Enlarging rainfall area of tropical cyclones by atmospheric aerosols

The size of a tropical cyclone (TC), measured by the area of either rainfall or wind, is an important indicator for the potential damage by TC. Modeling studies suggested that aerosols tend to enhance rainfall in the outer rainbands, which enlarges the eyewall radius and expands the extent of rainfall area. However, no observational evidence has yet been reported. Using TC rainfall area and aerosol optical depth (AOD) data, we find that aerosols have a distinguishable footprint in the TC size. Other dynamical factors for TC size, such as relative SST and Coriolis parameter, are also quantified and discussed. We show that, on average, TC rainfall size increases 9–20 km for each 0.1 increase of AOD in the western North Pacific. This finding implies that anthropogenic aerosol pollution can increase not only TC rainfall rate, but also TC rainfall area, resulting in potentially more destructive flooding affecting larger areas

Evaluation of Intercomparisons of Four Different Types of Model Simulating TWP-ICE

Four model intercomparisons were run and evaluated using the TWP-ICE field campaign, each involving different types of atmospheric model. Here we highlight what can be learnt from having single-column model (SCM), cloud-resolving model (CRM), global atmosphere model (GAM) and limited-area model (LAM) intercomparisons all based around the same field campaign. We also make recommendations for anyone planning further large multi-model intercomparisons to ensure they are of maximum value to the model development community. CRMs tended to match observations better than other model types, although there were exceptions such as outgoing long-wave radiation. All SCMs grew large temperature and moisture biases and performed worse than other model types for many diagnostics. The GAMs produced a delayed and significantly reduced peak in domain-average rain rate when compared to the observations. While it was shown that this was in part due to the analysis used to drive these models, the LAMs were also driven by this analysis and did not have the problem to the same extent. Based on differences between the models with parametrized convection (SCMs and GAMs) and those without (CRMs and LAMs), we speculate that that having explicit convection helps to constrain liquid water whereas the ice contents are controlled more by the representation of the microphysics

Enlarging rainfall area of tropical cyclones by atmospheric aerosols

The size of a tropical cyclone (TC), measured by the area of either rainfall or wind, is an important indicator for the potential damage by TC. Modeling studies suggested that aerosols tend to enhance rainfall in the outer rainbands, which enlarges the eyewall radius and expands the extent of rainfall area. However, no observational evidence has yet been reported. Using TC rainfall area and aerosol optical depth (AOD) data, we find that aerosols have a distinguishable footprint in the TC size. Other dynamical factors for TC size, such as relative SST and Coriolis parameter, are also quantified and discussed. We show that, on average, TC rainfall size increases 9–20 km for each 0.1 increase of AOD in the western North Pacific. This finding implies that anthropogenic aerosol pollution can increase not only TC rainfall rate, but also TC rainfall area, resulting in potentially more destructive flooding affecting larger areas

Disentangling land model uncertainty via Matrix-based Ensemble Model Inter-comparison Platform (MEMIP)

Background Large uncertainty in modeling land carbon (C) uptake heavily impedes the accurate prediction of the global C budget. Identifying the uncertainty sources among models is crucial for model improvement yet has been difficult due to multiple feedbacks within Earth System Models (ESMs). Here we present a Matrix-based Ensemble Model Inter-comparison Platform (MEMIP) under a unified model traceability framework to evaluate multiple soil organic carbon (SOC) models. Using the MEMIP, we analyzed how the vertically resolved soil biogeochemistry structure influences SOC prediction in two soil organic matter (SOM) models. By comparing the model outputs from the C-only and CN modes, the SOC differences contributed by individual processes and N feedback between vegetation and soil were explicitly disentangled. Results Results showed that the multi-layer models with a vertically resolved structure predicted significantly higher SOC than the single layer models over the historical simulation (1900–2000). The SOC difference between the multi-layer models was remarkably higher than between the single-layer models. Traceability analysis indicated that over 80% of the SOC increase in the multi-layer models was contributed by the incorporation of depth-related processes, while SOC differences were similarly contributed by the processes and N feedback between models with the same soil depth representation. Conclusions The output suggested that feedback is a non-negligible contributor to the inter-model difference of SOC prediction, especially between models with similar process representation. Further analysis with TRENDY v7 and more extensive MEMIP outputs illustrated the potential important role of multi-layer structure to enlarge the current ensemble spread and the necessity of more detail model decomposition to fully disentangle inter-model differences. We stressed the importance of analyzing ensemble outputs from the fundamental model structures, and holding a holistic view in understanding the ensemble uncertainty

Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21-month (April 2009–December 2010) comprehensive dataset documenting clouds, aerosols, and precipitation using the Atmospheric Radiation Measurement Program (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols, and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the northeast Atlantic Ocean and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulus and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1 to 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back-trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging. The data from Graciosa are being compared with short-range forecasts made with a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.Keywords: Atmosphere-ocean interaction, Decadal variability, Spring season, La Nina, Meridional overturning circulation, Hadley circulationKeywords: Atmosphere-ocean interaction, Decadal variability, Spring season, La Nina, Meridional overturning circulation, Hadley circulatio

Description and Evaluation of a New Deep Convective Cloud Model Considering In‐Cloud Inhomogeneity

