scholarly journals Evolution of Precipitation Structure During the November DYNAMO MJO Event: Cloud‐Resolving Model Intercomparison and Cross Validation Using Radar Observations

2018 ◽  
Vol 123 (7) ◽  
pp. 3530-3555 ◽  
Author(s):  
Xiaowen Li ◽  
Matthew A. Janiga ◽  
Shuguang Wang ◽  
Wei‐Kuo Tao ◽  
Angela Rowe ◽  
...  
Keyword(s):  
Cross Validation ◽  
Model Intercomparison ◽  
Radar Observations ◽  
Cloud Resolving Model ◽  
Precipitation Structure

scholarly journals Cloud‐resolving model intercomparison of an MC3E squall line case: Part I—Convective updrafts

2017 ◽  
Vol 122 (17) ◽  
pp. 9351-9378 ◽  
Author(s):  
Jiwen Fan ◽  
Bin Han ◽  
Adam Varble ◽  
Hugh Morrison ◽  
Kirk North ◽  
...  
Keyword(s):  
Squall Line ◽  
Model Intercomparison ◽  
Cloud Resolving Model ◽  
Case Part

scholarly journals Cloud‐Resolving Model Intercomparison of an MC3E Squall Line Case: Part II. Stratiform Precipitation Properties

2019 ◽  
Vol 124 (2) ◽  
pp. 1090-1117 ◽  
Author(s):  
Bin Han ◽  
Jiwen Fan ◽  
Adam Varble ◽  
Hugh Morrison ◽  
Christopher R. Williams ◽  
...  
Keyword(s):  
Squall Line ◽  
Model Intercomparison ◽  
Stratiform Precipitation ◽  
Cloud Resolving Model ◽  
Case Part

Comparing the Convective Structure and Microphysics in Two Sahelian Mesoscale Convective Systems: Radar Observations and CRM Simulations

2013 ◽  
Vol 141 (2) ◽  
pp. 582-601 ◽  
Author(s):  
Nick Guy ◽  
Xiping Zeng ◽  
Steven A. Rutledge ◽  
Wei-Kuo Tao
Keyword(s):  
Three Dimensional ◽  
Mesoscale Convective Systems ◽  
Modeling Framework ◽  
Microphysics Scheme ◽  
Radar Observations ◽  
Convective Systems ◽  
Convective Structure ◽  
High Reflectivity ◽  
Mesoscale Convective ◽  
Cloud Resolving Model

Abstract Two mesoscale convective systems (MCSs) observed during the African Monsoon Multidisciplinary Analyses (AMMA) experiment are simulated using the three-dimensional (3D) Goddard Cumulus Ensemble model. This study was undertaken to determine the performance of the cloud-resolving model in representing distinct convective and microphysical differences between the two MCSs over a tropical continental location. Simulations are performed using 1-km horizontal grid spacing, a lower limit on current embedded cloud-resolving models within a global multiscale modeling framework. Simulated system convective structure and microphysics are compared to radar observations using contoured frequency-by-altitude diagrams (CFADs), calculated ice and water mass, and identified hydrometeor variables. Vertical distributions of ice hydrometeors indicate underestimation at the mid- and upper levels, partially due to the inability of the model to produce adequate system heights. The abundance of high-reflectivity values below and near the melting level in the simulation led to a broadening of the CFAD distributions. Observed vertical reflectivity profiles show that high reflectivity is present at greater heights than the simulations produced, thought to be a result of using a single-moment microphysics scheme. Relative trends in the population of simulated hydrometeors are in agreement with observations, though a secondary convective burst is not well represented. Despite these biases, the radar-observed differences between the two cases are noticeable in the simulations as well, suggesting that the model has some skill in capturing observed differences between the two MCSs.

scholarly journals Observations of the altitude of the volcanic plume during the eruption of Eyjafjallajökull, April–May 2010

