Investigating the impact of cloud-radiative feedbacks on tropical precipitation extremes

AbstractAlthough societally important, extreme precipitation is difficult to represent in climate models. This study shows one robust aspect of extreme precipitation across models: extreme precipitation over tropical oceans is strengthened through a positive feedback with cloud-radiative effects. This connection is shown for a multi-model ensemble with experiments that make clouds transparent to longwave radiation. In all cases, tropical extreme precipitation reduces without cloud-radiative effects. Qualitatively similar results are presented for one model using the cloud-locking method to remove cloud feedbacks. The reduced extreme precipitation without cloud-radiative feedbacks does not arise from changes in the mean climate. Rather, evidence is presented that cloud-radiative feedbacks enhance organization of convection and most extreme precipitation over tropical oceans occurs within organized systems. This result suggests that climate models must correctly predict cloud structure and properties, as well as capture the essence of organized convection in order to accurately represent extreme rainfall.

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Assessing the Impact of Climate Change on the Waterlogging Risk in Coastal Cities: A Case Study of Guangzhou, South China

Journal of Hydrometeorology ◽

10.1175/jhm-d-16-0157.1 ◽

2017 ◽

Vol 18 (6) ◽

pp. 1549-1562 ◽

Cited By ~ 8

Author(s):

Han Zhang ◽

Chuanhao Wu ◽

Wenjie Chen ◽

Guoru Huang

Keyword(s):

Climate Change ◽

Sea Level ◽

Extreme Precipitation ◽

Climate Models ◽

Extreme Rainfall ◽

Tidal Level ◽

Future Period ◽

Coastal Cities ◽

Emissions Scenarios ◽

The Impact

Abstract Climate warming is expected to occur with an increased magnitude of extreme precipitation and sea level rise, which leads to an increased probability of waterlogging in coastal cities. In this paper, a combined probability model is developed to evaluate the impact of climate change on waterlogging in Guangzhou by using eight climate models with four emissions scenarios [Special Report on Emissions Scenarios (SRES) scenario A1B and representative concentration pathway (RCP) scenarios RCP2.6, RCP4.5, and RCP8.5]. The copula method was applied to derive the bivariate distributions of extreme rainfall and tidal level. The uncertainty in the projected future temperature, extreme rainfall, sea level, and the combined extreme rainfall and tidal level probability were discussed. The results show that although there is a large uncertainty driven by both climate models and emissions scenarios in the projection of climate change, most modeling results predict an increase in temperature and extreme precipitation in Guangzhou during the future period of 2020–50, relative to the historical period of 1970–2000. Moreover, greater increases are projected for higher emissions scenarios. The sea level is projected to increase in the range of 11.40–23.37 cm during the period 2020–50, consistent with climate warming. Both simultaneous probability and waterlogging probability are projected to show an upward trend in the future period 2020–50, with the largest and smallest increases in the RCP4.5 and RCP2.6 scenarios, respectively. The results of this paper provide a new scientific reference for waterlogging control in Guangzhou under climate change conditions.

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The cloud-free global energy balance and inferred cloud radiative effects: an assessment based on direct observations and climate models

Climate Dynamics ◽

10.1007/s00382-018-4413-y ◽

2018 ◽

Vol 52 (7-8) ◽

pp. 4787-4812 ◽

Cited By ~ 6

Author(s):

Martin Wild ◽

Maria Z. Hakuba ◽

Doris Folini ◽

Patricia Dörig-Ott ◽

Christoph Schär ◽

...

Keyword(s):

Energy Balance ◽

Climate Models ◽

Radiative Effects ◽

Global Energy ◽

Global Energy Balance ◽

Direct Observations ◽

Cloud Radiative Effects

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Monte Carlo-based subgrid parameterization of vertical velocity and stratiform cloud microphysics in ECHAM5.5-HAM2

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-5477-2013 ◽

2013 ◽

Vol 13 (2) ◽

pp. 5477-5507

Author(s):

J. Tonttila ◽

P. Räisänen ◽

H. Järvinen

Keyword(s):

