scholarly journals The Ocean–Land–Atmosphere Model: Optimization and Evaluation of Simulated Radiative Fluxes and Precipitation

2010 ◽  
Vol 138 (5) ◽  
pp. 1923-1939 ◽  
Author(s):  
David Medvigy ◽  
Robert L. Walko ◽  
Martin J. Otte ◽  
Roni Avissar
Keyword(s):  
Large Scale ◽  
Likelihood Function ◽  
Droplet Diameter ◽  
Radiant Energy ◽  
Diameter Distribution ◽  
Precipitation Pattern ◽  
Parameter Uncertainties ◽  
Radiative Fluxes ◽  
Atmosphere Model ◽  
The Impact

Abstract This work continues the presentation and evaluation of the Ocean–Land–Atmosphere Model (OLAM), focusing on the model’s ability to represent radiation and precipitation. OLAM is a new, state-of-the-art earth system model, capable of user-specified grid resolution and local mesh refinement. An objective optimization of the microphysics parameterization is carried out. Data products from the Clouds and the Earth’s Radiant Energy System (CERES) and the Global Precipitation Climatology Project (GPCP) are used to construct a maximum likelihood function, and thousands of simulations using different values for key parameters are carried out. Shortwave fluxes are found to be highly sensitive to both the density of cloud droplets and the assumed shape of the cloud droplet diameter distribution function. Because there is considerable uncertainty in which values for these parameters to use in climate models, they are targeted as the tunable parameters of the objective optimization procedure, which identified high-likelihood volumes of parameter space as well as parameter uncertainties and covariances. Once optimized, the model closely matches observed large-scale radiative fluxes and precipitation. The impact of model resolution is also tested. At finer characteristic length scales (CLS), smaller-scale features such as the ITCZ are better resolved. It is also found that the Amazon was much better simulated at 100- than 200-km CLS. Furthermore, a simulation using OLAM’s variable resolution functionality to cover South America with 100-km CLS and the rest of the world with 200-km CLS generates a precipitation pattern in the Amazon similar to the global 100-km CLS run.

A Stochastic Parameter Perturbation Method to Represent Uncertainty in a Microphysics Scheme

2021 ◽  
Author(s):  
Gregory Thompson ◽  
Judith Berner ◽  
Maria Frediani ◽  
Jason A. Otkin ◽  
Sarah M. Griffin
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Random Perturbation ◽  
Longwave Radiation ◽  
Parameter Uncertainties ◽  
Microphysics Scheme ◽  
Convective Systems ◽  
Temporal Correlations ◽  
Precipitation Characteristics ◽  
The Impact

AbstractCurrent state-of-the art regional numerical weather forecasts are run at horizontal grid spacings of a few kilometers, which permits medium to large-scale convective systems to be represented explicitly in the model. With the convection parameterization no longer active, much uncertainty in the formulation of subgrid-scale processes moves to other areas such as the cloud microphysical, turbulence, and land-surface parameterizations. The goal of this study is to investigate experiments with stochastically-perturbed parameters (SPP) within a microphysics parameterization and the model’s horizontal diffusion coefficients. To estimate the “true” uncertainty due to parameter uncertainty, the magnitudes of the perturbations are chosen as realistic as possible and not with purposeful intent of maximal forecast impact as some prior work has done. Spatial inhomogeneities and temporal persistence are represented using a random perturbation pattern with spatial and temporal correlations. The impact on the distributions of various hydrometeors, precipitation characteristics, and solar/longwave radiation are quantified for a winter and summer case. In terms of upscale error growth, the impact is relatively small and consists primarily of triggering atmospheric instabilities in convectively unstable regions. In addition, small in situ changes with potentially large socio-economic impacts are observed in the precipitation characteristics such as maximum hail size. Albeit the impact of introducing physically-based parameter uncertainties within the bounds of aerosol uncertainties is small, their influence on the solar and longwave radiation balances may still have important implications for global model simulations of future climate scenarios.

scholarly journals Is Diminishing Solar Activity Detrimental to Canadian Prairie Agriculture?

