National Weather Service United States Department of Commerce

Office of Science and Technology Integration

National Program

44th NOAA Annual Climate Diagnostic and Prediction Workshop

Weather.gov > Office of Science and Technology Integration > 44th NOAA Annual Climate Diagnostic and Prediction Workshop

Poster Session Presentations

October 22 - 23, 2019

(Click the image to enlarge the poster.)

 

I. Diagnostics and Attribution

Role of the subtropical North Atlantic water cycle in recent U.S. extreme precipitation events

Role of the subtropical North Atlantic water cycle in recent U.S. extreme precipitation events

by Laifang Li, Raymond W. Schmitt, Caroline C. Ummenhofer , Duke University, Durham, NC; Woods Hole Oceanographic Institution, Woods Hole, MA

 MJO propagation and its influence on temperature and precipitation over the US

MJO propagation and its influence on temperature and precipitation over the US

by Kirstin J. Harnos, Wanqiu Wang, NOAA Climate Prediction Center; Innovim LLC

 An analysis on dependence of seasonal predictability of ENSO SSTs in Copernicus Climate Change Service (C3S) Hincast

An analysis on dependence of seasonal predictability of ENSO SSTs in Copernicus Climate Change Service (C3S) Hincast

by Bhaskar Jha, Arun Kumar, NOAA Climate Prediction Center; Innovim LLC

 The role of sea surface temperatures in pervasive Northern-Hemisphere heatwave conditions during summer 2018

The role of sea surface temperatures in pervasive Northern-Hemisphere heatwave conditions during summer 2018

by Shunya Wakamatsu, Kazuto Takemura, Akihiko Shimpo, Hiroki Togawa, Yutaro Kubo, Yuhei Takaya, Chiaki Kobayashi, and Shuhei Maeda,

 Why is the East Asian summer monsoon extremely strong in 2018? — Collaborative effects of SST and snow cover anomalies

Why is the East Asian summer monsoon extremely strong in 2018? — Collaborative effects of SST and snow cover anomalies

by Lijuan Chen, Wei Gu, Weijing Li, Beijing Climate Center, China Meteorological Administration
Climate diagnostics of the extreme floods in Peru during early 2017

Climate diagnostics of the extreme floods in Peru during early 2017

by Rackhun Son, S.-Y. Simon Wang, Wan-Ling Tseng, Christian W. Barreto Schuler, Emily Becker, Jin-Ho Yoon

 The dominant modes of precipitation over Eastern China during the rainy season of Yangtze River Valley and the possible mechanisms

The dominant modes of precipitation over Eastern China during the rainy season of Yangtze River Valley and the possible mechanisms

by Qingyun Zhang, Heng Guo, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

 A link between ocean eddies and enhanced subseasonal forecast skill over subtropical western North Pacific

A link between ocean eddies and enhanced subseasonal forecast skill over subtropical western North Pacific

by Chueh–Hsin Chang, Bo Qiu, Nathaniel C. Johnson, Hsiao– Ching Huang, Changhyun Yoo

 Attribution of extreme streamflow changes over headwater of the Yellow River basin in China: Impacts of anthropogenic climate change, land cover change and reservoir operation

Attribution of extreme streamflow changes over headwater of the Yellow River basin in China: Impacts of anthropogenic climate change, land cover change and reservoir operation
 

II.   Simulation and Prediction

Verification of the Global Tropics Hazards Outlook using the CPC Unified Precipitation DatasetVerification of the Global Tropics Hazards Outlook using the CPC Unified Precipitation Dataset
WRF simulations of a flood– producing heavy rainstorm in current and future environmentsWRF simulations of a flood– producing heavy rainstorm in current and future environments
Skillful all-season S2S prediction of U.S. precipitation using the MJO and QBOSkillful all-season S2S prediction of U.S. precipitation using the MJO and QBO
 Future changes in extreme heat waves in high-resolution time-slice simulations

Future changes in extreme heat waves in high-resolution time-slice simulations

 

 Assessment of CPC Global Daily Surface Air Temperature (CPC-T2m) Analysis

Assessment of CPC Global Daily Surface Air Temperature (CPC-T2m) Analysis
Simulations of tropical impacts on North American seasonal precipitation