Abstract Convections still need to be parameterized in general circulation models (GCMs) in the coming decades. Performances of GCMs are significantly influenced by the convection schemes used. In contrast to most conventional cloud models that ignore in‐cloud inhomogeneities, a new convective cloud model explicitly considering in‐cloud inhomogeneities is developed. The new model adopts a single bulk plume approach, but divides the plume into a series of interacting sub‐plumes in order to mimic the transition from the plume core to its edges. We implemented the new cloud model in NCAR Community Atmosphere Model version 5.0 (CAM5) and evaluated its performance. Single‐column tests show a stronger mass flux profile and low‐level detrainment with the new model. In global simulations, the long‐lasting wet bias in the tropical free troposphere of CAM5 is alleviated. Spatial pattern and intensity distribution of precipitation is improved, but the global hydrological cycle is over‐enhanced. The diurnal cycle of tropical precipitation is also better captured though the precipitation peak still occurs earlier than the observations and the amplitude of the cycle tends to weaken. MJO simulation is slightly improved with the new scheme. In addition, the new cloud model generated more tropical cyclones, in better agreement with observations

Tropical cyclone cold wake size dataset

1. Mixing of the upper ocean by the wind field associated with tropical cyclones (TCs) creates observable cold wakes in sea surface temperature and may potentially influence ocean heat uptake. We derive a novel oceanic metric of tropical cyclone size based on its induced cold wake using sea surface temperature data for a period from 2002 to 2011. 2. The cold wake size dataset is based on the daily NOAA 1/4° Optimum Interpolation Sea Surface Temperature, AVHRR + AMSR subset. Two objective cold wake size metrics are derived based on image processing methods: rROI -- based on the Region of Interest method, and rPOL -- based on the azimuthal mean of cold wake in polar coordinates. More information about the pretreatment and determination of rROI/rPOL please refer to Zhang et al. (2019). The cold wake size file is TCCW-R_individual_cyclones.zip

CESM coupled simulation dataset with Park-RH and Gauss-PDF cloud scheme

1. Double ITCZ remains a challenging problem in climate models. We developed and implemented a new statistical cloud macrophysics scheme (called as Gauss-PDF) in NCAR CESM1.2.1. It shows the ability to improve the marine low cloud simulation and double ITCZ bias in coupled simulation when compared to the default cloud scheme (called as Park-RH). 2. Using Park-RH and Gauss-PDF, two coupled simulations forced by present-day climatological forcing (12 years) were conducted. Monthly mean atmospheric (atm) and oceanic (ocn) model simulations are archived here. The resolution is around 2 latitude x 2 longitude. 3. Because of the large size of each file, we separated all data into 100 M small files. "post-process.sh" is used to transfer these small files into the raw data. BC5_f19g16_cosp denotes the simulation with Park-RH scheme. BC5_f19g16_mac2_cosp denotes the simulation with Gauss-PDF scheme

Madden-Julian Oscillations Seen in the Upper-Troposphere Vorticity Field: Interactions with Rossby Wave Trains

International audienceThe vorticity variability associated with the Madden-Julian oscillation (MJO) is examined. The analysis is focused on the 150-hPa pressure level, because a clear dipolar-vortex signal, reminiscent of the theoretically proposed strongly nonlinear solitary Rossby wave solution (albeit with the opposite sign), is seen in raw data at that level. A local empirical orthogonal function (EOF) analysis over the equatorial region of the Eastern Hemisphere (08-1808E) identifies the two principal components representing an eastward propagation of a dipolar vortex trapped to the equator. Association of this propagation structure with the moist convective variability of the MJO is demonstrated by regressing the outgoing longwave radiation (OLR) against this EOF pair. The obtained evolution of the OLR field is similar to the one obtained by a direct application of the EOF to the OLR. A link of the local vorticity variability associated with the MJO to the global dynamics is further investigated by regressing the global vorticity field against the time series of the identified local EOF pair. The Rossby wave trains tend to propagate toward the Indian Ocean from higher latitudes, just prior to an initiation of the MJO, and in turn, they propagate back toward the higher latitudes from the MJO active region over the Indian Ocean. A three-dimensional regression reveals an equivalent barotropic structure of the MJO vortex pair with the signs opposite to those at 150 hPa underneath. A vertical normal mode analysis finds that this vertical structure is dominated by the equivalent height of about 10 km

Fluid Dynamics Is atmospheric convection organised?: information entropy analysis

International audienceIn order to quantify the degree of organisation of atmospheric con-vection, an analysis based on the information entropy, which is widely considered a measure of organisation in information science, is performed. Here, the information entropy is defined in terms of the spectrum of the empirical orthogonal functions (EOFs). Satellite-based brightness temperature data from CLAUS (Cloud Archive User Service) is used over the domain covering the Indian Ocean and the Western Pacific with a spatial resolution of 2/3 • from January 1985 to June 2009. The information entropy remains close to a mean value of 0.899 with a very small standard deviation of 2.7 × 10 −3 , suggesting that the atmospheric convection is always disorganised under a measure of the information entropy, which is against our common understanding. To better interpret this result, some basic theoretical analyses are performed, and the values of the information entropy for different systems (English literature texts, turbulent flows) from previous studies are reviewed. The same analysis is further performed on the Ising model, which is characterised by a clustering tendency of spin distribution, akin to convective organisation morphologically, at the critical temperature. The study suggests a need for a careful use of the term "organised". Atmospheric convection represents a tendency for clustering up to the planetary scale in analogous manner as the critical-point behaviour of the Ising model. However, neither is considered an "ordered" state under a measure of the information entropy. ARTICLE HISTOR