2020 ◽  
Vol 3 (3) ◽  
Keyword(s):  
Solar Activity ◽  
Large Scale ◽  
Time Frame ◽  
Precipitation Pattern ◽  
Canadian Prairie ◽  
Canadian Prairies ◽  
Temperature And Precipitation ◽  
Mean Temperature ◽  
Grain Yield And Quality ◽  
The Impact

During the grain growing months of May-July, the mean temperature on the Canadian prairies has cooled down by 2ºC in the last 30 years. The cooling appears to be most certainly linked to diminishing solar activity as the Sun approaches a Grand Solar Minimum in the next decade or so. This cooling has led to a reduction in Growing Degree Days (GDDs) and has also impacted the precipitation pattern. The GDDs in conjunction with mean temperature and precipitation are important parameters for the growth of various grains (wheat, barley, canola etc.) on the prairies. In this study, we investigate the impact of declining GDDs and associated temperature and precipitation patterns on Prairie grain yields and quality. Our analysis shows that there has been a loss of about 100 GDDs over the time frame of 1985-2019. The loss in GDDs is also linked to some of the large-scale Atmosphere-Ocean parameters like the Pacific Decadal Oscillation (PDO), North Pacific Index (NPI) and Arctic Oscillation (AO). Our analysis suggests grain yield and quality could be significantly impacted in the coming years as solar activity continues to diminish.

scholarly journals A sensitivity study of radiative fluxes at the top of atmosphere to cloud-microphysics and aerosol parameters in the community atmosphere model CAM5

2013 ◽  
Vol 13 (21) ◽  
pp. 10969-10987 ◽  
Author(s):  
C. Zhao ◽  
X. Liu ◽  
Y. Qian ◽  
J. Yoon ◽  
Z. Hou ◽  
...  
Keyword(s):  
Regional Scale ◽  
Cloud Microphysics ◽  
Model Parameters ◽  
Parameter Uncertainties ◽  
Dimensional Parameter ◽  
Individual Parameter ◽  
Radiative Fluxes ◽  
Community Atmosphere Model ◽  
Atmosphere Model ◽  
Global Mean

Abstract. In this study, we investigated the sensitivity of net radiative fluxes (FNET) at the top of atmosphere (TOA) to 16 selected uncertain parameters mainly related to the cloud microphysics and aerosol schemes in the Community Atmosphere Model version 5 (CAM5). We adopted a quasi-Monte Carlo (QMC) sampling approach to effectively explore the high-dimensional parameter space. The output response variables (e.g., FNET) are simulated using CAM5 for each parameter set, and then evaluated using the generalized linear model analysis. In response to the perturbations of these 16 parameters, the CAM5-simulated global annual mean FNET ranges from −9.8 to 3.5 W m−2 compared to 1.9 W m−2 with the default parameter values. Variance-based sensitivity analysis is conducted to show the relative contributions of individual parameter perturbations to the global FNET variance. The results indicate that the changes in the global mean FNET are dominated by changes in net cloud forcing (CF) within the parameter ranges being investigated. The threshold size parameter related to auto-conversion of cloud ice to snow is identified as one of the most influential parameters for FNET in CAM5 simulations. The strong heterogeneous geographic distribution of FNET variance shows that parameters have a clear localized effect over regions where they are acting. However, some parameters also have non-local impacts on FNET variance. Although external factors, such as perturbations of anthropogenic and natural emissions, largely affect FNET variance at the regional scale, their impact is weaker than that of model internal parameters in terms of simulating global mean FNET. The interactions among the 16 selected parameters contribute a relatively small portion to the total FNET variance over most regions of the globe. This study helps us better understand the parameter uncertainties in the CAM5 model, and thus provides information for further calibrating uncertain model parameters with the largest sensitivity.

scholarly journals A sensitivity study of radiative fluxes at the top of atmosphere to cloud-microphysics and aerosol parameters in the Community Atmosphere Model CAM5

2013 ◽  
Vol 13 (5) ◽  
pp. 12135-12176 ◽  
Author(s):  
C. Zhao ◽  
X. Liu ◽  
Y. Qian ◽  
J. Yoon ◽  
Z. Hou ◽  
...  
Keyword(s):  
Regional Scale ◽  
Cloud Microphysics ◽  
Model Parameters ◽  
Parameter Uncertainties ◽  
Dimensional Parameter ◽  
Individual Parameter ◽  
Radiative Fluxes ◽  
Community Atmosphere Model ◽  
Atmosphere Model ◽  
Global Mean

Abstract. In this study, we investigated the sensitivity of net radiative fluxes (FNET) at the top of atmosphere (TOA) to 16 selected uncertain parameters mainly related to the cloud microphysics and aerosol schemes in the Community Atmosphere Model version 5 (CAM5). We adopted a quasi-Monte Carlo (QMC) sampling approach to effectively explore the high dimensional parameter space. The output response variables (e.g., FNET) were simulated using CAM5 for each parameter set, and then evaluated using the generalized linear model analysis. In response to the perturbations of these 16 parameters, the CAM5-simulated global annual mean FNET ranges from −9.8 to 3.5 W m−2 compared to the CAM5-simulated FNET of 1.9 W m−2 with the default parameter values. Variance-based sensitivity analysis was conducted to show the relative contributions of individual parameter perturbation to the global FNET variance. The results indicate that the changes in the global mean FNET are dominated by those of net cloud forcing (CF) within the parameter ranges being investigated. The threshold size parameter related to auto-conversion of cloud ice to snow is identified as one of the most influential parameters for FNET in CAM5 simulations. The strong heterogeneous geographic distribution of FNET variance shows parameters have a clear localized effect over regions where they are acting. However, some parameters also have non-local impacts on FNET variance. Although external factors, such as perturbations of anthropogenic and natural emissions, largely affect FNET variance at the regional scale, their impact is weaker than that of model internal parameters in terms of simulating global mean FNET. The interactions among the 16 selected parameters contribute a relatively small portion to the total FNET variance over most regions of the globe. This study helps us better understand the parameter uncertainties in the CAM5 model, and thus provides information for further calibrating uncertain model parameters with the largest sensitivity.

