scholarly journals On the Sensitivity of Atmospheric Ensembles to Cloud Microphysics in Long-Term Cloud-Resolving Model Simulations

2008 ◽  
Vol 86A ◽  
pp. 45-65 ◽  
Author(s):  
Xiping ZENG ◽  
Wei-Kuo TAO ◽  
Stephen LANG ◽  
Arthur Y. HOU ◽  
Minghua ZHANG ◽  
...  
2005 ◽  
Vol 62 (4) ◽  
pp. 1241-1254 ◽  
Author(s):  
Kuan-Man Xu

Abstract This study examines the sensitivity of diagnosed radiative fluxes and heating rates to different treatments of cloud microphysics among cloud-resolving models (CRMs). The domain-averaged CRM outputs are used in this calculation. The impacts of the cloud overlap and uniform hydrometeor assumptions are examined using outputs having spatially varying cloud fields from a single CRM. It is found that the cloud overlap assumption impacts the diagnosis more significantly than the uniform hydrometeor assumption for all radiative fluxes. This is also the case for the longwave radiative cooling rate except for a layer above 7 km where it is more significantly impacted by the uniform hydrometeor assumption. The radiative cooling above upper-tropospheric anvils and the warming below these clouds are overestimated by about 0.5 K day−1 using the domain-averaged outputs. These results are used to further quantify intermodel differences in radiative properties due to different treatments of cloud microphysics among 10 CRMs. The magnitudes of the intermodel differences, as measured by the deviations from the consensus of 10 CRMs, are found to be smaller than those due to the cloud overlap assumption and comparable to those due to the uniform hydrometeor assumption for most shortwave radiative fluxes and the net radiative fluxes at the top of the atmosphere (TOA) and at the surface. For all longwave radiative fluxes, they are smaller than those due to cloud overlap and uniform hydrometeor assumptions. The consensus of all diagnosed radiative fluxes except for the surface downward shortwave flux agrees with observations to a degree that is close to the uncertainties of satellite- and ground-based measurements.


2014 ◽  
Vol 28 (1) ◽  
pp. 66-85 ◽  
Author(s):  
Chung-Chieh Wang ◽  
Bo-Xun Lin ◽  
Cheng-Ta Chen ◽  
Shih-How Lo

Abstract To quantify the effects of long-term climate change on typhoon rainfall near Taiwan, cloud-resolving simulations of Typhoon (TY) Sinlaku and TY Jangmi, both in September 2008, are performed and compared with sensitivity tests where these same typhoons are placed in the climate background of 1950–69, which is slightly cooler and drier compared to the modern climate of 1990–2009 computed using NCEP–NCAR reanalysis data. Using this strategy, largely consistent responses are found in the model although only two cases are studied. In control experiments, both modern-day typhoons yield more rainfall than their counterpart in the sensitivity test using past climate, by about 5%–6% at 200–500 km from the center for Sinlaku and roughly 4%–7% within 300 km of Jangmi, throughout much of the periods simulated. In both cases, the frequency of more-intense rainfall (20 to >50 mm h−1) also increases by about 5%–25% and the increase tends to be larger toward higher rain rates. Results from the water budget analysis, again quite consistent between the two cases, indicate that the increased rainfall from the typhoons in the modern climate is attributable to both a moister environment (by 2.5%–4%) as well as, on average, a more active secondary circulation of the storm. Thus, a changing climate may already have had a discernible impact on TC rainfall near Taiwan. While an overall increase in TC rainfall of roughly 5% may not seem large, it is certainly not insignificant considering that the long-term trend observed in the past 40–50 yr, whatever the causes might be, may continue for many decades in the foreseeable future.


Author(s):  
Raquel Barata ◽  
Raquel Prado ◽  
Bruno Sansó

Abstract. We present a data-driven approach to assess and compare the behavior of large-scale spatial averages of surface temperature in climate model simulations and in observational products. We rely on univariate and multivariate dynamic linear model (DLM) techniques to estimate both long-term and seasonal changes in temperature. The residuals from the DLM analyses capture the internal variability of the climate system and exhibit complex temporal autocorrelation structure. To characterize this internal variability, we explore the structure of these residuals using univariate and multivariate autoregressive (AR) models. As a proof of concept that can easily be extended to other climate models, we apply our approach to one particular climate model (MIROC5). Our results illustrate model versus data differences in both long-term and seasonal changes in temperature. Despite differences in the underlying factors contributing to variability, the different types of simulation yield very similar spectral estimates of internal temperature variability. In general, we find that there is no evidence that the MIROC5 model systematically underestimates the amplitude of observed surface temperature variability on multi-decadal timescales – a finding that has considerable relevance regarding efforts to identify anthropogenic “fingerprints” in observational surface temperature data. Our methodology and results present a novel approach to obtaining data-driven estimates of climate variability for purposes of model evaluation.


