Moist Processes Research Articles

Sensitivity of rainfall and submonthly oscillations to moist physical processes schemes on Hainan island in autumn

In the autumns of 2010 and 2011, consecutive periods of heavy precipitation occurred in Hainan Island. Two groups of monthly-scale simulation experiments were conducted using the Weather Research and Forecasting model. Sensitivity of rainfall and submonthly oscillations to cumulus parameterization and cloud microphysical schemes were evaluated. Due to that the experiment combining the Tiedtke cumulus parameterization scheme and the WDM6 cloud microphysical scheme could reproduce submonthly oscillation characteristics, which showed the higher skill scores of the precipitation simulation than other experiments. Because the Tiedtke scheme is an overall mass flux convection scheme that describes various types of convection, the Grell-Devenyi scheme does not consider the shallow convection, which affects its simulation performance on submonthly oscillations and rainfall. However, in the same cumulus parameterization scheme, different microphysics schemes also have an impact on simulation performance. Experiments that failed to simulate the characteristics of submonthly oscillations exhibited a lower skill scores of precipitation simulation.Interactions of moist physical processes and submonthly oscillations led to the occurrence and development of two consecutive heavy autumn precipitation events on Hainan Island. Submonthly oscillations resulted in a significant effect on the two strong autumn precipitation events, but dominant frequency modes of submonthly oscillations, oscillation characteristics, and propagation paths differed. The autumn 2010 rainfall was dominated by the 8–15-day quasi-biweekly oscillations. The autumn 2011 rainfall was dominated by the 3–10-day synoptic-scale oscillations.

Using Megha‐Tropiques satellite data to constrain humidity in regional convective simulations: A northern Australian test case

AbstractConvective initiation and growth are sensitive to atmospheric conditions, especially humidity, in ways that need to be understood and quantified. It is not clear, however, how well current observations and modelling systems can serve to test this understanding. We simulate multiple cases of convergent cloud lines observed during January 2016 over northeastern Australia using the Weather Research and Forecasting (WRF) model (version 3.7.1), initialized by and nudged to reanalysis data. Overall, WRF appears to skilfully simulate the convergence lines. However, the associated convective clouds as seen by satellite were not properly captured by the model. The model humidity was tested against the current version (V3‐00) of the Megha‐Tropiques satellite, which although up to 30% too moist in the lowest retrieved layer over the dry continental interior compared to radiosondes, is usually accurate to within ±10% near the cloud lines. Unperturbed WRF simulations were found to be 10–20% too dry in this region. Compensating for this humidity bias via the model initialization produced more realistic simulations of clouds and convection, and this had a comparable or larger impact than changing model physics. This result highlights the importance of observations of water vapour that are accurate and have good spatial coverage, especially in the lower troposphere, for properly constraining simulations of convective environments and for model evaluation of moist processes.

Meridional and vertical variations of the water vapour isotopic composition in the marine boundary layer over the Atlantic and Southern Ocean

Abstract. Stable water isotopologues (SWIs) are useful tracers of moist diabatic processes in the atmospheric water cycle. They provide a framework to analyse moist processes on a range of timescales from large-scale moisture transport to cloud formation, precipitation and small-scale turbulent mixing. Laser spectrometric measurements on research vessels produce high-resolution time series of the variability of the water vapour isotopic composition in the marine boundary layer. In this study, we present a 5-month continuous time series of such ship-based measurements of δ2H and δ18O from the Antarctic Circumnavigation Expedition (ACE) in the Atlantic and the Southern Ocean in the time period from November 2016 to April 2017. We analyse the drivers of meridional SWI variations in the marine boundary layer across diverse climate zones in the Atlantic and Southern Ocean using Lagrangian moisture source diagnostics and relate vertical SWI differences to near-surface wind speed and ocean surface state. The median values of δ18O, δ2H and deuterium excess during ACE decrease continuously from low to high latitudes. These meridional SWI distributions reflect climatic conditions at the measurement and moisture source locations, such as air temperature, specific humidity and relative humidity with respect to sea surface temperature. The SWI variability at a given latitude is highest in the extratropics and polar regions with decreasing values equatorwards. This meridional distribution of SWI variability is explained by the variability in moisture source locations and its associated environmental conditions as well as transport processes. The westward-located moisture sources of water vapour in the extratropics are highly variable in extent and latitude due to the frequent passage of cyclones and thus widen the range of encountered SWI values in the marine boundary layer. Moisture loss during transport further contributes to the high SWI variability in the extratropics. In the subtropics and tropics, persistent anticyclones lead to well-confined narrow easterly moisture source regions, which is reflected in the weak SWI variability in these regions. Thus, the expected range of SWI signals at a given latitude strongly depends on the large-scale circulation. Furthermore, the ACE SWI time series recorded at 8.0 and 13.5 m above the ocean surface provide estimates of vertical SWI gradients in the lowermost marine boundary layer. On average, the vertical gradients with height found during ACE are -0.1‰m-1 for δ18O, -0.5‰m-1 for δ2H and 0.3 ‰ m−1 for deuterium excess. Careful calibration and post-processing of the SWI data and a detailed uncertainty analysis provide a solid basis for the presented gradients. Using sea spray concentrations and sea state conditions, we show that the vertical SWI gradients are particularly large during high wind speed conditions with increased contribution of sea spray evaporation or during low wind speed conditions due to weak vertical turbulent mixing. Although further SWI measurements at a higher vertical resolution are required to validate these findings, the simultaneous SWI measurements at several heights during ACE show the potential of SWIs as tracers for vertical mixing and sea spray evaporation in the lowermost marine boundary layer.