scholarly journals Evaluation of Microphysics Parameterization for Convective Clouds in the NCAR Community Atmosphere Model CAM5

2012 ◽  
Vol 25 (24) ◽  
pp. 8568-8590 ◽  
Author(s):  
Xiaoliang Song ◽  
Guang J. Zhang ◽  
J.-L. F. Li
Keyword(s):  
Large Scale ◽  
Convective Cloud ◽  
Number Concentration ◽  
Liquid Water Path ◽  
Microphysics Scheme ◽  
Convective Clouds ◽  
Community Atmosphere Model ◽  
Atmosphere Model ◽  
Subtropical Oceans ◽  
The Impact

Abstract A physically based two-moment microphysics parameterization scheme for convective clouds is implemented in the NCAR Community Atmosphere Model version 5 (CAM5) to improve the representation of convective clouds and their interaction with large-scale clouds and aerosols. The explicit treatment of mass mixing ratio and number concentration of cloud and precipitation particles enables the scheme to account for the impact of aerosols on convection. The scheme is linked to aerosols through cloud droplet activation and ice nucleation processes and to stratiform cloud parameterization through convective detrainment of cloud liquid/ice water content (LWC/IWC) and droplet/crystal number concentration (DNC/CNC). A 5-yr simulation with the new convective microphysics scheme shows that both cloud LWC/IWC and DNC/CNC are in good agreement with observations, indicating the scheme describes microphysical processes in convection well. Moreover, the microphysics scheme is able to represent the aerosol effects on convective clouds such as the suppression of warm rain formation and enhancement of freezing when aerosol loading is increased. With more realistic simulations of convective cloud microphysical properties and their detrainment, the mid- and low-level cloud fraction is increased significantly over the ITCZ–southern Pacific convergence zone (SPCZ) and subtropical oceans, making it much closer to the observations. Correspondingly, the serious negative bias in cloud liquid water path over subtropical oceans observed in the standard CAM5 is reduced markedly. The large-scale precipitation is increased and precipitation distribution is improved as well. The long-standing precipitation bias in the western Pacific is significantly alleviated because of microphysics–thermodynamics feedbacks.

scholarly journals Two MODIS Aerosol Products over Ocean on the Terra and Aqua CERES SSF Datasets

2005 ◽  
Vol 62 (4) ◽  
pp. 1008-1031 ◽  
Author(s):  
Alexander Ignatov ◽  
Patrick Minnis ◽  
Norman Loeb ◽  
Bruce Wielicki ◽  
Walter Miller ◽  
...  
Keyword(s):  
Single Channel ◽  
Radiant Energy ◽  
Cloud Amount ◽  
Energy System ◽  
Poor Quality ◽  
Radiation Budget ◽  
Quality Data ◽  
Radiative Fluxes ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact

Abstract Understanding the impact of aerosols on the earth’s radiation budget and the long-term climate record requires consistent measurements of aerosol properties and radiative fluxes. The Clouds and the Earth’s Radiant Energy System (CERES) Science Team combines satellite-based retrievals of aerosols, clouds, and radiative fluxes into Single Scanner Footprint (SSF) datasets from the Terra and Aqua satellites. Over ocean, two aerosol products are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) using different sampling and aerosol algorithms. The primary, or M, product is taken from the standard multispectral aerosol product developed by the MODIS aerosol group while a simpler, secondary [Advanced Very High Resolution Radiometer (AVHRR) like], or A, product is derived by the CERES Science Team using a different cloud clearing method and a single-channel aerosol algorithm. Two aerosol optical depths (AOD), τA1 and τA2, are derived from MODIS bands 1 (0.644 μm) and 6 (1.632 μm) resembling the AVHRR/3 channels 1 and 3A, respectively. On Aqua the retrievals are made in band 7 (2.119 μm) because of poor quality data from band 6. The respective Ångström exponents can be derived from the values of τ. The A product serves as a backup for the M product. More importantly, the overlap of these aerosol products is essential for placing the 20+ year heritage AVHRR aerosol record in the context of more advanced aerosol sensors and algorithms such as that used for the M product. This study documents the M and A products, highlighting their CERES SSF specifics. Based on 2 weeks of global Terra data, coincident M and A AODs are found to be strongly correlated in both bands. However, both domains in which the M and A aerosols are available, and the respective τ/α statistics significantly differ because of discrepancies in sampling due to differences in cloud and sun-glint screening. In both aerosol products, correlation is observed between the retrieved aerosol parameters (τ/α) and ambient cloud amount, with the dependence in the M product being more pronounced than in the A product.

