A One-dimensional Time Dependent Cloud Model

Chen, Shu Hua; Sun, Wen‐Yih

doi:10.2151/jmsj.80.99

Cited by 448 publications

(249 citation statements)

References 29 publications

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“…The surface fluxes of moisture and heat are parameterized following Monin−Obukhov similarity theory. Microphysics is simulated using the Purdue−Lin bulk scheme (34), which has six species: water vapor, cloud water, cloud ice, rain, snow, and graupel. Radiative fluxes are determined interactively using the National Center for Atmospheric Research Community Atmosphere Model version 3.0 scheme for shortwave and longwave radiation.…”

Section: Methodsmentioning

confidence: 99%

Fog and rain in the Amazon

Anber

Gentine

Wang

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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The diurnal and seasonal water cycles in the Amazon remain poorly simulated in general circulation models, exhibiting peak evapotranspiration in the wrong season and rain too early in the day. We show that those biases are not present in cloud-resolving simulations with parameterized large-scale circulation. The difference is attributed to the representation of the morning fog layer, and to more accurate characterization of convection and its coupling with large-scale circulation. The morning fog layer, present in the wet season but absent in the dry season, dramatically increases cloud albedo, which reduces evapotranspiration through its modulation of the surface energy budget. These results highlight the importance of the coupling between the energy and hydrological cycles and the key role of cloud albedo feedback for climates over tropical continents.cloud-resolving models T ropical forests, and the Amazon in particular, are the biggest terrestrial CO 2 sinks on the planet, accounting for about 30% of the total net primary productivity in terrestrial ecosystems. Hence, the climate of the Amazon is of particular importance for the fate of global CO 2 concentration in the atmosphere (1). Besides the difficulty of estimating carbon pools (1-3), our incapacity to correctly predict CO 2 fluxes in the continental tropics largely results from inaccurate simulation of the tropical climate (1, 2, 4, 5). More frequent and more intense droughts in particular are expected to affect the future health of the Amazon and its capacity to act as a major carbon sink (6-8). The land surface is not isolated, however, but interacts with the weather and climate through a series of land−atmosphere feedback loops, which couple the energy, carbon, and water cycles through stomata regulation and boundary layer mediation (9).Current General Circulation Models (GCMs) fail to correctly represent some of the key features of the Amazon climate. In particular, they (i) underestimate the precipitation in the region (10, 11), (ii) do not reproduce the seasonality of either precipitation (10, 11) or surface fluxes such as evapotranspiration (12), and (iii) produce errors in the diurnal cycle and intensity of precipitation, with a tendency to rain too little and too early in the day (13,14). In the more humid Western part of the basin, surface incoming radiation, evapotranspiration, and photosynthesis all tend to peak in the dry season (15-17), whereas GCMs simulate peaks of those fluxes in the wet season (10, 11). Those issues might be related to the representation of convection (1,2,4,5,13,14) and vegetation water stress (6)(7)(8)(15)(16)(17) in GCMs.We here show that we can represent the Amazonian climate using a strategy opposite to GCMs in which we resolve convection and parameterize the large-scale circulation (Methods). The simulations lack many of the biases observed in GCMs and more accurately capture the differences between the dry and wet season of the Amazon in surface heat fluxes and precipitation. Besides top-of-the-atmosphere inso...

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Section: Methodsmentioning

confidence: 99%

Fog and rain in the Amazon

Anber

Gentine

Wang

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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“…Based on these tests and previous work, the physical options chosen in this study include the Mellor-YamadaJanjic planetary boundary-layer scheme (Mellor and Yamada 1982;Janjic 1990Janjic , 1996Janjic , 2002, the MoninObukhov Janjic surface-layer scheme (Monin and Obukhov 1954;Janjic 1994Janjic , 1996Janjic , 2002, the new Kain-Fritsch cumulus scheme Fritsch 1990, 1993), and the Purdue Lin microphysics scheme (Lin et al 1983;Rutledge Tao et al 1989;Chen and Sun 2002). Longwave radiation is calculated by the RRTM scheme (Mlawer et al 1997), and shortwave is represented by the Dudhia (1989) scheme.…”

Section: Methodology For Generating Confident Future Climate Predictionsmentioning

confidence: 99%

Northern African climate at the end of the twenty-first century: an integrated application of regional and global climate models