Validation of moist and dry heat processes used for sterilization and depyrogenation during ampoules manufacturing

Pyrogens are fever-producing substances, which are metabolic products of microorganisms and most potent pyrogens are the endotoxins. Depyrogenation can be defined as the elimination of all pyrogenic substances which is an important part of the manufacture of sterile pyrogen free pharmaceutical products. This study compared between sterilization and depyrogenation using moist heat by autoclave, as well as dry heat. After incubation period (24 hours) at 55oC-60oC the color of Geobacillus stearothermophillus spores’ control vial which didn’t sterilized in autoclave changed from blue to yellow color representing the (+ve) result, while the other sterilized vials have no color change (-ve). In addition, all examined endotoxin containing ampoules showed gel formation (+ve) when examined by Limulus Amebocyte Lysate) LAL). All ampoule groups that have autoclaved for periods of 1 hour to 4 hours showed gel formation (+ve) after LAL test, while only the last group which have autoclaving periods of 5 hours (5 cycles) showed no gel formation (-ve). Sterility of vials that contained spores of Geobacillus stearothermophillus after dry heating at 250oC for 30 min showed no color change (-ve). In addition, LAL test for endotoxin containing ampoules after dry heating at 250oC for 30 min showed no gel formation representing -ve pyrogen. So, moist heat is effective in sterilization and not for depydrogenation, whereas, dry heat is effective in sterilization as well as for depyrogenation.

Convective distribution of dust over the Arabian Peninsula: the impact of model resolution

Abstract. Along the coasts of the Arabian Peninsula, convective dust storms are a considerable source of mineral dust to the atmosphere. Reliable predictions of convective dust events are necessary to determine their effects on air quality, visibility, and the radiation budget. In this study, the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) is used to simulate a 2016 summertime dust event over the Arabian Peninsula and examine the variability in dust fields and associated vertical transport due to the choice of convective parameterization and convection-permitting versus parameterized convection. Simulations are run at 45 and 15 km grid spacing with multiple cumulus parameterizations, and are compared to a 3 km simulation that permits explicit dry and moist convective processes. Five separate cumulus parameterizations at 15 km grid spacing were tested to quantify the spread across different parameterizations. Finally, the impact these variations have on radiation, specifically aerosol heating rates is also investigated. On average, in these simulations the convection-permitting case produces higher quantities of dust than the parameterized cases in terms of dust uplift potential, vertical dust concentrations, and vertical dust fluxes. Major drivers of this discrepancy between the simulations stem from the convection-permitting case exhibiting higher surface wind speeds during convective activity; lower dust emission wind threshold velocities due to drier soil; and more frequent, stronger vertical velocities which transport dust aloft and increase the atmospheric lifetime of these particles. For aerosol heating rates in the lowest levels, the shortwave effect prevails in the convection-permitting case with a net cooling effect, whereas a longwave net warming effect is present in the parameterized cases. The spread in dust concentrations across cumulus parameterizations at the same grid resolution (15 km) is an order of magnitude lower than the impact of moving from parameterized towards explicit convection. We conclude that tuning dust emissions in coarse-resolution simulations can only improve the results to first-order and cannot fully rectify the discrepancies originating from disparities in the representation of convective dust transport.

