Assessing the CAM5 physics suite in the WRF-Chem model: implementation, resolution sensitivity, and a first evaluation for a regional case study

Abstract. A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 when the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem, provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.

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Assessing the CAM5 physics suite in the WRF-Chem model: implementation, evaluation, and resolution sensitivity

Geoscientific Model Development Discussions ◽

10.5194/gmdd-6-6157-2013 ◽

2013 ◽

Vol 6 (4) ◽

pp. 6157-6218 ◽

Cited By ~ 6

Author(s):

P.-L. Ma ◽

P. J. Rasch ◽

J. D. Fast ◽

R. C. Easter ◽

W. I. Gustafson Jr. ◽

...

Keyword(s):

Climate Model ◽

Mesoscale Model ◽

Global Climate Model ◽

Cloud Microphysics ◽

Horizontal Resolution ◽

Surface Fluxes ◽

The Arctic ◽

Shallow Convection ◽

Modeling Framework ◽

Near Surface

Abstract. A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with Chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 when the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem, provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.

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Diagnosing factors in parameterised and resolved convection with physical tendency output in AROME-Arctic during a Cold-Air Outbreak event

10.5194/egusphere-egu2020-7610 ◽

2020 ◽

Author(s):

Marvin Kähnert ◽

Teresa M. Valkonen ◽

Harald Sodemann

Keyword(s):

Weather Prediction ◽

Cloud Microphysics ◽

High Impact ◽

Surface Fluxes ◽

The Arctic ◽

Shallow Convection ◽

Time Step ◽

Cold Air ◽

Weather Events ◽

High Impact Weather

Numerical weather prediction (NWP) models generally display comparatively low predictive skill in the Arctic. Particularly, the large impact of sub-grid scale, parameterised processes, such as surface fluxes, radiation or cloud microphysics during high-latitude weather events pose a substantial challenge for numerical modelling. Such processes are most influential during mesoscale weather events, such as polar lows, often embedded in cold air outbreaks (CAO), some of which cause high impact weather. Uncertainty in Arctic weather forecasts is thus critically dependent on parameterised processes. The strong influence from several parameterised processes also makes model forecasts particularly susceptible to compensation of errors from different parameterisations, which potentially limits model improvement. Here we analyse model output of individual parameterised tendencies of wind, temperature and humidity during Arctic high-impact weather in AROME-Arctic, the operational NWP model used by the Norwegian Meteorological Institute Norway for the European Arctic. Individual tendencies describe the contribution of each applied physical parameterisation to a respective variable per model time step. We study a CAO-event taking place during 24 - 27 December 2015. This intense and widespread CAO event, reaching from the Fram Straight to Norway and affecting a particularly large portion of the Nordic seas at a time, was characterised by strong heat fluxes along the sea ice edge.&#160; Model intern definitions for boundary layer type become apparent as a decisive factor in tendency contributions. Especially the interplay between the dual mass flux and the turbulence scheme is of essence here. Furthermore, sensitivity experiments, featuring a run without shallow convection and a run with a new statistical cloud scheme, show how a physically similar result is obtained by substantially different tendencies in the model.

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How Can Climate Change Affect the UNESCO Cultural Heritage Sites in Panama?

Geosciences ◽

10.3390/geosciences8080296 ◽

2018 ◽

Vol 8 (8) ◽

pp. 296 ◽

Cited By ~ 3

Author(s):

Chiara Ciantelli ◽

Elisa Palazzi ◽

Jost von Hardenberg ◽

Carmela Vaccaro ◽

Francesca Tittarelli ◽

...

Keyword(s):

Climate Change ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Construction Materials ◽

Horizontal Resolution ◽

Damage Functions ◽

Near Surface ◽

Heritage Sites ◽

The Impact

This work investigates the impact of long-term climate change on heritage sites in Latin America, focusing on two important sites in the Panamanian isthmus included in the World Heritage List: the monumental site of Panamá Viejo (16th century) and the Fortresses of Portobelo and San Lorenzo (17th to 18th centuries). First of all, in order to support the conservation and valorisation of these sites, a characterisation of the main construction materials utilized in the building masonries was performed together with an analysis of the meteoclimatic conditions in their vicinity as provided by monitoring stations recording near-surface air temperature, relative humidity, and rainfall amounts. Secondly, the same climate variables were analysed in the historical and future simulations of a state-of-the-art global climate model, EC-Earth, run at high horizontal resolution, and then used with damage functions to make projections of deterioration phenomena on the Panamanian heritage sites. In particular, we performed an evaluation of the possible surface recession, biomass accumulation, and deterioration due to salt crystallisation cycles on these sites in the future (by midcentury, 2039–2068) compared to the recent past (1979–2008), considering a future scenario of high greenhouse gas emissions.