Monte Carlo ◽

Vertical Velocity ◽

Cloud Droplet ◽

Cloud Microphysics ◽

Radiative Effects ◽

Cloud Droplets ◽

Microphysical Properties ◽

Cloud Radiative Effects ◽

Cloud Activation ◽

The Impact

Abstract. A new method for parameterizing the subgrid variations of vertical velocity and cloud droplet number concentration (CDNC) is presented for GCMs. These parameterizations build on top of existing parameterizations that create stochastic subgrid cloud columns inside the GCM grid-cells, which can be employed by the Monte Carlo independent column approximation approach for radiative transfer. The new model version adds a description for vertical velocity in individual subgrid columns, which can be used to compute cloud activation and the subgrid distribution of the number of cloud droplets explicitly. This provides a consistent way for simulating the cloud radiative effects with two-moment cloud microphysical properties defined in subgrid-scale. The primary impact of the new parameterizations is to decrease the CDNC over polluted continents, while over the oceans the impact is smaller. This promotes changes in the global distribution of the cloud radiative effects and might thus have implications on model estimation of the indirect radiative effect of aerosols.

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The impact of RCM formulation and resolution on simulated precipitation in Africa

10.5194/esd-2019-55 ◽

2019 ◽

Cited By ~ 2

Author(s):

Minchao Wu ◽

Grigory Nikulin ◽

Erik Kjellström ◽

Danijel Belušić ◽

Colin Jones ◽

...

Keyword(s):

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Horizontal Resolution ◽

Added Value ◽

Primary Control ◽

Model Formulation ◽

Simulated Precipitation ◽

Mean Climate ◽

The Impact

Abstract. We investigate the impact of model formulation and horizontal resolution on the ability of Regional Climate Models (RCMs) to simulate precipitation in Africa. Two RCMs – SMHI-RCA4 and HCLIM38-ALADIN are utilized for downscaling the ERA-Interim reanalysis over Africa at four different resolutions: 25, 50, 100 and 200 km. Additionally to the two RCMs, two different configurations of the same RCA4 are used. Contrasting different RCMs, configurations and resolutions it is found that model formulation has the primary control over many aspects of the precipitation climatology in Africa. Patterns of spatial biases in seasonal mean precipitation are mostly defined by model formulation while the magnitude of the biases is controlled by resolution. In a similar way, the phase of the diurnal cycle is completely controlled by model formulation (convection scheme) while its amplitude is a function of resolution. Although higher resolution in many cases leads to smaller biases in the time mean climate, the impact of higher resolution is mixed. An improvement in one region/season (e.g. reduction of dry biases) often corresponds to a deterioration in another region/season (e.g. amplification of wet biases). The experiments confirm a pronounced and well known impact of higher resolution – a more realistic distribution of daily precipitation. Even if the time-mean climate is not always greatly sensitive to resolution, what the time-mean climate is made up of, higher order statistics, is sensitive. Therefore, the realism of the simulated precipitation increases as resolution increases. Our results show that improvements in the ability of RCMs to simulate precipitation in Africa compared to their driving reanalysis in many cases are simply related to model formulation and not necessarily to higher resolution. Such model formulation related improvements are strongly model dependent and in general cannot be considered as an added value of downscaling.

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Impacts on agriculture

Proceedings of the Royal Society of Victoria ◽

10.1071/rs13012 ◽

2013 ◽

Vol 125 (1) ◽

pp. 24

Author(s):

Leanne Webb

Keyword(s):

Extreme Events ◽

Agricultural Production ◽

Climate Models ◽

Climate Extremes ◽

Extreme Rainfall ◽

Agricultural Communities ◽

Eastern Australia ◽

Weather And Climate ◽

Challenging Environment ◽

Mean Climate

p>Agricultural production in Victoria includes the dairy, lamb and mutton, grains and perennial and annual horticultural sectors, with Victorian farmers contributing a major proportion of the Australian production total in many of these sectors. All these industries are exposed in different ways to weather and climate extremes. With projected warming of approximately 0.8°C by 2030 and by 1.4–2.7°C by 2070 (emissions dependent), and most climate models indicating reduced rainfall for the Victorian region (median of model results projecting a reduction of 4% by 2030 and 6%–11% by 2070; emissions dependent), a range of sectorspecific impacts could result. Increases in extreme events, such as heatwaves (e.g. for Mildura, days >35°C could nearly double from 32 to 59 annually by 2070), bushfires and drought, as well as an increased chance of extreme rainfall are all anticipated. Increasing frequencies of extreme events have the potential to affect agricultural production more than changes to the mean climate. For example, the exceptional heatwave that occurred in south-eastern Australia during January and February 2009 resulted in unprecedented impacts, with significant heat-stress related crop losses reported at many sites. Flooding in 2011 was also very costly to Victorian farmers with many crops being lost in the floodwaters and reduced agricultural production costing an estimated Au$500–600 million. Responses to climate variability already practised by the farming sector will inform some adaptation options that will assist farmers to cope in an increasingly challenging environment. As well as taking advantage of their underlying resilience, initiatives aimed at increasing the adaptive capacity of farmers are being implemented at many levels in agricultural communities.