Dynamics of rainfall extremes over India: A new perspective

AbstractA comprehensive analysis of the role of Indo‐Pakistan arid region (IPAR) in modulating the boreal summer heavy extreme rainfall events over monsoon core zone (MCZ over Indian subcontinent) at subseasonal to daily time scales is presented. The objective is to bring new perspectives on the dynamics of such rainfall extremes. Time‐lagged composite analysis shows the clustering of Monsoon Intra‐Seasonal Oscillation with monsoon rainfall daily extremes. However, our results additionally bring out the distinct role of surface thermal forcing and moist processes over IPAR as another potential and significant precursor, 16–10 days in advance, causing monsoon rainfall daily extremes over MCZ. Further analysis reveals that the warming over IPAR is initially found in the northern part of the domain, 20–15 days before the rainfall events over MCZ and is triggered by subtropical‐midlatitude interactions characterized by the intrusion of a midlatitude (i.e., Eurasian) atmospheric wave train into the Asian domain. Our analysis further reveals strong moist static energy (MSE) build‐up over the IPAR 12 days in advance, which is initially dominated by anomalous warming in the lower atmosphere, but with an incremental contribution of low‐level specific humidity as we moved forward in time towards the rainfall event. Hydrodynamic‐longwave radiative teleconnections are the primary mechanism for the persistence of the surface warming and MSE buildup over IPAR after the initial intrusion of the Eurasian wave train. The persistent warming over IPAR reinforces the land‐sea contrast between the Middle East and western equatorial Indian Ocean to its south, and this subsequently leads to pressure anomalies and monsoon circulation changes through geostrophic wind adjustment, thus enhancing westerlies over Arabian Sea. All these factors lead to the development of a gigantic monsoon trough over central India thus causing the rainfall extremes over MCZ through the genesis of synoptic vortices.

Barrier winds in the Italian region and effects of moist processes

Barrier winds form when a sufficiently high mountain range causes a stratified airflow directed towards the orographic barrier to slow down at the low levels, producing a pressure imbalance, which in turn generates a mountain-parallel wind. The present study analyses barrier wind occurrence in the Italian region and surrounding seas from both a climatological and dynamical perspective. The main goals are to assess the applicability of the linear theory of upstream blocking to real-world cases and to investigate the role of atmospheric moist processes in promoting the formation and influencing the evolution of barrier winds. A 2-year climatology of barrier winds reveals that they occur more frequently than the opposite regime of flow over the orography, especially in the cold season. Barrier wind events are found to be associated with an upstream flow having a significantly higher inverse Froude number (or non-dimensional mountain height) values than flow-over events on average, consistently with the theory. An Alpine case study is simulated using numerical models and sensitivity tests are performed to investigate the dependence of barrier wind development and properties on the non-dimensional mountain height. Simulations reveal the strong influence of precipitation-related diabatic processes on the development of an upstream cold pool, which in turn supports barrier wind maintenance and strengthens its intensity. Idealized numerical experiments with varying upstream flow moisture shed light on processes leading to significant strengthening of barrier wind intensity, in particular on the crucial role of latent heat exchanges associated with precipitation.

Moist Processes in the Atmosphere

Processes related to water in the atmosphere lead to severe uncertainties in weather forecasting and climate research. Atmospheric water vapor and cloud water strongly influence the Earth’s energy budget through, e.g., energy conversions associated with phase changes, fluid dynamical effects associated with buoyancy, and through their influence on radiative transfer properties of the atmosphere. Given the critical green-house effect of water vapor, it seems astounding that climate modellers cannot with certainty state whether the Earth’s cloud system has a positive or negative influence on the global mean temperature. The formation of clouds involves small-scale processes currently unresolved by climate models, and thus cloud cover is one of the main sources of uncertainty. This large uncertainty has its roots in the extremely wide range of length and time scales associated with moist processes, which pose an equally wide range of challenges to mathematical and computational modelling. New and innovative methods, modeling frameworks, efficient computational techniques, and complex statistical data analysis procedures as well as their mathematical analysis are urgently needed in order to make progress in this new field – from the mathematicians point of view. One of the main goals of this workshop is to show the path forward for current and future applied mathematical scientists, to work hand in hand across the disciplines of mathematics, physics, and atmospheric science, in order to tackle the complex problem of dynamical and thermodynamical processes associated with clouds and moisture, both from the theoretical and the applied view points.