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High-Resolution Climate Change Impact Analysis on Expected Future Water Availability in the Upper Jordan Catchment and the Middle East

Journal of Hydrometeorology ◽

10.1175/jhm-d-13-0153.1 ◽

2014 ◽

Vol 15 (4) ◽

pp. 1517-1531 ◽

Cited By ~ 15

Author(s):

Gerhard Smiatek ◽

Harald Kunstmann ◽

Andreas Heckl

Keyword(s):

Climate Change ◽

High Resolution ◽

Water Availability ◽

Impact Analysis ◽

River Flow ◽

Climate Model ◽

Mesoscale Model ◽

Global Climate Model ◽

Full Range ◽

The Impact

Abstract The impact of climate change on the future water availability of the upper Jordan River (UJR) and its tributaries Dan, Snir, and Hermon located in the eastern Mediterranean is evaluated by a highly resolved distributed approach with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) run at 18.6- and 6.2-km resolution offline coupled with the Water Flow and Balance Simulation Model (WaSiM). The MM5 was driven with NCEP reanalysis for 1971–2000 and with Hadley Centre Coupled Model, version 3 (HadCM3), GCM forcings for 1971–2099. Because only one regional–global climate model combination was applied, the results may not give the full range of possible future projections. To describe the Dan spring behavior, the hydrological model was extended by a bypass approach to allow the fast discharge components of the Snir to enter the Dan catchment. Simulation results for the period 1976–2000 reveal that the coupled system was able to reproduce the observed discharge rates in the partially karstic complex terrain to a reasonable extent with the high-resolution 6.2-km meteorological input only. The performed future climate simulations show steadily rising temperatures with 2.2 K above the 1976–2000 mean for the period 2031–60 and 3.5 K for the period 2070–99. Precipitation trends are insignificant until the middle of the century, although a decrease of approximately 12% is simulated. For the end of the century, a reduction in rainfall ranging between 10% and 35% can be expected. Discharge in the UJR is simulated to decrease by 12% until 2060 and by 26% until 2099, both related to the 1976–2000 mean. The discharge decrease is associated with a lower number of high river flow years.

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A bias-corrected CMIP5 dataset for Africa using the CDF-t method – a contribution to agricultural impact studies

Earth System Dynamics ◽

10.5194/esd-9-313-2018 ◽

2018 ◽

Vol 9 (1) ◽

pp. 313-338 ◽

Cited By ~ 18

Author(s):

Adjoua Moise Famien ◽

Serge Janicot ◽

Abe Delfin Ochou ◽

Mathieu Vrac ◽

Dimitri Defrance ◽

...

Keyword(s):

West Africa ◽

Air Temperature ◽

Climate Model ◽

Global Climate Model ◽

Cumulative Distribution ◽

Shortwave Radiation ◽

Climate Change Scenarios ◽

Reference Dataset ◽

Near Surface ◽

The Impact

Abstract. The objective of this paper is to present a new dataset of bias-corrected CMIP5 global climate model (GCM) daily data over Africa. This dataset was obtained using the cumulative distribution function transform (CDF-t) method, a method that has been applied to several regions and contexts but never to Africa. Here CDF-t has been applied over the period 1950–2099 combining Historical runs and climate change scenarios for six variables: precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface downwelling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. WFDEI has been used as the reference dataset to correct the GCMs. Evaluation of the results over West Africa has been carried out on a list of priority user-based metrics that were discussed and selected with stakeholders. It includes simulated yield using a crop model simulating maize growth. These bias-corrected GCM data have been compared with another available dataset of bias-corrected GCMs using WATCH Forcing Data as the reference dataset. The impact of WFD, WFDEI, and also EWEMBI reference datasets has been also examined in detail. It is shown that CDF-t is very effective at removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets. This is particularly true for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields. Projections of future yields over West Africa are quite different, depending on the bias-correction method used. However all these projections show a similar relative decreasing trend over the 21st century.

