AMIE (ACRF MJO Investigation Experiment): Observations of the Madden Julian Oscillation for Modeling Studies
1 October 2011 - 31 March 2012
Lead Scientist: Chuck Long
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, 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 coincided with a large international MJO initiation field campaign called CINDY2011 (Cooperative Indian Ocean experiment on intraseasonal variability in the Year 2011) that took place in and around the Indian Ocean from October 2011 to January 2012. AMIE, in conjunction with CINDY2011 efforts, provided an unprecedented data set that allowed investigation of the evolution of convection within the framework of the MJO. AMIE observations also complemented the long-term MJO statistics produced using ARM Manus data and allowed 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 Manus ARM site, we proposed to increase the number of sonde launches to 8/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 lasted 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 provided better diurnal understanding of the thermodynamic profiles, and thus a better representation within the variational analysis dataset. Finally, a small surface radiation and ceilometer system was deployed at the PNG Lombrum Naval Base about 6 km away from the Manus ARM site in order to provide some documentation of scale variability with respect to the representativeness of the ARM measurements.
Ciesielski P, R Johnson, X Jiang, Y Zhang, and S Xie. 2017. "Relationships between radiation, clouds, and convection during DYNAMO." Journal of Geophysical Research: Atmospheres, 122(5), 10.1002/2016JD025965.
Wang H, W Su, N Loeb, D Achuthavarier, and S Schubert. 2017. "The role of DYNAMO in situ observations in improving NASA CERES-like daily surface and atmospheric radiative flux estimates." Earth and Space Science, , 10.1002/2016EA000248.
Qian Y, H Yan, LK Berg, S Hagos, Z Feng, B Yang, and M Huang. 2016. "Assessing Impacts of PBL and Surface Layer Schemes in Simulating the Surface–Atmosphere Interactions and Precipitation over the Tropical Ocean Using Observations from AMIE/DYNAMO." Journal of Climate, 29(22), 10.1175/jcli-d-16-0040.1.
Ahmed F, C Schumacher, Z Feng, and S Hagos. 2016. "A Retrieval of Tropical Latent Heating Using the 3D Structure of Precipitation Features." Journal of Applied Meteorology and Climatology, 55(9), 10.1175/jamc-d-15-0038.1.
Long CN. 2016. Atmospheric Radiation Measurement Madden-Julian Oscillation Investigation Experiment Field Campaign Report. Ed. by Robert Stafford, DOE ARM Climate Research Facility. DOE/SC-ARM-16-039.
Janiga MA and C Zhang. 2016. "MJO Moisture Budget during DYNAMO in a Cloud-Resolving Model." Journal of the Atmospheric Sciences, 73(6), 10.1175/jas-d-14-0379.1.
Brogniez H, S English, J Mahfouf, A Behrendt, W Berg, S Boukabara, S Buehler, P Chambon, A Gambacorta, A Geer, W Ingram, E Kursinski, M Matricardi, T Odintsova, V Payne, P Thorne, M Tretyakov, and J Wang. 2016. "A review of sources of systematic errors and uncertainties in observations and simulations at 183 GHz." Atmospheric Measurement Techniques, 9(5), 10.5194/amt-9-2207-2016.
Hannah WM, BE Mapes, and GS Elsaesser. 2016. "A Lagrangian View of Moisture Dynamics during DYNAMO." Journal of the Atmospheric Sciences, 73(5), 10.1175/jas-d-15-0243.1.
Brogniez H, R Fallourd, C Mallet, R Sivira, and C Dufour. 2016. "Estimating Confidence Intervals around Relative Humidity Profiles from Satellite Observations: Application to the SAPHIR Sounder." Journal of Atmospheric and Oceanic Technology, 33(5), 10.1175/JTECH-D-15-0237.1.
Hagos SM, Z Feng, CD Burleyson, C Zhao, MN Martini, and LK Berg. 2016. "Moist Process Biases in Simulations of the Madden–Julian Oscillation Episodes Observed during the AMIE/DYNAMO Field Campaign." Journal of Climate, 29(3), 10.1175/jcli-d-15-0349.1.
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