Simulations of tropical impacts on North American seasonal precipitation

 The benefits of using high-resolution sea surface temperatures for simulating historical and future climate extremes

The benefits of using high-resolution sea surface temperatures for simulating historical and future climate extremes

 Benchmark decadal forecast skill for terrestrial water storage

Benchmark decadal forecast skill for terrestrial water storage

 Enabling numerical seasonal forecasts for high resolution modeling of Blue Nile River Basin

Enabling numerical seasonal forecasts for high resolution modeling of Blue Nile River Basin

 Extending the prediction of extremes to seasonal forecasts

Extending the prediction of extremes to seasonal forecasts
Consistent sub-monthly and monthly forecast by combining GEFS and CFS data

Consistent sub-monthly and monthly forecast by combining GEFS and CFS data

 A comparison of seasonal hurricane forecasts: Dynamical model versus dynamical–statistical model

A comparison of seasonal hurricane forecasts: Dynamical model versus dynamical–statistical model

 A comparison of CCSM4 high-resolution and low-resolution predictions for south Florida and southeast United States drought

A comparison of CCSM4 high-resolution and low-resolution predictions for south Florida and southeast United States drought

 MJO forecast verification and diagnostics for CWB S2S models

MJO forecast verification and diagnostics for CWB S2S models

 Modeling the impact of expanding irrigated agriculture on future climate projections in an arid environment

Modeling the impact of expanding irrigated agriculture on future climate projections in an arid environment

III.  Forecast Models and Tools

The beginning of a deep learning approach to predicting ENSO at CPC by Kyle MacRitchie, Stephen Baxter, Allen Mewhinney, NOAA Climate Prediction Center; Penn State University

The beginning of a deep learning approach to predicting ENSO at CPC

by Kyle MacRitchie, Stephen Baxter, Allen Mewhinney, NOAA Climate Prediction Center; Penn State University
Development of an objective confidence metric for CPC's extended range forecast by Daniel S. Harnos, Stephen Baxter, Jon Gottschalck, Scott Handel, Matthew Rosencrans, NOAA Climate Prediction Center

Development of an objective confidence metric for CPC's extended range forecast

by Daniel S. Harnos, Stephen Baxter, Jon Gottschalck, Scott Handel, Matthew Rosencrans, NOAA Climate Prediction Center
Overview of the CPC Sea Ice initialization System (CSIS) and its use in experimental sea ice forecasting at the NOAA Climate Prediction Center by Thomas Collow, Yanyun Liu, Wanqiu Wang, Arun Kumar, NOAA Climate Prediction Center; Innovim LLC

Overview of the CPC Sea Ice initialization System (CSIS) and its use in experimental sea ice forecasting at the NOAA Climate Prediction Center

by Thomas Collow, Yanyun Liu, Wanqiu Wang, Arun Kumar, NOAA Climate Prediction Center; Innovim LLC
A preliminary study for deep learning based drought forecast by Li Xu, Kingtse Mo NOAA Climate Prediction Center; Innovim LLC

A preliminary study for deep learning based drought forecast

by Li Xu, Kingtse Mo NOAA Climate Prediction Center; Innovim LLC
Improving ENSO forecasts using Bayesian Model Averaging (BMA) by Pao-Shin Chu, Luke He, Hanpei Zhang, David Unger, University of Hawaii; NOAA Climate Prediction Center

Improving ENSO forecasts using Bayesian Model Averaging (BMA)

by Pao-Shin Chu, Luke He, Hanpei Zhang, David Unger, University of Hawaii; NOAA Climate Prediction Center
Cluster analysis resolution of diurnal wind pattern modes utilizing K-Means - A case-study with Raleigh, N.C. Data (1946-2019)Cluster analysis resolution of diurnal wind pattern modes utilizing K-Means - A case-study with Raleigh, N.C. Data (1946-2019)
Promoting in-depth development of neural net applications for climate prediction and services improvement