2009

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A method for simulating future climate on regional space scales is developed and applied to northern Africa. Simulation with a regional model allows for the horizontal resolution needed to resolve the region's strong meridional gradients and the optimization of parameterizations and land-surface model. The control simulation is constrained by reanalysis data, and realistically represents the present day climate. Atmosphere-ocean general circulation model (AOGCM) output provides SST and lateral boundary condition anomalies for 2081-2100 under a business-as-usual emissions scenario, and the atmospheric CO 2 concentration is increased to 757 ppmv. A ninemember ensemble of future climate projections is generated by using output from nine AOGCMs. The consistency of precipitation projections for the end of the twenty-first century is much greater for the regional model ensemble than among the AOGCMs. More than 77% of ensemble members produce the same sign rainfall anomaly over much of northern Africa. For West Africa, the regional model projects wetter conditions in spring, but a midsummer drought develops during June and July, and the heat stoke risk increases across the Sahel. Wetter conditions resume in late summer, and the likelihood of flooding increases. The regional model generally projects wetter conditions over eastern Central Africa in June and drying during August through September. Severe drought impacts parts of East Africa in late summer. Conditions become wetter in October, but the enhanced rainfall does not compensate for the summertime deficit. The risk of heat stroke increases over this region, although the threat is not projected to be as great as in the Sahel.

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“…Besides the differences in the land surface model, all simulations employed the same set of atmospheric physics schemes stemming from the WRF model. These include the Purdue scheme for microphysics (Chen and Sun, 2002), the Rapid Radiative Transfer Model for long wave radiation (Mlawer et al, 1997), the Dudhia scheme for shortwave radiation (Dudhia, 1989), the Monin-Obukhov similarity scheme for surface layer physics of nonvegetated surfaces and the ocean, and the MRF scheme for the planetary boundary layer (Hong and Pan, 1996). WRF runs at a 60-second time step, while the radiation scheme and the land surface schemes are called every 30 minutes.…”

Section: Model Setupmentioning

confidence: 99%

Impact of canopy representations on regional modeling of evapotranspiration using the WRF-ACASA coupled model

Pyles

et al. 2017

Agricultural and Forest Meteorology

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The MIT Joint Program on the Science and Policy of Global Change combines cutting-edge scienti c research with independent policy analysis to provide a solid foundation for the public and private decisions needed to mitigate and adapt to unavoidable global environmental changes. Being data-driven, the Program uses extensive Earth system and economic data and models to produce quantitative analysis and predictions of the risks of climate change and the challenges of limiting human in uence on the environment-essential knowledge for the international dialogue toward a global response to climate change.To this end, the Program brings together an interdisciplinary group from two established MIT research centers: the Center for Global Change Science (CGCS) and the Center for Energy and Environmental Policy Research (CEEPR). These two centers-along with collaborators from the Marine Biology Laboratory (MBL) at Woods Hole and short-and longterm visitors-provide the united vision needed to solve global challenges.At the heart of much of the Program's work lies MIT's Integrated Global System Model. Through this integrated model, the Program seeks to: discover new interactions among natural and human climate system components; objectively assess uncertainty in economic and climate projections; critically and quantitatively analyze environmental management and policy proposals; understand complex connections among the many forces that will shape our future; and improve methods to model, monitor and verify greenhouse gas emissions and climatic impacts.This reprint is one of a series intended to communicate research results and improve public understanding of global environment and energy challenges, thereby contributing to informed debate about climate change and the economic and social implications of policy alternatives. AbstractIn this study, we couple the Weather Research and Forecasting Model (WRF) with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high complexity land surface model, to investigate the impact of canopy representation on regional evapotranspiration. The WRF-ACASA model uses a multilayer structure to represent the canopy, consequently allowing microenvironmental variables such as leaf area index (LAI), air and canopy temperature, wind speed and humidity to vary both horizontally and vertically. The improvement in canopy representation and canopy-atmosphere interaction allow for more realistic simulation of evapotranspiration on both regional and local scales. Accurate estimates of evapotranspiration (both potential and actual) are especially important for regions with limited water availability and high water demand, such as California. Water availability has been and will continue to be the most important issue facing California for years and perhaps decades to come. Terrestrial evapotranspiration is influenced by many processes and interactions in the atmosphere and the bio-sphere such as water, carbon, and momentum exchanges. The need to improve representation within of surface-atmosphere ...

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A One-dimensional Time Dependent Cloud Model

Cited by 448 publications

References 29 publications

Fog and rain in the Amazon

Fog and rain in the Amazon

Northern African climate at the end of the twenty-first century: an integrated application of regional and global climate models

Impact of canopy representations on regional modeling of evapotranspiration using the WRF-ACASA coupled model

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