The extratropical transition of Hurricane Ophelia (2017) as diagnosed with a generalized omega equation and vorticity equation

Hurricane Ophelia was a category 3 hurricane which underwent extratropical transition and made landfall in Europe as an exceptionally strong post-tropical cyclone in October 2017. In Ireland, Ophelia was the worst storm in 50 years and resulted in significant damage and even loss of life. In this study, the different physical processes affecting Ophelia’s transformation from a hurricane to a mid-latitude cyclone are studied. For this purpose, we have developed software that uses OpenIFS model output and a system consisting of a generalized omega equation and vorticity equation. By using these two equations, the atmospheric vertical motion and vorticity tendency are separated into the contributions from different physical processes: vorticity advection, thermal advection, friction, diabatic heating, and the imbalance between the temperature and vorticity tendencies. Vorticity advection, which is often considered an important forcing for the development of mid-latitude cyclones, is shown to play a small role in the re-intensification of the low-level cyclone. Instead, our results show that the adiabatic upper-level forcing was strongly amplified by moist processes, and thus, the diabatic heating was the dominant forcing in both the tropical and extratropical phases of Ophelia. Furthermore, we calculated in more detail the diabatic heating contributions from different model parameterizations. We find that the temperature tendency due to the convection scheme was the dominant forcing for the vorticity tendency during the hurricane phase, but as Ophelia transformed into a mid-latitude cyclone, the microphysics temperature tendency, presumably dominated by large-scale condensation, gradually increased becoming the dominant forcing once the transition was complete. Temperature tendencies caused by other diabatic processes, such as radiation, surface processes, vertical diffusion, and gravity wave drag, were found to be negligible in the development of the storm.

Adjoint Sensitivity Analysis of High-Impact Extratropical Cyclones

Abstract The initial state sensitivity of high-impact extratropical cyclones over the North Atlantic and United Kingdom is investigated using an adjoint modeling system that includes moist processes. The adjoint analysis indicates that the 48-h forecast of precipitation and high winds associated with the extratropical cyclone “Desmond” was highly sensitive to mesoscale regions of moisture at the initial time. Mesoscale moisture and potential vorticity structures along the poleward edge of an atmospheric river at the initialization time had a large impact on the development of Desmond as demonstrated with precipitation, kinetic energy, and potential vorticity response functions. Adjoint-based optimal perturbations introduced into the initial state exhibit rapidly growing amplitudes through moist energetic processes over the 48-h forecast. The sensitivity manifests as an upshear-tilted structure positioned along the cold and warm fronts. Perturbations introduced into the nonlinear and tangent linear models quickly expand vertically and interact with potential vorticity anomalies in the mid- and upper levels. Analysis of adjoint sensitivity results for the winter 2013/14 show that the moisture sensitivity magnitude at the initial time is well correlated with the kinetic energy error at the 36-h forecast time, which supports the physical significance and importance of the mesoscale regions of high moisture sensitivities.

On the Causal Relationship Between the Moist Diabatic Circulation and Cloud Rapid Adjustment to Increasing CO2

AbstractGeneral circulation models predict that clouds in the atmosphere rapidly adjust to the radiative perturbation of an abrupt increase in atmospheric CO2 concentration on a short time scale of about 10 days. This rapid adjustment consists of an increase of clouds in the boundary layer and a decrease of clouds in the free troposphere. Our focus is the mechanism for the decrease of clouds in the free troposphere, which is the dominating component of cloud rapid adjustment in most general circulation models. We propose that the decrease in clouds in the free troposphere arises from the causal relationship between the moist diabatic circulation and the production of condensates that forms clouds in moist processes. As CO2 concentration increases, tropospheric radiative cooling is reduced, resulting in weakening of the moist diabatic circulation and a decrease in precipitation. As the hydrologic cycle weakens and the moist processes involving phase change of water vapor to form the condensates in the atmosphere lessen, the mass of cloud condensates decreases. This decrease in cloud condensates can be predicted from the decrease in the radiative subsidence mass flux, which is a metric for the strength of the moist diabatic circulation in the free troposphere.

