynamic forcings. The control set of simulations uses observed sea surface temperatures (SSTs) and is forced by advective cooling and moistening tendencies derived from a large-scale model analysis matched to the time and location of each cloud object. Cloud properties, such as albedo, effective cloud height, cloud ice and snow path, and cloud radiative forcing (CRF), are analyzed in terms of their frequency distributions rather than their mean values. Two sets of simulations, F+50% and F−50%, use advective tendencies that are 50% greater and 50% smaller than the control tendencies, respectively. The increased cooling and moistening tendencies cause more widespread convection in the F+50% set of simulations, resulting in clouds that are optically thicker and higher than those produced by the control and F−50% sets of simulations. The magnitudes of both longwave and shortwave CRF are skewed toward higher values with the increase in advective forcing. These significant changes in overall cloud properties are associated with a substantial increase in deep convective cloud fraction (from 0.13 for the F−50% simulations to 0.34 for the F+50% simulations) and changes in the properties of non–deep convective clouds, rather than with changes in the properties of deep convective clouds. Two other sets of simulations, SST+2K and SST−2K, use SSTs that are 2 K higher and 2 K lower than those observed, respectively. The updrafts in the SST+2K simulations tend to be slightly stronger than those of the control and SST−2K simulations, which may cause the SST+2K cloud tops to be higher. The changes in cloud properties, though smaller than those due to changes in the dynamic forcings, occur in both deep convective and non–deep convective cloud categories. The overall changes in some cloud properties are moderately significant when the SST is changed by 4 K. The changes in the domain-averaged shortwave and longwave CRFs are larger in the dynamic forcing sensitivity sets than in the SST sensitivity sets. The cloud feedback effects estimated from the SST−2K and SST+2K sets are comparable to prior studies.


2018 ◽  
Vol 31 (13) ◽  
pp. 5189-5204 ◽  
Author(s):  
Mingcheng Wang ◽  
Guang J. Zhang

Using 4 years of CloudSat data, the simulation of tropical convective cloud-top heights (CCTH) above 6 km simulated by the convection scheme in the Community Atmosphere Model, version 5 (CAM5), is evaluated. Compared to CloudSat observations, CAM5 underestimates CCTH by more than 2 km on average. Further analysis of model results suggests that the dilute CAPE calculation, which has been incorporated into the convective parameterization since CAM4, is a main factor restricting CCTH to much lower levels. After removing this restriction, more convective clouds develop into higher altitudes, although convective clouds with tops above 12 km are still underestimated significantly. The environmental conditions under which convection develops in CAM5 are compared with CloudSat observations for convection with similar CCTHs. It is shown that the model atmosphere is much more unstable compared to CloudSat observations, and there is too much entrainment in CAM5. Since CCTHs are closely associated with cloud radiative forcing, the impacts of CCTH on model simulation are further investigated. Results show that the change of CCTH has important impacts on cloud radiative forcing and precipitation. With increased CCTHs, there is more cloud radiative forcing in tropical Africa and the eastern Pacific, but less cloud radiative forcing in the western Pacific. The contribution to total convective precipitation from convection with cloud tops above 9 km is also increased substantially.


2017 ◽  
Vol 145 (12) ◽  
pp. 5059-5082 ◽  
Author(s):  
Junya Uchida ◽  
Masato Mori ◽  
Masayuki Hara ◽  
Masaki Satoh ◽  
Daisuke Goto ◽  
...  

A nonhydrostatic, regional climate limited-area model (LAM) was used to analyze lateral boundary condition (LBC) errors and their influence on the uncertainties of regional models. Simulations using the fully compressible nonhydrostatic LAM (D-NICAM) were compared against the corresponding global quasi-uniform-grid Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and a stretched-grid counterpart (S-NICAM). By this approach of sharing the same dynamical core and physical schemes, possible causes of model bias and LBC errors are isolated. The simulations were performed for a 395-day period from March 2011 through March 2012 with horizontal grid intervals of 14, 28, and 56 km in the region of interest. The resulting temporal mean statistics of the temperatures at 500 hPa were generally well correlated between the global and regional simulations, indicating that LBC errors had a minor impact on the large-scale flows. However, the time-varying statistics of the surface precipitation showed that the LBC errors lead to the unpredictability of convective precipitation, which affected the mean statistics of the precipitation distributions but induced only minor influences on the large-scale systems. Specifically, extratropical cyclones and orographic precipitation are not severely affected. It was concluded that the errors of the precipitation distribution are not due to the difference of the model configurations but rather to the uncertainty of the system itself. This study suggests that applications of ensemble runs, internal nudging, or simulations with longer time scales are needed to obtain more statistically significant results of the precipitation distribution in regional climate models.


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