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Subtropical clouds stabilize near-Snowball Earth states

10.5194/egusphere-egu2020-10617 ◽

2020 ◽

Author(s):

Christoph Braun ◽

Aiko Voigt ◽

Johannes Hörner ◽

Joaquim G. Pinto

Keyword(s):

Sea Ice ◽

General Circulation ◽

General Circulation Models ◽

Snowball Earth ◽

Radiative Effects ◽

Albedo Feedback ◽

The Earth ◽

Cloud Radiative Effects ◽

Planetary Albedo ◽

The Impact

Atmospheric general circulation models developed for the Earth system include comprehensive parameterizations of clouds. Applying them to exoplanet atmospheres provides an opportunity to advance understanding of clouds, atmosphere dynamics, and their coupling in the context of planetary climate dynamics and habitability.Here, we study a deep-time extreme climate of Earth as an example of the cold limit of the habitable zone. Geological evidence indicates near-global ice cover during the Neoproterozoic (1000 &#8211; 541 Million years ago) associated with considerable hysteresis of atmospheric CO2. The Snowball Earth hypothesis provides a straightforward interpretation of Neoproterozoic proxies based on a runaway of the sea-ice albedo feedback. However, the Snowball Earth hypothesis relies on the existence of local habitats to explain the survival of photosynthetic marine species on an entirely ice-covered planet. The Jormungand hypothesis may resolve this issue by considering a weakening of the sea-ice albedo feedback by exposure of dark bare sea ice when sea ice enters the subtropics. This potentially allows the Earth system to stabilize in a climate state - the Jormungand state - with near-global ice cover. Around the equator, a narrow strip of ocean remains ice-free, where life would have easily survived during the pan-glaciations.The weakening of the sea-ice albedo feedback is based on the change of the meridional structure of planetary albedo with a moving sea-ice edge. While previous work focused on the contribution of surface albedo to planetary albedo, we here focus on the impact of subtropical and tropical cloudiness on planetary albedo. Enhanced cloudiness generally weakens the sea-ice albedo feedback and thus decreases the climate sensitivity of the Jormungand state, i.e. it stabilizes the Jormungand state. We analyze the impact of cloudiness on the stability of the Jormungand state in the general circulation models CAM3 and ICON-AES with idealized aquaplanet setups. While CAM3 shows significant CO2-hysteresis of the Jormungand state, ICON-AES exhibits no stable Jormungand state. Consistently, CAM3 exhibits stronger cloudiness than ICON-AES, especially in the subtropics. An analysis with a one-dimensional energy balance model shows that the Jormungand hysteresis strongly depends on the sensitivity of the planetary albedo to an advance of sea ice into the subtropics. Accordingly, we demonstrate that the absence of cloud-radiative effects within vertical columns in the subtropics drastically decreases the Jormungand hysteresis in CAM3.Overall, the magnitude of the Jormungand hysteresis is tightly linked to the representation of cloud-radiative effects in general circulation models. Our results highlight the important role of uncertainties associated with cloud-radiative effects for climate feedbacks on planet Earth in the context of extreme climates, such as they have occurred in Earth&#8217;s deep past or might be found on Earth-like planets. In consequence, this also stresses the need and challenges of accounting for adequate cloud modeling for planetary climates.