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An Intraseasonal Mode Linking Wintertime Surface Air Temperature over Arctic and Eurasian Continent

Journal of Climate ◽

10.1175/jcli-d-21-0495.1 ◽

2021 ◽

pp. 1-47

Keyword(s):

Air Temperature ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Surface Air Temperature ◽

Arctic Sea Ice ◽

The Arctic ◽

Free Atmosphere ◽

Temperature Anomalies ◽

Downward Longwave Radiation

Abstract Key processes associated with the leading intraseasonal variability mode of wintertime surface air temperature (SAT) over Eurasia and the Arctic region are investigated in this study. Characterized by a dipole distribution in SAT anomalies centered over north Eurasia and the Arctic, respectively, and coherent temperature anomalies vertically extending from the surface to 300hPa, this leading intraseasonal SAT mode and associated circulation have pronounced influences on global surface temperature anomalies including the East Asian winter monsoon region. By taking advantage of realistic simulations of the intraseasonal SAT mode in a global climate model, it is illustrated that temperature anomalies in the troposphere associated with the leading SAT mode are mainly due to dynamic processes, especially via the horizontal advection of winter mean temperature by intraseasonal circulation. While the cloud-radiative feedback is not critical in sustaining the temperature variability in the troposphere, it is found to play a crucial role in coupling temperature anomalies at the surface and in the free-atmosphere through anomalous surface downward longwave radiation. The variability in clouds associated with the intraseasonal SAT mode is closely linked to moisture anomalies generated by similar advective processes as for temperature anomalies. Model experiments suggest that this leading intraseasonal SAT mode can be sustained by internal atmospheric processes in the troposphere over the mid-to-high latitudes by excluding forcings from Arctic sea ice variability, tropical convective variability, and the stratospheric processes.

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How detailed do cloud microphysics need to be in climate models?

10.5194/egusphere-egu21-7115 ◽

2021 ◽

Author(s):

Ulrike Proske ◽

Sylvaine Ferrachat ◽

David Neubauer ◽

Ulrike Lohmann

Keyword(s):

Radiative Forcing ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Computing Time ◽

Cloud Microphysics ◽

Model Response ◽

Microphysical Processes ◽

Improved Accuracy

Clouds are of major importance for the climate system, but the radiative forcing resulting from their interaction with aerosols remains uncertain. To improve the representation of clouds in climate models, the parameterisations of cloud microphysical processes (CMPs) have become increasingly detailed. However, more detailed climate models do not necessarily result in improved accuracy for estimates of radiative forcing (Knutti and Sedl&#225;&#269;ek, 2013; Carslaw et al., 2018). On the contrary, simpler formulations are cheaper, sufficient for some applications, and allow for an easier understanding of the respective process' effect in the model.This study aims to gain an understanding which CMP parameterisation complexity is sufficient through simplification. We gradually phase out processes such as riming or aggregation from the global climate model ECHAM-HAM, meaning that the processes are only allowed to exhibit a fraction of their effect on the model state. The shape of the model response as a function of the artificially scaled effect of a given process helps to understand the importance of this process for the model response and its potential for simplification. For example, if partially removing a process induces only minor alterations in the present day climate, this process presents as a good candidate for simplification. This may be then further investigated, for example in terms of computing time. The resulting sensitivities to CMP complexity are envisioned to guide CMP model simplifications as well as steer research towards those processes where a more accurate representation proves to be necessary.&#160; Carslaw, Kenneth, Lindsay Lee, Leighton Regayre, and Jill Johnson (Feb. 2018). &#8220;Climate Models Are Uncertain, but We Can Do Something About It&#8221;. In: Eos 99. doi: 10.1029/2018EO093757Knutti, Reto and Jan Sedl&#225;&#269;ek (Apr. 2013). &#8220;Robustness and Uncertainties in the New CMIP5 Climate Model Projections&#8221;. In: Nature Climate Change 3.4, pp. 369&#8211;373. doi: 10.1038/nclimate1716

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The role of serial European windstorm clustering for extreme seasonal losses as determined from multi-centennial simulations of high-resolution global climate model data