2019 ◽  
Vol 12 (11) ◽  
pp. 4551-4570 ◽  
Author(s):  
Max Heikenfeld ◽  
Peter J. Marinescu ◽  
Matthew Christensen ◽  
Duncan Watson-Parris ◽  
Fabian Senf ◽  
...  

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.


2011 ◽  
Vol 68 (7) ◽  
pp. 1424-1434 ◽  
Author(s):  
Xiping Zeng ◽  
Wei-Kuo Tao ◽  
Toshihisa Matsui ◽  
Shaocheng Xie ◽  
Stephen Lang ◽  
...  

Abstract The ice crystal enhancement (IE) factor, defined as the ratio of the ice crystal to ice nuclei (IN) number concentrations for any particular cloud condition, is needed to quantify the contribution of changes in IN to global warming. However, the ensemble characteristics of IE are still unclear. In this paper, a representation of the IE factor is incorporated into a three-ice-category microphysical scheme for use in long-term cloud-resolving model (CRM) simulations. Model results are compared with remote sensing observations, which suggest that, absent a physically based consideration of how IE comes about, the IE factor in tropical clouds is about 103 times larger than that in midlatitudinal ones. This significant difference in IE between the tropics and middle latitudes is consistent with the observation of stronger entrainment and detrainment in the tropics. In addition, the difference also suggests that cloud microphysical parameterizations depend on spatial resolution (or subgrid turbulence parameterizations within CRMs).


2014 ◽  
Vol 14 (15) ◽  
pp. 7909-7927 ◽  
Author(s):  
Y. Kanaya ◽  
H. Irie ◽  
H. Takashima ◽  
H. Iwabuchi ◽  
H. Akimoto ◽  
...  

Abstract. We conducted long-term network observations using standardized Multi-Axis Differential optical absorption spectroscopy (MAX-DOAS) instruments in Russia and ASia (MADRAS) from 2007 onwards and made the first synthetic data analysis. At seven locations (Cape Hedo, Fukue and Yokosuka in Japan, Hefei in China, Gwangju in Korea, and Tomsk and Zvenigorod in Russia) with different levels of pollution, we obtained 80 927 retrievals of tropospheric NO2 vertical column density (TropoNO2VCD) and aerosol optical depth (AOD). In the technique, the optimal estimation of the TropoNO2VCD and its profile was performed using aerosol information derived from O4 absorbances simultaneously observed at 460–490 nm. This large data set was used to analyze NO2 climatology systematically, including temporal variations from the seasonal to the diurnal scale. The results were compared with Ozone Monitoring Instrument (OMI) satellite observations and global model simulations. Two NO2 retrievals of OMI satellite data (NASA ver. 2.1 and Dutch OMI NO2 (DOMINO) ver. 2.0) generally showed close correlations with those derived from MAX-DOAS observations, but had low biases of up to ~50%. The bias was distinct when NO2 was abundantly present near the surface and when the AOD was high, suggesting a possibility of incomplete accounting of NO2 near the surface under relatively high aerosol conditions for the satellite observations. Except for constant biases, the satellite observations showed nearly perfect seasonal agreement with MAX-DOAS observations, suggesting that the analysis of seasonal features of the satellite data were robust. Weekend reduction in the TropoNO2VCD found at Yokosuka and Gwangju was absent at Hefei, implying that the major sources had different weekly variation patterns. While the TropoNO2VCD generally decreased during the midday hours, it increased exceptionally at urban/suburban locations (Yokosuka, Gwangju, and Hefei) during winter. A global chemical transport model, MIROC-ESM-CHEM (Model for Interdisciplinary Research on Climate–Earth System Model–Chemistry), was validated for the first time with respect to background NO2 column densities during summer at Cape Hedo and Fukue in the clean marine atmosphere.


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