Promoting in-depth development of neural net applications for climate prediction and services improvement

by Jiayu Zhou, David DeWitt, Office of Science and Technology Integration, National Weather Service; NOAA Climate Prediction Center
Multivariate statistical model for seasonal snowfall prediction using NMME temperature and precipitation forecasts by D. Barandiaran and S. Baxter, NOAA Climate Prediction Center; Innovim LLC

Multivariate statistical model for seasonal snowfall prediction using NMME temperature and precipitation forecasts

by D. Barandiaran and S. Baxter, NOAA Climate Prediction Center; Innovim LLC
Integration of the Noah MP Land Surface Model into the Unified Forecast System by Helin Wei, Rongqian Yang, Jack Kain, Kingtse MoIMSG; NOAA Environmental Modeling Center; NOAA Climate Prediction Center

Integration of the Noah MP Land Surface Model into the Unified Forecast System

by Helin Wei, Rongqian Yang, Jack Kain, Kingtse MoIMSG; NOAA Environmental Modeling Center; NOAA Climate Prediction Center
Development and result of TCWB1T by Tzu-Yu Wu, Hann-Ming Henry Juang, Pang-Yen Liu, Yun-Lan Chen, Ching-Teng Lee, Jen-Her Chen, Tony Liao

Development and result of TCWB1T

by Tzu-Yu Wu, Hann-Ming Henry Juang, Pang-Yen Liu, Yun-Lan Chen, Ching-Teng Lee, Jen-Her Chen, Tony Liao
Model comparisons and optimized weighting scheme for consolidating week 3-4 forecasting tools by Emerson LaJoie, NOAA Climate Prediction Center; Innovim LLC

Model comparisons and optimized weighting scheme for consolidating week 3-4 forecasting tools

by Emerson LaJoie, NOAA Climate Prediction Center; Innovim LLC

 Evaluation and intercomparison of Noah MP LSM-based Land Data Assimilation System with Noah LSM-based Land Data Assimilation Systems and Reanalyses in the NCEP operations by Rongqian Yang, Jesse Meng, Youlong Xia, Jack Kain, and Michael Ek, IMSG; NOAA Environmental Modeling Center; RAL/NCAR

Evaluation and intercomparison of Noah MP LSM-based Land Data Assimilation System with Noah LSM-based Land Data Assimilation Systems and Reanalyses in the NCEP operations
 
 
 

IV. Observation and Monitoring

Preview, NCEI daily gridded data and selected derived products by Karin L. Gleason, Derek S. Arndt, Carl J. Schreck III, Chris L. Fenimore, NOAA National Centers for Environmental InformationPreview, NCEI daily gridded data and selected derived products

by Karin L. Gleason, Derek S. Arndt, Carl J. Schreck III, Chris L. Fenimore, NOAA National Centers for Environmental Information
Remote sensing and covariance fluxes to evaluate productivity in buffelgrass (C. ciliaris) and subtropical scrub in arid zones of Northwest Mexico by Sofía Choza Farías, José Raúl Romo León, Alejandro Castellanos Villegas, Universidad de Sonora, MéxicoRemote sensing and covariance fluxes to evaluate productivity in buffelgrass (C. ciliaris) and subtropical scrub in arid zones of Northwest Mexico

by Sofía Choza Farías, José Raúl Romo León, Alejandro Castellanos Villegas
Is Standardized Potential Evapotranspiration Index (SPEI) a better drought index for Africa? by Miliaritiana Robjhon, Wassila Thiaw, NOAA Climate Prediction Center; Innovim LLCIs Standardized Potential Evapotranspiration Index (SPEI) a better drought index for Africa?

 

by Miliaritiana Robjhon, Wassila Thiaw, NOAA Climate Prediction Center; Innovim LLC
Detection of vegetation drought onset from space by Atefeh Hosseini, Arsalan Zolfaghari Shahrak, Wilfried Konrad, University of Kansas, Lawrence, KS; University of Tuebingen, Tuebingen, Germany

Detection of vegetation drought onset from space

by Atefeh Hosseini, Arsalan Zolfaghari Shahrak, Wilfried Konrad, University of Kansas, Lawrence, KS; University of Tuebingen, Tuebingen, Germany
 

 

Note:  The images were taken from the 44th NOAA Annual CDPW poster session.  Contact presenters for details.