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Environmental Response in Coupled Energy and Water Cloud Impact Parameters Derived from A-Train Satellite, ERA-Interim and MERRA-2

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-21-0078.1 ◽

2021 ◽

Keyword(s):

Climate Models ◽

Water Cycle ◽

Cloud Microphysics ◽

Dynamic Regime ◽

Radiative Heating ◽

Radiative Effects ◽

Surface Cooling ◽

Heating Efficiency ◽

Cloud Radiative Effects ◽

Impact Parameters

Abstract Understanding the connections between latent heating from precipitation and cloud radiative effects is essential for accurately parameterizing cross-scale links between cloud microphysics and global energy and water cycles in climate models. While commonly examined separately, this study adopts two cloud impact parameters (CIPs), the surface radiative cooling efficiency, Rc, and atmospheric radiative heating efficiency, Rh, that explicitly couple cloud radiative effects and precipitation to characterize how efficiently precipitating cloud systems influence the energy budget and water cycle using A-Train observations and two reanalyses. These CIPs exhibit distinct global distributions that suggest cloud energy and water cycle coupling are highly dependent on cloud regime. The dynamic regime (ω500) controls the sign of Rh, while column water vapor (CWV) appears to be the larger control on the magnitude. The magnitude of Rc is highly coupled to the dynamic regime. Observations show that clouds cool the surface very efficiently per unit rainfall at both low and high sea surface temperature (SST) and CWV, but reanalyses only capture the former. Reanalyses fail to simulate strong Rh and moderate Rc in deep convection environments but produce stronger Rc and Rh than observations in shallow, warm rain systems in marine stratocumulus regions. While reanalyses generate fairly similar climatologies in the frequency of environmental states, the response of Rc and Rh to SST and CWV results in systematic differences in zonal and meridional gradients of cloud atmospheric heating and surface cooling relative to A-Train observations that may have significant implications for global circulations and cloud feedbacks.

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The implications of soil erosion model conceptualization, bias-correction methods and climate model ensembles on soil erosion projections under climate change

10.5194/egusphere-egu2020-8158 ◽

2020 ◽

Author(s):

Joris de Vente ◽

Joris Eekhout

Keyword(s):

Climate Change ◽

Soil Erosion ◽

Extreme Precipitation ◽

Climate Models ◽

Climate Model ◽

Erosion Model ◽

Distribution Mapping ◽

Climate Model Ensembles ◽

Model Ensembles ◽

The Impact

Climate models project increased extreme precipitation for the coming decades, which may lead to higher soil erosion in many locations worldwide. The impact of climate change on soil erosion is most often assessed by applying a soil erosion model forced by bias-corrected climate model output. A literature review among more than 100 papers showed that many studies use different soil erosion models, bias-correction methods and climate model ensembles. In this study, we assessed how these differences affect the outcome of climate change impact assessments on soil erosion. The study was performed in two contrasting Mediterranean catchments (SE Spain), where climate change is projected to lead to a decrease in annual precipitation sum and an increase in extreme precipitation, based on the RCP8.5 emission scenario. First, we assessed the impact of soil erosion model selection using the three most widely used model concepts, i.e. a model forced by precipitation (RUSLE), a model forced by runoff (MUSLE), and a model forced by precipitation and runoff (MMF). Depending on the model, soil erosion in the study area is projected to decrease (RUSLE) or increase (MUSLE and MMF). The differences between the model projections are inherently a result of their model conceptualization, such as a decrease of soil loss due to decreased annual precipitation sum (RUSLE) and an increase of soil loss due to increased extreme precipitation and, consequently, increased runoff (MUSLE). An intermediate result is obtained with MMF, where a projected decrease in detachment by raindrop impact is counteracted by a projected increase in detachment by runoff. Second, we evaluated the implications of three bias&#8208;correction methods, i.e. delta change, quantile mapping and scaled distribution mapping. Scaled distribution mapping best reproduces the raw climate change signal, in particular for extreme precipitation. Depending on the bias&#8208;correction method, soil erosion is projected to decrease (delta change) or increase (quantile mapping and scaled distribution mapping). Finally, we assessed the effect of climate model ensembles on soil erosion projections. We showed that individual climate models may project opposite changes with respect to the ensemble average, hence, climate model ensembles are essential in soil erosion impact assessments to account for climate model uncertainty. We conclude that in climate change impact assessments it is important to select a soil erosion model that is forced by both precipitation and runoff, which under climate change may have a contrasting effect on soil erosion. Furthermore, the impact of climate change on soil erosion can only accurately be assessed with a bias&#8208;correction method that best reproduces the projected climate change signal, in combination with a representative ensemble of climate models.