2011 ◽  
Vol 4 (1) ◽  
pp. 1-25 ◽  
Author(s):  
P. Arason ◽  
G. N. Petersen ◽  
H. Bjornsson
Keyword(s):  
Time Series ◽  
Cross Validation ◽  
Weather Radar ◽  
Volcanic Plume ◽  
Explosive Activity ◽  
Radar Observations ◽  
International Airport ◽  
Web Camera ◽  
The Village

Abstract. The eruption of Eyjafjallajökull volcano in 2010 lasted for 39 days, 14 April–23 May. The eruption had two explosive phases separated by a phase with lava formation and reduced explosive activity. The height of the plume was monitored every 5 min with a C-band weather radar located in Keflavík International Airport, 155 km distance from the volcano. Furthermore, several web cameras were mounted with a view of the volcano, and their images saved every five seconds. Time series of the plume-top altitude were constructed from the radar observations and images from a web camera located in the village Hvolsvöllur at 34 km distance from the volcano. This paper presents the independent radar and web camera time series and performs cross validation. The echo top radar series of the altitude of the volcanic plume are publicly available from the Pangaea Publishing Network (http://doi.pangaea.de/10.1594/PANGAEA.760690).

scholarly journals Evaluation of cloud-resolving model intercomparison simulations using TWP-ICE observations: Precipitation and cloud structure

2011 ◽  
Vol 116 (D12) ◽  
Author(s):  
Adam Varble ◽  
Ann M. Fridlind ◽  
Edward J. Zipser ◽  
Andrew S. Ackerman ◽  
Jean-Pierre Chaboureau ◽  
...  
Keyword(s):  
Model Intercomparison ◽  
Cloud Structure ◽  
Cloud Resolving Model

scholarly journals Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0)

2019 ◽  
Author(s):  
Stefan Lange
Keyword(s):  
Statistical Downscaling ◽  
Cross Validation ◽  
Extreme Values ◽  
Interpolation Method ◽  
Impact Model ◽  
Model Intercomparison ◽  
Bias Adjustment ◽  
New Methods ◽  
Validation Framework ◽  
Intercomparison Project

Abstract. In this paper I present new methods for bias adjustment and statistical downscaling that are tailored to the requirements of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). In comparison to their predecessors, the new methods allow for a more robust bias adjustment of extreme values, preserve trends more accurately across quantiles, and facilitate a clearer separation of bias adjustment and statistical downscaling. The new statistical downscaling method is stochastic and better at adjusting spatial variability than the old interpolation method. Improvements in bias adjustment and trend preservation are demonstrated in a cross-validation framework.

scholarly journals Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0)

2019 ◽  
Vol 12 (7) ◽  
pp. 3055-3070 ◽  
Author(s):  
Stefan Lange
Keyword(s):  
Statistical Downscaling ◽  
Cross Validation ◽  
Extreme Values ◽  
Interpolation Method ◽  
Impact Model ◽  
Model Intercomparison ◽  
Bias Adjustment ◽  
New Methods ◽  
Validation Framework ◽  
Intercomparison Project

Abstract. In this paper I present new methods for bias adjustment and statistical downscaling that are tailored to the requirements of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). In comparison to their predecessors, the new methods allow for a more robust bias adjustment of extreme values, preserve trends more accurately across quantiles, and facilitate a clearer separation of bias adjustment and statistical downscaling. The new statistical downscaling method is stochastic and better at adjusting spatial variability than the old interpolation method. Improvements in bias adjustment and trend preservation are demonstrated in a cross-validation framework.

Correction to “Evaluation of cloud-resolving model intercomparison simulations using TWP-ICE observations: Precipitation and cloud structure”

2012 ◽  
Vol 117 (D16) ◽  
pp. n/a-n/a
Author(s):  
Adam Varble ◽  
Ann M. Fridlind ◽  
Edward J. Zipser ◽  
Andrew S. Ackerman ◽  
Jean-Pierre Chaboureau ◽  
...  
Keyword(s):  
Model Intercomparison ◽  
Cloud Structure ◽  
Cloud Resolving Model
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