Natural Hazards and Earth System Science ◽

10.5194/nhess-18-2991-2018 ◽

2018 ◽

Vol 18 (11) ◽

pp. 2991-3006 ◽

Cited By ~ 4

Author(s):

Matthew D. K. Priestley ◽

Helen F. Dacre ◽

Len C. Shaffrey ◽

Kevin I. Hodges ◽

Joaquim G. Pinto

Keyword(s):

High Resolution ◽

Return Period ◽

Large Scale ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Geographic Region ◽

Near Surface ◽

Short Period

Abstract. Extratropical cyclones are the most damaging natural hazard to affect western Europe. Serial clustering occurs when many intense cyclones affect one specific geographic region in a short period of time which can potentially lead to very large seasonal losses. Previous studies have shown that intense cyclones may be more likely to cluster than less intense cyclones. We revisit this topic using a high-resolution climate model with the aim to determine how important clustering is for windstorm-related losses. The role of windstorm clustering is investigated using a quantifiable metric (storm severity index, SSI) that is based on near-surface meteorological variables (10 m wind speed) and is a good proxy for losses. The SSI is used to convert a wind footprint into losses for individual windstorms or seasons. 918 years of a present-day ensemble of coupled climate model simulations from the High-Resolution Global Environment Model (HiGEM) are compared to ERA-Interim reanalysis. HiGEM is able to successfully reproduce the wintertime North Atlantic/European circulation, and represent the large-scale circulation associated with the serial clustering of European windstorms. We use two measures to identify any changes in the contribution of clustering to the seasonal windstorm loss as a function of return period. Above a return period of 3 years, the accumulated seasonal loss from HiGEM is up to 20 % larger than the accumulated seasonal loss from a set of random resamples of the HiGEM data. Seasonal losses are increased by 10 %–20 % relative to randomized seasonal losses at a return period of 200 years. The contribution of the single largest event in a season to the accumulated seasonal loss does not change with return period, generally ranging between 25 % and 50 %. Given the realistic dynamical representation of cyclone clustering in HiGEM, and comparable statistics to ERA-Interim, we conclude that our estimation of clustering and its dependence on the return period will be useful for informing the development of risk models for European windstorms, particularly for longer return periods.

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100 Years of Progress in Boundary Layer Meteorology

Meteorological Monographs ◽

10.1175/amsmonographs-d-18-0013.1 ◽

2019 ◽

Vol 59 ◽

pp. 9.1-9.85 ◽

Cited By ~ 13

Author(s):

Margaret A. LeMone ◽

Wayne M. Angevine ◽

Christopher S. Bretherton ◽

Fei Chen ◽

Jimy Dudhia ◽

...

Keyword(s):

Boundary Layer ◽

Boundary Layers ◽

Numerical Models ◽

Cloud Microphysics ◽

Lessons Learned ◽

The Arctic ◽

Surface Model ◽

Near Surface ◽

Boundary Layer Meteorology ◽

Weather And Climate

AbstractOver the last 100 years, boundary layer meteorology grew from the subject of mostly near-surface observations to a field encompassing diverse atmospheric boundary layers (ABLs) around the world. From the start, researchers drew from an ever-expanding set of disciplines—thermodynamics, soil and plant studies, fluid dynamics and turbulence, cloud microphysics, and aerosol studies. Research expanded upward to include the entire ABL in response to the need to know how particles and trace gases dispersed, and later how to represent the ABL in numerical models of weather and climate (starting in the 1970s–80s); taking advantage of the opportunities afforded by the development of large-eddy simulations (1970s), direct numerical simulations (1990s), and a host of instruments to sample the boundary layer in situ and remotely from the surface, the air, and space. Near-surface flux-profile relationships were developed rapidly between the 1940s and 1970s, when rapid progress shifted to the fair-weather convective boundary layer (CBL), though tropical CBL studies date back to the 1940s. In the 1980s, ABL research began to include the interaction of the ABL with the surface and clouds, the first ABL parameterization schemes emerged; and land surface and ocean surface model development blossomed. Research in subsequent decades has focused on more complex ABLs, often identified by shortcomings or uncertainties in weather and climate models, including the stable boundary layer, the Arctic boundary layer, cloudy boundary layers, and ABLs over heterogeneous surfaces (including cities). The paper closes with a brief summary, some lessons learned, and a look to the future.

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