Explaining Scales and Statistics of Tropical Precipitation Clusters with a Stochastic Model

AbstractPrecipitation clusters are contiguous raining regions characterized by a precipitation threshold, size, and the total rainfall contained within—termed the cluster power. Tropical observations suggest that the probability distributions of both cluster size and power contain a power-law range (with slope ~ −1.5) bounded by a large-event “cutoff.” Events with values beyond the cutoff signify large, powerful clusters and represent extreme events. A two-dimensional stochastic model is introduced to reproduce the observed cluster distributions, including the slope and the cutoff. The model is equipped with coupled moisture and weak temperature gradient (WTG) energy equations, empirically motivated precipitation parameterization, temporally persistent noise, and lateral mixing processes, all of which collectively shape the model cluster distributions. Moisture–radiative feedbacks aid clustering, but excessively strong feedbacks push the model into a self-aggregating regime. The power-law slope is stable in a realistic parameter range. The cutoff is sensitive to multiple model parameters including the stochastic forcing amplitude, the threshold moisture value that triggers precipitation, and the lateral mixing efficiency. Among the candidates for simple analogs of precipitation clustering, percolation models are ruled out as unsatisfactory, but the stochastic branching process proves useful in formulating a neighbor probability metric. This metric measures the average number of nearest neighbors that a precipitating entity can spawn per time interval and captures the cutoff parameter sensitivity for both cluster size and power. The results here suggest that the clustering tendency and the horizontal scale limiting large tropical precipitating systems arise from aggregate effects of multiple moist processes, which are encapsulated in the neighbor probability metric.

Uncertainty of Observation Impact Estimation in an Adjoint Model Investigated with an Observing System Simulation Experiment

Abstract Adjoint models are often used to estimate the impact of different observations on short-term forecast skill. A common difficulty with the evaluation of short-term forecast quality is the choice of verification fields. The use of self-analysis fields for verification is typical but incestuous, and it introduces uncertainty resulting from biases and errors in the analysis field. In this study, an observing system simulation experiment (OSSE) is used to explore the uncertainty in adjoint model estimations of observation impact. The availability of the true state for verification in the OSSE framework in the form of the nature run allows calculation of the observation impact without the uncertainties present in self-analysis verification. These impact estimates are compared with estimates calculated using self-analysis verification. The Global Earth Observing System, version 5 (GEOS-5), forecast model with the Gridpoint Statistical Interpolation system is used with the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) OSSE capability. The adjoint model includes moist processes, with total wet energy selected as the norm for evaluation of observation impacts. The results show that there are measurable but small errors in the adjoint model estimation of observation impact as a result of self-analysis verification. In general, observations of temperature and winds tend to have overestimated impacts with self-analysis verification while observations of humidity and moisture-affected observations tend to have underestimated impacts. The small magnitude of the differences in impact estimates supports the robustness of the adjoint method of estimating observation impacts.

Simulations of Monsoon Intraseasonal Oscillation Using Climate Forecast System Version 2: Insight for Horizontal Resolution and Moist Processes Parameterization

In the present study, we analyze the Climate Forecast System version 2 (CFSv2) model in three resolutions, T62, T126, and T382. We evaluated the performance of all three resolutions of CFSv2 in simulating the Monsoon Intraseasonal Oscillation (MISO) of the Indian summer monsoon (ISM) by analyzing a suite of dynamic and thermodynamic parameters. Results reveal a slower northward propagation of MISO in all models with the characteristic northwest–southeast tilted rain band missing over India. The anomalous moisture convergence and vorticity were collocated with the convection center instead of being northwards. This affected the northward propagation of MISO. The easterly shear to the north of the equator was better simulated by the coarser resolution models than CFS T382. The low level specific humidity showed improvement only in CFS T382 until ~15° N. The analyses of the vertical profiles of moisture and its relation to rainfall revealed that all CFSv2 resolutions had a lower level of moisture in the lower level (< 850 hPa) and a drier level above. This eventually hampered the growth of deep convection in the model. These model shortcomings indicate a possible need of improvement in moist process parameterization in the model in tune with the increase in resolution.