scholarly journals Impact of 4D-Var data assimilation on performance of the coupled land-atmosphere model WRF-TOPX: A case study of flood event in the Wangjiaba watershed, China

2021 ◽  
Author(s):  
Lu Yi ◽  
Bin Yong ◽  
Junxu Chen ◽  
Ziyan Zheng ◽  
Ling Li
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Large Scale ◽  
Eastern China ◽  
Wrf Model ◽  
Coupled Model ◽  
Flood Event ◽  
Potential Evaporation ◽  
Atmosphere Model ◽  
The Impact

AbstractTo assess the impact of four-dimensional variational (4D-Var) data assimilation on the performance of land-atmosphere coupled model, the satellite precipitation of the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM IMERG) was assimilated into the Weather Research Forecast (WRF) model, and the WRF was coupled to the hydrological model TOPX. Precipitation and evaporation were both investigated as connecting element in the coupled model WRF-TOPX. Different in whether applied the 4D-Var data assimilation and evaporation, one control experiment and four experiments were performed to simulate a historical flood event happened in the Wangjiaba watershed in eastern China. The key hydrological variables of precipitation, potential evaporation, soil moisture and discharge in the studied flood process were evaluated. The results showed that 1) the 4D-Var data assimilation with the GPM IMERG could reduce both the overestimations of the WRF-predicted precipitation and potential evaporation; 2) the applied 4D-Var data assimilation could improve considerably the accuracy of the soil moisture and discharges from the coupled model WRF-TOPX; 3) evaporation was also an important factor to influence the net precipitation to affect the performance of the coupled land-atmosphere model. With the two connecting elements of precipitation and evaporation, the 4D-Var assimilation based on the GPM IMERG could improve the Nash coefficient of the coupled model WRF-TOPX from 0.483 to 0.521 at hourly scale. These investigations can provide important implications for the land-atmosphere coupling with both the precipitation and evaporation and using the 4D-Var data assimilation with the GPM IMERG for flood simulation at large scale.

Impact of COVID-19 on Nuclear Medicine in Germany, Austria and Switzerland: An International Survey in April 2020

2020 ◽  
Vol 59 (04) ◽  
pp. 294-299 ◽  
Author(s):  
Lutz S. Freudenberg ◽  
Ulf Dittmer ◽  
Ken Herrmann
Keyword(s):  
Nuclear Medicine ◽  
Health Systems ◽  
Personal Protective Equipment ◽  
Large Scale ◽  
Diagnostic Procedures ◽  
Protective Equipment ◽  
Current Crisis ◽  
Web Based ◽  
Public Versus Private ◽  
The Impact

Abstract Introduction Preparations of health systems to accommodate large number of severely ill COVID-19 patients in March/April 2020 has a significant impact on nuclear medicine departments. Materials and Methods A web-based questionnaire was designed to differentiate the impact of the pandemic on inpatient and outpatient nuclear medicine operations and on public versus private health systems, respectively. Questions were addressing the following issues: impact on nuclear medicine diagnostics and therapy, use of recommendations, personal protective equipment, and organizational adaptations. The survey was available for 6 days and closed on April 20, 2020. Results 113 complete responses were recorded. Nearly all participants (97 %) report a decline of nuclear medicine diagnostic procedures. The mean reduction in the last three weeks for PET/CT, scintigraphies of bone, myocardium, lung thyroid, sentinel lymph-node are –14.4 %, –47.2 %, –47.5 %, –40.7 %, –58.4 %, and –25.2 % respectively. Furthermore, 76 % of the participants report a reduction in therapies especially for benign thyroid disease (-41.8 %) and radiosynoviorthesis (–53.8 %) while tumor therapies remained mainly stable. 48 % of the participants report a shortage of personal protective equipment. Conclusions Nuclear medicine services are notably reduced 3 weeks after the SARS-CoV-2 pandemic reached Germany, Austria and Switzerland on a large scale. We must be aware that the current crisis will also have a significant economic impact on the healthcare system. As the survey cannot adapt to daily dynamic changes in priorities, it serves as a first snapshot requiring follow-up studies and comparisons with other countries and regions.

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