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Contributions of Climate Feedbacks to Changes in Atmospheric Circulation

Journal of Climate ◽

10.1175/jcli-d-17-0189.1 ◽

2017 ◽

Vol 30 (22) ◽

pp. 9097-9118 ◽

Cited By ~ 25

Author(s):

Paulo Ceppi ◽

Theodore G. Shepherd

Keyword(s):

Water Vapor ◽

Atmospheric Circulation ◽

Surface Albedo ◽

Climate Models ◽

Cmip5 Models ◽

Climate Feedbacks ◽

Wide Range ◽

Radiative Feedbacks ◽

Opposing Effects ◽

The Impact

The projected response of the atmospheric circulation to the radiative changes induced by CO2 forcing and climate feedbacks is currently uncertain. In this modeling study, the impact of CO2-induced climate feedbacks on changes in jet latitude and speed is assessed by imposing surface albedo, cloud, and water vapor feedbacks as if they were forcings in two climate models, CAM4 and ECHAM6. The jet response to radiative feedbacks can be broadly interpreted through changes in midlatitude baroclinicity. Clouds enhance baroclinicity, favoring a strengthened, poleward-shifted jet; this is mitigated by surface albedo changes, which have the opposite effect on baroclinicity and the jet, while water vapor has opposing effects on upper- and lower-level baroclinicity with little net impact on the jet. Large differences between the CAM4 and ECHAM6 responses illustrate how model uncertainty in radiative feedbacks causes a large spread in the baroclinicity response to CO2 forcing. Across the CMIP5 models, differences in shortwave feedbacks by clouds and albedo are a dominant contribution to this spread. Forcing CAM4 with shortwave cloud and albedo feedbacks from a representative set of CMIP5 models yields a wide range of jet responses that strongly correlate with the meridional gradient of the anomalous shortwave heating and the associated baroclinicity response. Differences in shortwave feedbacks statistically explain about 50% of the intermodel spread in CMIP5 jet shifts for the set of models used, demonstrating the importance of constraining radiative feedbacks for accurate projections of circulation changes.

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Understanding the Varied Influence of Midlatitude Jet Position on Clouds and Cloud Radiative Effects in Observations and Global Climate Models

Journal of Climate ◽

10.1175/jcli-d-16-0295.1 ◽

2016 ◽

Vol 29 (24) ◽

pp. 9005-9025 ◽

Cited By ~ 22

Author(s):

Kevin M. Grise ◽

Brian Medeiros

Keyword(s):

Vertical Velocity ◽

Climate Models ◽

Global Climate ◽

Storm Track ◽

Cloud Amount ◽

Global Climate Models ◽

Radiative Effects ◽

Velocity Anomalies ◽

Cooling Effects ◽

Cloud Radiative Effects

Abstract This study examines the dynamical mechanisms responsible for changes in midlatitude clouds and cloud radiative effects (CRE) that occur in conjunction with meridional shifts in the jet streams over the North Atlantic, North Pacific, and Southern Oceans. When the midlatitude jet shifts poleward, extratropical cyclones and their associated upward vertical velocity anomalies closely follow. As a result, a poleward jet shift contributes to a poleward shift in high-topped storm-track clouds and their associated longwave CRE. However, when the jet shifts poleward, downward vertical velocity anomalies increase equatorward of the jet, contributing to an enhancement of the boundary layer estimated inversion strength (EIS) and an increase in low cloud amount there. Because shortwave CRE depends on the reflection of solar radiation by clouds in all layers, the shortwave cooling effects of midlatitude clouds increase with both upward vertical velocity anomalies and positive EIS anomalies. Over midlatitude oceans where a poleward jet shift contributes to positive EIS anomalies but downward vertical velocity anomalies, the two effects cancel, and net observed changes in shortwave CRE are small. Global climate models generally capture the observed anomalies associated with midlatitude jet shifts. However, there is large intermodel spread in the shortwave CRE anomalies, with a subset of models showing a large shortwave cloud radiative warming over midlatitude oceans with a poleward jet shift. In these models, midlatitude shortwave CRE is sensitive to vertical velocity perturbations, but the observed sensitivity to EIS perturbations is underestimated. Consequently, these models might incorrectly estimate future midlatitude cloud feedbacks in regions where appreciable changes in both vertical velocity and EIS are projected.

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