Toward Convective-Scale Prediction within the Next Generation Global Prediction System

AbstractThe Geophysical Fluid Dynamics Laboratory (GFDL) has developed a new variable-resolution global model with the ability to represent convective-scale features that serves as a prototype of the Next Generation Global Prediction System (NGGPS). The goal of this prediction system is to maintain the skill in large-scale features while simultaneously improving the prediction skill of convectively driven mesoscale phenomena. This paper demonstrates the new capability of this model in convective-scale prediction relative to the current operational Global Forecast System (GFS). This model uses the stretched-grid functionality of the Finite-Volume Cubed-Sphere Dynamical Core (FV3) to refine the global 13-km uniform-resolution model down to 4-km convection-permitting resolution over the contiguous United States (CONUS), and implements the GFDL single-moment 6-category cloud microphysics to improve the representation of moist processes. Statistics gathered from two years of simulations by the GFS and select configurations of the FV3-based model are carefully examined. The variable-resolution FV3-based model is shown to possess global forecast skill comparable with that of the operational GFS while quantitatively improving skill and better representing the diurnal cycle within the high-resolution area compared to the uniform mesh simulations. Forecasts of the occurrence of extreme precipitation rates over the southern Great Plains are also shown to improve with the variable-resolution model. Case studies are provided of a squall line and a hurricane to demonstrate the effectiveness of the variable-resolution model to simulate convective-scale phenomena.

The properties and genesis environments of South Atlantic cyclones

A new climatology of South Atlantic cyclones is produced to provide new insights into the conditions leading to genesis in different regions of the domain. Cyclones are identified and tracked based on the relative vorticity at 850 hPa computed from the NCEP-CFSR winds. The characteristics of the cyclones are obtained by diagnostic variables sampled within a radial distance from the cyclone centers to produce the spatial distribution of cyclone properties at the time of genesis. Also, cyclone centered composites are used to analyze the cyclone structure and evolution during their genesis. There are four main cyclogenesis regions in the South Atlantic Ocean: the Southern Brazilian coast (SE-BR, $$30^\circ {\text {S}}$$ ), over the continent near the La Plata river discharge region (LA PLATA, $$35^\circ {\text {S}}$$ ), the southeastern coast of Argentina (ARG, $$40^\circ {\text {S}}$$ – $$55^\circ {\text {S}}$$ ) and the Southeastern Atlantic (SE-SAO, centered at $$45^\circ {\text {S}}$$ and $$10^\circ {\text {W}}$$ ). We found that cyclogenesis northward of $$35^\circ {\text {S}}$$ occurs mainly due to low-level forcing associated with moisture transport in the summer, and is associated with upper-level forcing in the winter due to a strong baroclinic environment. Southward of $$35^\circ {\text {S}}$$ , cyclones develop in a high baroclinic environment throughout the year with only a small influence from moist processes. The cyclone composites reveal that SE-BR and SE-SAO cyclones are associated with secondary development, the LA PLATA cyclones development is influenced by an orographic low in their early stages, and ARG cyclones are influenced by thermal advection as an essential mechanism in the reduction of static stability.

Improvements in Forecasting Intense Rainfall: Results from the FRANC (Forecasting Rainfall Exploiting New Data Assimilation Techniques and Novel Observations of Convection) Project

The FRANC project (Forecasting Rainfall exploiting new data Assimilation techniques and Novel observations of Convection) has researched improvements in numerical weather prediction of convective rainfall via the reduction of initial condition uncertainty. This article provides an overview of the project’s achievements. We highlight new radar techniques: correcting for attenuation of the radar return; correction for beams that are over 90% blocked by trees or towers close to the radar; and direct assimilation of radar reflectivity and refractivity. We discuss the treatment of uncertainty in data assimilation: new methods for estimation of observation uncertainties with novel applications to Doppler radar winds, Atmospheric Motion Vectors, and satellite radiances; a new algorithm for implementation of spatially-correlated observation error statistics in operational data assimilation; and innovative treatment of moist processes in the background error covariance model. We present results indicating a link between the spatial predictability of convection and convective regimes, with potential to allow improved forecast interpretation. The research was carried out as a partnership between University researchers and the Met Office (UK). We discuss the benefits of this approach and the impact of our research, which has helped to improve operational forecasts for convective rainfall events.

