skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report

Abstract

This is a multi-institutional, collaborative project using a three-tier modeling approach to bridge field observations and global cloud-permitting models, with emphases on cloud population structural evolution through various large-scale environments. Our contribution was in data analysis for the generation of high value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: the development of a synergistic cloud and precipitation cloud classification that identify different cloud (e.g. shallow cumulus, cirrus) and precipitation types (shallow, deep, convective, stratiform) using profiling ARM observations and the development of a quantitative precipitation rate retrieval algorithm using profiling ARM observations. Similar efforts have been developed in the past for precipitation (weather radars), but not for the millimeter-wavelength (cloud) radar deployed at the ARM sites.

Authors:
 [1]
  1. McGill Univ., Montreal, QC (Canada). Atmospheric and Oceanic Sciences Dept.
Publication Date:
Research Org.:
McGill Univ., Montreal, QC (Canada)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1343071
Report Number(s):
DOE-MCGILL-0008780
DOE Contract Number:
SC0008780
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; KAZR; ARM; rain rates; convective/stratiform; precipitation AMIE

Citation Formats

Kollias, Pavlos. Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report. United States: N. p., 2017. Web. doi:10.2172/1343071.
Kollias, Pavlos. Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report. United States. doi:10.2172/1343071.
Kollias, Pavlos. Thu . "Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report". United States. doi:10.2172/1343071. https://www.osti.gov/servlets/purl/1343071.
@article{osti_1343071,
title = {Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report},
author = {Kollias, Pavlos},
abstractNote = {This is a multi-institutional, collaborative project using a three-tier modeling approach to bridge field observations and global cloud-permitting models, with emphases on cloud population structural evolution through various large-scale environments. Our contribution was in data analysis for the generation of high value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: the development of a synergistic cloud and precipitation cloud classification that identify different cloud (e.g. shallow cumulus, cirrus) and precipitation types (shallow, deep, convective, stratiform) using profiling ARM observations and the development of a quantitative precipitation rate retrieval algorithm using profiling ARM observations. Similar efforts have been developed in the past for precipitation (weather radars), but not for the millimeter-wavelength (cloud) radar deployed at the ARM sites.},
doi = {10.2172/1343071},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Feb 09 00:00:00 EST 2017},
month = {Thu Feb 09 00:00:00 EST 2017}
}

Technical Report:

Save / Share:
  • Methods of convective/stratiform precipitation classification and surface rain rate estimation based on the Atmospheric Radiation Measurement (ARM) program cloud radar measurements were developed and evaluated. Simultaneous and collocated observations of the Ka-band ARM zenith radar (KAZR), two scanning precipitation radars (NCAR S-PolKa and Texas A&M University SMART-R), and surface precipitation during the DYNAMO/AMIE field campaign were used. The motivation of this study is to apply the unique long-term ARM cloud radar observations without accompanying precipitation radars to the study of cloud lifecycle and precipitation features under different weather and climate regimes.
  • The NCAR role in this project was to host a visiting PostDoc from the University of Miami. The NCAR PI (Jimy Dudhia) provided oversight of the PostDoc's work and mentoring and guidance as needed throughout the duration of the project. The University of Miami (the lead of this project), will provide the final technical report on the main work carried out under this proposal, which will be submitted once their no-cost extension period is completed.
  • Motivated by the success of the AMIE/DYNAMO field campaign, which collected unprecedented observations of cloud and precipitation from the tropical Indian Ocean in Octber 2011 – March 2012, this project explored how such observations can be applied to assist the development of global cloud-permitting models through evaluating and correcting model biases in cloud statistics. The main accomplishment of this project were made in four categories: generating observational products for model evaluation, using AMIE/DYNAMO observations to validate global model simulations, using AMIE/DYNAMO observations in numerical studies of cloud-permitting models, and providing leadership in the field. Results from this project provide valuablemore » information for building a seamless bridge between DOE ASR program’s component on process level understanding of cloud processes in the tropics and RGCM focus on global variability and regional extremes. In particular, experience gained from this project would be directly applicable to evaluation and improvements of ACME, especially as it transitions to a non-hydrostatic variable resolution model.« less
  • During the three years of this grant performance, the PI and her research group have made a number of significant contributions towards determining properties of tropical deep convective clouds and how models depict and respond to the heating associated with tropical convective systems. The PI has also been an active ARM/ASR science team member, including playing a significant role in AMIE and GoAmazon2014/5. She served on the DOE ASR radar science steering committee and was a joint chair of the Mesoscale Convective Organization group under the Cloud Life Cycle working group. This grant has funded a number of graduate students,more » many of them women, and the PI and her group have presented their DOE-supported work at various universities and national meetings. The PI and her group participated in the AMIE (2011-12) and GoAmazon2014/5 (2014-15) DOE field deployments that occurred in the tropical Indian Ocean and Brazilian Amazon, respectively. AMIE observational results (DePasquale et al. 2014, Feng et al. 2014, Ahmed and Schumacher 2015) focus on the variation and possible importance of Kelvin waves in various phases of the Madden-Julian Oscillation (MJO), on the synergy of the different wavelength radars deployed on Addu Atoll, and on the importance of humidity thresholds in the tropics on stratiform rain production. Much of the PIs GoAmazon2014/5 results to date relate to overviews of the observations made during the field campaign (Martin et al. 2015, 2016; Fuentes et al. 2016), but also include the introduction of the descending arm and its link to ozone transport from the mid-troposphere to the surface (Gerken et al. 2016). Vertical motion and mass flux profiles from GoAmazon (Giangrande et al. 2016) also show interesting patterns between seasons and provide targets for model simulations. Results from TWP-ICE (Schumacher et al. 2015), which took place in Darwin, Australia in 2006 show that vertical velocity retrievals from the profilers provide structure to better quantify the transition between convective, stratiform, and anvil cloud types.« less
  • Deep convection in the tropics plays an important role in driving global circulations and the transport of energy from the tropics to the mid-latitudes. Understanding the mechanisms that control tropical convection is a key to improving climate modeling simulations of the global energy balance. One of the dominant sources of tropical convective variability is the Madden-Julian Oscillation (MJO), which has a period of approximately 30–60 days. There is no agreed-upon explanation for the underlying physics that maintain the MJO. Many climate models do not show well-defined MJO signals, and those that do have problems accurately simulating the amplitude, propagation speed,more » and/or seasonality of the MJO signal. Therefore, the MJO is a very important modeling target for the ARM modeling community geared specifically toward improving climate models. The ARM MJO Investigation Experiment (AMIE) period coincides with a large international MJO initiation field campaign called CINDY2011 (Cooperative Indian Ocean experiment on intraseasonal variability in the Year 2011) that will take place in and around the Indian Ocean from October 2011 to January 2012. AMIE, in conjunction with CINDY2011 efforts, will provide an unprecedented data set that will allow investigation of the evolution of convection within the framework of the MJO. AMIE observations will also complement the long-term MJO statistics produced using ARM Manus data and will allow testing of several of the current hypotheses related to the MJO phenomenon. Taking advantage of the expected deployment of a C-POL scanning precipitation radar and an ECOR surface flux tower at the ARM Manus site, we propose to increase the number of sonde launches to eight per day starting in about mid-October of the field experiment year, which is climatologically a period of generally suppressed conditions at Manus and just prior to the climatologically strongest MJO period. The field experiment will last until the end of the MJO season (typically March), affording the documentation of conditions before, during, and after the peak MJO season. The increased frequency of sonde launches throughout the experimental period will provide better diurnal understanding of the thermodynamic profiles, and thus a better representation within the variational analysis data set. Finally, a small surface radiation and ceilometer system will be deployed at the PNG Lombrum Naval Base about 6 km away from the ARM Manus site in order to provide some documentation of scale variability with respect to the representativeness of the ARM measurements.« less