DCMIP2016: the splitting supercell test case

Abstract. This paper describes the splitting supercell idealized test case used in the 2016 Dynamical Core Model Intercomparison Project (DCMIP2016). These storms are useful test beds for global atmospheric models because the horizontal scale of convective plumes is O(1 km), emphasizing non-hydrostatic dynamics. The test case simulates a supercell on a reduced-radius sphere with nominal resolutions ranging from 4 to 0.5 km and is based on the work of Klemp et al. (2015). Models are initialized with an atmospheric environment conducive to supercell formation and forced with a small thermal perturbation. A simplified Kessler microphysics scheme is coupled to the dynamical core to represent moist processes. Reference solutions for DCMIP2016 models are presented. Storm evolution is broadly similar between models, although differences in the final solution exist. These differences are hypothesized to result from different numerical discretizations, physics–dynamics coupling, and numerical diffusion. Intramodel solutions generally converge as models approach 0.5 km resolution, although exploratory simulations at 0.25 km imply some dynamical cores require more refinement to fully converge. These results can be used as a reference for future dynamical core evaluation, particularly with the development of non-hydrostatic global models intended to be used in convective-permitting regimes.

Evaluating models' response of tropical low clouds to SST forcings using CALIPSO observations

Abstract. Recent studies have shown that, in response to a surface warming, the marine tropical low-cloud cover (LCC) as observed by passive-sensor satellites substantially decreases, therefore generating a smaller negative value of the top-of-the-atmosphere (TOA) cloud radiative effect (CRE). Here we study the LCC and CRE interannual changes in response to sea surface temperature (SST) forcings in the GISS model E2 climate model, a developmental version of the GISS model E3 climate model, and in 12 other climate models, as a function of their ability to represent the vertical structure of the cloud response to SST change against 10 years of CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) observations. The more realistic models (those that satisfy the observational constraint) capture the observed interannual LCC change quite well (ΔLCC/ΔSST=-3.49±1.01 % K−1 vs. ΔLCC/ΔSSTobs=-3.59±0.28 % K−1) while the others largely underestimate it (ΔLCC/ΔSST=-1.32±1.28 % K−1). Consequently, the more realistic models simulate more positive shortwave (SW) feedback (ΔCRE/ΔSST=2.60±1.13 W m−2 K−1) than the less realistic models (ΔCRE/ΔSST=0.87±2.63 W m−2 K−1), in better agreement with the observations (ΔCRE/ΔSSTobs=3±0.26 W m−2 K−1), although slightly underestimated. The ability of the models to represent moist processes within the planetary boundary layer (PBL) and produce persistent stratocumulus (Sc) decks appears crucial to replicating the observed relationship between clouds, radiation and surface temperature. This relationship is different depending on the type of low clouds in the observations. Over stratocumulus regions, cloud-top height increases slightly with SST, accompanied by a large decrease in cloud fraction, whereas over trade cumulus (Cu) regions, cloud fraction decreases everywhere, to a smaller extent.

The Circulation Response to Volcanic Eruptions: The Key Roles of Stratospheric Warming and Eddy Interactions

Proxy data and observations suggest that large tropical volcanic eruptions induce a poleward shift of the North Atlantic jet stream in boreal winter. However, there is far from universal agreement in models on this effect and its mechanism, and the possibilities of a corresponding jet shift in the Southern Hemisphere or the summer season have received little attention. Using a hierarchy of simplified atmospheric models, this study examines the impact of stratospheric aerosol on the extratropical circulation over the annual cycle. In particular, the models allow the separation of the dominant shortwave (surface cooling) and longwave (stratospheric warming) impacts of volcanic aerosol. It is found that stratospheric warming shifts the jet poleward in both the summer and winter hemispheres. The experiments cannot definitively rule out the role of surface cooling, but they provide no evidence that it shifts the jet poleward. Further study with simplified models demonstrates that the response to stratospheric warming is remarkably generic and does not depend critically on the boundary conditions (e.g., the planetary wave forcing) or the atmospheric physics (e.g., the treatment of radiative transfer and moist processes). It does, however, fundamentally involve both zonal-mean and eddy circulation feedbacks. The time scales, seasonality, and structure of the response provide further insight into the mechanism, as well as its connection to modes of intrinsic natural variability. These findings have implications for the interpretation of comprehensive model studies and for postvolcanic prediction.